Rationale
In the late sixteenth century, the introduction of tulip bulbs from Constantinople to Holland by Conrad Guestner sparked a massive investment frenzy Tulips quickly became a status symbol among the Dutch elite due to their beauty and rarity, prompting speculators to enter the market The obsession with tulips extended to the middle class, leading many to sell their possessions to acquire these prized bulbs, anticipating their value would continue to rise At the peak of the tulip mania in 1636, prices soared to levels equivalent to several tons of grain or valuable livestock However, the bubble burst in 1637 when speculators began selling off their tulips, causing prices to plummet by nearly 90% in just one month, resulting in significant financial losses for many investors.
The narrative illustrates a classic example of economic bubbles, which have not only been evident in the tulip bulb market but also in the Florida real estate market and, notably, in stock markets.
(South Sea bubble, Great Depression in America, dotcom bubble, etc.) So, besides the speculation, it is questioned if there are any other factors creating the bubbles in the markets.
If the answer to the previous question is "No," it prompts a discussion on stock market bubbles, highlighting that this market has experienced the highest number of bubbles in history.
Since the inception of stock markets, investors and financial analysts have created numerous numerical techniques to assess and predict stock values, rooted in standard finance principles that assume rational investors and efficient markets This framework suggests that if investors act rationally and markets function efficiently, speculation alone should not lead to market bubbles Yet, the persistent occurrence of bubbles in stock markets raises critical questions about these assumptions.
After the Nobel Prize in Economics of Daniel Kahneman for his study of Prospect Theory in 2002, behavioral finance became popular among financial practitioners and academics.
Behavioral finance explores how emotional and psychological factors influence investor behavior, contrasting with traditional finance's assumption of rationality It identifies various biases, such as overconfidence, overreaction, mental accounting, and herding behavior, which can lead to market bubbles by creating unrealistic expectations and driving prices away from their true value Additionally, these irrational behaviors can cause abnormal fluctuations in stock prices.
Together with bias discoveries, suggestions to solve those biases have been also developed by the economists to help investors enhance their investment returns
Behavioral finance has evolved over the past 40 years globally but remains a relatively new concept in Vietnam This research aims to explore the behaviors of Vietnamese individual investors, specifically focusing on identifying their irrational behaviors in the current stock market.
Background of Vietnam stock market
Vietnam stock market officially came into operation since July 20, 2000 with an establishment of Ho Chi Minh Stock Exchange (HOSE) Then, in March 8, 2005, Hanoi
Stock Exchange (HNX) was inaugurated From only two companies listed in HOSE in
2000, the number of listed companies in Vietnam stock market at the moment is 682, with
The Vietnam stock market has experienced rapid growth, with 313 companies listed on HOSE and 396 on HNX, along with 27 companies on both exchanges This surge can be attributed to the straightforward registration process and low initial investment requirements, making it accessible for a wide range of investors.
After 12 years of operation, the Vietnam stock market has navigated various phases, beginning with a startup stage from 2000 to 2005, during which its capitalization was modest, representing only about 1% of the total GDP This was followed by a significant boom in 2006, marking a pivotal moment in its growth trajectory.
In 2007, Vietnam's stock market capitalization reached 43% of GDP, but faced significant challenges in 2008 due to domestic and global economic difficulties, leading to a decline to 18% The market began to recover in 2009, with stock market capitalization rising to 37.7% of GDP, and further increasing to 40% in 2010 However, 2011 proved to be a tough year for both the Vietnamese economy and its stock market, as high inflation prompted the government to tighten monetary policy and cut public spending.
At the end of the year, Vietnam's stock market experienced a significant decline, with market capitalization dropping to approximately 20% of the total GDP However, following the first quarter of 2012, positive indicators from the government's inflation-reduction initiatives have led to a modest recovery in both market capitalization and liquidity in the Vietnam stock market.
Over the past 12 years, the Vietnam stock market has experienced significant volatility, characterized by sharp fluctuations in stock prices Notably, during the 2006 bubble, stock prices surged across the board, while in 2011, they plummeted regardless of companies' business performance This phenomenon highlights that stock prices are theoretically influenced solely by the information available in the market.
Hence, in the economic conditions and operating information of companies in 2006 or
2011, those abnormal movements of Vietnamese stock market may be the consequences of psychological factors of investors in market.
Research objectives
Investors in the Vietnam stock market have gained significantly more experience compared to 12 years ago In 2006, during the peak of the market bubble, the investor demographic was diverse, encompassing various occupations, ages, and education levels This period was marked by a notable herding behavior among investors However, following the bubble's collapse, the composition of active market participants has evolved, indicating a shift in the characteristics of investors over time.
This research investigates the cognitive errors of individual investors in the Vietnamese stock market, identifying common biases and their correlation with personal factors The study aims to offer recommendations that help investors modify irrational behaviors and improve their investment outcomes.
Research questions
In this research, the following questions are going to be answered:
1 Is prospect theory applicable for individual investors in Vietnam stock market?
2 Do behavioral biases exist in Vietnam stock market? If yes, what are those biases?
How is the relationship between those biases and personal factors of individual investors?
Significance of Research
Behavioral finance, a field gaining traction among global financial practitioners and academics, reveals significant insights into investor biases In Vietnam, however, this discipline remains relatively unexplored, with the predominant focus on herding behavior among investors.
Vietnam stock market is mentioned
This research offers a comprehensive analysis of individual investor behavior in the Vietnamese stock market, focusing on herding behavior and various cognitive biases It explores biases rooted in Daniel Kahneman's prospect theory, including overconfidence, over-optimism, representativeness, loss aversion, regret aversion, and seasonality The findings can enhance the understanding of standard finance principles, enabling individual investors in Vietnam to apply these insights to their investment strategies.
Research scope
Research has shown no geographical differences in investor behavior, leading to a focused study on individual investors in the Hanoi stock exchange This study aims to identify cognitive errors among Vietnamese investors, utilizing primary sources for data collection.
LITERATURE REVIEW 11 1 Standard Finance
Four Pillars of Standard Finance’s Model
a Modigliani – Miller Theorems (Capital Structure Irrelevance Principle), Franco
In 1958, Franco Modigliani and Merton Miller introduced a theorem that asserts, under specific conditions such as the absence of taxes, bankruptcy costs, and asymmetric information in an efficient market, a company's method of financing its assets does not influence its overall value.
The theorem, which is made up of two propositions, was initially proven under the assumption without taxes
VU is the value of an unlevered firm
VL is the value of a levered firm
ke is the required rate of return on equity, or cost of equity.
k0 is the company unlevered cost of capital
kd is the required rate of return on borrowings, or cost of debt.
is the debt-to-equity ratio.
Two propositions can also be extended to a situation with taxes.
VL is the value of a levered firm.
VU is the value of an unlevered firm.
TCD is the tax rate (TC) x the value of debt (D)
rE is the required rate of return on equity
r0 is the company cost of equity capital with no leverage
rD is the required rate of return on borrowings, or cost of debt.
D / E is the debt-to-equity ratio.
Tc is the tax rate.
The Modigliani–Miller theorem has significantly influenced capital markets by encouraging the use of leverage, as firms can deduct interest payments in a taxed environment Additionally, Modern Portfolio Theory, developed by Harry Markowitz, emphasizes the importance of diversification in investment portfolios to optimize returns while minimizing risk.
Modern Portfolio Theory was introduced in a 1952 article and a 1959 book named
“Portfolio Selection” by Harry Markowitz
This theory provides portfolio managers with a useful tool to decide the weights of different assets in order to set up an optimal portfolio MPT based on the concept of
“diversification”, which is a collection of various investment assets that generally lower the risks created by individual assets.
In Modern Portfolio Theory (MPT), asset returns are modeled as a normally distributed function, with risk quantified by the standard deviation of those returns A portfolio consists of a weighted assortment of assets, and its overall return is derived from the weighted average of the individual asset returns By strategically combining assets that are imperfectly positively correlated, MPT effectively minimizes the overall variance of the portfolio's return.
Portfolio return is the proportion-weighted combination of the different assets' returns
Rp is the return on the portfolio
Ri is the return on asset i and wi is the weighting of component asset i
Portfolio volatility is a function of the correlations ρij of the component assets, for all asset pairs (i, j) We have the following formulations:
Where ρij is the correlation coefficient between the returns on assets i and j
Alternatively the expression can be written as:
Portfolio-return volatility (standard deviation): c Capital Asset Pricing Model (CAPM), John Lintner & William Sharpe
Based on MPT of Harry Markowitz, Capital Asset Pricing Model was developed by
The Capital Asset Pricing Model (CAPM) is a framework utilized for determining the price of individual securities or portfolios It employs the Security Market Line (SML) to illustrate the relationship between expected returns and systematic risk, represented by beta, thereby demonstrating how the market values individual securities based on their risk classification.
is the expected return on the capital asset
is the risk-free rate of interest
(the beta) is the sensitivity of the expected excess asset returns to the expected excess market returns, or also
is the expected return of the market
is known as the market premium d Black-Scholes Model (Options Pricing Model), Fischer Black, Myron Scholes &
The Black-Scholes Model was first devised in 1973 by Fischer Black and Myron Scholes, and then developed by Robert Merton
S is the price of the stock
V(S,t) is the price of a derivative as a function of time and stock price.
r is the annualized risk-free interest rate, continuously compounded.
σ is the volatility of the stock's returns
Investors can mitigate risk by strategically buying and selling the appropriate underlying assets, as indicated by the equation This hedging approach suggests that there is a singular correct price for the option, as determined by the Black-Scholes formula, which specifically values a call option.
The price of a corresponding put option based on put-call parity is:
is the cumulative distribution function of the standard normal distribution
C(S,t) the price of a European call option and P(S,t) the price of a European put option.
T − t is the time to maturity
S is the spot price of the underlying asset
r is the risk free rate
σ is the volatility of returns of the underlying asset
Standard Finance Approach
Standard Finance focuses on two primary objectives: risk and return The four models within this framework aim to minimize or eliminate risks while maximizing returns This approach is based on two simplified assumptions: that investors act rationally and that markets are efficient, meaning asset prices consistently reflect their intrinsic values.
Input Elements of Standard Finance
Standard Finance utilizes statistical measures of risk and return to create optimal investment portfolios However, these models often overlook important factors, such as the unique characteristics and preferences of individual investors.
Limitation of Standard Finance
The framework of Standard Finance makes assumptions about both investors and markets that create limitations for application in reality.
Standard Finance's primary limitation lies in its assumption that all investors seek to maximize economic utility, along with the belief that they are rational and risk-averse However, in reality, investors frequently exhibit biases and are influenced by various external factors.
One key limitation of the efficient market hypothesis is the assumption that market prices always equal intrinsic values In reality, market prices frequently diverge from true asset values due to irrational investor behavior Moreover, not all investors have simultaneous access to the same information, leading to disparities in decision-making Additionally, the notion that all investors act as price takers is flawed, as large investors can significantly influence market dynamics through their substantial buying and selling activities.
In conclusion, while estimating the covariance of certain assets is feasible, accurately measuring expected returns remains challenging Constructing a portfolio solely based on statistical measures of risk and returns can lead to oversimplified outcomes, making it impossible to achieve an exact optimal solution tailored to each investor's needs.
Behavioral Finance
Prospect theory regarded as the foundation of behavioral finance was firstly developed by
Daniel Kahneman and Amos Tversky in 1979, Tversky and Kahneman in 1992 Later on, some further ideologies based on prospect theory were developed by Chew and Mac
Crimmon (1979), Chew (1983), Bell (1982), Loomes and Sugden (1982), Quiggin (1982),
Segan (1987, 1989), Yarri (1987) and so on.
The paper on prospect theory that was introduced the first time by Daniel Kahneman and
In 1979, Amos Tversky critiqued expected utility theory as a descriptive model for decision-making under risk, highlighting its limitations In contrast, prospect theory offers a more accurate understanding of human behavior in real-world scenarios involving risk and uncertainty This innovative approach not only addresses the shortcomings of expected utility theory but also presents an alternative model for evaluating decision-making processes.
2.1.1 Critique on expected utility theory a Expected utility theory
Expected utility theory serves as a crucial cornerstone of behavioral finance, examining how individuals make decisions in the face of risk and uncertainty This theory delves into the process of evaluating different prospects and making informed choices when outcomes are uncertain.
A prospect is defined as a contract that produces an outcome \( x_i \) with a corresponding probability \( p_i \), where the sum of all probabilities equals one For simplicity, we exclude null outcomes and represent a prospect as \( (x, p) \), indicating that it yields \( x \) with probability \( p \) and zero with probability \( 1 - p \) Additionally, a riskless prospect that guarantees the outcome \( x \) is represented simply as \( (x) \).
Choosing between different prospects relies on their respective utilities, which can be quantified using the utility function The expected utility of an outcome, denoted as u(xi), plays a crucial role in this evaluation The application of expected utility theory to decision-making is founded on three fundamental principles.
(ii) Asset integration: (x 1 , p 1 ; x 2 , p 2 ; …; x n, p n )is acceptable at asset position w if U(w
(iii) Risk aversion: u is concave (u ''