International Finance: USD/AUD Trend and Forecasting Report

This report provides an in-depth analysis of the USD/AUD exchange rate, focusing on forecasting models and investment strategies. It begins by examining continuously compounded returns and assessing whether the distribution of USD/AUD differs from a normal distribution using the 68-95-99.7 rule. The report then evaluates the differences between artificial and actual returns and identifies the overall trend of USD/AUD, offering effective trading strategies. Hypothesis testing for the next 30 days of investment is also conducted. The significance of the FX market is explored using the Random Walk Model and Autoregressive of order 1 model to determine the best model for future forecasting. Finally, the report assesses the overall risk implications of investing on a daily basis using parametric and historical methods, concluding with a summary of the findings and recommendations for investors. This assignment is published on Desklib, a platform providing AI-based study tools and resources for students.

Running head: INTERNATIONAL FINANCE
International Finance
Name of the Student:
Name of the University:
Author’s Note:

2
INTERNATIONAL FINANCE
Table of Contents
Introduction:...............................................................................................................................3
a) Drawing continuously compounded returns of (USD/AUD):...............................................3
b) Using 68-95-97 provided relevant evidence whether distribution of USD/AUD is different
from the normal:.........................................................................................................................4
c) Evaluating the overall difference in artificially and actual created returns:..........................5
d) Mentioning the overall trend of USD/AUD and providing effective trading strategies:.......6
e) Mentioning the hypothesis testing for next 30 days of investment:......................................7
f1) Mentioning the overall significance of FX market with the help of Random Walk Model
and Autoregressive of order 1 model:........................................................................................8
f2) Depicting the best model possible future forecasting:.........................................................9
g) Mentioning the overall risk implications for investing in daily basis:................................10
Conclusion:..............................................................................................................................12
Reference:................................................................................................................................14

3
INTERNATIONAL FINANCE
Introduction:
The overall study is mainly conducted to identify the significance of forecasting that
might be helpful for investors while making adequate investment decisions. Different types
of forecasting models are evaluated in the study to understand its future trend. There are
different types of Normal Distribution method that is used in identifying the trend of
USD/AUD. However, the data is mainly collected from 2003 to understand the overall trend
of USD/AUD, which could be used by investors in making adequate investment decisions.
a) Drawing continuously compounded returns of (USD/AUD):
1/2/2003
8/2/2003
3/2/2004
10/2/2004
5/2/2005
12/2/2005
7/2/2006
2/2/2007
9/2/2007
4/2/2008
11/2/2008
6/2/2009
1/2/2010
8/2/2010
3/2/2011
10/2/2011
5/2/2012
12/2/2012
7/2/2013
2/2/2014
9/2/2014
4/2/2015
11/2/2015
6/2/2016
1/2/2017
8/2/2017
-8.00000
-6.00000
-4.00000
-2.00000
0.00000
2.00000
4.00000
6.00000
8.00000
10.00000
USD/AUD-Continues Compound Return
Figure 1: Mentioning the overall continuous return of USD/AUD
(Source: Rba.gov.au 2017)
Figure 1 mainly States the continuous return of USD/AUD from 2003 till 2017. After
the evaluation in the figure it is identified that a non symmetric distribution approaches was

4
INTERNATIONAL FINANCE
seen for USD/AUD. On the other hand, Ardia et al. (2016) argued that Statistical distribution
is hardly used current by investors, as it needs high evaluation an experience to identify the
accurate price action.
b) Using 68-95-97 provided relevant evidence whether distribution of USD/AUD is
different from the normal:
Mean -0.009133
SD 0.824756
Rule From To Number of observations
At 68% of the rule -0.833889 0.815623 2773
At 95% of the rule -1.658645 1.640380 564
At 97.7% of the rule -2.483401 2.465136 55
Total 3392
Table 1: Mentioning the distribution level of USD/AUD based on 68-95-99.7 thumb rule
(Source: Rba.gov.au 2017)
The table mainly helps in identifying the observation that lie under 68-95-99.7 normal
thumb rule distribution. Under the 68% rule 2773 is mainly seen, while fewer than 95% rule
564 observations are seen and fewer than 99.7% rule 55 observations are seen. This
evaluation of different distribution level mainly states that normal distribution method does
not apply to the returns provided by USD/AUD. Bollerslev et al. (2014) mentioned that stock
market maybe provide regular distribution of Returns, as investors need to use adequate
investment measures and models to increase return and reduce risk.

5
INTERNATIONAL FINANCE
c) Evaluating the overall difference in artificially and actual created returns:
1/2/2003
8/2/2003
3/2/2004
10/2/2004
5/2/2005
12/2/2005
7/2/2006
2/2/2007
9/2/2007
4/2/2008
11/2/2008
6/2/2009
1/2/2010
8/2/2010
3/2/2011
10/2/2011
5/2/2012
12/2/2012
7/2/2013
2/2/2014
9/2/2014
4/2/2015
11/2/2015
6/2/2016
1/2/2017
8/2/2017
-8.00000
-6.00000
-4.00000
-2.00000
0.00000
2.00000
4.00000
6.00000
8.00000
10.00000
Continues Compound Return Artificial return
Figure 2: Mentioning the overall difference between actual and artificial returns
(Source: Rba.gov.au 2017)
The above figure mainly represents the difference between actual and continuous
Returns provided by USD/AUD. A continuous compound returns have different calculations
where returns are calculated based on the price movement of USD/AUD. However, the
artificial return depicted in the figure mainly provides a constant return, while continuous
returns directly jumped during 2007. Ghosh, Ostry and Qureshi (2013) argued that evaluation
of returns is mainly conducted by investors to identify the overall return of security, where
relevant investments could be conducted,

6
INTERNATIONAL FINANCE
d) Mentioning the overall trend of USD/AUD and providing effective trading strategies:
1/2/2003
7/2/2003
1/2/2004
7/2/2004
1/2/2005
7/2/2005
1/2/2006
7/2/2006
1/2/2007
7/2/2007
1/2/2008
7/2/2008
1/2/2009
7/2/2009
1/2/2010
7/2/2010
1/2/2011
7/2/2011
1/2/2012
7/2/2012
1/2/2013
7/2/2013
1/2/2014
7/2/2014
1/2/2015
7/2/2015
1/2/2016
7/2/2016
0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
1.4000
1.6000
1.8000
2.0000
USD/AUD
Figure 3: Mentioning the trend of USD/AUD
(Source: Rba.gov.au 2017)
16-03-17
26-03-17
05-04-17
15-04-17
25-04-17
05-05-17
15-05-17
25-05-17
04-06-17
14-06-17
24-06-17
04-07-17
14-07-17
24-07-17
03-08-17
1.18
1.2
1.22
1.24
1.26
1.28
1.3
1.32
1.34
1.36
1.38
USD/AUD
USD/AUD
Figure 4: Mentioning the current trend of USD/AUD with 30 days
(Source: Rba.gov.au 2017)

7
INTERNATIONAL FINANCE
The evaluation of figure 3 a n4 mainly depicts the current trend of USD/AUD from
2013 to 2017, which is currently in an uptrend. The current price of USD/AUD is mainly at
1.26, which is relatively lower than the current price trend. Therefore, it is estimated that
current trend of USD/AUD is mainly in a downtrend. Hughes-Morgan and Ferrier (2014)
mentioned that evaluation of current trend mainly helps in identifying the relevant investment
opportunity, which could be utilised by investors.
e) Mentioning the hypothesis testing for next 30 days of investment:
Regression Statistics
Multiple R 0.115568154
R Square 0.013355998
Adjusted R Square -0.02188129
Standard Error 0.025280314
Observations 30
ANOVA
df SS MS F Significa
nce F
Regressio
n
1 0.000242
236
0.000
242
0.379030
277
0.54309
5
Residual 28 0.017894
639
0.000
639
Total 29 0.018136
875
Coefficie Standard t Stat P-value Lower Upper Lower Upper

8
INTERNATIONAL FINANCE
nts Error 95% 95% 95.0% 95.0%
Intercept 1.279867
313
0.004663
949
274.4
171
1.43549
E-49
1.27031
4
1.289
421
1.270
314
1.289
421
X Variable
1
0.004602
936
0.007476
495
0.615
654
0.543095
107
-0.01071 0.019
918
-
0.010
71
0.019
918
Table 2: Mentioning the regression of USD/AUD
(Source: Rba.gov.au 2017)
The above table 2 mainly depicts the overall hypothesis, which could be used in
making adequate investment decisions. The short term trend is mainly declining, which could
be utilised by the investor by using sell side of the trade. Furthermore, the standard error of
0.025280314 mainly confirms that investment should be conducted on sell side. McLean and
Pontiff (2016) mentioned that hypothesis testing allows investors to identify the relevant
trend, which would help in making adequate investment decisions.
f1) Mentioning the overall significance of FX market with the help of Random Walk
Model and Autoregressive of order 1 model:
The use of ‘Autoregressive of order 1 model’ and ‘Random Walk Model’ the
investors effectively derive the future price movement of USD/AUD. Use of forecasting
method allows investors to adequately improve its return on investment. Moralles et al.
(2013) argued that use of forecasting methods mainly loses its friction if adequate evaluation
and research are not conducted by the investor.

9
INTERNATIONAL FINANCE
f2) Depicting the best model possible future forecasting:
Random Walk Model:
Random Walk Model MSE RMSE MAE
0.21790 0.466796625 0.4667
Date A F Abs SQ error Error(A-F)
7/27/2017 1.242854 0.7892 0.45361804 0.205769323 0.45361804
7/28/2017 1.254705 0.789471111 0.46523403 0.216442706 0.46523403
7/31/2017 1.252035 0.789706667 0.46232789 0.213747077 0.46232789
8/1/2017 1.248284 0.789942222 0.45834139 0.210076828 0.45834139
8/2/2017 1.255966 0.790177778 0.46578806 0.216958517 0.46578806
8/3/2017 1.262148 0.790413333 0.47173484 0.222533762 0.47173484
8/4/2017 1.253604 0.790648889 0.46295522 0.214327538 0.46295522
8/8/2017 1.262148 0.790884444 0.47126373 0.222089505 0.47126373
8/9/2017 1.268392 0.79112 0.47727168 0.227788256 0.47727168
8/10/2017 1.270164 0.791355556 0.4788083 0.229257384 0.4788083
Table 3: Forecasting with the help of Random Walk Model
(Source: Rba.gov.au 2017)
Autoregressive of order 1 model:
Autoregressive of order 1 model RMSE MAE MSE
0.026497674 (0.0244) 0.00070
Date A F SQ error Abs Error(A-F)
7/27/2017 1.242853592 1.292306091 0.00244555 0.049452499 -0.049452499

10
INTERNATIONAL FINANCE
7/28/2017 1.254705144 1.267250194 0.000157378 0.012545049 -0.012545049
7/31/2017 1.252034556 1.279334386 0.000745281 0.02729983 -0.02729983
8/1/2017 1.24828361 1.276611376 0.000802462 0.028327766 -0.028327766
8/2/2017 1.255965838 1.2727868 0.000282945 0.016820963 -0.016820963
8/3/2017 1.262148176 1.280619826 0.000341202 0.01847165 -0.01847165
8/4/2017 1.253604112 1.286923521 0.001110183 0.033319409 -0.033319409
8/8/2017 1.262148176 1.278211741 0.000258038 0.016063565 -0.016063565
8/9/2017 1.268391679 1.286923521 0.000343429 0.018531842 -0.018531842
8/10/2017 1.270163851 1.293289581 0.000534799 0.02312573 -0.02312573
Table 4: Forecasting with the help of Autoregressive of order 1 model
(Source: Rba.gov.au 2017)
The evaluation of table 3 and 4 mainly helps in identifying the random walk model
and autoregressive of order one model. The negative MAE mainly states that forecasting for
USD/AUD could lose friction and might hamper investments. The use of random walk model
is mainly allowed the investor to the closest forecast, which would help in making adequate
investment decisions. Reboredo (2013) argued that the continuous volatility in the currency
market does not allow investors to adequately forecast a future values, it mainly provides a
jest of the trend.
g) Mentioning the overall risk implications for investing in daily basis:
Parameters Value
Portfolio Value $ 1,000,000
Average Return 0.018375422

11
INTERNATIONAL FINANCE
Standard Deviation 0.00009796
Confidence Level 0.99
Calculations
Min Return with 99% prob 0.0181
Value of Portfolio $ 981,852.4662
Value at Risk 18,147.5338
Risk percentage 1.8%
Table 5: Mentioning the parametric method for identifying investment risk
(Source: Rba.gov.au 2017)
With the help of parametric method investors are mainly able to identify the relevant
risk attribute of the portfolio. The rate of interest percentage of 1.8% is identified from the
calculation where value at risk is mainly at 18147.53. Zhang et al. (2013) mentioned that
predictive prices ring in economic crises mainly loses its friction, as risk of the portfolio
increases, which hampers return and increases risk from investment.

12
INTERNATIONAL FINANCE
-7.15617147278543
-5.91510681928535
-4.67404216578528
-3.4329775122852
-2.19191285878512
-0.950848205285047
0.29021644821503
1.53128110171511
2.77234575521518
4.01341040871525
5.25447506221533
6.49553971571541
0
100
200
300
400
500
600
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
Histogram
Frequency
Cumulative %
Bin
Frequency
Figure 5: Mentioning the historical method for evaluating investment risk
(Source: Rba.gov.au 2017)
The overall table mainly depicts the risk ranges from -7.156171473 to 6.991965577,
which effectively depicts the maximum and minimum return that could be generated from 1
million USD investments. In addition, the maximum risk is only within -1.943699928 to
1.779494032, which could affect the overall investment risk of 1 Million USD.
Conclusion:
The study helps in evaluating different type of investment strategies, which could be
used by investors to make adequate investment decisions. Random Walk Model is depicted as
the appropriate forecasting method, which might be used by investors to make adequate
investment decisions. In addition, the novice has effectively depicted the overall risk
evaluation that could be conducted by parametric and historical simulation method. Lastly,