The Psychology of Investing
A successful investment firm requires a meticulously selected team. Just as the Golden State Warriors have spent an extraordinary amount of time recruiting and sculpting their lineup, it is no surprise that so does companies such as Blackrock Inc. As the largest investment management company in the world, they help manage 5.7 Trillion dollars’ worth of assets (Blackrock, 2017). So, who do the top banks, private equity, and hedge funds recruit to determine the flow of capital through the global markets?
Everyone has seen the stereotypes of traders in the modern entertainment such as Bobby Axelrod (Left) from the show Billions or Jordan Belfort (Right) from The Wolf of Wall Street. These are Alpha-male traders, driven by testosterone, listening to their impulses, and partaking in trading that resembles gambling more than any type of knowledge a business university can give.
The alpha-male investment banker has recently been revived in modern entertainment but has been prevalent since at least 1987 when the movie Wall Street showcased the very first alpha-male trader – Gordon Gecko. However, as technology and the way that investments are decided begin to change, so do the characters that we enjoy to watch. Whether it is Michael Burry (Left), a reclusive, quantitative, antisocial character played by Christian Bale in The Big Short, or Taylor Mason (Right), a non-gender binary, quantitative genius from the show Billions, these characters reflect and inspire a new wave of investment analysts.
So what mindset is actually behind the screens on Wall Street, who is actually taking the credit or blame of market conditions, and who is making the decisions that could potentially thrust us into prosperity or sink into another depression? We need to first look at the demographics of traders to determine the psychology behind these highly important decisions.
Wall Street Demographics – a rapidly changing environment
Who will Wall Street choose, the head of the Stanford coding club or the Princeton football captain that led his team to a championship? At this point, it is hard to tell, however, there is no doubt that the trading floor environment is changing. According to the Wall Street Journal, Quantitative hedge funds are now responsible for 27% of all U.S. stock trades, up from 14% in 2013, and hold more than 30% of all hedge-fund assets (Hope, 2017). With such a sizable percentage of quantitative firms hiring algorithmic traders as well as non-quantitative firms inevitably employing data scientists to stay ahead of the curve, how does this affect the office environment as a whole? Brett Steenbarger, who has worked with several funds as a trading psychologist argues that “professional trading markets have become not so manly and alpha in their approaches but rather geekier, equating firm environments to more Big Bang Theory than Wolf of Wall Street” (Weisenthal & Alloway, 2017). Before we can decide how this shift has changed the markets we need to look at what makes a successful trader. according to Steenbarger, this depends on the kind of trading. Day traders require fast processing of information and parallel processing of information, they need to rapidly detect patterns. For Macroeconomic researchers, Steenbarger argues they need to do deep research in global economies and formulate investment strategies on this basis. Deep thinking, not fast thinking is required (Weisenthal & Alloway, 2017). Steenbarger also argues that the greatest challenge facing investors is the correlation between their competitors.
Top traders are becoming very unique in their approach. It is just as important to enhance leadership, creativity, and not just worry about your emotions (Weisenthan & Alloway, 2017). As Alpha traders are looking for the next big idea, quant traders are hunched over their computers looking at the data for the next algorithm to beat the market. In the early 1980s when Quant trading just started to pick up, it was easy to be creative. But now, after almost forty years, it has become quite harder. So, what happens when quants are unable to create unique algorithms? What happens when it becomes just about the data and not about value? Market situations such as the Quant Meltdown of 2007 happens. In 2007 quants had strategies that were far too similar in their approach, creating a massive algorithm selloff dropping the value of the market (Wigglesworth, 2017).
Investing Behavior –Theory and Implications
Recent market behavior has demonstrated that standard finance models are not sufficient in a time of crisis. The Regret Theory (Bell, 1982) explains that the fear of regret can make investors either risk averse or motivate them to take greater risks. For example, suppose that Tom buys stock in a small growth company based only on a friend’s recommendation. After six months, the stock falls to 50% of the purchase price, so Tom sells the stock at a loss. To avoid this regret in the future, Tom will ask questions and research any stocks that his friend recommends. On the other side, say Tom didn’t take the friend’s recommendation to buy the stock, but the price increased by 50% rather than decreasing. Hence, to avoid the regret of missing out, he will be less risk averse and buy any stocks that his friends recommends in the future.
It is clear that investors past experience will shape how they will behave in the future. Fear of regret will impact investors timing on making asset allocation decisions change to their portfolio. The regret theory elaborates that investors who anticipate regret of making a wrong investment choice will take more time when making decisions. The theory also mentions that fear of regret might play a huge role in dissuading or motivating traders to make investment decisions and that traders who anticipate regret sell more shares at the first-time period than traders who do not expect it. As a result, in times of high financial uncertainty, stock price might fall further when there are more traders anticipating regret than those who are not.
Investor personality traits moderate the relationship between the key sources of information and trading behavior. Financial advisors tend to increase the frequency of trading in investors with openness, extraversion, neuroticism and agreeableness personality traits, and tend to decrease the intensity of trading in investors with conscientiousness trait (Tauni, 2017). On the other hand, financial information acquired from word-of-mouth communication is more likely to enhance trading frequency in extroverted and agreeable investors and is more liable to reduce trading frequency in investors with openness, conscientiousness and neuroticism traits. Finally, the use of specialized press (a high level of journalistic, real economic facts published in the economy sections of newspapers) leads to more adjustment in portfolios of the investors with openness and conscientiousness traits than those with other personality traits.
The cost incurred by the investors in acquiring information is compensated by investment in risky assets, and in doing so, the investors expect greater returns (Tauni, 2017) Investors having more information and high-risk investments are expected to adjust their portfolio more frequently and, therefore, are likely to trade more (Peress, 2004). The existing literature gives evidence that investors use various information search strategies to help them make trading decisions. These information search strategies are usually based on the time spent on information search, number of contacts by phone or visit and the number of sources used by investors to gather market information. It is implied that the quality of information source has an impact on investor trading behavior, as a piece of news from a reliable source may lead to more trading than from a less trustworthy one (Epstein and Schneider, 2008). In one of the sub-disciplines of psychology, i.e. personality psychology, it is argued that personality is a key determinant of human behavior and performance. A relative lack of investigation into the impact of the main sources of information on trading may affect psychological behavior of investors in the futures market. The impact of different sources of information on trading behavior may vary depending on the investor personality traits.
Most investors initially think that all they have to do is find the “right” strategy, make an investment, follow their plan and everything will be fine. Doing this is easier said than done. For example, you have made your investments and built your carefully planned portfolio but along comes the first major correction in the share market and you start losing money. How are you going to react and what will you feel? Most new investors (and even some more experienced ones) will watch as the value of their investments falls and the emotion of not wanting to lose money means that they hold onto a position in the “hope” that one day it will recover.
Studies have shown that people suffer almost twice as much pain losing $1 as they would feel pleasure in gaining $1 (Kahneman and Tversky, 1991) hence motivating investors to hold onto losing positions rather than selling to preserve their capital so that they can invest another day. In this case, emotion is hijacking the investors decision making skills. Even though they know that they should “cut losses early and let profits run”, investors hold onto a position with the view that until they actually sell the position they have not actually made the loss or that is their rationale, even though it is not a logical one.
Investing should be a rational process but investors often make it an emotional one. A good investor should spend the time to gain a better understanding of how they think, become aware of their flaws and develop discipline to combat negative psychological effects, hence becoming a more effective and successful investor.
About Us | Investing in a New World | BlackRock. (2017). BlackRock. Retrieved 26 August 2017, from https://www.blackrock.com/au/individual/about-blackrock
Hope, G. (2017). The Quants Run Wall Street Now. WSJ. Retrieved 26 August 2017, from https://www.wsj.com/articles/the-quants-run-wall-street-now-1495389108
Weisenthal, M., & Alloway, M. (2017). Odd Lots: This Is What a Real-Life Wendy Rhoades Actually Does. Bloomberg.com. Retrieved 26 August 2017, from https://www.bloomberg.com/news/articles/2017-06-26/odd-lots-this-is-what-a-real-life-wendy-rhoades-actually-does
Wigglesworth, R. (2017). Goldman Sachsâ€™ lessons from the â€˜quant quakeâ€™. Ft.com. Retrieved 26 August 2017, from https://www.ft.com/content/fdfd5e78-0283-11e7-aa5b-6bb07f5c8e12
Seasholes, M. S., & Wu, G. (2007). Predictable behavior, profits, and attention. Journal of Empirical Finance, 15, 590â€“610.
Alicke, M.D., & Govorun, O. (2005). The better-than-average effect. In M.D. Alicke, D.A. Dunning, & J. I. Krueger, (Eds.), The self in social judgment. New York: Psychology Press.
Gong-Meng Chena, Kenneth A. Kimb, John R. Nofsingerd, Oliver M. Ruie (2005): Behavior and performance of emerging market investors: Evidence from China
L. Osler (March 2003): STOP-LOSS ORDERS AND PRICE CASCADES IN CURRENCY MARKETS, Graduate School of International Economics and Finance; Brandeis University
Trade Mentor Chap 3.3 Trading Phycology – The Corner Bank Website- https://www.cornertrader.ch/export/sites/cornertrader/.content/.galleries/downloads/website/tutorials/3-3-trading-psychology.pdf
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Master of International Business student in Melbourne Business School. Prior to his time in the MBS, he was working at the Institute of Social and Economic Research-Universitas Indonesia and has published several working papers on the implication of economic and social developments toward the perceived level of corruption in both developing and developed countries.