Behavioral Finance

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Behavioral Finance

The conventional financial theories indicate that the world and market participants are mostly rational and wealth maximizers (Barberis & Thaler, 2003). Nevertheless, other instances of individual decision-making process are influenced by psychology and emotion causing people and companies to behave in irrational and unpredictable ways. Behavioral finance field recommends psychology-based principles to describe the stock market anomalies. In behavioral finance, the proposed theories assume that the characteristics of market partakers and structure of information influence systematically institutional and individual investment decisions and the market outcomes (Burton & Shah, 2013). This paper will critique a behavioral finance article (Undervalued Stocks for those who think patience is a virtue) using noise trader, arbitrage and value investing models to offer a comprehensive insight on behavioral finance.

According to Buckingham (2014), corrections, pullbacks and enduring market have not been expelled despite the recent straight move up in equity markets. While stocks have been outstanding for profit-taking in the market, transformation of asset allocation, change of investors` attitude towards risk and patience strategies have delayed investments in the stock market (Buckingham, 2014). The past events indicate that one out of three individuals can hold dividend-paying or value-priced stock for more than a month or even increase the period of holding to one year in order to decrease negative returns/outcomes. Buckingham`s article suggests that the longer the period of holding a value-priced stock, the lesser likely will the stock ends up with negative returns. Considering that most stocks are sometimes 10% less expensive, dividend yields will move high and interest rate decrease. These events have led most investors to be less aggressive and even the central banks in most countries have change their focus from fighting inflation to aiding economy growth which has made the domestic economy to remain on track (Buckingham, 2014).

The behavioral finance paradigm employs less constricted models than the ones presented by arbitrage assumption and the utility theory of Von Neumman-Morgenstern (Ackert & DeaveS, 2010; Bruce, 2010). Vast psychology literature has documented the errors individuals make in the way they think (depending on the recent experiences or being overconfident). Furthermore, people`s preferences can lead to distortions in thinking. The behavioral finance employs models where agents are not fully rational due to mistaken beliefs or preferences. For instance, due to preferences, individuals can be opposed to loss; $2.5 gain might make investors feel better like a $0.5 loss make them feel worse (Thaler, 2005). Mistaken beliefs are likely to arise since individuals are bad Bayesians. The modern finance employs efficient markets hypothesis as its building block whereby it suggests that competition between financiers who seek abnormal profits forces the prices to their right value (correct price) (Kling, Congdon, & Mullainathan, 2011). Efficient markets hypothesis (EMH) does not adopt the notion that all individuals are rational but it argues that markets are rational. EMH is based on markets being unbiased in forecasting the future but not foreseeing the future. However, behavioral finance argues that the financial markets can be informed inefficiently in some events.

Psychological biases do not lead to all misvaluations; some occur due to temporary imbalances of demand and supply. For instance, tranny indexing can cause demand changes that are not linked to future cash flows of a given company (Cronqvist et al., 2012). In 1999, Yahoo was added to S&P 500 and the index fund manager was forced to buy the stock when it had limited public float. Since the demand was high, the prices went up by 50% within a week and 100% within a month. However, 18 months later, the price went down by approximately 90% (Pompian, 2011). When individuals can take positions by buying undervalued stocks or shorting overvalued stocks and the misvaluations can be corrected within a short duration, then arbitrageurs can take position and eradicate the mispricing before damages are done. However, if it is hard to take positions attributed to short sales constraints, or if mispricing corrections are not guaranteed in a short period, arbitrage cannot correct the mispricing. Furthermore, arbitrageurs can even avoid the market with severe mispricing since the risks are high (Ritter, 2003). This is true especially for investors dealing with a huge market like the Japanese market of 1980s or the USA technology stocks market of 1990s. The arbitrageurs who tried to short Japanese stocks in 1987 and hedge by going long to the USA stocks were correct after a long period but they lost enormous quantity of cash later in 1987 when U.S markets crashed more than the market of Japan. When arbitrageurs got limited money, they are sometimes pressured to cover their positions when relative misvaluations are greatest hence additional buying pressure when stocks are overvalued (Baker & Wurgler, 2011).

Value investing

For many value managers, they have to buy whatever individuals are selling in the market. This can be a psychologically difficult situation. This is due to the bias that when they buy at the scary situations, they will reap maximum returns later (Tilson, 2005). The value investor`s objectives includes determining the intrinsic value of the stocks being bought with the hope that the stock will be trading at a discount to its actual value. Warren Buffett mentor and Graham offer an equation for value investing (Parikh, 2009).

IV= (8.5+ 2g) × EPS

IV= intrinsic value

8.5= the P/E ratio of a no-growing firm

EPS= trailing 12 months earnings per share

G= the long-term rate of growth of a company

 

 

Cognitive Biases

Psychologists have developed patterns in relation to how individuals behave. One pattern includes rules of thumbs (heuristics) that make decision-making process easier (Sun et al., 2013). Heuristics lead to suboptimal investment decisions. Overconfidence is another factor affecting decision making and it manifests itself in several way. For instance, too little over-diversification since many have the tendency of investing too much (Sun et al., 2013). Other individuals even separate decisions that should be integrated in principle (mental accounting). Another pattern of behavioral finance includes framing notion which relies on how a concept is framed to people. Other factors that lead to biases include representativeness, conservatism and disposition effect.

The limits to arbitrage

The misevaluation of asset is common but unreliable in making abnormal profits off (Ljungqvist & Qian, 2014). For the recurrent misevaluations, individuals with trading strategies can make profits reliably since the market is efficient for assets and relative. However, for nonrepeating long-term misvaluations, it is impossible to determine troughs and peaks in real time till they have passed. Therefore, getting in too early can lead to the risks of losses or even worse. If a limited number of partners or financiers are supplying funds, the withdrawals of money after loss may result into selling or buying pressures that exacerbates the inefficiency (Sun et al., 2013).

Arbitrage pricing theory (APT) provides a method for asset pricing whereby expected return can be modeled into a linear function of several macro-economic indices, security and market specific factors (Malloy, 2011).

E(rj) = rf + bj1RP1 + bj2RP2 + bj3RP3 + bj4RP4 + … + bjnRPn

E(rj) = Represent the asset`s expected return rate

RP= Risk premium linked with particular factor

bj = The sensitivity of asset`s return

rf= Risk-free rate

Noise trader risk

The noise trader risk concept was introduced by De Long and colleagues and examined further later (De Long et al., 1997). It involves the risk that mispricing being exploited by arbitrageurs worsens within a short run. For instance, even if General Motors present a perfect substitute security to Ford, the arbitrageurs will still face the risk that investors who are pessimistic cause Ford to be undervalued in the first place since the more pessimistic will lower its prices further (Burger & Curtis, 2014). When an individual has granted the possibility that prices of security can be different from their fundamental value, the individual should grant also the possibility that the movements of future prices can increase divergence. The noise trader risk is vital since it can put pressure on the arbitrageurs to liquidate their positions much earlier leading to potential steep losses. According to Mendel and Shleifer (2012), the professional portfolio managers or arbitrageurs do not manage their money but they manage other people`s money (separations of capital and brains). This agency has significant consequences. Investors who lack expert knowledge to assess the arbitrageurs` strategy can assess them based on returns (Forbes, 2009). When a mispricing that arbitrageurs would like to exploit worsens in a short run and generates negative outcomes, investors might indicate that they are incompetent and withdraw their money. These can force the arbitrageurs to liquidate their positions prematurely. Therefore, the fear of premature liquidation makes them less aggressive in struggling with mispricing in the first place. These challenges might be severely intensified by creditors (Beer, Watfa & Zouaoui, 2012; Wang & Li, 2012).

The equation capturing the pricing fluctuations of the risk asset due to the variation of the noise traders` misperceptions is shown below.

P* = mean misperception (measure of the average bullishness)

σ2p= variance of the noise trade of the misperceptions of the expected return per unit of the risk asset

m= a given asset


References

Ackert, L. F., & DeaveS, R. (2010). Behavioral finance: psychology, decision-making, and markets. Mason, OH, South-Western Cengage Learning.

Baker, M., & Wurgler, J. (2011). Behavioral corporate finance: An updated survey (No. w17333). National Bureau of Economic Research.

Barberis, N., & Thaler, R. (2003). A survey of behavioral finance. Handbook of the Economics of Finance, 1, 1053-1128.

Beer, F., Watfa, M., & Zouaoui, M. (2012). Do investors care about noise trader risk?. Journal of Financial Transformation, 35, 49-56.

Bruce, B. R. (2010). Handbook of behavioral finance. Cheltenham, UK, Edward Elgar. http://public.eblib.com/choice/publicfullrecord.aspx?p=615079.

Buckingham, J. (2014, October 16). 30 Undervalued Stocks For Those Who Think Patience Is A Virtue. Retrieved January 22, 2015, from Forbes: http://www.forbes.com/sites/johnbuckingham/2014/10/16/30-undervalued-stocks-for-those-who-think-patience-is-a-virtue/

Burger, M. A., & Curtis, A. (2014). Aggregate Noise Trader Risk, Mispricing, and Accounting Fundamentals. Mispricing, and Accounting Fundamentals (April 18, 2014).

Burton, E. T., & Shah, S. N. (2013). Behavioral finance: understanding the social, cognitive, and economic debates. http://www.123library.org/book_details/?id=96751.

Cronqvist, H., Makhija, A. K., & Yonker, S. E. (2012). Behavioral consistency in corporate finance: CEO personal and corporate leverage. Journal of financial economics, 103(1), 20-40.

De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1997). Noise trader risk in financial markets. Journal of political Economy, 703-738.

Forbes, W. (2009). Behavioural finance. New York, Wiley. P130-134

Kling, J. R., Congdon, W. J., & Mullainathan, S. (2011). Policy and choice: public finance through the lens of behavioral economics. Brookings Institution Press.

Ljungqvist, A., & Qian, W. (2014). How Constraining Are Limits to Arbitrage?. Available at SSRN 2356414.

Malloy, C. (2011, September). The psychology and sociology of investing: incorporating behavioral finance and network analysis into equity research and portfolio management. In CFA Institute Conference Proceedings Quarterly (Vol. 28, No. 3, pp. 9-17). CFA Institute.

Mendel, B., & Shleifer, A. (2012). Chasing noise. Journal of Financial Economics, 104(2), 303-320.

Parikh, P. (2009). Value investing and behavioral finance. Tata McGraw-Hill Education.

Pompian, M. (2011). Behavioral finance and wealth management: how to build optimal portfolios that account for investor biases (Vol. 667). John Wiley & Sons.

Ritter, J. R. (2003). Behavioral finance. Pacific-Basin Finance Journal, 11(4), 429-437.

Sun, D. S., Tsai, S. C., & Wang, W. (2013). Behavioral investment strategy matters: a statistical arbitrage approach. Emerging Markets Finance and Trade, 49, 47-61.

Thaler, R. H. (2005). Advances in Behavioral Finance, 2. Princeton, Princeton University Press. http://public.eblib.com/choice/publicfullrecord.aspx?p=537711.

Tilson, W. (2005). Applying Behavioral Finance to Value Investing. Artikel T2 Partners LLC.

Wang, S. S., & Li, W. (2012). The Measure of Noise Trader Risk Based on BAPM——An Example of Punished Listed Company. Operations Research and Management Science, 1, 023.