MN3138: Behavioral Finance, Investment Strategies, and Biases

This essay delves into the realm of behavioral finance, exploring the impact of cognitive biases and emotions on investment decision-making. It examines various biases such as anchoring, hindsight bias, confirmation bias, and herd behavior, highlighting their influence on investor behavior. The essay further analyzes market anomalies, including short-term momentum, long-run reversal, and the value effect, as well as the limits to arbitrage. It discusses how biases and emotions can be harnessed to design successful investment strategies. The essay emphasizes the importance of understanding biases to avoid common pitfalls and identify market opportunities, particularly for value investors. It also explores strategies such as passive investing, liquid assets, and quantitative investing to mitigate the negative effects of cognitive biases and emotions. Ultimately, the essay underscores the significance of managing biases effectively for improved investment outcomes.

Running head: BEHAVIOURAL FINANCE AND INVESTMENT STRATEGIES
Behavioural Finance and Investment Strategies
Name of the Student
Name of the University
Author’s Note

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Introduction
Biases have a crucial role to play in the investment decisions and these biases are the
parts of behavioural finance. Investment managers are not speared from these biases as
described in behavioural finance. Even investment experts and analysts fall prey to cognitive
biases (Khan 2017). Therefore, it is crucial for the investment advisors and wealth managers
are required to be aware of these biases when making investment decisions as these can
impact the investment decisions. Through learning about the degrees of observed behaviour
in the investment market, investors can learn how to mitigate the errors in investment
decisions (Khan 2017). The main aim of this report is to discuss about different aspects of
cognitive and other biases and impacts of the same on success investment of money. More
specifically, this report discusses about the types of biases having impact on investment
decisions. After that, it considers analysing aspects like market anomalies and limits of
arbitrage. Lastly, it discusses about the roles of biases and emotions in the decisions to invest
money.
Types of Bias
There are certain biases and psychological factors that create major impact on the
investment decisions-making process of the investors. They are as follows:
Anchoring is considered as a bias in which a psychological benchmark is used by the
investors that carries a disproportionately high weight in a decision-making process. This
contributes to the development of assumption of greater risk to hold the investment in the
hope that the security will gain its purchase price (Kansal and Sing 2015). For example, a
group of investors hear the price of gold at $2500, and on an immediate basis, on aggregate,
they commence thinking that $3000 might be expensive and $2000 is cheap. Hindsight bias is
another type of bias where the ability of predicting the future is overestimated grounded on

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the recent past. This means the tendency of overemphasizing the recent performance in the
thinking. Another types of bias is the confirmation bias where the investors selectively seek
information that supports the present theories while ignoring the information that disprove the
same theories (Bakar and Yi 2016). Herd behaviour is considered as another major
psychological factor which states that the investors are biologically wired for imitating the
actions of the larger group of investors. This behaviour allows the investors in quickly
reacting and absorbing the intelligence of other around the investors and this also contributes
to self-reinforcing cycles of aggregate behaviour (Kansal and Sing 2015). Overconfidence is
another type of psychological factor where the there is a tendency of over-estimating the
intelligence and capabilities relative to others (Kumar and Goyal 2015). For example, in the
2006 study of “Behaving Badly’, 74% of the managers believed that above-average job
performance was delivered by them. These are the major biases having impact on the
investment decision-making process.
Market Anomalies
Market anomalies are considered as the price actions contradicting the stock markets’
expected behaviours. The presence of six types of market anomalies can be seen having
impact on the investment decision making process and they are discusses below:
The first market anomaly is the short-term momentum which is the propensity of the
recent performance of an asset to continue in the near future. Long-run reversal can be
considered as the second market anomaly which is the tendency of performance over a longer
history of revert; this can be considered as the winner-loser effect (Avramov et al. 2017).
The value effect is the third type of market anomaly which is the propensity of the price to
accounting measures ration of an asset to predict the future returns. The small firm effect can
be considered as the fourth market anomaly which represents the propensity of the small
companies to outperform the companies with large market capitalization (Avramov et al.

3BEHAVIOURAL FINANCE AND INVESTMENT STRATEGIES
2017). The high volatility needs to be considered as the fifth market anomaly and this is the
price of an asset relative to measure of the discounted future payoff streams. The last market
anomaly is the post-earnings-announcements drift and this is the propensity of the earnings of
the stocks surprise in the prediction of future returns (Levy 2015). These are the major market
anomalies that refer to the difference of the performance of a stock from its assumed price
trajectory.
Limits to Arbitrage
Arbitrate refers to the process to simultaneously buy and sell an asset in order to gain
profit from a different in its price (Ljungqvist and Qian 2016). As per the theory of limits to
arbitrage, these prices may stay in an unbalanced position for a major period of time because
of the restrictions on the rational traders. There are factors that put limitations on the
capability of the rational traders to gain profit from mispricing; and presence of the risk can
be seen where this mispricing will become larger before it becomes smaller (Ljungqvist and
Qian 2016).
The presence of three crucial factors can be seen that leads to the development of
limits to arbitrage; they are fundamental risk, costs of hedging and noise traders’ risk
(Edmans, Goldstein and Jiang 2015). When a mispriced asset on the market is observed by an
arbitrageur, he/she is required to find a smaller asset that is correctly priced on another
market in order to enable them for correcting the mispricing; and therefore, taking an
opposite position in arbitrage. Fundamental risk is faced by the trader in case he/she is unable
in taking up the position. The next factor is hedging cost. There might be involvement of
borrowing the securities in the process of short-selling which is the costs to borrow the sock
to be sold short that may exceed the potential profit. The last factor is noise trader risk. The
noise traders may derive the price further from the fundamental value; and this create force

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on the arbitrage for liquidating their positions (Edmans, Goldstein and Jiang 2015). For this
reason, there is a big possibility that the noise traders may dominate the market.
The example of ‘twin shares’ case can be presented here. Royal Dutch and Shell
merged their interests in 1907 on a 60:40 basis while both remaining separate entities. The
trading of the shares of Royal Dutch was on US and Dutch Stock Exchange while claiming
60% of the total cash flows; and the shares of Shell were traded in UK while claiming 40% of
the total cash flows of the two companies. As per theory, the market value of the equity of
Royal Dutch should always be 1.5 times greater than that of Shell. As per the evidence, Royal
Dutch was 35% under-priced as compared to Shell; and they were 15% overpriced at times. It
took until 2001 for the shares of these companies to be sold in their correct value. This
examples shows that two shares are perfectly substitute to each other would allow the
opportunity of easy arbitrage profit. Noise trader risk is the main risk in here as there is the
fear that the share will become even more undervalued in the near future (Frantz 2015).
Roles of Biases and Emotions in Financial Decision-Making
Biases and emotions are considered as a crucial part of behavioural finance as it takes
into consideration the cognitive biases and psychological factors affecting the investment
decision-making process (Otuteye and Siddiquee 2015). An understanding of biases and
emotions provides the investors with two advantages; first, understanding different processes
to make decisions which assists in avoiding common deceptions in the stock market; second,
understanding of the market participants’ financial behaviours that assists in identifying the
market opportunities. It requires to mention that biases and emotions tend to be
disadvantageous when it negatively influence the decision-making process, but they are
advantageous when the way they affect the investment decision-making process can be
understood (Montier 2018). Cognitive biases and emotions can lead to the creation of
opportunities for the value investors who are prepares to do their additional research and

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investigation on the investment projects. Inventors often refuses to face the reality when there
is declination in the stock prices. Later when they yield, the stocks will be traded below the
fair value. There is a close relation between market sentiments and financial psychology.
Emotions are often considered as the best way for tracking the effects of bias and emotions in
the stock market. When these are combined with other investment models, the investors can
use them for the identification of profitable opportunities (Fraser-Sampson 2013).
The best way for reducing the negative effects of cognitive bias and emotions on
investment decision-making is to assume the presence of these biases and emotions as this
assists in developing certain investment strategies for avoiding these traps in stock market
(Fraser-Sampson 2013). Investors can adopt the strategy of passive investing that helps in
removing the opportunity of committing mistakes when reacting to the events in stock
market. The chances to make irrational decisions can be avoided by investing in the liquid
assets because this helps in preventing impulsive behaviour (Subrahmanyam 2008).
Quantitative investing is another major strategy which is based on historical data and
evidence. The effects of traditional model along with financial psychology are includes in this
data. The effects of cognitive bias and investing can also be reduced through ensuring broad
allocation of assets. Therefore, it can be said that considering the presence of cognitive bias
and emotions in investment decision-making helps in considering their negative impacts on
decision-making process which leads to the urgency to develop effete investment strategies
for mitigating the negative influence of the same (Otuteye and Siddiquee 2015). Thus, when
effectively managed, cognitive biases and emotions help in better investment decision-
making process.
Conclusion
It can be seen from the above discussion that there are different types of cognitive
biases and emotions that can be seen in the investment decision-making process such as

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anchoring, hindsight bias, confirmation bias, herd behaviour, overconfidence and others; and
these biases create negative impact on the decision making process of the investors. Two
crucial aspects that need to be considered are the presence of market anomalies and limits to
arbitrage as these also create negative impact on the decision making process of the investors.
The above discussion states that the negative impact of biases and emotions can be eradicated
through considering presence of the same. It becomes possible to develop appropriate
investing strategies in the presence of cognitive biases and emotions; and these strategies
ensure considering all the market anomalies and other negative aspects.

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References
Avramov, D., Cheng, S., Schreiber, A. and Shemer, K., 2017. Scaling up market
anomalies. The Journal of Investing, 26(3), pp.89-105.
Bakar, S. and Yi, A.N.C., 2016. The impact of psychological factors on investors’ decision
making in Malaysian stock market: a case of Klang Valley and Pahang. Procedia Economics
and Finance, 35, pp.319-328.
Edmans, A., Goldstein, I. and Jiang, W., 2015. Feedback effects, asymmetric trading, and the
limits to arbitrage. American Economic Review, 105(12), pp.3766-97.
Frantz, R., 2015. LIMITS OF ARBITRAGE. Real-World Decision Making: An
Encyclopedia of Behavioral Economics: An Encyclopedia of Behavioral Economics, p.249.
Fraser-Sampson, G., 2013. Intelligent Investing: A Guide to the Practical and Behavioural
Aspects of Investment Strategy. Springer.
Kansal, P. and Sing, S., 2015. ANCHORING EFFECT IN INVESTMENT DECISION
MAKING-A SYSTEMATIC LITERATURE REVIEW. Asia Pacific Journal of Research
Vol: I. Issue XXXII.
Khan, M.Z.U., 2017. Impact of availability bias and loss aversion bias on investment decision
making, moderating role of risk perception. Management & Administration (IMPACT:
JMDGMA), 1(1), pp.17-28.
Kumar, S. and Goyal, N., 2015. Behavioural biases in investment decision making–a
systematic literature review. Qualitative Research in financial markets.
Levy, H., 2015. Stochastic dominance: Investment decision making under uncertainty.
Springer.

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Ljungqvist, A. and Qian, W., 2016. How constraining are limits to arbitrage?. The Review of
Financial Studies, 29(8), pp.1975-2028.
Montier, J. 2018, Behavioural Finance: Insights Into Irrational Minds and Markets, New
York: Wiley.
Otuteye, E. and Siddiquee, M., 2015. Overcoming cognitive biases: A heuristic for making
value investing decisions. Journal of Behavioral Finance, 16(2), pp.140-149.
Subrahmanyam, A., 2008. Behavioural finance: A review and synthesis. European Financial
Management, 14(1), pp.12-29.