Deviation from Covered Interest Rate Parity in Hong Kong

This dissertation explores the deviations from covered interest rate parity in Hong Kong and its impact on the currency value. It includes a literature review on the factors causing changes in the covered interest parity, theoretical implications, and empirical investigation. The study uses regression analysis and explores the relationship between interest rate differentials and spot exchange rates. The findings suggest that the covered interest parity condition in Hong Kong has deteriorated.

DISSERTATION
(DEVIATION FROM COVERED
INTEREST RATE PARITY IN
HONGKONG)

TABLE OF CONTENTS
cHAPTER 1 INTRODUCTION................................................................................................1
CHAPTER 2 LITERATURE REVIEW AND THEORY.........................................................3
2.1 Literature Review.............................................................................................................3
2.1.1. Changes take places in the covered interest parity in Hong Kong...........................3
2.1.2 Factors that causes differences between swap rate and interest rate in Hong Kong. 5
2.1.3 To tests the validity of the covered interest parity in Hong-Kong.............................7
2.1.4 Impact of foreign exchange liquidity conditions of bank on Covered interest parity9
2.2 Theoretical framework...................................................................................................12
CHAPTER 3 DATA AND METHODS..................................................................................14
3.1 Research methodology...................................................................................................14
3.2 Research approach..........................................................................................................15
3.3 Research design..............................................................................................................15
3.4 Research method............................................................................................................17
3.5 Data collection................................................................................................................17
3.6 Ethical considerations.....................................................................................................17
CHAPTER 4 ANALYSIS AND RESULTS............................................................................18
4.1 Descriptive statistics.......................................................................................................18
4.2 USDHKD Interest rates analysis using regression.........................................................73
4.3 Spot exchange rates........................................................................................................77
4.5 Regression among spot exchange and USD and HKD values.......................................81
Vector Auto aggressive model..........................................................................................96
CHAPTER 5 DISCUSSION AND CONCLUSIONS.............................................................98
5.1 Summary.........................................................................................................................98
5.2 Theoretical implications.................................................................................................98
5.3 Practical implications.....................................................................................................99
5.4 Limitations of research...................................................................................................99
5.5 Reflections....................................................................................................................100
5.6 Conclusion....................................................................................................................101
REFERENCES.......................................................................................................................102

INDEX OF TABLES
Table 1 Currency prices of USD-HKD....................................................................................36
Table 2 Descriptive statistics of currency prices.....................................................................36
Table 3 Opening prices of USD and HKD...............................................................................54
Table 4 Descriptive statistics of opening prices of USD and HKD.........................................55
Table 5 Low prices...................................................................................................................64
Table 6 Descriptive statistics of low prices..............................................................................64
Table 7 % changes in prices....................................................................................................73
Table 8 Regression Statistics...................................................................................................74
Table 9 ANOVA........................................................................................................................74
Table 10 RESIDUAL OUTPUT...............................................................................................75
Table 11 PROBABILITY OUTPUT..........................................................................................76
Table 12 Residual Plot.............................................................................................................76
Table 13 Normal Probability plot............................................................................................77
Table 14 Spot Exchange rates..................................................................................................80
Table 15 Regression analysis...................................................................................................86
Table 16 Regression Statistics.................................................................................................86
Table 17 ANOVA......................................................................................................................86
Table 18 RESIDUAL OUTPUT...............................................................................................88
Table 19 PROBABILITY OUTPUT..........................................................................................90
Table 20 Residual Plot.............................................................................................................91
Table 21 Line Fit Plot.............................................................................................................92
Table 22 Normal Probability plot............................................................................................93
Table 23 Interest rates of USD and HKD................................................................................95
Table 24 SUMMARY OUTPUT...............................................................................................95
Table 25 ANOVA......................................................................................................................95
Table 26 Coefficient.................................................................................................................96
Table 27 RESIDUAL OUTPUT...............................................................................................97
Table 28 Residual Plot.............................................................................................................97
Table 29 Overnight swaps........................................................................................................97
Table 30 NDF 3 month swap rate............................................................................................98
Table 31 SUMMARY OUTPUT...............................................................................................98
Table 32 ANOVA......................................................................................................................98
Table 33 Coefficient.................................................................................................................98
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Table 34 RESIDUAL OUTPUT...............................................................................................98
CHAPTER 1 INTRODUCTION
Unique topic has selected for this research study that steals the attention of all the
technical or non-technical users. The users will get insights about market trends from this
study and to take enough benefit from this. Nowadays, the scope of the stock market and
forex trading has increased with time as everyone wants to earn higher profit by investing in
the forex market. The biggest reason behind the fewer investments in the forex trading is due
to lack of knowledge and awareness about this concept as no one knows about this concept in
detail due to which they can make investments decisions.
In increasing awareness among the people about this field, the researcher performs
this research study to explore the hidden or known aspects of the covered interest parity
conditions. The topic of this research is to determine the deviations from the covered interest
parity. The interest differentials between the swap rate and the interest rates analyses for this
research study. The majority of its audiences do not aware of this concept as by conducting
this research they will get to know about all the components of an investigation. Dependent
and independent variables developed for this study to generate the outcomes of a research
study.
This the study will target several components of research such as analysing the latest
interest rates, swap rates, closing values of the exchange rates and the currency values of two
of the countries. A researcher uses the cutting-edge data in this research which allows all the
investors to get updated with the latest results and this also help a user as a quick guide to
investing in the foreign market directly. It can say that this research study will act as an
instruction manual or a study guide that allow a newbie to enter into the international
financial market and money market and invests in a suitable asset that generates a higher
return. The risks will get decreases by a user by itself by taking help of investment analysis
tools such as VAR and regression analysis as discussed in this report.
The topic of this research study is the deviations from the covered interest parity in
the Hong-Kong denote that a researcher will identify the factors that are the cause roots of the
changes in the CIP. This study will reflect the theoretical and empirical investigations
conducted in this research analysis by deeply exploring all the facts relates to this study. This
study initially conducts the literature review which will describe the theoretical perspectives
of research. The abstract framework shows the relationships of a research variable such as
overnight swaps and the NDF swap rate identifies using Vector auto-regression model to
check the relationship among these two elements.
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A Motive of a researcher behind selecting this model is to know its further impact.
The researcher analyses to know its final impact on the main objective of the research. The
interest rate differentials and the spot exchange rates of USD and HKD identify by a
researcher using simple ordinary linear coefficients tests which is one of a kind of regression
analysis that uses residual plots and line fit plots for comparing the data. This tool will show
whether the data will fit in a straight line will get out of a mark.
The empirical investigation reveals the real efforts of a researcher in performing this
research study that says about the positive or increasing trend of the currency value of US and
Hong-Kong from one period to another due to the low inflation rate. Negative estimated
results about spot exchange rates and the currency prices of two of the countries that the
unfavourable outcome signifies no correlation between these two components. The negative
consequence is determine as these affect by the external environment all the factors such as
political, economic and cultural factors are which are primary suspects of triggering changes
in the covered interest parity. By linking the singular results of all the analysis performed by
a user in this study, the final result is a summation of all the examination that says that the
covered interest parity’s condition is not as good as the deteriorated position of CIP has
witnessed by all the users. The empirical investigation along with the theoretical study will
aid an individual in compiling its final report that the research objectives successfully tested
and the result is not in favour of the party as CIP is negative.
After the completion of this research, an individual got to learn several lessons of
keeping patience, working systematically by managing the time, using authentic and reliable
information from the credible sources. All these lessons learnt from this study will help a
person in performing systematic research in the future to get it complete before the stipulated
time of research.
This study will challenges the future research scholars in terms of knowledge and
quality of information mention in a research. A user will get to know about special features
of covered interest parity by reading this dissertation. They will get an experience while
performing this study as they get a clue to perform its own research in the future by taking
help or guide for their own research.
Considering the issue takes places in research, the entire study will get changes by making
modifications in the file by changing the timeline of this project, using different
methodologies of the research study. Un-available data and time- consuming research process
will results in an estimate of project failure as due to this the interest of a researcher gets
decreases.
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CHAPTER 2 LITERATURE REVIEW AND THEORY
2.1 Literature Review
2.1.1. Changes take places in the covered interest parity in Hong Kong
Glau, Grbac, Scherer & Zagst, 2016), has asserted that covered interest parity is a
term that denotes the actual meaning of this term that shows the interest rate differential
between two currencies. The study says that the interest differential of the two currencies in
the cash market should get equal the shortcomings lie in the forward and the spot exchange
rates (Wong, Leung & Ng, 2017). The covered interest parity is a close examination of the
interest differential of the two currencies dealing in the international market to know the
impact of the external market on its trading. Increasing or decreasing covered interest parity
will, in turn, shows its overall effect on the currency value of two of the countries.
According to the viewpoint of Avdjiev, Du, Koch & Shin, 2016), says that due to the
global financial crises immense reappraisal of the third party credit risks and the liquidity
risks in the international finance market has evident. This increasing risk will, in turn, change
the currency value of the country. The fluctuating position of the covered interest parity
amazes all the economists top think over on this matter again in estimating the reasons behind
this issue (Borio, McCauley McGuire & Sushko, 2016). The London interbank offered rate
also gets increases overnight whose purpose is not certain to the investment analysts due to
which the indexed swap rate has also increased. The sudden increase in the Libor and the
indexed swap rates is to be identifying throughout the research study.
The Motive of the researcher is to understand the cause behind that why covered
interest parity is no longer exists in the international finance market as what factors triggering
positive or negative changes in the growth of CIRP. From the perspective of the lender, the
counterparty risk is essential for borrowing which is not secured through collateral security as
a lender gets no return in exchange when giving loan to the borrower (Sushko, Borio,
McCauley & McGuire, 2017). On another hand, a lending party will enjoy interest or
something in return of the loan is given to a borrower by taking collateral security in
exchange for a credit. From the angle of swap indexed rate, the interest differential is identify
which signifies the difference between the forward and the spot interest rate. The interest
differential rate will act as a benchmark rate that will help spot rate and the forward rate too
show increasing performance (Du, Tepper & Verdelhan, 2018). The investments in the stock
market will get beneficiary advantages due to the growing performance of these two rates.
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Another theory says that the difference among the domestic and foreign currencies is the
interest differential rate.
As per the viewpoint of Osei-Kyei & Chan, (2017), a factor held responsible for
changing covered interest parity in Hong-Kong is due to the transactions costs of investment
in the international finance market. Due to the existence of transaction costs, the interest rates
and the exchange rates will get parallel to each other before investing in the market. It says
that when an individual capitalizes in the market, then the interest and the exchange rates gets
equal but when the same individuals borrow from another party in same market will consider
as a foreign currency exchange.
Cheng & Wu, (2017), says that another factor causing changes in the covered interest
parity of the given country are political risk as Hong-Kong contains two financial controls
such as of the current nation and the regulation of China. Two political rules and the
conventions applicable on this country which is not beneficial for the businesses and the
individuals trade in the international market. Fluctuations in the political rules and the
regulations of the nation will directly affect the covered interest parity. This will in, turn,
creates severe changes in the interest rate as due to turbulence in the political structure of the
nation. Due to the changes in the political conditions of the nations, an investors has to face
higher interest rate which will get stabilizes by interest rate parity as this will rectify the
situations of the external market (Baldwin, Brunsdon, Gaudoin & Hirsch, 2018).
From the viewpoint of Liao, (2016), that says that withholding tax is another point
that held responsible for deviations in the interest rate parity (Halaweh, 2018). While trading
in the international market, when a domestic user pay to the foreign party then the taxes
withhold to that payment has to deposit to the government before clearing the payment made
to the other party. Poor condition of the covered interest parity of the Hong-Kong is due to
the changing taxation policies of the nation as the value of tax withhold on the payment to the
foreign party was higher than the actual payment (Kerr, 2018). This leads to the problems
which, in turn, decreases the forward and the spot rate who direct impact show on the overall
performance of the interest rate parity. Due to this situation, the value of Hong-Kong dollar
weakens as compared to other currencies in the international market (Whicher, Philbin &
Aronson, 2018). It is essential to closely observe the taxation rates and the overall structure to
safeguard the position of IRP (Interest rate parity of the nation (Zhao, Valdes-Vasquez,
Simmons & Parrish, 2018, January).
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Nishimura & Ozaki, (2017), says that liquidity preference is another issues identifies
by a researcher when detailed analysis conducted to analyse the position of the covered
interest party of the nation (van Veen, 2018). It is essential to now all the factors which is
affecting the currency value of Hong-Kong to eliminate the effect of all the factors which is
creating issues for the nation. After knowing its effect, actions will take by the government to
resolve all the issues. The liquidity of assets is to be identifying before investing in the
international market as this costs will also directly affects the interest rate parity (Levenko,
Oja & Staehr, 2019). Higher the costs involved in the converting the investments assets into
cash will increases the costs burden on an entity. The increasing liquidity costs will increases
the liquidity of an investment before its maturity which is not appropriate for investors.
2.1.2 Factors that causes differences between swap rate and interest rate in Hong
Kong
Hui, Lo & Fung, (2017), has asserted that latest research conducted to identify the
determinants held responsible for driving the Hong- Kong dollar interest rate swap spreads
are Liquidity and credit. From the perspective of the international market that considers swap
spread as an alternative way for banking liquidity (Bekaert & Mehl, 2019). Before
performing detailed analysis about these two factors that causes differences in the interest
rate and swap rate in the nation, it is essential to clarify this concept to aware its audiences
about its actual meaning and its significance.
Swap shows the trading relationship between two parties involved in exchanging cash
flows in the future period that utilizes swap interest rates (Benos, Payne & Vasios, 2018).
Commonly, fixed for floating method of swap interest rate uses by the parties to the
agreement where one party receives the variable interest rate payments and other party will
pay the fixed rate that is swap rate. The Hong-Kong dollar interest rate swap is very high as
compared to other countries in the counter market due to the favourable economic and
monetary conditions of this nation (Xia, You, Jiang & Guo, 2018).
International finance market releases two interpretations theories regarding swap
interest rates that firstly this is consider as an “ effective proxy for banking and liquidity” and
secondly, this is consider as a “ proxy for AA credit” (Fratzscher, Duca & Straub, 2016). This
theory determines two factors that cause differences between the interest rates and swap rates
in the nation. This research paper will analyses the major effect of one of a factor for the
differences caused in the swap spread.
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In the second half of 2007, increase in the Hong- Kong dollar swap spreads has
witnessed which further collide with the occurrence of sub-prime crises in the United States.
This crisis has affected the value of swap spreads of the nation and also affects the famous
financial institutions of the United States (Kwan, Wong & Hui, 2015). Two of the reasons
come in a bigger picture stating the effect of this rises on the interest rates swap of Hong
Kong due to credit concern and the liquidity concern (Gonenc & Ursu, 2018). This
preliminary investigations about two of the factors identifies with the help of Vector-Error
correction model. This model helps in analysing the time series of this crisis to track the
effect of this crisis on the performance of Hong- Kong dollar and the swap spreads (Vokić,
Klindžić & Hernaus, 2018).
In continuation to this, the time series of swap spreads and Hong- Kong Interbank
offered rate and the credit spreads are also analyses to identify the main reason behind the
fluctuating trends (Li, Shi, Allan & Evans, 2019). After the end of this model’s analysis
(Giglio, 2016). The major effect for the deviations of swap spread is due to the increasing
liquidity risks that induces the interest rates. In the swap spreads, interest rate is variable in
nature and swap is fixed in nature which remains the same throughout the changes in the
market. Higher the changes in the market, higher will be the interest rates (González,
Oosterlynck, Ribera-Fumaz & Rossi, 2018).
After identifying the liquidity risks triggering changes in the swap spreads, the next
factor is identified by applying by convenience yield model. This model shows that another
factor causing higher changes in the swap spreads is credit risks (John, S., Oosterlynck,
Ribera-Fumaz & Rossi, 2019). This model tracks the increasing trends of the swap interest
rates which are due to credit spreads of non-government bonds of the nation (Badaoui,
Cathcart & El-Jahel, 2016). This credit spreads shows the difference between the returns
generated over the period from the exchange fund of Hong- Kong. The Credit value of nom-
government fund bonds is tracked by using index values of HSB weighted return scales
(Höllerer, Jancsary & Grafström, 2018). The values determined by using this scale. Inclining
or declining trend of this weighted scale will in return shows the impact of credit risks for
swap spreads. By measuring the trends of this scale, the government will eliminate the credit
risks affecting the performance of swap spreads. The interest rate swap spreads shows the
strength of an investor while trading in the external market.
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The time series of the swap spreads is tested by using the break point tests by
considering two of the determinants such as liquidity and the credit risks affecting the swap
spreads. Structural changes has observes by an investors in analysing the overall performance
of the interest rates and the swap rates (Bai & Wu, 2016). The three refinements introduces
by the Hong- Kong government in decreasing pressures of the external market in stabilizing
the deviations of the swap rates and the interest rates. Three refinements are linked exchange
rate system, emergence of US-subprime crisis and Injection of cross bank liquidity
considering as the triggering factors for the changes in the swap spreads of the country. All
the monetary and the nom-monetary factors are also taken into account in analysing the entire
performance of the interest swap spreads (Cayon, Thorp & Wu, 2018).
2.1.3 To tests the validity of the covered interest parity in Hong-Kong
Ito, (2018), has asserted that it is essential to tests the validity and the authenticity of the
covered interest parity to make sure that all the information about the forward and the spot
rates of the cross countries (Bruno, Kim & Shin, 2018). By testing the validity of this model a
researcher will uses an appropriate way to estimate the authenticity of the model and the
information use in building the same (Schmidt, Caccavaio, Carpinelli & Marinelli, 2018).
The economic status of two of the trading entries can be analysed by identifying the valid
data about the covered interest parity. In this phase, rank approach is used by an evaluator in
testing the covered interest parity of the cross currencies by analysing the currencies of Hong-
Kong and the US dollar (Lane & Milesi-Ferretti, 2018). As the covered interest parity depicts
the relationship between the two country’s interest rates in a trading market along with its
own forward and the spot exchange rates when they trade with each other (Cifarelli &
Paladino, 2018). These two rates are important to trade in the international finance market
which decides the destiny of an investor to generate higher returns in the future competitive
market. By keeping track on these two rates, an investor’s will able to decrease its trade
obligations and transform them into its strengths.
(1+Rdk)= Fk/S (1+Rfk)
The above mention formula is a criterion of this approach to tests the efficiency and
effectiveness of the covered interest parity by analysing its components such as exchange
rates and the spot rates (Suh, 2018). These spot, forward and the interest rates will differ from
period to period depends on the circumstances.
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Rdk denotes the nominal interest rate of a local or domestic country at the time of the
maturity. A maturity period of an investment means the completion of the time period for
which an investment holds in the money market (Christensen & Krogstrup, 2018). On
another hand, Rfk signifies the nominal interest rate of the foreign country at the maturity date
(Cheung, Hui & Tsang, 2018). Fk shows nominal forward rate and S denotes the spot
exchange rates of an investments. It can says that forward and spot rates describes the identity
of an investment as by using these rates the nature of the interest rate is determined to know
whether an investment will succeed or will get fail at the time of a maturity date (Shi & Wu,
2018).
In the international finance market, there are a lot of opportunities as several entities
are trading in this field as everyone wants to earn higher profit which, in turn increases the
level of market risk along with the increasing competition level of an international market
(Berg & Mark, 2018). Covered interest parity will act as a benchmark that inspires all the
traders in the money market to beat the increasing market risks and earn its desired profit in a
stipulated time period (Avdjiev, Bruno, Koch & Shin, 2019). This benchmark will help a
trader to earn riskless profit by eliminating all the risks and the issues take places in the
external environment (Kennedy-Hendricks and et al., 2018).
B= Fk/S (1+Rfk)-(1+Rdk)
B denotes the cross currency basis which is the main thing that is evaluates by a
researcher in testing the validity of the covered interest parity of two of the countries trades in
the money market to get the enough returns at the maturity date (Bernstein, Hughson &
Weidenmier, 2019). Using this criterion, the deviations incurred in the interest parity can be
tracked as in the actual money market, the fluctuations on the interest parity conditions are
observed from zero to another level in order to determine the element held responsible for
this fluctuations or deviations (Pumir, Jelassi & Boumal, 2018). Increasing or decreasing
value of the transactions costs involved in an investment agreement held responsible for a
minute change take place in the covered interest parity. Increasing costs of the transactions of
an investment will direly affects the value of the host country that holds investments in the
international market (Biswas, Kumar & Prakash, 2019).
With the emergence of covered interest parity’s concept through various empirical
studies conducted on this field are underestimated by some of the economists and the
financial experts that consider this topic as vague (Warburton, 2018). But due to the
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international financial crisis, the image of covered interest parity gets cleared in the eyes of
economists and the financial professionals. As they witness increasing deviations in the CIP
in the international market due to the direct effect of this event. Several real examples take
places in the market is enough to prove this statement that the scope of CIRP has increases
due to the global financial crisis in the money market (Cayon, Thorp & Wu, 2018). Though,
event affects several entities and traders by spoiling the returns of the investments holds by
an investor. Failure of Libor based CIP has witness after the year 2007 in relation to the G 10
currencies for both short run and the long run. Due to the event incurred in the year 2007,
where the value of US dollar shows negative value which shows the fluctuations of the
Covered interest parity in the currency market. Violations in the CIP is not due to global
financial crisis as this has changes visible in the performance of CIPT even before than this
event (Iida, Kimura & Sudo, 2018). This shows that the covered interest parity gets affected
with the external as well as internal environment which is responsible for the deviations
taking place in the CIP. Turbulences in the international finance market are another reason
for shifting the movement of the Interest parity conditions in moving from left to right.
Other factors held responsible for the fluctuations of the covered interest parity
conditions to hold an investment in the international market that banking regulations also
affect CIP. Forward rate and spot rate’s interest rates will get differ from on period to another
due to banking rules and the regulations as every banks work according to the order of the
Apex bank that is reserve bank (Morse, 2019). Due to tough banking conditions where a bank
struggling to meet its capital and liquidity requirements due to which the trade will get risk
free but at the same time, the condition of CIP gets deteriorated. This severe condition of the
CIP gets affected as interest parity will fail to hold its position in the external market due to
uncomfortable situations faces by an entity in the international money market (Wang and et
al., 2018). The analysis also proves that the excessive fluctuations or changes in the CIRP
incurred due to the increasing transactions costs and higher operational risks. In the presence
of these two risks such as increasing costs and the operational and the financial risks affects
the position of CIRP and all the investments associates with it gets affected.
2.1.4 Impact of foreign exchange liquidity conditions of a bank on Covered interest
parity
As per the view of Hassan & Mano, (2018), that the concept of covered interest parity
shows the holding of interest paid by an investor on two assets of a similar category that of
different currency’s type gets equalize with the foreign exchange rate (Gallien, Kassibrakis,
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Klimenko Malamud & Teguia, 2018). The fulfilment of this condition denotes the rigid
global capital mobility of the investments in the money market. One of theory shows the
prediction based on the covered interest parity that an investor who borrows foreign currency
using the spot rate of the foreign exchange market along with the hedging in the exchange
rate shows cross-currency to the zero value (Dumičić, 2019). Banking regulations proved as
an immense player in affecting the condition of the covered interest parity due to the majority
of positions handed in the trading money market (Hameed & Rose, 2018). Around, two-third
of the banking institutions trades in the foreign exchange swap market that shows the market
dominance of this institution. By knowing this, the dominance of the banking institution
which, in turn, affects the covered interest parity conditions in the money market as changing
interest rates and the swap rates will directly affect the future market.
After the global financial crisis, the banking institutions got affected with this event
that affects the covered interest parity’s conditions by increasing the costs incurred by banks
in meeting the international trade obligations (Kremens & Martin, 2019). The increasing
costs to banks in offering US dollars to the foreign exchange swap market also declines the
returns associated with the CIP arbitrage. Before explaining the incentives related with the
covered interest parity, to discuss the CIP arbitrage to move the entire researcher in a
particular direction. CIP arbitrage is a trading strategy under which investors capitalize the
difference of the interest rates among domestic and foreign country to the trading agreement
(Hettig, Müller & Wolf, 2019). In this a mutual agreement between the investor’s they use a
forward contract to overcome the exchange rate risk of the current period. In the present
period, the party to contract enters into a future contract to avoid the risks of the excessive
fluctuations incurred in the interest rates of the investments. Using the forward contract, the
investors or banking institutes to utilize this contract to get discounts on the investment costs
and also earn higher risk-free profits. Generating profits from the investments signifies the
favourable position of covered interest parity by disregarding a myth that CIP constantly
holds in the international market. After the crisis, the sudden changes in the bank regulations
will affect the CIP and decreasing the returns of CIP arbitrage (Kavtaradze & Mokhtari,
2018). Decreasing premiums and profits arises from the covered interest parity will affect the
bank who apply money in investing in the international market loses its image in front of
other competitors lies in the market.
Augustin, Chernov & Song, (2018), has observed that CIP is struggling in the
international fiancé market due to rigid liquidity differences lies across the major currencies
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values of two of the countries involves in a trading agreement with each other. Recent study
conducted on the segmented money markets and the covered interest parity to identify the
key elements responsible for the increase or decrease in the interest parity conditions. In
observing the conditions of CIP, various results comes in a bigger picture about the funding
issues related to the US dollars to invest in the money market in strengthening the value of its
currency in comparison to its competitors (Lindström & Sten, 2018). Another challenge faced
by CIP is related to the swap market which gets contracted due to the increasing liquidity
issues in the international money market.
The concept of the covered interest parity is consider as an important regulations in
the international finance market that regulates the overall investment holds by investors to
generate enough returns at the date of maturity (Njindan Iyke & Ho, 2018). Likewise, to the
concept of CIP another they released by the economist and the financial professionals in that
no profit is earned by borrowing one currency and lend in another currency without
considering the foreign exchange risks. As when an individual trades with two currencies
together then this will attracts the concept of the foreign currency exchange risks. So if
investor wants to earn seamless profit, then they have to cover the foreign exchange risks
before investing the same in the money market (Lin, Sun & Yu, 2018).
(1+r$) = F/S (1+r*)
This expression is used to determine the relationship between the covered interest
parity and the foreign exchange risks whose direct impact is to be shown on the swap market
and the international fiancé market (Plantin & Tirole, 2018). The interest of all the investors
will get affected with the increasing foreign exchange risk when two countries trade with
each other using their different currency type. The symbols used in this expression needs to
discuss to awake all the audiences about its actual earnings such as r$ shows foreign interest
rates at the maturity and r* also signified the similar meaning. S denotes the spot exchange
rate which is expressed in the monetary unit of US dollars as a single unit per foreign
currency. In analysing the foreign exchange transactions; the US dollar is consider as a
standard currency (Serletis & Xu, 2018). F signifies the forward rate of the interest bearing
assets which will get matured at the time of the maturity. Simultaneous closing of all the
investment transactions and zero counterparty risks is a symbol of the declining of the non-
arbitrage covered interest parity conditions. The study also emphasizes on explaining the
effect of the CIP deviations on the arbitrage profits. This shows that there is a positive
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correlation between the fluctuations in the CIP with the arbitrage profits as increasing or
decreasing covered interest parity situations will directly affect the economic profits as this is
directly associates with it (Bonga-Bonga, 2018). All these events witnesses by the entire
economy of the Hong-Kong are due to the global financial crisis. This event is not only
affected Hon-Kong as this affects the entire world by creating liquidity issues which is
creating a barrier in the progress of the covered interest parity (Kaltenbrunner & Painceira,
2018).
2.2 Theoretical framework
The theoretical framework discusses the deviations of the covered interest parity in
the Hong-Kong by comparing the same with the US dollar. This phase will include the
variables of the study by comprising both dependent and the independent variables of the
research (Albuquerque, Brandão-Marques, Ferreira & Matos, 2018). Theories develop for
this research to tests the research variables in the future as the motive of a researcher is to
show the effect of the independent variable on the dependent variable. Assumptions develops
in this research to tests its validity throughout the research analysis that the developed
hypothesis will get null or rejected or else this will get accepted (Luo & Bu, 2018).
The covered interest parity conditions concept has explained in this researcher where
the problem is to examine the deviations or fluctuations incurred in the interest rates. This
thesis will help in understanding the factors held responsible for increasing or decreasing the
changes in the CIP. This research will allow a user in knowing its effect on the international
finance market (Luque & Pascoa, 2018). A Motive of a researcher is to closely observe the
trading movements from one period to another to track the overall progress of CIP
(Omotubora & Basu, 2018). Other elements discusses along with the CIP’s concept that also
plays an important role in triggering the changes in the investments holds by investors in the
international money market (Ibhagui, 2018). The eligibility of an investor to hold an
investment is essential to determine to eliminate all the future issues which will affect its
future market positions (Crump & Santos, 2018).
15

Above mentioned three variables consider as elements that help a researcher to
perform its research in identifying the deviations incurred in the covered interest parity in the
Hong-Kong. Three variables to this research will test by a researcher throughout the research
in determining its effect on the main element of this study that is the aim of this research
(Cenedese, Della Corte & Wang, 2019). A Purpose of a researcher behind this study is to
explore all the hidden and the known fact regarding this concept which is not known by
group of people. The literature review identifies three of the elements that held responsible
for creating fluctuations in the covered interest parity. It consists of differences between the
swap and the interest rates, impact of foreign liquidity and the validity of the CIP. All these
are hypothesis develops by scrutinizers in testing the same in its entire research (Han, Jiang &
Yin, 2019).
The above mention theoretical framework will emphasize on various parameters such
as identify the factors cause behind the fluctuations in the CIP, identifying about a swap and
the interest and finally checks the authenticity of the information enclosed in research (Du,
Im & Schreger, 2018).
The significance of this research study is analysed by a researcher whose motive is to
overcome all the issues faces by an individual throughout the study by targeting the main
areas to this study (Warburton, 2018). A researcher will focus on determining the latest
market trends about the swap and, the interest rates of the investments holds in the
16
Changes
in CIP
Differences
in swap and
interest rates
Impact of
foreign
liquidity
Validity of
CIP

international finance market. For estimating the value of currency’s it is important to know
the latest changes takes places in the global market to invest rightly in this field (Del Negro,
Giannone, Giannoni & Tambalotti, 2019). A right investment will generate enough returns
for its owner that it is essential to find out all the information about the source of asset and
the entire market to test the feasibility of all the investments. Several methods used by a
researcher in analysing the investment and its market to test the validity and the authenticity
of the investments.
This framework will concentrate on utilizing various theories which will further tested
during this research in determining the final results by using all these theories. In estimating
the changes incurred in the covered interest parity, the international covered interest parity is
used as a benchmark that will act as a standard in resolving all the issues related to this
particular concept (Chortareas, Kapetanios & Magkonis, 2018). A researcher will search for
the information related to the covered interest parity by taking two currencies comparison of
Hong-Kong and United states dollar currency value to know the impact of the external
elements on these two currencies and on the overall covered interest parity (Ghebrezghi,
2018).
CHAPTER 3 DATA AND METHODS
3.1 Research methodology
It is considering as an aspect of a research study that allows a researcher in exploring
all the aspects of study in collecting an appropriate facts and data. It is compares with a
compass that guides a ship to reach its destination by providing right direction just like it
provides a proper direction to a user in moving its research by accomplishing research aims
and goals on time. Selecting an appropriate method of a study depends on the nature of
research as there is no stereotype approaches to the research. As there is no such mentality by
imposing pressure on scholar to select as they can prefer any method which suits the nature of
research as an definitive aim is to tests the claim of a research by collecting the data.
The research methodology section of thesis is considers as one of an element as this describes
how investigator will collect data from what sources data get collected and also which
research technique used in testing the research problems (Laarman and et al., 2018). Usually,
two of the research methods understand by a user for collecting the relevant data for
completing the aim of research. These two consists of primary or secondary and qualitative or
quantitative which depend on the situations and the circumstances where researchers consider
17

after analysing the nature of a research and the overall issue of the study. Scientific
approaches selects by scholar in exploring the facts in detail to select the specific details
about a research problem by disregarding all the generalize viewpoints about a study
(Gomez-Gonzalez and et al., 2019).
3.2 Research approach
Before performing any research, it is to follow right research approach which will
depends on the nature of a study as the study is theoretical, more practical or combination of
theoretical or practical. Taking time in the initial phase, in selecting the suitable research
approach signifies the competency of a user that gives time to all the details in selecting
suitable approach in collecting the data. Three kinds of research approach are deductive,
inductive and abductive options which commonly users by all the users in conducting its
research.
Deductive approach- This approach considers by a researcher when they create theories or
hypothesis for its research with an intention to tests its claim by confirming or rejecting the
same throughout the investigation. Then this approach is considers by a user.
Inductive approach- This is a contradictory version of deductive approach under which
there is no need of hypothesis to develop for the research as this process will involve in
creating examination question, aims and the objectives which will accomplish in the study.
Abductive approach- This approach is followed in a case where a study will involve
incomplete facts and the observations which is yet to explore in the analysis and will get
identify in the future then this will use.
In the current research study, the deviations take places in the covered interest parity
of the Hong-Kong, where users utilize deductive research approach as this study requires
establishing a hypothesis which will accept or reject after the end of the study. The end result
of the study will contribute to knowing whether to confirm or rejects all the research
hypothesis develops by a researcher.
3.3 Research design
This section of a research study consists of systematic methods and procedures use by
a researcher in collating the data and evaluate the same using various criteria’s. The research
design that categorize into several parts such as descriptive, correlational, semi-experimental,
experimental, review and meta-analysis tools.
18

The descriptive research design is a method which includes case study, real observation and
conducting survey as the aim of this approach is to collect detailed data by performing a close
analysis of all the characteristics mention in an examination.
A Correlational method emphasize on identifying the relationship between the elements of
research by developing observational study by tracking the performance of key element of
research (Williams, 2017) In the observational study, a researcher will collect the data by
observing the things in reality to include the same in concluding the final research.
Semi-experimental designing of research relates to performing market experiment to get the
sense of reality and able to detect the issues or problems by personally collecting the data.
This mode will give quick and spontaneous results of the experiment performed by an
individual as part of research (Pandey, 2019).
In the experimental design a researcher will randomly pick some of the samples out of the
total population of a research and performs its experiment to record the final results.
Review method of a research design includes the literature review in which the past literature
gaps of a previous author will get filled in the current research (Mason and et al., 2018).
These will also include systematic review, in which a researcher will review the entire
researcher by creating several parameters to the research to get the final results whether
favourable or unfavourable to conclude the same.
A Meta-analysis research design will take the help of scientific studies in analysing the
research aims and the objectives as this is statistical analysis tool. This analysis will include
the concepts which will utilize in testing all the objectives of enquiry.
In this analysis, assessment design is considered under which the literature review is used to
fulfil the shortcomings of the previous author who conducted research related to the covered
interest parity, interest rates or swap rates (Mason, Cogua-Lopez, Fleming & Scheier, 2018).
The previous studies of research scholars consider as a basis in this research which gives new
direction to entire research in achieving the aims and the objectives in the current research
study.
3.4 Research method
It will consist of two of the main methods such as qualitative and quantitative research
methods use by a researcher for this study after assessing the nature of the current study.
19

Qualitative research method stresses about the theoretical aspects of research by testing the
dependent or independent variables of a investigation. On another hand, quantitative research
method focuses on the numerical data collected by a user and tests the same by applying
statistical tools and the techniques such as descriptive statistics, Annova, F test, T tests,
regression and correlation (Gruber & Vigfusson, 2018). The regression method is used to
determine the future trend a research element to estimate in advance in the existing period.
In this research, a researcher will use two of the methods of enquiry such as
regression analysis and vector auto-aggressive technique using impulse response analysis and
avarice decompositionos. These methods will utilize by an individual in checking the validity
the entire research study which is about identifying the deviations takes places in the covered
interest parity.
3.5 Data collection
There are two methods of data collection uses by a user in moving ahead with is
research such as primary as well as a secondary approach of study (Krosnick, 2018). Primary
data collection is used when the personal data collection possible for the entire study and
where specific and examined information is require in concluding the investigation (Tincani
& Travers, 2018). It will include questionnaires to be filled by all the participants of research,
survey and interview methods (MunafA & Smith, 2018). On the contrary to this approach,
another method of the data collection is secondary method where internet, books and
journals, census data and reliable sites use in getting the reliable data to include in research.
After collecting the data from these modes the next step is to analyse the collected data using
the statistical and non-statistical tools (Hoffmann, Langfield, Pierobon & Vuillemey, 2018).
3.6 Ethical considerations
Seeking permission and consent of a party whose articles utilize in research is
essential to avoid the allegation of forgery and plagiarism before starting any research (Slater,
2018). Attaching references to the research scholars in the dissertation or research study when
its material consumes in study of a user. Without adding references, the authenticity or
reliability of the entire research study will not identifiable as in that case, the owner will
cancel the whole study (Madsen and et al., 2015). To save the entire research from any
allegation, it’s advisable to a research compiler to ask permission to all the research scholars
and the authors by adding their references in its research to justify their position in case of
default.
20

First criteria use by all the assessors in testing the dissertation submits by the research
students or scholars is to test the reliability and the authenticity of the research information.
For challenging the reliability and the validity of the information mentions in a researcher, an
assessor checks the references used in the dissertation which verifies that all the information
is a true and fair (Gibson & Lang, 2018, March). A forged thesis that do not use any
references of previous research scholars in its research is not considered as valid as this will
consider as false studies (Alam, McGregor & Houston, 2018). As if any study consider as
false studies will not get published which further results into the failure of the efforts applies
by a student in collecting the primary or secondary facts and the figures in preparing this
research study will go in a vain. It is essential to use valid references by in texting in the
pieces of information used in a research study (Karabulut‐Ilgu, A., Jaramillo Cherrez, N., &
Jahren, 2018).
CHAPTER 4 ANALYSIS AND RESULTS
4.1 Descriptive statistics
Date Price Open High Low Change %
18-Apr-19 7.8452 7.8453 7.8467 7.8439 0.00%
17-Apr-19 7.8453 7.8435 7.846 7.8425 0.03%
16-Apr-19 7.8427 7.8398 7.8441 7.8376 0.04%
15-Apr-19 7.8399 7.8429 7.8453 7.8373 -0.03%
14-Apr-19 7.8422 7.8429 7.8435 7.8422 -0.01%
12-Apr-19 7.8429 7.8426 7.8473 7.8395 0.00%
11-Apr-19 7.8426 7.8365 7.8449 7.836 0.08%
10-Apr-19 7.8366 7.8414 7.8426 7.8301 -0.06%
9-Apr-19 7.8415 7.8471 7.8476 7.8407 -0.07%
8-Apr-19 7.8471 7.8492 7.8498 7.845 -0.03%
7-Apr-19 7.8495 7.8492 7.8495 7.8492 0.00%
5-Apr-19 7.8494 7.8492 7.8501 7.8486 0.00%
4-Apr-19 7.8491 7.8491 7.8495 7.8475 -0.01%
3-Apr-19 7.8495 7.8498 7.8501 7.8486 0.00%
2-Apr-19 7.8498 7.8496 7.8502 7.8491 0.00%
1-Apr-19 7.8498 7.8496 7.8499 7.8492 0.00%
31-Mar-19 7.8499 7.8499 7.8499 7.8498 0.00%
29-Mar-19 7.8499 7.8501 7.8504 7.8498 0.00%
28-Mar-19 7.8498 7.8488 7.8501 7.8486 0.01%
27-Mar-19 7.8487 7.8492 7.8498 7.8483 -0.01%
26-Mar-19 7.8494 7.8468 7.8495 7.8467 0.03%
21

25-Mar-19 7.8469 7.8472 7.8491 7.8456 -0.01%
24-Mar-19 7.8474 7.8474 7.8479 7.8471 0.00%
22-Mar-19 7.8473 7.8473 7.848 7.8452 0.00%
21-Mar-19 7.8473 7.8498 7.8498 7.8452 -0.03%
20-Mar-19 7.8498 7.8499 7.8501 7.8495 0.00%
19-Mar-19 7.8498 7.8498 7.8501 7.8494 0.00%
18-Mar-19 7.8499 7.8501 7.8501 7.8486 0.00%
17-Mar-19 7.8499 7.85 7.85 7.8492 0.00%
15-Mar-19 7.8501 7.8498 7.8503 7.8483 0.00%
14-Mar-19 7.8499 7.8496 7.8501 7.8492 0.00%
13-Mar-19 7.8499 7.8499 7.85 7.8497 0.00%
12-Mar-19 7.8499 7.8498 7.8503 7.8494 0.00%
11-Mar-19 7.8498 7.8497 7.85 7.8491 0.00%
10-Mar-19 7.8499 7.8498 7.8499 7.8498 0.00%
8-Mar-19 7.8498 7.8499 7.8502 7.8497 0.00%
7-Mar-19 7.8499 7.8497 7.85 7.849 0.00%
6-Mar-19 7.8499 7.8497 7.8501 7.8495 0.00%
5-Mar-19 7.8498 7.8491 7.8499 7.849 0.01%
4-Mar-19 7.8491 7.8487 7.8498 7.8486 0.00%
3-Mar-19 7.8489 7.8488 7.849 7.8485 0.00%
1-Mar-19 7.8487 7.8498 7.8499 7.8476 -0.02%
28-Feb-19 7.8499 7.8494 7.8499 7.8488 0.00%
27-Feb-19 7.8496 7.8491 7.8498 7.8488 0.01%
26-Feb-19 7.8491 7.8487 7.8498 7.8483 0.01%
25-Feb-19 7.8487 7.8483 7.8494 7.8478 0.01%
24-Feb-19 7.8479 7.8481 7.8484 7.8475 0.00%
22-Feb-19 7.8482 7.8472 7.8491 7.8468 0.01%
21-Feb-19 7.8472 7.8491 7.8492 7.846 -0.02%
20-Feb-19 7.8491 7.8487 7.8495 7.8483 0.01%
19-Feb-19 7.8487 7.8479 7.8494 7.8475 0.01%
18-Feb-19 7.8478 7.8481 7.8485 7.8472 0.00%
17-Feb-19 7.8481 7.8479 7.8481 7.8479 0.00%
15-Feb-19 7.8479 7.8472 7.8486 7.8471 0.01%
14-Feb-19 7.8472 7.8484 7.8487 7.8468 -0.02%
13-Feb-19 7.8484 7.8484 7.8491 7.8476 0.00%
12-Feb-19 7.8486 7.8478 7.8489 7.8465 0.01%
11-Feb-19 7.8478 7.8471 7.8488 7.8463 0.01%
10-Feb-19 7.8468 7.8474 7.8474 7.8464 -0.01%
8-Feb-19 7.8473 7.8476 7.8479 7.845 0.00%
7-Feb-19 7.8476 7.8463 7.8479 7.845 0.02%
6-Feb-19 7.8464 7.8454 7.8468 7.8449 0.01%
5-Feb-19 7.8454 7.8467 7.8467 7.8445 -0.02%
4-Feb-19 7.8466 7.8469 7.8472 7.8441 0.01%
3-Feb-19 7.8456 7.8467 7.847 7.8456 -0.02%
1-Feb-19 7.8468 7.8467 7.8476 7.8434 0.00%
31-Jan-19 7.8468 7.8438 7.8472 7.8404 0.05%
22

30-Jan-19 7.8429 7.8463 7.8466 7.8375 -0.04%
29-Jan-19 7.8461 7.8457 7.8468 7.8454 0.00%
28-Jan-19 7.846 7.8453 7.8467 7.845 0.01%
27-Jan-19 7.8454 7.8453 7.8457 7.8452 0.00%
25-Jan-19 7.8457 7.8457 7.8469 7.8448 0.00%
24-Jan-19 7.8458 7.8453 7.8472 7.8444 0.01%
23-Jan-19 7.8453 7.8461 7.8472 7.8449 0.00%
22-Jan-19 7.8453 7.8454 7.8469 7.845 0.00%
21-Jan-19 7.8453 7.8437 7.846 7.8427 0.02%
20-Jan-19 7.844 7.8433 7.8449 7.8428 0.01%
18-Jan-19 7.8434 7.8429 7.845 7.8427 0.01%
17-Jan-19 7.843 7.8457 7.8457 7.8422 0.00%
16-Jan-19 7.843 7.8431 7.8457 7.8429 0.00%
15-Jan-19 7.8433 7.8425 7.8444 7.8411 0.01%
14-Jan-19 7.8422 7.8393 7.844 7.8393 0.03%
13-Jan-19 7.8396 7.8394 7.8405 7.8394 0.00%
11-Jan-19 7.8393 7.8384 7.8421 7.8381 0.01%
10-Jan-19 7.8385 7.8376 7.8403 7.8369 0.01%
9-Jan-19 7.8376 7.8388 7.8411 7.8366 -0.02%
8-Jan-19 7.8388 7.8344 7.8394 7.8343 0.05%
7-Jan-19 7.8345 7.8341 7.8376 7.8328 0.02%
6-Jan-19 7.833 7.8344 7.8347 7.833 -0.02%
4-Jan-19 7.8345 7.8308 7.8358 7.8274 0.05%
3-Jan-19 7.8304 7.8331 7.8355 7.83 -0.04%
2-Jan-19 7.8332 7.8312 7.8377 7.8308 0.02%
1-Jan-19 7.8318 7.8313 7.8319 7.8307 0.00%
31-Dec-18 7.8316 7.8304 7.8338 7.8289 0.00%
30-Dec-18 7.8314 7.831 7.832 7.8308 0.01%
28-Dec-18 7.8304 7.8303 7.8343 7.8282 0.01%
27-Dec-18 7.8294 7.8286 7.8353 7.8267 0.01%
26-Dec-18 7.8285 7.8323 7.8338 7.8274 -0.05%
25-Dec-18 7.8327 7.8328 7.8342 7.832 0.00%
24-Dec-18 7.8327 7.8323 7.8347 7.8284 -0.01%
23-Dec-18 7.8334 7.8323 7.8346 7.8322 0.01%
21-Dec-18 7.8327 7.8301 7.8346 7.8239 0.03%
20-Dec-18 7.8303 7.8265 7.8316 7.8238 0.05%
19-Dec-18 7.8267 7.8192 7.8273 7.8187 0.10%
18-Dec-18 7.8192 7.8132 7.8216 7.8125 0.08%
17-Dec-18 7.8126 7.8128 7.8153 7.8112 -0.01%
16-Dec-18 7.8137 7.8129 7.8149 7.811 0.01%
14-Dec-18 7.8133 7.8127 7.818 7.8075 0.01%
13-Dec-18 7.8125 7.8135 7.8156 7.8076 -0.01%
12-Dec-18 7.8134 7.8171 7.8179 7.8129 -0.05%
11-Dec-18 7.817 7.8155 7.8175 7.8125 0.02%
10-Dec-18 7.8156 7.8156 7.8164 7.8121 -0.01%
9-Dec-18 7.8164 7.8151 7.8167 7.8148 0.01%
23

7-Dec-18 7.816 7.8105 7.8174 7.8082 0.07%
6-Dec-18 7.8106 7.8129 7.8177 7.808 -0.03%
5-Dec-18 7.8129 7.8037 7.816 7.8023 0.12%
4-Dec-18 7.8036 7.8152 7.8181 7.8011 -0.15%
3-Dec-18 7.8153 7.824 7.8257 7.8149 -0.09%
2-Dec-18 7.8224 7.8241 7.8256 7.8224 -0.02%
30-Nov-18 7.8236 7.822 7.8266 7.819 0.02%
29-Nov-18 7.8217 7.8254 7.8274 7.8212 -0.05%
28-Nov-18 7.8255 7.8262 7.8286 7.8239 -0.01%
27-Nov-18 7.8266 7.8235 7.8299 7.8205 0.04%
26-Nov-18 7.8235 7.8261 7.827 7.8205 -0.04%
25-Nov-18 7.8263 7.8254 7.8269 7.8248 0.01%
23-Nov-18 7.8257 7.8307 7.8307 7.8232 -0.06%
22-Nov-18 7.8305 7.8331 7.8332 7.8277 -0.03%
21-Nov-18 7.8332 7.8301 7.8335 7.8293 0.04%
20-Nov-18 7.8303 7.8319 7.8335 7.83 -0.02%
19-Nov-18 7.832 7.8296 7.8335 7.8293 0.02%
18-Nov-18 7.8305 7.8298 7.8309 7.8296 0.02%
16-Nov-18 7.8293 7.8293 7.8335 7.8281 0.00%
15-Nov-18 7.8294 7.8305 7.8343 7.8285 -0.02%
14-Nov-18 7.8313 7.8305 7.8335 7.8301 0.01%
13-Nov-18 7.8307 7.8338 7.8349 7.8277 -0.04%
12-Nov-18 7.8342 7.8319 7.835 7.8286 0.03%
11-Nov-18 7.8315 7.8317 7.8329 7.8312 -0.01%
9-Nov-18 7.8323 7.8266 7.8332 7.8263 0.07%
8-Nov-18 7.8266 7.83 7.8328 7.8242 -0.05%
7-Nov-18 7.8304 7.8315 7.8351 7.8281 -0.02%
6-Nov-18 7.8317 7.8315 7.8372 7.828 0.00%
5-Nov-18 7.8315 7.8172 7.8362 7.8172 0.10%
4-Nov-18 7.8239 7.8232 7.8249 7.8172 0.09%
2-Nov-18 7.8172 7.8338 7.8391 7.8125 -0.21%
1-Nov-18 7.8339 7.8412 7.8441 7.8338 -0.09%
31-Oct-18 7.8411 7.8434 7.8476 7.8387 -0.03%
30-Oct-18 7.8435 7.8433 7.8468 7.8425 0.01%
29-Oct-18 7.843 7.8407 7.8438 7.8399 0.03%
28-Oct-18 7.8406 7.8402 7.8408 7.8399 0.00%
26-Oct-18 7.8407 7.8407 7.8415 7.8384 0.00%
25-Oct-18 7.8408 7.8407 7.8414 7.8362 0.00%
24-Oct-18 7.8408 7.8385 7.8423 7.838 0.03%
23-Oct-18 7.8385 7.8393 7.8406 7.8379 -0.01%
22-Oct-18 7.8395 7.8403 7.8414 7.838 -0.02%
21-Oct-18 7.8407 7.8408 7.8414 7.8393 -0.01%
19-Oct-18 7.8412 7.8384 7.8421 7.838 0.04%
18-Oct-18 7.8384 7.8392 7.8399 7.8379 -0.01%
17-Oct-18 7.8392 7.8361 7.8399 7.836 0.04%
16-Oct-18 7.8362 7.835 7.838 7.8341 0.02%
24

15-Oct-18 7.8349 7.8331 7.838 7.8331 0.00%
14-Oct-18 7.8347 7.8325 7.8354 7.8325 0.00%
12-Oct-18 7.8347 7.8343 7.8369 7.8319 0.00%
11-Oct-18 7.8345 7.837 7.838 7.8341 -0.03%
10-Oct-18 7.8372 7.8334 7.838 7.8328 0.05%
9-Oct-18 7.8332 7.8285 7.8351 7.8271 0.06%
8-Oct-18 7.8285 7.8346 7.8368 7.8231 -0.10%
7-Oct-18 7.8363 7.835 7.8363 7.8346 0.02%
5-Oct-18 7.835 7.835 7.8374 7.8319 0.00%
4-Oct-18 7.8351 7.8377 7.8393 7.8309 -0.03%
3-Oct-18 7.8377 7.8332 7.8396 7.8331 0.05%
2-Oct-18 7.8334 7.827 7.8384 7.8269 0.08%
1-Oct-18 7.8271 7.8281 7.83 7.8257 -0.02%
30-Sep-18 7.8286 7.8268 7.8286 7.8256 0.01%
28-Sep-18 7.8281 7.8155 7.829 7.8149 0.16%
27-Sep-18 7.8155 7.8126 7.8167 7.8045 0.03%
26-Sep-18 7.8128 7.8105 7.8187 7.8045 0.03%
25-Sep-18 7.8105 7.8114 7.8136 7.8084 -0.03%
24-Sep-18 7.8129 7.8092 7.8136 7.7977 0.02%
23-Sep-18 7.8112 7.8111 7.8121 7.8058 0.03%
21-Sep-18 7.8092 7.8426 7.8434 7.7928 -0.43%
20-Sep-18 7.8426 7.8448 7.8457 7.8422 -0.03%
19-Sep-18 7.8453 7.8431 7.8469 7.8431 0.02%
18-Sep-18 7.8434 7.8444 7.8459 7.843 -0.01%
17-Sep-18 7.8444 7.8459 7.8486 7.8431 -0.03%
16-Sep-18 7.8466 7.8468 7.847 7.8464 0.01%
14-Sep-18 7.8461 7.8482 7.8491 7.8461 -0.03%
13-Sep-18 7.8482 7.8489 7.8494 7.8475 -0.01%
12-Sep-18 7.8487 7.849 7.8495 7.848 -0.01%
11-Sep-18 7.8492 7.8498 7.8502 7.8491 -0.01%
10-Sep-18 7.8498 7.8494 7.8501 7.8494 0.00%
9-Sep-18 7.8498 7.8499 7.8499 7.8497 0.00%
7-Sep-18 7.8499 7.8494 7.8503 7.8492 0.01%
6-Sep-18 7.8494 7.8492 7.8499 7.8484 0.00%
5-Sep-18 7.8492 7.8496 7.8499 7.8488 0.00%
4-Sep-18 7.8492 7.8491 7.8498 7.848 0.00%
3-Sep-18 7.8494 7.8491 7.8498 7.8482 0.00%
2-Sep-18 7.8491 7.849 7.85 7.8479 0.00%
31-Aug-18 7.8491 7.849 7.8495 7.8479 0.00%
30-Aug-18 7.8491 7.8489 7.8498 7.8486 0.00%
29-Aug-18 7.8489 7.8498 7.8502 7.8483 -0.01%
28-Aug-18 7.8496 7.8498 7.8502 7.8491 0.00%
27-Aug-18 7.8498 7.8494 7.8501 7.8494 0.00%
26-Aug-18 7.8498 7.85 7.85 7.849 0.00%
24-Aug-18 7.8498 7.8502 7.8503 7.8496 0.00%
23-Aug-18 7.8499 7.8495 7.8502 7.8491 0.01%
25

22-Aug-18 7.8495 7.8494 7.8501 7.8491 0.00%
21-Aug-18 7.8495 7.8495 7.8499 7.8491 0.00%
20-Aug-18 7.8497 7.8496 7.8502 7.8492 0.00%
19-Aug-18 7.8496 7.8491 7.8502 7.8484 0.00%
17-Aug-18 7.8495 7.8496 7.8501 7.8491 -0.01%
16-Aug-18 7.8499 7.8502 7.8503 7.849 0.00%
15-Aug-18 7.8501 7.8496 7.8503 7.8494 0.00%
14-Aug-18 7.8499 7.8501 7.8503 7.8497 0.00%
13-Aug-18 7.8499 7.8497 7.8503 7.8495 0.01%
12-Aug-18 7.8495 7.8487 7.8498 7.8484 -0.01%
10-Aug-18 7.8499 7.8497 7.8503 7.8495 0.00%
9-Aug-18 7.8497 7.8492 7.8502 7.8489 0.01%
8-Aug-18 7.8492 7.85 7.8502 7.849 -0.01%
7-Aug-18 7.8497 7.8491 7.8501 7.8484 0.01%
6-Aug-18 7.8491 7.8491 7.8498 7.8483 0.00%
5-Aug-18 7.849 7.8489 7.8496 7.8488 0.00%
3-Aug-18 7.8491 7.8497 7.8501 7.8485 -0.01%
2-Aug-18 7.8496 7.8487 7.8498 7.848 0.01%
1-Aug-18 7.8486 7.8491 7.8499 7.8484 -0.01%
31-Jul-18 7.8491 7.8483 7.8494 7.8464 0.01%
30-Jul-18 7.8486 7.8479 7.8493 7.8473 0.01%
29-Jul-18 7.8482 7.8478 7.8483 7.8475 0.01%
27-Jul-18 7.8478 7.848 7.8493 7.8472 0.00%
26-Jul-18 7.848 7.8459 7.8488 7.8446 0.03%
25-Jul-18 7.8457 7.8468 7.8474 7.8449 -0.01%
24-Jul-18 7.8468 7.8486 7.8487 7.8452 -0.02%
23-Jul-18 7.8481 7.8498 7.8498 7.8475 -0.02%
22-Jul-18 7.8493 7.8504 7.8504 7.8492 -0.01%
20-Jul-18 7.8498 7.8499 7.8502 7.8484 0.00%
19-Jul-18 7.8496 7.8498 7.8501 7.8484 0.00%
18-Jul-18 7.8498 7.8487 7.8498 7.8483 0.01%
17-Jul-18 7.8489 7.849 7.8494 7.8482 0.00%
16-Jul-18 7.849 7.8485 7.8494 7.8483 0.01%
15-Jul-18 7.8484 7.8487 7.8487 7.8441 0.00%
13-Jul-18 7.8486 7.849 7.8494 7.8482 0.00%
12-Jul-18 7.8488 7.8491 7.8494 7.848 0.00%
11-Jul-18 7.8491 7.8486 7.8498 7.8483 0.01%
10-Jul-18 7.8483 7.8487 7.8494 7.8476 0.00%
9-Jul-18 7.8486 7.8482 7.8492 7.8475 0.01%
8-Jul-18 7.8482 7.8477 7.8495 7.8477 0.00%
6-Jul-18 7.8483 7.847 7.8494 7.8463 0.02%
5-Jul-18 7.8471 7.843 7.8479 7.8426 0.05%
4-Jul-18 7.8431 7.8452 7.8454 7.8421 -0.02%
3-Jul-18 7.845 7.8449 7.8464 7.8438 0.00%
2-Jul-18 7.8449 7.8463 7.8473 7.844 -0.03%
1-Jul-18 7.8473 7.8458 7.8473 7.8458 0.01%
26

29-Jun-18 7.8464 7.848 7.849 7.8449 -0.02%
28-Jun-18 7.8479 7.8479 7.8486 7.8468 0.00%
27-Jun-18 7.8479 7.849 7.8495 7.8463 -0.01%
26-Jun-18 7.849 7.8468 7.8495 7.8459 0.03%
25-Jun-18 7.8469 7.8456 7.8483 7.8452 0.00%
24-Jun-18 7.8468 7.8457 7.847 7.8455 0.01%
22-Jun-18 7.8464 7.8457 7.8471 7.8437 0.01%
21-Jun-18 7.846 7.8464 7.8468 7.8434 -0.01%
20-Jun-18 7.8464 7.8494 7.8495 7.8459 -0.04%
19-Jun-18 7.8492 7.8498 7.8501 7.8487 -0.01%
18-Jun-18 7.8497 7.8493 7.8501 7.8491 0.00%
17-Jun-18 7.8494 7.8484 7.8495 7.8484 0.00%
15-Jun-18 7.8493 7.8492 7.8501 7.8482 0.00%
14-Jun-18 7.8492 7.8485 7.8497 7.8471 0.01%
13-Jun-18 7.8483 7.8472 7.8489 7.8468 0.01%
12-Jun-18 7.8472 7.8468 7.8476 7.8458 0.01%
11-Jun-18 7.8465 7.8457 7.8471 7.8454 0.00%
10-Jun-18 7.8462 7.8452 7.8472 7.8452 0.01%
8-Jun-18 7.8457 7.8459 7.8465 7.8449 -0.01%
7-Jun-18 7.8461 7.8472 7.8475 7.8441 -0.02%
6-Jun-18 7.8475 7.8472 7.8479 7.8464 0.00%
5-Jun-18 7.8474 7.8457 7.8478 7.8453 0.02%
4-Jun-18 7.8456 7.8459 7.8473 7.8451 0.00%
3-Jun-18 7.8454 7.8445 7.8458 7.8445 0.00%
1-Jun-18 7.8453 7.8435 7.8468 7.8435 0.02%
31-May-18 7.8434 7.8475 7.8492 7.8411 -0.05%
30-May-18 7.8475 7.8454 7.848 7.8444 0.02%
29-May-18 7.8457 7.8453 7.8482 7.8445 0.01%
28-May-18 7.8453 7.8453 7.8469 7.843 0.01%
27-May-18 7.8446 7.8457 7.8462 7.8444 -0.01%
25-May-18 7.8457 7.8475 7.8479 7.8426 -0.03%
24-May-18 7.8479 7.8494 7.8494 7.8469 -0.02%
23-May-18 7.8495 7.8498 7.8499 7.8482 0.00%
22-May-18 7.8495 7.8484 7.8501 7.8472 0.01%
21-May-18 7.8487 7.8495 7.8501 7.848 -0.01%
18-May-18 7.8498 7.8499 7.8503 7.8495 0.00%
17-May-18 7.8498 7.8501 7.8501 7.8491 0.00%
16-May-18 7.8499 7.8498 7.8499 7.8494 0.00%
15-May-18 7.8499 7.8495 7.8501 7.8494 0.00%
14-May-18 7.8498 7.8495 7.8501 7.8492 0.00%
11-May-18 7.8498 7.8498 7.8502 7.8492 0.00%
10-May-18 7.8498 7.8498 7.8502 7.8492 0.00%
9-May-18 7.8499 7.8495 7.8499 7.8492 0.00%
8-May-18 7.8496 7.8496 7.8499 7.8491 0.00%
7-May-18 7.8498 7.8494 7.8499 7.849 0.01%
4-May-18 7.8492 7.8494 7.8499 7.849 0.00%
27

3-May-18 7.8494 7.8495 7.8498 7.8483 0.00%
2-May-18 7.8496 7.8494 7.8501 7.849 0.00%
1-May-18 7.8494 7.8484 7.8495 7.8483 0.01%
30-Apr-18 7.8484 7.8475 7.8492 7.8474 0.01%
27-Apr-18 7.8475 7.8457 7.8493 7.8457 0.02%
26-Apr-18 7.8457 7.8467 7.8484 7.8454 -0.01%
25-Apr-18 7.8467 7.8464 7.8491 7.8457 0.00%
24-Apr-18 7.8464 7.8418 7.848 7.8418 0.05%
23-Apr-18 7.8421 7.8441 7.8457 7.8415 -0.03%
20-Apr-18 7.8441 7.8479 7.8483 7.8435 -0.05%
19-Apr-18 7.8479 7.8498 7.8501 7.844 -0.03%
18-Apr-18 7.8499 7.8498 7.8499 7.8495 0.00%
17-Apr-18 7.8498 7.8498 7.8501 7.8491 0.00%
16-Apr-18 7.8499 7.8495 7.8501 7.8495 0.00%
13-Apr-18 7.8499 7.8498 7.8501 7.8495 0.00%
12-Apr-18 7.8499 7.8498 7.8503 7.8495 0.00%
11-Apr-18 7.8498 7.8496 7.8502 7.8492 0.00%
10-Apr-18 7.8495 7.8491 7.8498 7.8487 0.00%
9-Apr-18 7.8492 7.8483 7.8495 7.8479 0.01%
6-Apr-18 7.8484 7.8487 7.8495 7.8479 -0.01%
5-Apr-18 7.8488 7.849 7.8496 7.8487 0.00%
4-Apr-18 7.8491 7.8486 7.8495 7.8477 0.01%
3-Apr-18 7.8487 7.8486 7.8494 7.8482 0.00%
2-Apr-18 7.8487 7.8484 7.8488 7.8479 0.00%
30-Mar-18 7.8487 7.8484 7.8494 7.8475 0.00%
29-Mar-18 7.8484 7.8472 7.8491 7.8464 0.01%
28-Mar-18 7.8473 7.8465 7.8483 7.8454 0.01%
27-Mar-18 7.8468 7.846 7.8479 7.8457 0.01%
26-Mar-18 7.8459 7.8464 7.8487 7.8454 0.00%
23-Mar-18 7.846 7.848 7.8495 7.8452 -0.03%
22-Mar-18 7.848 7.8456 7.8483 7.8445 0.03%
21-Mar-18 7.8457 7.8444 7.8467 7.8441 0.02%
20-Mar-18 7.8445 7.8423 7.8449 7.8422 0.03%
19-Mar-18 7.8423 7.8426 7.8446 7.8418 -0.01%
16-Mar-18 7.8434 7.8421 7.8444 7.8415 0.02%
15-Mar-18 7.8416 7.8411 7.8423 7.84 0.01%
14-Mar-18 7.8411 7.8404 7.8419 7.8395 0.01%
13-Mar-18 7.8406 7.841 7.8412 7.8387 0.00%
12-Mar-18 7.8403 7.8376 7.841 7.8365 0.04%
9-Mar-18 7.8368 7.8411 7.8444 7.8366 -0.05%
8-Mar-18 7.8408 7.8354 7.8438 7.8331 0.07%
7-Mar-18 7.8355 7.8335 7.8366 7.8331 0.03%
6-Mar-18 7.8335 7.8323 7.8342 7.8312 0.02%
5-Mar-18 7.8323 7.8304 7.8336 7.83 0.02%
2-Mar-18 7.8305 7.8278 7.8323 7.827 0.03%
1-Mar-18 7.828 7.8261 7.8282 7.8251 0.02%
28

28-Feb-18 7.8263 7.8274 7.8299 7.825 -0.01%
27-Feb-18 7.8274 7.8233 7.8278 7.8228 0.05%
26-Feb-18 7.8236 7.8229 7.8244 7.8229 0.00%
23-Feb-18 7.8236 7.8243 7.8248 7.822 -0.01%
22-Feb-18 7.8243 7.8252 7.8274 7.8239 -0.01%
21-Feb-18 7.8254 7.8243 7.8258 7.8239 0.02%
20-Feb-18 7.8242 7.8217 7.825 7.8212 0.03%
19-Feb-18 7.8219 7.8216 7.8229 7.8209 -0.01%
16-Feb-18 7.8223 7.8205 7.8229 7.8197 0.02%
15-Feb-18 7.8205 7.8221 7.8235 7.8198 -0.03%
14-Feb-18 7.8225 7.8231 7.8231 7.8212 -0.01%
13-Feb-18 7.8232 7.8193 7.8238 7.8193 0.05%
12-Feb-18 7.8193 7.8185 7.8215 7.818 0.02%
9-Feb-18 7.8181 7.8214 7.8216 7.8179 -0.04%
8-Feb-18 7.8216 7.8182 7.8227 7.8174 0.04%
7-Feb-18 7.8182 7.8187 7.82 7.8178 -0.01%
6-Feb-18 7.8186 7.8205 7.8216 7.8182 -0.03%
5-Feb-18 7.8206 7.8201 7.8228 7.8197 -0.01%
2-Feb-18 7.8214 7.8195 7.8217 7.819 0.02%
1-Feb-18 7.8197 7.8231 7.8231 7.8194 -0.04%
31-Jan-18 7.8228 7.8209 7.8231 7.819 0.03%
30-Jan-18 7.8208 7.8177 7.821 7.8172 0.04%
29-Jan-18 7.8178 7.8181 7.8198 7.817 0.01%
26-Jan-18 7.8172 7.8177 7.8197 7.8168 -0.01%
25-Jan-18 7.8178 7.8183 7.8186 7.8159 -0.01%
24-Jan-18 7.8183 7.8187 7.8197 7.8171 -0.01%
23-Jan-18 7.8189 7.8182 7.8201 7.8167 0.01%
22-Jan-18 7.8183 7.8175 7.821 7.8163 0.02%
19-Jan-18 7.8166 7.8167 7.8209 7.8163 0.00%
18-Jan-18 7.8167 7.8181 7.8219 7.8151 -0.02%
The prices of Hong-Kong and US dollar value those changes from one period to
another as two year’s data is given above that starts from 2018 till April 2019 (Kraus,
Ribeiro-Soriano & Schüssler, 2018). The trend of the above data is analysed to know its
impact on the covered interest parity conditions of Hong-Kong. The prices of the currency
values show an increasing trend of all the daily values of the two years mentioned above. The
increasing value of the US and Hong-Kong dollar denotes the favourable market condition as
the external adversities are not affecting the currency value of these two countries (Bae,
Bhattacharya, Kang & Rhee, 2018).
29

US Dollar Hong Kong
Dollar
7.8452
7.8453
7.8427
7.8399
7.8422
7.8429
7.8426
7.8366
7.8415
7.8471
7.8495
7.8494
7.8491
7.8495
7.8498
7.8498
7.8499
7.8499
7.8498
7.8487
7.8494
7.8469
7.8474
7.8473
7.8473
7.8498
7.8498
7.8499
7.8499
7.8501
7.8499
7.8499
7.8499
7.8498
7.8499
7.8498
7.8499
7.8499
7.8498
7.8491
7.8489
30

7.8487
7.8499
7.8496
7.8491
7.8487
7.8479
7.8482
7.8472
7.8491
7.8487
7.8478
7.8481
7.8479
7.8472
7.8484
7.8486
7.8478
7.8468
7.8473
7.8476
7.8464
7.8454
7.8466
7.8456
7.8468
7.8468
7.8429
7.8461
7.846
7.8454
7.8457
7.8458
7.8453
7.8453
7.8453
7.844
7.8434
7.843
7.843
7.8433
7.8422
7.8396
7.8393
7.8385
7.8376
7.8388
31

7.8345
7.833
7.8345
7.8304
7.8332
7.8318
7.8316
7.8314
7.8304
7.8294
7.8285
7.8327
7.8327
7.8334
7.8327
7.8303
7.8267
7.8192
7.8126
7.8137
7.8133
7.8125
7.8134
7.817
7.8156
7.8164
7.816
7.8106
7.8129
7.8036
7.8153
7.8224
7.8236
7.8217
7.8255
7.8266
7.8235
7.8263
7.8257
7.8305
7.8332
7.8303
7.832
7.8305
7.8293
7.8294
32

7.8313
7.8307
7.8342
7.8315
7.8323
7.8266
7.8304
7.8317
7.8315
7.8239
7.8172
7.8339
7.8411
7.8435
7.843
7.8406
7.8407
7.8408
7.8408
7.8385
7.8395
7.8407
7.8412
7.8384
7.8392
7.8362
7.8349
7.8347
7.8347
7.8345
7.8372
7.8332
7.8285
7.8363
7.835
7.8351
7.8377
7.8334
7.8271
7.8286
7.8281
7.8155
7.8128
7.8105
7.8129
7.8112
33

7.8092
7.8426
7.8453
7.8434
7.8444
7.8466
7.8461
7.8482
7.8487
7.8492
7.8498
7.8498
7.8499
7.8494
7.8492
7.8492
7.8494
7.8491
7.8491
7.8491
7.8489
7.8496
7.8498
7.8498
7.8498
7.8499
7.8495
7.8495
7.8497
7.8496
7.8495
7.8499
7.8501
7.8499
7.8499
7.8495
7.8499
7.8497
7.8492
7.8497
7.8491
7.849
7.8491
7.8496
7.8486
7.8491
34

7.8486
7.8482
7.8478
7.848
7.8457
7.8468
7.8481
7.8493
7.8498
7.8496
7.8498
7.8489
7.849
7.8484
7.8486
7.8488
7.8491
7.8483
7.8486
7.8482
7.8483
7.8471
7.8431
7.845
7.8449
7.8473
7.8464
7.8479
7.8479
7.849
7.8469
7.8468
7.8464
7.846
7.8464
7.8492
7.8497
7.8494
7.8493
7.8492
7.8483
7.8472
7.8465
7.8462
7.8457
7.8461
35

7.8475
7.8474
7.8456
7.8454
7.8453
7.8434
7.8475
7.8457
7.8453
7.8446
7.8457
7.8479
7.8495
7.8495
7.8487
7.8498
7.8498
7.8499
7.8499
7.8498
7.8498
7.8498
7.8499
7.8496
7.8498
7.8492
7.8494
7.8496
7.8494
7.8484
7.8475
7.8457
7.8467
7.8464
7.8421
7.8441
7.8479
7.8499
7.8498
7.8499
7.8499
7.8499
7.8498
7.8495
7.8492
7.8484
36

7.8488
7.8491
7.8487
7.8487
7.8487
7.8484
7.8473
7.8468
7.8459
7.846
7.848
7.8457
7.8445
7.8423
7.8434
7.8416
7.8411
7.8406
7.8403
7.8368
7.8408
7.8355
7.8335
7.8323
7.8305
7.828
7.8263
7.8274
7.8236
7.8236
7.8243
7.8254
7.8242
7.8219
7.8223
7.8205
7.8225
7.8232
7.8193
7.8181
7.8216
7.8182
7.8186
7.8206
7.8214
7.8197
37

7.8228
7.8208
7.8178
7.8172
7.8178
7.8183
7.8189
7.8183
7.8166
7.8167
Table 1 Currency prices of USD-HKD
US Dollar Hong Kong Dollar
Mean 7.840261
Standard Error 0.000587
Median 7.84585
Mode 7.8499
Standard Deviation 0.011326
Sample Variance 0.000128
Kurtosis 0.111343
Skewness -1.14435
Range 0.0465
Minimum 7.8036
Maximum 7.8501
Sum 2916.577
Count 372
Confidence Level (95.0%) 0.001155
Table 2 Descriptive statistics of currency prices
Descriptive statistics tool in the data analysis section of Ms excel is considered as a
detailed analysis of a variable to a research study as this analysis tool comprises of several
measures of statistics such as central tendency and measures of dispersion (Levine and et al.,
2018). Mean, median and mode covered under the measures of the central tendency and
standard deviation skewness and other tools form part of the measure of dispersion. The
motive of this entire tool is to determine the trend of the prices of the two of the currency
values (Hughes and et al., 2018).
Mean of the currency prices is 7.840261 which is the average of the total currency
prices of two of the strong entities under which one is domestic and the other one is a foreign
country (Wang & Chen, 2018). This shows that on an average the prices will achieve this
value which signifies its efficiency apart from external adversities or unfavourable condition
the currency will reach this particular value. Median of this data is 7.84585 that are the
38

middle value of the data sets mention above signifies its effectiveness that increases from
period to period (Mooi, Sarstedt & Mooi-Reci, 2018). The less standard deviation shows its
farness from its mean by depicting the differences among the data and the mean of the same
(Neri, 2018). The skewness shows a negative value that means no chances of incurring
fluctuations in the future period as positive values of the skewness shows the fluctuations in
the value of the currencies.
Open
7.8453
7.8435
7.8398
7.8429
7.8429
7.8426
7.8365
7.8414
7.8471
7.8492
7.8492
7.8492
7.8491
7.8498
7.8496
7.8496
7.8499
7.8501
7.8488
7.8492
7.8468
7.8472
7.8474
7.8473
7.8498
7.8499
7.8498
7.8501
7.85
7.8498
7.8496
7.8499
39

7.8498
7.8497
7.8498
7.8499
7.8497
7.8497
7.8491
7.8487
7.8488
7.8498
7.8494
7.8491
7.8487
7.8483
7.8481
7.8472
7.8491
7.8487
7.8479
7.8481
7.8479
7.8472
7.8484
7.8484
7.8478
7.8471
7.8474
7.8476
7.8463
7.8454
7.8467
7.8469
7.8467
7.8467
7.8438
7.8463
7.8457
7.8453
7.8453
7.8457
7.8453
7.8461
7.8454
7.8437
7.8433
7.8429
40

7.8457
7.8431
7.8425
7.8393
7.8394
7.8384
7.8376
7.8388
7.8344
7.8341
7.8344
7.8308
7.8331
7.8312
7.8313
7.8304
7.831
7.8303
7.8286
7.8323
7.8328
7.8323
7.8323
7.8301
7.8265
7.8192
7.8132
7.8128
7.8129
7.8127
7.8135
7.8171
7.8155
7.8156
7.8151
7.8105
7.8129
7.8037
7.8152
7.824
7.8241
7.822
7.8254
7.8262
7.8235
7.8261
41

7.8254
7.8307
7.8331
7.8301
7.8319
7.8296
7.8298
7.8293
7.8305
7.8305
7.8338
7.8319
7.8317
7.8266
7.83
7.8315
7.8315
7.8172
7.8232
7.8338
7.8412
7.8434
7.8433
7.8407
7.8402
7.8407
7.8407
7.8385
7.8393
7.8403
7.8408
7.8384
7.8392
7.8361
7.835
7.8331
7.8325
7.8343
7.837
7.8334
7.8285
7.8346
7.835
7.835
7.8377
7.8332
42

7.827
7.8281
7.8268
7.8155
7.8126
7.8105
7.8114
7.8092
7.8111
7.8426
7.8448
7.8431
7.8444
7.8459
7.8468
7.8482
7.8489
7.849
7.8498
7.8494
7.8499
7.8494
7.8492
7.8496
7.8491
7.8491
7.849
7.849
7.8489
7.8498
7.8498
7.8494
7.85
7.8502
7.8495
7.8494
7.8495
7.8496
7.8491
7.8496
7.8502
7.8496
7.8501
7.8497
7.8487
7.8497
43

7.8492
7.85
7.8491
7.8491
7.8489
7.8497
7.8487
7.8491
7.8483
7.8479
7.8478
7.848
7.8459
7.8468
7.8486
7.8498
7.8504
7.8499
7.8498
7.8487
7.849
7.8485
7.8487
7.849
7.8491
7.8486
7.8487
7.8482
7.8477
7.847
7.843
7.8452
7.8449
7.8463
7.8458
7.848
7.8479
7.849
7.8468
7.8456
7.8457
7.8457
7.8464
7.8494
7.8498
7.8493
44

7.8484
7.8492
7.8485
7.8472
7.8468
7.8457
7.8452
7.8459
7.8472
7.8472
7.8457
7.8459
7.8445
7.8435
7.8475
7.8454
7.8453
7.8453
7.8457
7.8475
7.8494
7.8498
7.8484
7.8495
7.8499
7.8501
7.8498
7.8495
7.8495
7.8498
7.8498
7.8495
7.8496
7.8494
7.8494
7.8495
7.8494
7.8484
7.8475
7.8457
7.8467
7.8464
7.8418
7.8441
7.8479
7.8498
45

7.8498
7.8498
7.8495
7.8498
7.8498
7.8496
7.8491
7.8483
7.8487
7.849
7.8486
7.8486
7.8484
7.8484
7.8472
7.8465
7.846
7.8464
7.848
7.8456
7.8444
7.8423
7.8426
7.8421
7.8411
7.8404
7.841
7.8376
7.8411
7.8354
7.8335
7.8323
7.8304
7.8278
7.8261
7.8274
7.8233
7.8229
7.8243
7.8252
7.8243
7.8217
7.8216
7.8205
7.8221
7.8231
46

7.8193
7.8185
7.8214
7.8182
7.8187
7.8205
7.8201
7.8195
7.8231
7.8209
7.8177
7.8181
7.8177
7.8183
7.8187
7.8182
7.8175
7.8167
7.8181
Open
Mean 7.840122
Standard Error 0.000592
Median 7.8457
Mode 7.8498
Standard
Deviation 0.011418
Sample Variance 0.00013
Kurtosis 0.041185
Skewness -1.12353
Range 0.0467
Minimum 7.8037
Maximum 7.8504
Sum 2916.525
Count 372
Confidence Level
(95.0%) 0.001164
The descriptive statistics shows that the opening prices of the historical data of two of
the currency values are showing fluctuated a value which starts declining in the beginning
and again rise to higher value (Cheung, Chinn, Pascual & Zhang, 2018). 7.84 mean is booked
by this data which is an average value of the entire data sets. Mode is a measure of a central
tendency records the repetitive values in the currency value that 7.8498 values is highly
47

repeats in the entire data sets. All the flavours of the analysis such as increasing, declining
and stability has witnessed in the data sets of US and Hong-Kong data values of two
currencies.
High
7.8467
7.846
7.8441
7.8453
7.8435
7.8473
7.8449
7.8426
7.8476
7.8498
7.8495
7.8501
7.8495
7.8501
7.8502
7.8499
7.8499
7.8504
7.8501
7.8498
7.8495
7.8491
7.8479
7.848
7.8498
7.8501
7.8501
7.8501
7.85
7.8503
7.8501
7.85
7.8503
7.85
7.8499
7.8502
48

7.85
7.8501
7.8499
7.8498
7.849
7.8499
7.8499
7.8498
7.8498
7.8494
7.8484
7.8491
7.8492
7.8495
7.8494
7.8485
7.8481
7.8486
7.8487
7.8491
7.8489
7.8488
7.8474
7.8479
7.8479
7.8468
7.8467
7.8472
7.847
7.8476
7.8472
7.8466
7.8468
7.8467
7.8457
7.8469
7.8472
7.8472
7.8469
7.846
7.8449
7.845
7.8457
7.8457
7.8444
7.844
49

7.8405
7.8421
7.8403
7.8411
7.8394
7.8376
7.8347
7.8358
7.8355
7.8377
7.8319
7.8338
7.832
7.8343
7.8353
7.8338
7.8342
7.8347
7.8346
7.8346
7.8316
7.8273
7.8216
7.8153
7.8149
7.818
7.8156
7.8179
7.8175
7.8164
7.8167
7.8174
7.8177
7.816
7.8181
7.8257
7.8256
7.8266
7.8274
7.8286
7.8299
7.827
7.8269
7.8307
7.8332
7.8335
50

7.8335
7.8335
7.8309
7.8335
7.8343
7.8335
7.8349
7.835
7.8329
7.8332
7.8328
7.8351
7.8372
7.8362
7.8249
7.8391
7.8441
7.8476
7.8468
7.8438
7.8408
7.8415
7.8414
7.8423
7.8406
7.8414
7.8414
7.8421
7.8399
7.8399
7.838
7.838
7.8354
7.8369
7.838
7.838
7.8351
7.8368
7.8363
7.8374
7.8393
7.8396
7.8384
7.83
7.8286
7.829
51

7.8167
7.8187
7.8136
7.8136
7.8121
7.8434
7.8457
7.8469
7.8459
7.8486
7.847
7.8491
7.8494
7.8495
7.8502
7.8501
7.8499
7.8503
7.8499
7.8499
7.8498
7.8498
7.85
7.8495
7.8498
7.8502
7.8502
7.8501
7.85
7.8503
7.8502
7.8501
7.8499
7.8502
7.8502
7.8501
7.8503
7.8503
7.8503
7.8503
7.8498
7.8503
7.8502
7.8502
7.8501
7.8498
52

7.8496
7.8501
7.8498
7.8499
7.8494
7.8493
7.8483
7.8493
7.8488
7.8474
7.8487
7.8498
7.8504
7.8502
7.8501
7.8498
7.8494
7.8494
7.8487
7.8494
7.8494
7.8498
7.8494
7.8492
7.8495
7.8494
7.8479
7.8454
7.8464
7.8473
7.8473
7.849
7.8486
7.8495
7.8495
7.8483
7.847
7.8471
7.8468
7.8495
7.8501
7.8501
7.8495
7.8501
7.8497
7.8489
53

7.8476
7.8471
7.8472
7.8465
7.8475
7.8479
7.8478
7.8473
7.8458
7.8468
7.8492
7.848
7.8482
7.8469
7.8462
7.8479
7.8494
7.8499
7.8501
7.8501
7.8503
7.8501
7.8499
7.8501
7.8501
7.8502
7.8502
7.8499
7.8499
7.8499
7.8499
7.8498
7.8501
7.8495
7.8492
7.8493
7.8484
7.8491
7.848
7.8457
7.8483
7.8501
7.8499
7.8501
7.8501
7.8501
54

7.8503
7.8502
7.8498
7.8495
7.8495
7.8496
7.8495
7.8494
7.8488
7.8494
7.8491
7.8483
7.8479
7.8487
7.8495
7.8483
7.8467
7.8449
7.8446
7.8444
7.8423
7.8419
7.8412
7.841
7.8444
7.8438
7.8366
7.8342
7.8336
7.8323
7.8282
7.8299
7.8278
7.8244
7.8248
7.8274
7.8258
7.825
7.8229
7.8229
7.8235
7.8231
7.8238
7.8215
7.8216
7.8227
55

7.82
7.8216
7.8228
7.8217
7.8231
7.8231
7.821
7.8198
7.8197
7.8186
7.8197
7.8201
7.821
7.8209
7.8219
Table 3 Opening prices of USD and HKD
High
Mean 7.841951
Standard Error 0.000539
Median 7.8473
Mode 7.8501
Standard
Deviation 0.010387
Sample Variance 0.000108
Kurtosis 0.218283
Skewness -1.22193
Range 0.0383
Minimum 7.8121
Maximum 7.8504
Sum 2917.206
Count 372
Confidence Level
(95.0%) 0.001059
Table 4 Descriptive statistics of opening prices of USD and HKD
This analysis shows the higher currency values of two currency’s data sets depicting
the higher prices of US and Hong-Kong dollar currency values. This data set shows the
higher values which are analysed by applying this tool (Suzuki, Yasunaga, Matsui, Fushimi
& Yamasoba, 2018). The high values of the data evaluated by a researcher by applying this
tool.
56

Low
7.8439
7.8425
7.8376
7.8373
7.8422
7.8395
7.836
7.8301
7.8407
7.845
7.8492
7.8486
7.8475
7.8486
7.8491
7.8492
7.8498
7.8498
7.8486
7.8483
7.8467
7.8456
7.8471
7.8452
7.8452
7.8495
7.8494
7.8486
7.8492
7.8483
7.8492
7.8497
7.8494
7.8491
7.8498
7.8497
7.849
7.8495
7.849
7.8486
7.8485
57

7.8476
7.8488
7.8488
7.8483
7.8478
7.8475
7.8468
7.846
7.8483
7.8475
7.8472
7.8479
7.8471
7.8468
7.8476
7.8465
7.8463
7.8464
7.845
7.845
7.8449
7.8445
7.8441
7.8456
7.8434
7.8404
7.8375
7.8454
7.845
7.8452
7.8448
7.8444
7.8449
7.845
7.8427
7.8428
7.8427
7.8422
7.8429
7.8411
7.8393
7.8394
7.8381
7.8369
7.8366
7.8343
58

7.8328
7.833
7.8274
7.83
7.8308
7.8307
7.8289
7.8308
7.8282
7.8267
7.8274
7.832
7.8284
7.8322
7.8239
7.8238
7.8187
7.8125
7.8112
7.811
7.8075
7.8076
7.8129
7.8125
7.8121
7.8148
7.8082
7.808
7.8023
7.8011
7.8149
7.8224
7.819
7.8212
7.8239
7.8205
7.8205
7.8248
7.8232
7.8277
7.8293
7.83
7.8293
7.8296
7.8281
7.8285
59

7.8301
7.8277
7.8286
7.8312
7.8263
7.8242
7.8281
7.828
7.8172
7.8172
7.8125
7.8338
7.8387
7.8425
7.8399
7.8399
7.8384
7.8362
7.838
7.8379
7.838
7.8393
7.838
7.8379
7.836
7.8341
7.8331
7.8325
7.8319
7.8341
7.8328
7.8271
7.8231
7.8346
7.8319
7.8309
7.8331
7.8269
7.8257
7.8256
7.8149
7.8045
7.8045
7.8084
7.7977
7.8058
60

7.7928
7.8422
7.8431
7.843
7.8431
7.8464
7.8461
7.8475
7.848
7.8491
7.8494
7.8497
7.8492
7.8484
7.8488
7.848
7.8482
7.8479
7.8479
7.8486
7.8483
7.8491
7.8494
7.849
7.8496
7.8491
7.8491
7.8491
7.8492
7.8484
7.8491
7.849
7.8494
7.8497
7.8495
7.8484
7.8495
7.8489
7.849
7.8484
7.8483
7.8488
7.8485
7.848
7.8484
7.8464
61

7.8473
7.8475
7.8472
7.8446
7.8449
7.8452
7.8475
7.8492
7.8484
7.8484
7.8483
7.8482
7.8483
7.8441
7.8482
7.848
7.8483
7.8476
7.8475
7.8477
7.8463
7.8426
7.8421
7.8438
7.844
7.8458
7.8449
7.8468
7.8463
7.8459
7.8452
7.8455
7.8437
7.8434
7.8459
7.8487
7.8491
7.8484
7.8482
7.8471
7.8468
7.8458
7.8454
7.8452
7.8449
7.8441
62

7.8464
7.8453
7.8451
7.8445
7.8435
7.8411
7.8444
7.8445
7.843
7.8444
7.8426
7.8469
7.8482
7.8472
7.848
7.8495
7.8491
7.8494
7.8494
7.8492
7.8492
7.8492
7.8492
7.8491
7.849
7.849
7.8483
7.849
7.8483
7.8474
7.8457
7.8454
7.8457
7.8418
7.8415
7.8435
7.844
7.8495
7.8491
7.8495
7.8495
7.8495
7.8492
7.8487
7.8479
7.8479
63

7.8487
7.8477
7.8482
7.8479
7.8475
7.8464
7.8454
7.8457
7.8454
7.8452
7.8445
7.8441
7.8422
7.8418
7.8415
7.84
7.8395
7.8387
7.8365
7.8366
7.8331
7.8331
7.8312
7.83
7.827
7.8251
7.825
7.8228
7.8229
7.822
7.8239
7.8239
7.8212
7.8209
7.8197
7.8198
7.8212
7.8193
7.818
7.8179
7.8174
7.8178
7.8182
7.8197
7.819
7.8194
64

7.819
7.8172
7.817
7.8168
7.8159
7.8171
7.8167
7.8163
7.8163
7.8151
Table 5 Low prices
Low
Mean 7.83836
Standard Error 0.000647
Median 7.8445
Mode 7.8492
Standard
Deviation 0.012482
Sample Variance 0.000156
Kurtosis 0.449799
Skewness -1.17813
Range 0.057
Minimum 7.7928
Maximum 7.8498
Sum 2915.87
Count 372
Confidence Level
(95.0%) 0.001273
Table 6 Descriptive statistics of low prices
Value of means, median and mode shows the effectiveness of the data and also show
that the changes will occur in the future (Leucht, Chaimani & Leucht, 2018). Witnessing low
fluctuations in the currency value wants by all the economies so is by the economy of US and
Hong-Kong economies. These two wants to increase its currency value but do not want
frequent changes to be takes places (Sung, 2018).
% changes
0.00%
0.03%
0.04%
65

-0.03%
-0.01%
0.00%
0.08%
-0.06%
-0.07%
-0.03%
0.00%
0.00%
-0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.01%
-0.01%
0.03%
-0.01%
0.00%
0.00%
-0.03%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.01%
0.00%
0.00%
-0.02%
0.00%
0.01%
0.01%
0.01%
0.00%
0.01%
-0.02%
66

0.01%
0.01%
0.00%
0.00%
0.01%
-0.02%
0.00%
0.01%
0.01%
-0.01%
0.00%
0.02%
0.01%
-0.02%
0.01%
-0.02%
0.00%
0.05%
-0.04%
0.00%
0.01%
0.00%
0.00%
0.01%
0.00%
0.00%
0.02%
0.01%
0.01%
0.00%
0.00%
0.01%
0.03%
0.00%
0.01%
0.01%
-0.02%
0.05%
0.02%
-0.02%
0.05%
-0.04%
0.02%
0.00%
0.00%
0.01%
67

0.01%
0.01%
-0.05%
0.00%
-0.01%
0.01%
0.03%
0.05%
0.10%
0.08%
-0.01%
0.01%
0.01%
-0.01%
-0.05%
0.02%
-0.01%
0.01%
0.07%
-0.03%
0.12%
-0.15%
-0.09%
-0.02%
0.02%
-0.05%
-0.01%
0.04%
-0.04%
0.01%
-0.06%
-0.03%
0.04%
-0.02%
0.02%
0.02%
0.00%
-0.02%
0.01%
-0.04%
0.03%
-0.01%
0.07%
-0.05%
-0.02%
0.00%
68

0.10%
0.09%
-0.21%
-0.09%
-0.03%
0.01%
0.03%
0.00%
0.00%
0.00%
0.03%
-0.01%
-0.02%
-0.01%
0.04%
-0.01%
0.04%
0.02%
0.00%
0.00%
0.00%
-0.03%
0.05%
0.06%
-0.10%
0.02%
0.00%
-0.03%
0.05%
0.08%
-0.02%
0.01%
0.16%
0.03%
0.03%
-0.03%
0.02%
0.03%
-0.43%
-0.03%
0.02%
-0.01%
-0.03%
0.01%
-0.03%
-0.01%
69

-0.01%
-0.01%
0.00%
0.00%
0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
-0.01%
0.00%
0.00%
0.00%
0.00%
0.01%
0.00%
0.00%
0.00%
0.00%
-0.01%
0.00%
0.00%
0.00%
0.01%
-0.01%
0.00%
0.01%
-0.01%
0.01%
0.00%
0.00%
-0.01%
0.01%
-0.01%
0.01%
0.01%
0.01%
0.00%
0.03%
-0.01%
-0.02%
-0.02%
-0.01%
70

0.00%
0.00%
0.01%
0.00%
0.01%
0.00%
0.00%
0.00%
0.01%
0.00%
0.01%
0.00%
0.02%
0.05%
-0.02%
0.00%
-0.03%
0.01%
-0.02%
0.00%
-0.01%
0.03%
0.00%
0.01%
0.01%
-0.01%
-0.04%
-0.01%
0.00%
0.00%
0.00%
0.01%
0.01%
0.01%
0.00%
0.01%
-0.01%
-0.02%
0.00%
0.02%
0.00%
0.00%
0.02%
-0.05%
0.02%
0.01%
71

0.01%
-0.01%
-0.03%
-0.02%
0.00%
0.01%
-0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.01%
0.00%
0.00%
0.00%
0.01%
0.01%
0.02%
-0.01%
0.00%
0.05%
-0.03%
-0.05%
-0.03%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.01%
-0.01%
0.00%
0.01%
0.00%
0.00%
0.00%
0.01%
0.01%
0.01%
72

0.00%
-0.03%
0.03%
0.02%
0.03%
-0.01%
0.02%
0.01%
0.01%
0.00%
0.04%
-0.05%
0.07%
0.03%
0.02%
0.02%
0.03%
0.02%
-0.01%
0.05%
0.00%
-0.01%
-0.01%
0.02%
0.03%
-0.01%
0.02%
-0.03%
-0.01%
0.05%
0.02%
-0.04%
0.04%
-0.01%
-0.03%
-0.01%
0.02%
-0.04%
0.03%
0.04%
0.01%
-0.01%
-0.01%
-0.01%
0.01%
0.02%
73

0.00%
-0.02%
Table 7 % changes in prices
The change in the prices is observed in the form of percentages by considering the
opening, high and low prices and finally presents in the form of change. This value is
showing negative figures as the changes are positive as this will result in the decreasing
prices from period to period. The reason for this decrease is also analysed with the help of
this analysis that the currency price gets declines due to some of the reasons. This will
include economic pressures, inflation rates, higher interest rates, changes in the international
money market; higher foreign exchange rates (Keynes, 2018). All these reasons held
responsible for the decreasing value of the US and Hong-Kong dollar’s value as the current
status is also compared with the positions of other counties such as USD and Japan’s
currency to draw a difference between its values. In Hong-Kong, two monetary systems
followed where one is of the nation itself and the other one is of Japan who regulates the
monetary system of this country. Due to a minute change in the external market, this country
gets affected majorly as this nation follow two different monetary systems that affect the
entire economy and all its users. The reasons behind the above condition say that the country
should think about its community users by introducing policies in favour of its users to
generate positive results by overcoming all the difficulties.
4.2 USDHKD Interest rates analysis using regression
Regression Statistics
Multiple R 0.78558
R Square 0.617135
Adjusted R Square 0.589358
Standard Error 0.003229
Observations 37
Table 8 Regression Statistics
ANOVA
df SS MS F
Significan
ce F
Regressi
on 1
0.00060
5
0.00060
5
58.0280
3 6.21E-09
Residual 36
0.00037
5
1.04E-
05
Total 37
0.00098
1
Coefficien Standar t Stat P-value Lower Upper Lower Upper
74

ts d Error 95% 95% 95.0% 95.0%
Intercept 0 #N/A #N/A #N/A #N/A #N/A #N/A #N/A
-0.02186 0.272637 0.03579
7.61761
3
5.17E-
09 0.200051
0.34522
3
0.20005
1
0.34522
3
Table 9 ANOVA
RESIDUAL OUTPUT
Observation Predicted -0.00199 Residuals Standard Residuals
1 -0.00597 0.003968 1.245726
2 -0.00518 0.003433 1.077706
3 -0.00519 0.003434 1.077991
4 -0.00511 0.003112 0.976967
5 -0.00519 0.001096 0.34394
6 -0.00446 -0.0002 -0.06354
7 -0.00556 0.003386 1.063112
8 -0.0052 0.003189 1.001217
9 -0.00491 0.002077 0.652202
10 -0.00506 0.003643 1.143646
11 -0.00449 0.000848 0.266098
12 -0.0052 0.000372 0.116759
13 -0.00506 0.000537 0.168717
14 -0.00461 -0.00113 -0.35466
15 -0.00497 0.000767 0.240933
16 -0.00449 -0.00033 -0.10435
17 -0.00385 -0.00065 -0.20332
18 -0.00389 -0.00123 -0.38684
19 -0.00412 -0.0004 -0.12401
20 -0.00411 -0.0005 -0.1574
21 -0.00406 -0.00167 -0.52527
22 -0.00414 -0.00284 -0.89117
23 -0.00347 -0.00212 -0.66534
24 -0.00383 -0.00101 -0.31862
25 -0.00322 -0.00269 -0.84541
26 -0.00322 -0.00297 -0.93331
27 -0.00319 -0.00304 -0.95528
28 -0.00225 -0.00372 -1.16895
29 -0.00191 -0.01109 -3.48209
30 -0.00155 -0.00477 -1.49709
31 -0.00155 -0.00477 -1.49709
32 -0.00103 -0.00318 -0.9973
33 -0.00103 -0.00318 -0.9973
34 -0.00148 -0.00199 -0.62547
75

35 -0.00255 -0.00371 -1.16499
36 -0.00204 -0.00174 -0.54647
37 -0.00358 -0.00393 -1.23302
Table 10 RESIDUAL OUTPUT
PROBABILITY OUTPUT
Percentile -0.00199
1.351351 -0.013
4.054054 -0.00751
6.756757 -0.00698
9.459459 -0.00632
12.16216 -0.00632
14.86486 -0.00626
17.56757 -0.00623
20.27027 -0.00619
22.97297 -0.00597
25.67568 -0.00591
28.37838 -0.00574
31.08108 -0.00573
33.78378 -0.00559
36.48649 -0.00512
39.18919 -0.00484
41.89189 -0.00483
44.59459 -0.00482
47.2973 -0.00466
50 -0.00461
52.7027 -0.00452
55.40541 -0.00452
58.10811 -0.0045
60.81081 -0.00421
63.51351 -0.00421
66.21622 -0.0042
68.91892 -0.00409
71.62162 -0.00378
74.32432 -0.00364
77.02703 -0.00347
79.72973 -0.00283
82.43243 -0.00217
85.13514 -0.00201
87.83784 -0.002
90.54054 -0.002
93.24324 -0.00176
76

95.94595 -0.00175
98.64865 -0.00142
Table 11 PROBABILITY OUTPUT
-2.50% -2.00% -1.50% -1.00% -0.50% 0.00%
-0.012
-0.01
-0.008
-0.006
-0.004
-0.002
0
0.002
0.004
0.006
-0.02186 Residual Plot
-0.02186
Residuals
Table 12 Residual Plot
0 20 40 60 80 100 120
-0.014
-0.012
-0.01
-0.008
-0.006
-0.004
-0.002
0
Normal Probability Plot
Sample Percentile
-0.00199
Table 13 Normal Probability plot
R square and R adjusted value show a positive result which is a sign that the data will
fits on a linear regression line plot. A higher value of R square is required to reflect the
efficiency of the data sets as it is important to collect the un-basic data without getting
affected from the internal or external points as it can say that the data is not collected from
unauthentic sources to affect its final results. The residual plot shows an un-systematic
arrangement of data where the data is not arranged in a systematic way that will affect its
entire data collection and its final results. The motto of a user behind conducting this analysis
is to generate a favourable result that meets all its objectives within a stipulated time period.
77

The estimated result of the regression analysis shows the negative value which is not a
sign of a proper analysis as this can be due to the inclusion of biased data in the analysis.
Getting unfavourable results will, in turn, shows weaknesses lies in the current proves of
research due to which negative results come up in a bigger picture. The normal probability
plot uses percentile parameter in analysing the estimated results of this analysis as to find or
the cause root of unfavourable results as increasing or decreasing estimated results can be
rectified but at the same time, negative results cannot be corrected. The reasons of this
negative and unfavourable result are due to the unbiased collection of data, wrong percentile
values, economic changes, changes in the international finance market, exchange rates of the
forex market, swap spreads. These are the reasons that decline in the regression analysis
under which the unfavourable results arise due to the changes takes places in the internal as
well as in the external market.
4.3 Spot exchange rates
16/04/2019 1 HKD = 0.1275
15/04/2019 1 HKD = 0.1275
14/04/2019 1 HKD = 0.1275
13/04/2019 1 HKD = 0.1275
12/4/2019 1 HKD = 0.1275
11/4/2019 1 HKD = 0.1275
10/4/2019 1 HKD = 0.1276
9/4/2019 1 HKD = 0.1275
8/4/2019 1 HKD = 0.1274
7/4/2019 1 HKD = 0.1274
6/4/2019 1 HKD = 0.1274
5/4/2019 1 HKD = 0.1274
4/4/2019 1 HKD = 0.1274
3/4/2019 1 HKD = 0.1274
2/4/2019 1 HKD = 0.1274
1/4/2019 1 HKD = 0.1274
31/03/2019 1 HKD = 0.1274
30/03/2019 1 HKD = 0.1274
29/03/2019 1 HKD = 0.1274
28/03/2019 1 HKD = 0.1274
27/03/2019 1 HKD = 0.1274
78

26/03/2019 1 HKD = 0.1274
25/03/2019 1 HKD = 0.1274
24/03/2019 1 HKD = 0.1274
23/03/2019 1 HKD = 0.1274
22/03/2019 1 HKD = 0.1274
21/03/2019 1 HKD = 0.1274
20/03/2019 1 HKD = 0.1274
19/03/2019 1 HKD = 0.1274
18/03/2019 1 HKD = 0.1274
17/03/2019 1 HKD = 0.1274
16/03/2019 1 HKD = 0.1274
15/03/2019 1 HKD = 0.1274
14/03/2019 1 HKD = 0.1274
13/03/2019 1 HKD = 0.1274
12/3/2019 1 HKD = 0.1274
11/3/2019 1 HKD = 0.1274
10/3/2019 1 HKD = 0.127
9/3/2019 1 HKD = 0.1274
8/3/2019 1 HKD = 0.1274
7/3/2019 1 HKD = 0.1274
6/3/2019 1 HKD = 0.1274
5/3/2019 1 HKD = 0.1274
4/3/2019 1 HKD = 0.1274
3/3/2019 1 HKD = 0.1274
2/3/2019 1 HKD = 0.1274
1/3/2019 1 HKD = 0.1274
28/02/2019 1 HKD = 0.1274
27/02/2019 1 HKD = 0.1274
26/02/2019 1 HKD = 0.1274
25/02/2019 1 HKD = 0.1274
24/02/2019 1 HKD = 0.1274
23/02/2019 1 HKD = 0.1274
22/02/2019 1 HKD = 0.1274
21/02/2019 1 HKD = 0.1274
20/02/2019 1 HKD = 0.1274
79

19/02/2019 1 HKD = 0.1274
18/02/2019 1 HKD = 0.1274
17/02/2019 1 HKD = 0.1274
16/02/2019 1 HKD = 0.1274
15/02/2019 1 HKD = 0.1274
14/02/2019 1 HKD = 0.1274
13/02/2019 1 HKD = 0.1274
12/2/2019 1 HKD = 0.1274
11/2/2019 1 HKD = 0.1274
10/2/2019 1 HKD = 0.1274
9/2/2019 1 HKD = 0.1274
8/2/2019 1 HKD = 0.1274
7/2/2019 1 HKD = 0.1274
6/2/2019 1 HKD = 0.1274
5/2/2019 1 HKD = 0.1275
4/2/2019 1 HKD = 0.1274
3/2/2019 1 HKD = 0.1275
2/2/2019 1 HKD = 0.1274
1/2/2019 1 HKD = 0.1274
31/01/2019 1 HKD = 0.1274
30/01/2019 1 HKD = 0.1275
29/01/2019 1 HKD = 0.1274
28/01/2019 1 HKD = 0.1274
27/01/2019 1 HKD = 0.1275
26/01/2019 1 HKD = 0.1275
25/01/2019 1 HKD = 0.1275
24/01/2019 1 HKD = 0.1275
23/01/2019 1 HKD = 0.1275
22/01/2019 1 HKD = 0.1275
21/01/2019 1 HKD = 0.1275
20/01/2019 1 HKD = 0.1275
19/01/2019 1 HKD = 0.1275
18/01/2019 1 HKD = 0.1275
17/01/2019 1 HKD = 0.1275
16/01/2019 1 HKD = 0.1275
15/01/2019 1 HKD = 0.1275
14/01/2019 1 HKD = 0.1275
13/01/2019 1 HKD = 0.1276
12/1/2019 1 HKD = 0.1276
11/1/2019 1 HKD = 0.1276
10/1/2019 1 HKD = 0.1276
9/1/2019 1 HKD = 0.1276
8/1/2019 1 HKD = 0.1276
7/1/2019 1 HKD = 0.1276
6/1/2019 1 HKD = 0.1277
5/1/2019 1 HKD = 0.1276
80

4/1/2019 1 HKD = 0.1276
3/1/2019 1 HKD = 0.1277
2/1/2019 1 HKD = 0.1276
1/1/2019 1 HKD = 0.1277
Table 14 Spot Exchange rates
Data set mention above shows the spot exchange rates which are essential to deal in
a foreign exchange market of a two year period. The daily value of the spot exchange rates
increases from one value to another as this value gets increases due to the changes incurred in
the foreign market. With the increasing investment in the forex market, the value of Hong-
Kong dollar in exchange to the US dollar gets increases or decreases or showing stable
values. The above analysis shows that the value of 1 Hong-Kong dollar in exchange to US
dollar gets increases daily from one month to another.
4.5 Regression among spot exchange and USD and HKD values
16/04/2019 1 HKD = 0.1275 7.8452
15/04/2019 1 HKD = 0.1275 7.8453
14/04/2019 1 HKD = 0.1275 7.8427
13/04/2019 1 HKD = 0.1275 7.8399
12/4/2019 1 HKD = 0.1275 7.8422
11/4/2019 1 HKD = 0.1275 7.8429
10/4/2019 1 HKD = 0.1276 7.8426
9/4/2019 1 HKD = 0.1275 7.8366
8/4/2019 1 HKD = 0.1274 7.8415
7/4/2019 1 HKD = 0.1274 7.8471
6/4/2019 1 HKD = 0.1274 7.8495
5/4/2019 1 HKD = 0.1274 7.8494
4/4/2019 1 HKD = 0.1274 7.8491
81

3/4/2019 1 HKD = 0.1274 7.8495
2/4/2019 1 HKD = 0.1274 7.8498
1/4/2019 1 HKD = 0.1274 7.8498
31/03/2019 1 HKD = 0.1274 7.8499
30/03/2019 1 HKD = 0.1274 7.8499
29/03/2019 1 HKD = 0.1274 7.8498
28/03/2019 1 HKD = 0.1274 7.8487
27/03/2019 1 HKD = 0.1274 7.8494
26/03/2019 1 HKD = 0.1274 7.8469
25/03/2019 1 HKD = 0.1274 7.8474
24/03/2019 1 HKD = 0.1274 7.8473
23/03/2019 1 HKD = 0.1274 7.8473
22/03/2019 1 HKD = 0.1274 7.8498
21/03/2019 1 HKD = 0.1274 7.8498
20/03/2019 1 HKD = 0.1274 7.8499
19/03/2019 1 HKD = 0.1274 7.8499
18/03/2019 1 HKD = 0.1274 7.8501
17/03/2019 1 HKD = 0.1274 7.8499
16/03/2019 1 HKD = 0.1274 7.8499
15/03/2019 1 HKD = 0.1274 7.8499
14/03/2019 1 HKD = 0.1274 7.8498
13/03/2019 1 HKD = 0.1274 7.8499
82

12/3/2019 1 HKD = 0.1274 7.8498
11/3/2019 1 HKD = 0.1274 7.8499
10/3/2019 1 HKD = 0.127 7.8499
9/3/2019 1 HKD = 0.1274 7.8498
8/3/2019 1 HKD = 0.1274 7.8491
7/3/2019 1 HKD = 0.1274 7.8489
6/3/2019 1 HKD = 0.1274 7.8487
5/3/2019 1 HKD = 0.1274 7.8499
4/3/2019 1 HKD = 0.1274 7.8496
3/3/2019 1 HKD = 0.1274 7.8491
2/3/2019 1 HKD = 0.1274 7.8487
1/3/2019 1 HKD = 0.1274 7.8479
28/02/2019 1 HKD = 0.1274 7.8482
27/02/2019 1 HKD = 0.1274 7.8472
26/02/2019 1 HKD = 0.1274 7.8491
25/02/2019 1 HKD = 0.1274 7.8487
24/02/2019 1 HKD = 0.1274 7.8478
23/02/2019 1 HKD = 0.1274 7.8481
22/02/2019 1 HKD = 0.1274 7.8479
21/02/2019 1 HKD = 0.1274 7.8472
20/02/2019 1 HKD = 0.1274 7.8484
19/02/2019 1 HKD = 0.1274 7.8486
83

18/02/2019 1 HKD = 0.1274 7.8478
17/02/2019 1 HKD = 0.1274 7.8468
16/02/2019 1 HKD = 0.1274 7.8473
15/02/2019 1 HKD = 0.1274 7.8476
14/02/2019 1 HKD = 0.1274 7.8464
13/02/2019 1 HKD = 0.1274 7.8454
12/2/2019 1 HKD = 0.1274 7.8466
11/2/2019 1 HKD = 0.1274 7.8456
10/2/2019 1 HKD = 0.1274 7.8468
9/2/2019 1 HKD = 0.1274 7.8468
8/2/2019 1 HKD = 0.1274 7.8429
7/2/2019 1 HKD = 0.1274 7.8461
6/2/2019 1 HKD = 0.1274 7.846
5/2/2019 1 HKD = 0.1275 7.8454
4/2/2019 1 HKD = 0.1274 7.8457
3/2/2019 1 HKD = 0.1275 7.8458
2/2/2019 1 HKD = 0.1274 7.8453
1/2/2019 1 HKD = 0.1274 7.8453
31/01/2019 1 HKD = 0.1274 7.8453
30/01/2019 1 HKD = 0.1275 7.844
29/01/2019 1 HKD = 0.1274 7.8434
28/01/2019 1 HKD = 0.1274 7.843
84

27/01/2019 1 HKD = 0.1275 7.843
26/01/2019 1 HKD = 0.1275 7.8433
25/01/2019 1 HKD = 0.1275 7.8422
24/01/2019 1 HKD = 0.1275 7.8396
23/01/2019 1 HKD = 0.1275 7.8393
22/01/2019 1 HKD = 0.1275 7.8385
21/01/2019 1 HKD = 0.1275 7.8376
20/01/2019 1 HKD = 0.1275 7.8388
19/01/2019 1 HKD = 0.1275 7.8345
18/01/2019 1 HKD = 0.1275 7.833
17/01/2019 1 HKD = 0.1275 7.8345
16/01/2019 1 HKD = 0.1275 7.8304
15/01/2019 1 HKD = 0.1275 7.8332
14/01/2019 1 HKD = 0.1275 7.8318
13/01/2019 1 HKD = 0.1276 7.8316
12/1/2019 1 HKD = 0.1276 7.8314
11/1/2019 1 HKD = 0.1276 7.8304
10/1/2019 1 HKD = 0.1276 7.8294
9/1/2019 1 HKD = 0.1276 7.8285
8/1/2019 1 HKD = 0.1276 7.8327
7/1/2019 1 HKD = 0.1276 7.8327
6/1/2019 1 HKD = 0.1277 7.8334
85

5/1/2019 1 HKD = 0.1276 7.8327
4/1/2019 1 HKD = 0.1276 7.8303
3/1/2019 1 HKD = 0.1277 7.8267
2/1/2019 1 HKD = 0.1276 7.8192
1/1/2019 1 HKD = 0.1277 7.8126
Table 15 Regression analysis
Regression Statistics
Multiple R 1
R Square 0.999999
Adjusted R Square 0.972221
Standard Error 0.000122
Observations 37
Table 16 Regression Statistics
ANOVA
df SS MS F
Significanc
e F
Regressio
n 1
0.60061
4
0.60061
4
4041259
6 1.1E-107
Residual 36
5.35E-
07
1.49E-
08
Total 37
0.60061
5
Coefficien
ts
Standar
d Error t Stat P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept 0 #N/A #N/A #N/A #N/A #N/A #N/A #N/A
7.8453 0.016235
2.55E-
06 6357.09 1.6E-110 0.01623
0.0162
4
0.0162
3
0.0162
4
Table 17 ANOVA
86

RESIDUAL OUTPUT
Observation Predicted 0.1275 Residuals Standard Residuals
1 0.127326 0.000174 1.449049
2 0.12728 0.00022 1.827072
3 0.127318 0.000182 1.516553
4 0.127329 0.000171 1.422047
5 0.127324 0.000276 2.294141
6 0.127227 0.000273 2.2726
7 0.127306 9.37E-05 0.779467
8 0.127397 2.82E-06 0.02342
9 0.127436 -3.6E-05 -0.3006
10 0.127435 -3.5E-05 -0.2871
11 0.12743 -3E-05 -0.2466
12 0.127436 -3.6E-05 -0.3006
13 0.127441 -4.1E-05 -0.3411
14 0.127441 -4.1E-05 -0.3411
15 0.127443 -4.3E-05 -0.3546
16 0.127443 -4.3E-05 -0.3546
17 0.127441 -4.1E-05 -0.3411
18 0.127423 -2.3E-05 -0.19259
19 0.127435 -3.5E-05 -0.2871
20 0.127394 6.06E-06 0.050422
87

21 0.127402 -2.1E-06 -0.01708
22 0.1274 -4.3E-07 -0.00358
23 0.1274 -4.3E-07 -0.00358
24 0.127441 -4.1E-05 -0.3411
25 0.127441 -4.1E-05 -0.3411
26 0.127443 -4.3E-05 -0.3546
27 0.127443 -4.3E-05 -0.3546
28 0.127446 -4.6E-05 -0.38161
29 0.127443 -4.3E-05 -0.3546
30 0.127443 -4.3E-05 -0.3546
31 0.127443 -4.3E-05 -0.3546
32 0.127441 -4.1E-05 -0.3411
33 0.127443 -4.3E-05 -0.3546
34 0.127441 -4.1E-05 -0.3411
35 0.127443 -4.3E-05 -0.3546
36 0.127443 -0.00044 -3.68097
37 0.127441 -4.1E-05 -0.3411
Table 18 RESIDUAL OUTPUT
PROBABILITY OUTPUT
Percentile 0.1275
1.351351 0.127
4.054054 0.1274
88

6.756757 0.1274
9.459459 0.1274
12.16216 0.1274
14.86486 0.1274
17.56757 0.1274
20.27027 0.1274
22.97297 0.1274
25.67568 0.1274
28.37838 0.1274
31.08108 0.1274
33.78378 0.1274
36.48649 0.1274
39.18919 0.1274
41.89189 0.1274
44.59459 0.1274
47.2973 0.1274
50 0.1274
52.7027 0.1274
55.40541 0.1274
58.10811 0.1274
60.81081 0.1274
63.51351 0.1274
89

66.21622 0.1274
68.91892 0.1274
71.62162 0.1274
74.32432 0.1274
77.02703 0.1274
79.72973 0.1274
82.43243 0.1274
85.13514 0.1275
87.83784 0.1275
90.54054 0.1275
93.24324 0.1275
95.94595 0.1275
98.64865 0.1276
Table 19 PROBABILITY OUTPUT
90

7.834
7.836
7.838
7.84
7.842
7.844
7.846
7.848
7.85
7.852
-0.0005
-0.0004
-0.0003
-0.0002
-0.0001
0
0.0001
0.0002
0.0003
0.0004
7.8453 Residual Plot
7.8453
Residuals
Table 20 Residual Plot
91

7.835 7.84 7.845 7.85 7.855
0.1267
0.1268
0.1269
0.127
0.1271
0.1272
0.1273
0.1274
0.1275
0.1276
0.1277
7.8453 Line Fit Plot
Series2
Predicted 0.1275
7.8453
0.1275
Table 21 Line Fit Plot
92

0 20 40 60 80 100 120
0.1267
0.1268
0.1269
0.127
0.1271
0.1272
0.1273
0.1274
0.1275
0.1276
0.1277
Normal Probability Plot
Sample Percentile
0.1275
Table 22 Normal Probability plot
The high value of r squared value of a regression line shows that the data will fit into
the regression line as the higher value is considered as good for a variable of this research.
Another parameter of this analysis is a residual plot which shows the estimation results that
the data will generate biased or unbiased results. The residual plot shows the haphazard
pattern of the data which means there is a high chance of generating biased results which do
not justify the validity and the authenticity of the collected data about the spot exchange rates
and the currency prices of US and Hon-Kong. The aim of this analysis is to know the impact
of both these elements on the covered interest parity conditions of the current nation that is
Hong -Kong. The line fit plots of this analysis shows that the predicted result is 0.1275 which
is showing in a proper line that denotes the efficiency and the effectiveness of the data sets
and also signifies tits un-biasness as a researcher collected the data using professional
criteria’s to generate favourable results to test the research claims.
The normal probability plot shows that in the future the spit and the currency value
will get equalize on the value of 0.1274 and the estimated r predicted results shows that both
will collide on a value of 0.1275. The probability output of this analysis analyses the data
from all the angles to know whether the claim of the research or result are interrelated with
93

each other or there is some sort of differences lie in the performances of both the results and
the aim of the research.
The relationship between the spot exchange rates and the currency values of the
countries to the research study are evaluated by a researcher using the regression analysis that
utilizes percentile as well as the predicted output. It has noticed that with the changes takes
places in the percentile; its direct impact is visible on the predicted is estimated results. The
initial estimates start with 0.1275 which keeps on changes till 0.1274 with a slight difference
of 0.01 among the current prediction and estimated results. The differences lie among two of
the value is due to the change in the external market.
Interest rates
Date Symbo
l
Long
Carry
Short
Carry
4/1/2019 USDHK
D -0.20% -2.19%
3/1/2019 USDHK
D -0.20% -2.19%
2/1/2019 USDHK
D -0.18% -1.90%
1/1/2019 USDHK
D -0.18% -1.91%
12/1/201
8
USDHK
D -0.20% -1.88%
11/1/201
8
USDHK
D -0.41% -1.90%
10/1/201
8
USDHK
D -0.47% -1.64%
9/1/2018 USDHK
D -0.22% -2.04%
8/1/2018 USDHK
D -0.20% -1.91%
7/1/2018 USDHK
D -0.28% -1.80%
6/1/2018 USDHK
D -0.14% -1.86%
5/1/2018 USDHK
D -0.36% -1.65%
4/1/2018 USDHK
D -0.48% -1.91%
3/1/2018 USDHK
D -0.45% -1.86%
2/1/2018 USDHK -0.57% -1.69%
94

D
1/1/2018 USDHK
D -0.42% -1.82%
12/1/201
7
USDHK
D -0.48% -1.65%
11/1/201
7
USDHK
D -0.45% -1.41%
10/1/201
7
USDHK
D -0.51% -1.43%
9/1/2017 USDHK
D -0.45% -1.51%
8/1/2017 USDHK
D -0.46% -1.51%
7/1/2017 USDHK
D -0.57% -1.49%
6/1/2017 USDHK
D -0.70% -1.52%
5/1/2017 USDHK
D -0.56% -1.27%
4/1/2017 USDHK
D -0.48% -1.40%
3/1/2017 USDHK
D -0.59% -1.18%
2/1/2017 USDHK
D -0.62% -1.18%
1/1/2017 USDHK
D -0.62% -1.17%
12/1/201
6
USDHK
D -0.60% -0.82%
11/1/201
6
USDHK
D -1.30% -0.70%
10/1/201
6
USDHK
D -0.63% -0.57%
9/1/2016 USDHK
D -0.63% -0.57%
8/1/2016 USDHK
D -0.42% -0.38%
7/1/2016 USDHK
D -0.42% -0.38%
6/1/2016 USDHK
D -0.35% -0.54%
5/1/2016 USDHK
D -0.63% -0.94%
4/1/2016 USDHK
D -0.38% -0.75%
3/1/2016 USDHK
D -0.75% -1.31%
Table 23 Interest rates of USD and HKD
95

(Source: Interest rates, 2018)
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.78558
R Square 0.617135
Adjusted R Square 0.589358
Standard Error 0.003229
Observations 37
Table 24 SUMMARY OUTPUT
ANOVA
df SS MS F Significance F
Regression 1 0.000605 0.000605 58.02803 6.21E-09
Residual 36 0.000375 1.04E-05
Total 37 0.000981
Table 25 ANOVA
Coefficien
ts
Standar
d Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Interce
pt 0 #N/A #N/A #N/A #N/A #N/A #N/A #N/A
-
0.0218
6 0.272637
0.0357
9
7.61761
3
5.17E
-09
0.20005
1
0.34522
3
0.20005
1
0.34522
3
Table 26 Coefficient
RESIDUAL OUTPUT
Observatio
n Predicted -0.00199 Residuals
1 -0.00597 0.003968
2 -0.00518 0.003433
3 -0.00519 0.003434
4 -0.00511 0.003112
5 -0.00519 0.001096
6 -0.00446 -0.0002
7 -0.00556 0.003386
8 -0.0052 0.003189
9 -0.00491 0.002077
10 -0.00506 0.003643
11 -0.00449 0.000848
96

12 -0.0052 0.000372
13 -0.00506 0.000537
14 -0.00461 -0.00113
15 -0.00497 0.000767
16 -0.00449 -0.00033
17 -0.00385 -0.00065
18 -0.00389 -0.00123
19 -0.00412 -0.0004
20 -0.00411 -0.0005
21 -0.00406 -0.00167
22 -0.00414 -0.00284
23 -0.00347 -0.00212
24 -0.00383 -0.00101
25 -0.00322 -0.00269
26 -0.00322 -0.00297
27 -0.00319 -0.00304
28 -0.00225 -0.00372
29 -0.00191 -0.01109
30 -0.00155 -0.00477
31 -0.00155 -0.00477
32 -0.00103 -0.00318
33 -0.00103 -0.00318
34 -0.00148 -0.00199
35 -0.00255 -0.00371
36 -0.00204 -0.00174
37 -0.00358 -0.00393
Table 27 RESIDUAL OUTPUT
-2.50% -2.00% -1.50% -1.00% -0.50% 0.00%
-0.012
-0.01
-0.008
-0.006
-0.004
-0.002
0
0.002
0.004
0.006
-0.02186 Residual Plot
-0.02186
Residuals
Table 28 Residual Plot
The value of multiple R and R square is positive but less than 1 which shows that
there are chances of having un-biased data which will not generate reliable or authentic data
97

to fully rely on the same (Regression analysis, 2013). There are in total 37 observation tested
on using different criteria’s in the regression as this analysis will help a user in testing the
current results to determine the future trend. A user is concerned in knowing about its future
trend that what will be the estimate the interest rate of the future as the interest rate is an
important consideration before analysing the deviations from the covered interest parity
conditions as the interest differentials are to be analysed by a user after taking into account all
the elements.
Vector Auto aggressive model
Particulars Long pips Short pips Long(USD) Short(USD)
USD/HKD 1.51 1.51 0.02 0.02
Table 29 Overnight swaps
(Source: Overnight swap rates, 2018)
Particulars Bid Price Ask Price Mid Price
USD/HKD 3-Month Forward -146 -143 -144.5
Table 30 NDF 3 month swap rate
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.71276
R Square 0.508027
Adjusted R Square -0.49197
Standard Error 1.059219
Observations 2
Table 31 SUMMARY OUTPUT
ANOVA
df SS MS F Significance F
Regression 1 1.158555 1.158555 1.03263 #NUM!
Residual 1 1.121945 1.121945
Total 2 2.2805
Table 32 ANOVA
Coefficien
ts
Standar
d Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Interce
pt 0 #N/A #N/A #N/A #N/A #N/A #N/A #N/A
146 0.005295 0.00521
1.01618
4
0.4948
9
-
0.0609
1
0.07149
7
-
0.0609
1
0.07149
7
Table 33 Coefficient
RESIDUAL OUTPUT
98

Observation Predicted 1.51 Residuals
1 0.757121 0.752879
2 0.765063 -0.74506
Table 34 RESIDUAL OUTPUT
Vector auto regression model is used by a user which is a regression analysis to
consider the interdependencies on the model to know the impact of the multiple time series.
This analysis will applicable on two of the variable such as overnight swap rate and non-
delivered forward swap rate of 3 months of USD/HKD dollar values (VAR model, 2018).
The prediction says that the overnight swap the rate will have 75% chances of increasing the
overall swap rates of the countries to research and on the contrary, to this, three-month swap
rate has 0.76 that 76% chances of increment in the future.
CHAPTER 5 DISCUSSION AND CONCLUSIONS
5.1 Summary
It is summarize from the above research that the analysis has conduct to identify the
study problem about the deviations taking place in the covered interest parity in the Hong-
Kong. The concept of the covered interest parity explained in this research and also governs
the variables of this study. These variables that have helped in testing the claims of research
that consists of interest differential of swap and interest rate, the impact of foreign liquidity
conditions of the bank and finally testing the validity of the CIRP that is the covered interest
rate parity conditions. All these elements of research or important variables to research has
identified in a theoretical framework of research.
The analysis and the results section of this section analyses several components of this
research such as evaluating the historical data of USD to HKD currency prices, spot
exchange rates, interest rates to know it is positive or negative impact on the overall
performance of the covered interest parity (Beugelsdijk, Kostova, Kunst, Spadafora & van
Essen, 2018).
After applying the descriptive statistics on the normal prices, opening, low and high
currencies prices of daily values of two year period, it has determined that all the values are
positive. The favourable values of the data show that the value of currency keeps on increases
from period to period as this has not affected by the external environment and its adversities
which positively contributes to the positivity of the covered interest parity conditions
(Bokamba, 2018).
99

The regression is applied in testing the relationship between the spot exchange rates and the
currency prices that analysis reveals the positive values as the estimated data figures of this
analysis. Under this analysis, the data will show a reclining position that flows in a line fit
plot in a very systematic position.
5.2 Theoretical implications
Current the research study is about identifying the changes or deviations from the
covered interest parity in the Hong-Kong. This concept is very unique for the majority of the
users who are technical audiences that have knowledge about the interest rates, spot exchange
rate, and interest’s differentials, forward and swap rates and its summation as the covered or
uncovered interest parity conditions. With the help of this research, all the technical –non-
technical users in a community get enough benefit in understanding these terms and its usage
in the trading. This research will contribute to increasing the forex market trading as the
user’s curiosity gets increases with the time in taking interest in this field to know more about
all the elements of research (Chiang, Ramsey-Musolf & Senaha, 2018).
A student or new investors intend to make a career or investing in forex or stick
market will get benefit by reading this research article to clarify all its doubts about the
interest rates, swap rates, exchange rates. Knowing the condition of CIRP, an investor will
make a wise decision whether to invest in the market or wait for the right time as investing in
irrelevant sources will not generate any returns for a user as this, in turn, increases the
chances of loss and increasing its market risks to investing against in a similar component.
5.3 Practical implications
It is recommended to a user to stabilize the unfavourable conditions of interest rates of
long term or short term, period as this is showing negative results. This will get improve by a
user by using analytical tools and forex trader applications to track the situations in advance
to act accordingly. The interest rates, spot exchange rates and forward rates can’t determine
in advance but a user can assume the rates based on past results. It is suggested to a user to
judge the past trends of the interest’s rates. It is also advised to a user to compare the current
interest with other country’s interest in knowing the differences as these differences will give
an insight into the reasons for the same.
Based on these research findings and the methodology used in collecting the research
facts, it is advisable to a user to use artificial intelligence and data science tools and technique
in tracking the future adversities as a tableau the language will help in knowing about the
100

future interest rates. The condition of CIRP can get improved by using this automatic tool
which will for its analysis based on the collected data as this analysis will consider the
criteria’s on its own that saves the time of an individual in generating the final results and
take the final action based on the same.
5.4 Limitations of research
Unavailability of the specific information to use it in research is the biggest challenge
faced by a researcher as in this research there are some section involves generalized
information. The focus of this research is on estimating the deviations incurred in the covered
interest parity along with the identification of the factors. The researchers have conducted
deep research in collecting the desirable information that is related to the research objectives.
The objective of this research is to find out the factors behind the deviations in the CIP, the
impact of foreign liquidity banks and to test the validity of CIP. Collecting data for this
research is a big threat encounter by a researcher as generalized data has not considered for
this analysis.
Another limitation witness by a user in relation to this research is time-consuming as
conducting research like this requires a lot of time in understanding the research objectives
and its application in concluding the same. Spending too much time on the literature review
affect the entire timeline prepared for this the project as due to the unavailability of the
information, other chapters of a dissertation gets affected as the timeline of the entire project
needs to change to match up with the final deadline.
This study will be useful for the future research scholar who performs its study on a
similar research or area or a study related to covered interests parity, related to Hong-Kong
country, interest rates, swap spreads, swap rates, exchange and forward rates. The market of
forex trading will get new opportunities with the help of this research study. This study will
fulfil gaps of the past research articles and the gaps lie in this study will fill in the future. This
is also beneficial for a student intends to make its career in the forex trading and the stock
market can get great insights using this research.
5.5 Reflections
This study utilizes the quantitative method of research in analysing all the variables or
components of research as a motive of a user to meet its research goals. This dissertation has
successfully achieved its entire research objective by collecting relevant data in testing all the
101

claims. Credit risk and liquidity risks are the two main factors held responsible for shifting
the CIP from positive to negative side as these are considered as a rigid factor.
When performing a literature review, the research process was very tough as unavailable
information related to the research goals was showcasing a situation of a project failure which
keeps on getting easy when moving to other sections or chapters of this dissertation. The
research methodology is considered as a very easy chapter of this dissertation as research
methods were already selected in the research proposal. The outcomes generated in the
analysis and results chapter give a sigh of relief that research objectives are aligned with the
final outcomes of this research.
I have noticed various difficulties encountered in conducting this research involves
unavailable data, time-consuming research process, failure of time plan, lack of authentic
sources of information. All these issues I have witnessed will get resolved by taking help of
previous research articles similar to this area of study in getting authentic and reliable
information to include in a literature review. Changes made in the timeline for this project by
adding a 1-week buffer for all the chapters to compensate the uncertainties incurred while
preparing the dissertation.
I have learned to keep patience and to search for authentic and reliable information from
various sources from this research. Collecting authentic information for the literature taught
me a great lesson to give attention to all the details.
I would like to improve the literature review section by taking help of Google scholar site to
get access to authentic research articles of all the authors who have performed its research on
the area exactly similar to his or somewhat related to this field. I will improve this chapter as
I have experienced this mode of information at the end of the chapters I have used other
modes such as books, materials, internet for searching the information to include in the
research which may go wrong and leads to excessive time.
5.6 Conclusion
It is concluded from this research that the status of covered interest parity condition is
sot good as this gets affected due to credit risks and liquidity which majorly affected this
concept. A change in the banking rules and the regulations is another important reason for the
deviations taking place in this concept.
102

The results of this analysis show that the predicted result of vector auto regression says that
overnight swap rate and NDF three-month swap rate shows a higher prediction up to .76 to
increase the rates in the future. Taking this result as a basis, an investor will withdraw its
interest from the forex markets that are prone to excessive risks where swap rates are not
stable with the time.
103

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