ACFI 5078 The Psychology Behind Stock Market Bubbles Assignment Sample

ACFI 5078 The Psychology Behind Stock Market Bubbles

Introduction - ACFI 5078 Understanding Stock Market Bubbles Through Behavioral Finance Theories

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Stock Market bubbles can be understood as an economic cycle wherein the market value escalates in comparison to the value of assets that do not follow the exuberant market behavior. This brings us to the realization of financial literacy and the vitality of the study of Financial Behavior to understand what blows the bubble and what happens when it bursts. Financial Behavior is the study of human psychology regarding financial decisions. It discusses how even the most literate and knowledgeable man can be trapped by an unbalanced emotional quotient and biases (BENJAMIN, 2020). A bubble is identified when the market value is much more than the underlying fundamental value of the assets of the companies. Black Monday pushed the US market down by more than 20% in one day. One of the causes was no correction in the bull market for straight 5 years. In this report, we are going to shed light on how Behavioral Finance determines the cause and effect of such vicious bubbles (De Grauwe and Grimaldi, 2018). It will discuss Japan’s Bubble Economy, the Dot-Com bubble of the late 90s, the 2008 Market bubble, and China’s 2015 Bubble.

Japan’s Bubble Economy

During the period of 1960 and 1980, Japan’s economy saw unprecedented growth and was the fastest growing economy at that time. To combat the effects of the endaka recession, the government adopted an aggressive fiscal policy and injected money into the market through public investments. With easy access to loans and low-interest rates, corporates were overwhelmed with the inflow of money in the market driving inflation up. Instead of making way to infrastructure development, this money was used by capitalists to earn through speculations (De Grauwe and Grimaldi, 2018). A corporate invention, Zaitech leveraged speculations to be seen as a means to earn profit. So here, it was clear that the money was rolling and the production by each company was not meeting the market value at what these were positioned (Hu and Oxley, 2018).

Moreover, these companies reported that 50% of their earnings was from speculation trading and not from the production of goods and services. With land collateral (as these were highly valued), people became highly influenced by the profit that rolled out from the stock market and took loans against their properties to gain from the market. In self-deception theory, one ceases to learn and deceive themselves by not applying the wisdom one learned from the past. There was no production and only the money was rolling that has happened before also but investors failed to acknowledge it (Grohmann, 2018).

The government realized the ongoing situation and tightened monetary policies taking the interest rate higher in five rounds, from 2.5% to 6%. The Nikkie reached the zenith on 31st December 1989 following a gloomy fall in January. It dropped from 37,189 in January 1990 to drop dead 23,849 in December 1990 plunging by more than 35% (Hu and Oxley, 2018). The herd instinct defines that as human beings, we tend to follow the trend and we follow the mass because it is easier than learning valuing stocks.

19 October 1987 Black Monday

What can possibly happen in 90 mins span? DJIA can hit rock bottom by plunging 22%. It did happen and the market triggers reported are weakening dollar, persistent trade deficit, and tax legislation that hiked the taxes for corporates. But the underlying factor ascertained was cognitive biases theory including the gut feeling of investors that the stocks are valued at much higher prices than the value of assets held by companies. We will discuss the exogenous change that triggered investors' behavior and perception (element of the cognitive biases theory) that led to this steep decline. It is true that market news was one of the visible reasons for this steep decline but how investors perceived the whole situation could be the major reason (Quennouëlle-Corre, 2021). As the confusion rose among global investors regarding the volatility in the market and prices of stock held by them, contagion fear spread rampantly. The feedback loop was created and investors who spread the news of the stock market being overvalued received the same news from their peers in the industry. This is also known as noise trading when people follow market psychology to form their decisions. Basing decisions on unauthentic and unquantifiable information led to taking erroneous actions. It is widely accepted with the provision of evidence that most of the trades are based on half-baked knowledge and irrelevant information and facts, an example of Heuristic Simplification (Grohmann, 2018). This resulted in the bubble bursting on Monday, taking 19 countries' indexes to plunge more than 20% with Hong Kong being the worst hit by 45.8 % in a single day. People lost their hard-earned earnings, got trapped in vicious debt, and learned a lesson on this unfortunate day (Quennouëlle-Corre, 2021).

Dot-Com Bubble- 1995

The Tech industry has performed wonders, not only in the real marketplace but also in the stock market. The heuristic simplification suggests that people make decisions based on simplified alternatives than finding answers for complicated situations. It is truly perceived that the internet has immense scope to grow in the future but what company would be the driver, was not known. People started pumping money into every other internet start-up, not analyzing their potential, revenue model, and their business’s vision and operations. In 1993, with the introduction of mosaic, World Wide Web, internet traffic increased by 35%. This created an urge to invest in internet-based companies, at any valuation. This was spread across the investors and it was assumed to be the most appropriate decision at that time (Singh, Babshetti, and Shivaprasad, 2021). These companies spent the amount they received through venture capital in advertising and increasing their network which led them to run operating losses. They were not just being inefficient, they were not doing what investors perceived them to do! Grow the internet business. It was indeed the fastest rise and fall in the stock market (Nanayakkara, Nimal, and Weerakoon, 2019). This teaches us to stick to fundamental analysis and ascertain the business operations and growth prospects before investing. Following the Herd instincts theory, a mass trend whether it is in the general economy or the stock market can lead to the disclosure of catastrophe later. In the span of five years the NASDAQ Composite Stock market sky-rocketed to 400% when it reached its peak and fell to 78% in October 2002 (Singh, Babshetti, and Shivaprasad, 2021).

2008 Market Bubble

It is a story of ‘How a dream for a house can turn into a nightmare. It all started with the idea of subprime mortgages that aimed at lending home loans to poor people with low credit ratings and high-risk levels. Due to the high-risk levels, the interest rates were also kept high but the EMIs were initially affordable and modest but increased subsequently. This is the perfect example of Heuristic Simplification that implies erroneous processing of information to simplify decisions (Nanayakkara, Nimal, and Weerakoon, 2019). The idea was that even if the borrower falls defaulter, the lender will take back the house and sell it at a profit as prices of land and building appreciate with economic growth. This idea fueled up the stock market prices of Mortgage-backed securities. These securities were even given AAA ratings which meant these are the safest and most profitable instruments and investors fell into this trap (Fields and Hodkinson, 2018). Following a predatory approach, lending institutes started to produce more mortgages without even verifying the income of borrowers. But when there was a large number of defaulters, their houses were available on sale. And when supply is more than demand, the prices start to fall. According to Heuristic Simplification, investors failed to realize that when all borrowers would default, who will buy the houses? Financial institutes stopped investing in these securities and investors realized there was no turning back, there were houses but no buyers. It meant that their money was blocked. By 2007, these big lenders concluded bankruptcy raising alarms for investors (Fields and Hodkinson, 2018). And in the following year, the US market witnessed a catastrophic crash. Dow Jones recorded 3,600 points in just 20 days from 11,483 on 19th September 2008 to 7,882 on 10th October,2008. Investors lost their capital and many mortgage companies went bankrupt. Behavioral Finance suggests two pillars to make rational decisions, cognitive Psychology, and limits to arbitrage, both of which, were ignored in this scenario (BENJAMIN, 2020).

China’s 2015, Black Monday

Now the largest economy by the GDP, Chinese investors had predicted this growth back in 2015. Driven by young enthusiastic investors and over-confidence in economic growth, the stocks were valued higher in the market due to increased demand than the actual economic growth and what the companies could produce out of their assets as profit. It is the perfect example of lack of self-control, the role of media, and the government in influencing the financial decisions of an individual. Even if you live in a house full of investors, it is better to carry out research yourself! When the Chinese government faced sluggish economic growth after the 2007-08 recession, it introduced a stimulus package and through state-owned media influenced individuals to trade in the stock market (Wang and Hui, 2018). About 85% of the total population constituted the retail investors' group with most of them borrowing money to trade. This led to the Shanghai Stock Exchange falling more than 30%. This was a consequence of the sharp increase by 150% in the prices of stock in just one year. With the Self-deception theory in place (lack of knowledge of own financial health and market), even a slight correction created an urgency to sell among retail investors because most of these investors had no stock market literacy. Graham correctly stated in ‘Intelligent Investor’ that one must be enabled to harness the emotions and be thoughtful along with being disciplined and patient to become a successful investor. He further adds that it is a behavioral trait rather than a mind game (Wang and Hui, 2018)..

Conclusion

This essay discusses how human psychology can defeat financial literacy to drive the market upside down. Even, Einstein stated that he “could measure the motion of heavenly bodies, but not the madness of the people.” Theories such as cognitive biases, Self-deception, Herd instincts, and Heuristic Simplification suggest that even financial literacy couldn’t prevent investors to fall into the trap of a stock market bubble. Each bubble might have different stories but the core question was whether the highly valued companies were generating enough revenue from their operations or not. The mortgage securities justify the quote that Statistics are like bikinis, what they reveal is suggestive but what they conceal is vital. The unmatched supply-demand, blocked capital were concealed implications of this bubble. And therefore, I emphasized ‘Revenue from operations’. Emotional Intelligence is primal to becoming an investor.

 References

BENJAMIN, E.G., 2020. THE INTELLIGENT INVESTOR REV.

De Grauwe, P. and Grimaldi, M., 2018. The exchange rate in a behavioral finance framework. Princeton University Press.

Fields, D.J. and Hodkinson, S.N., 2018. Housing policy in crisis: An international perspective. Housing Policy Debate, 28(1), pp.1-5.

Grohmann, A., 2018. Financial literacy and financial behavior: Evidence from the emerging Asian middle class. Pacific-Basin Finance Journal, 48, pp.129-143.

Hu, Y. and Oxley, L., 2018. Bubble contagion: Evidence from Japan’s asset price bubble of the 1980-90s. Journal of the Japanese and International Economies, 50, pp.89-95.

Nanayakkara, N.S., Nimal, P.D. and Weerakoon, Y.K., 2019. Behavioural asset pricing: a review. International Journal of Economics and Financial Issues, 9(4), p.101.

Quennouëlle-Corre, L., 2021. The 1987 Stock Exchange Crash in Historical Perspective. Remembering and Learning from Financial Crises, p.165.

Singh, J.E., Babshetti, V. and Shivaprasad, H.N., 2021. Efficient Market Hypothesis to Behavioral Finance: A Review of Rationality to Irrationality. Materials Today: Proceedings.

Wang, X. and Hui, X., 2018. Cross-sectoral information transfer in the Chinese stock market around its crash in 2015. Entropy, 20(9), p.663.