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Behavioral Finance Theory

2023/2/24 16:26:04  Classification:   Participation: 7  

Behavioral f rebateinforextradingance rebatesinforex the application of cashback forex science, psychology best forex rebate cognitive science results to financial markets, finite rationality and finite arbitrage are its two pillars It uses prospect the bestforexrebate to describe the real nature of people, rebatemeaninginforex investors in financial markets is not with long-term rational behavior, at most have limited rationality in the short term, in a specific decision, investors may be rational, correct; but In the long run, investors do not have an integrated, continuous optimal investment decision, can not act in strict accordance with Bayesian rules, their investment behavior is irrational, or even wrong (a) theoretical basis 1. expectation theory expectation theory is an important theoretical basis of behavioral finance Kahneman and Tversky (1979) found through experimental comparison, most investors are not standard Financial investors but behavioral investors, their behavior is not always rational, and not always risk-averse expectancy theory that the investors utility function of the return is a concave function, while the utility function of the loss is a convex function, which shows that investors are more risk averse when investing in book value loss, and in the investment of book value profit, with the increase in earnings, the speed of its satisfaction slowed down expectancy theory has become a behavioral However, since Kahneman and Tversky did not give a key reference point in the expectation theory to determine the value function and the specific value function of the value function, they have not been able to explain the anomalies in the financial market, such as the Allais paradox, the equity premium puzzle, and the option smile. -2. Behavioral Portfolio Theory (BPT) and Behavioral Asset Pricing Model (BAPM) Some researchers in financial theory believe that it is inappropriate to completely oppose behavioral financial theory with modern financial theory. The BPT argues that real investors are unable to do this, and that the actual portfolio they construct is a pyramidal behavioral portfolio based on their knowledge of the risk level of different assets and their investment objectives, with the assets located at each level of the pyramid linked to a specific The correlations between the layers are ignored BAPM is an extension of the modern Capital Asset Pricing Model (CAPM) Unlike CAPM, investors in BAPM are divided into two categories: information traders and noise traders Information traders are rational traders who act strictly according to CAPM and do not suffer from systematic biases; noise traders do not act according to CAPM and In fact, in BAPM, the problem of capital market portfolio still exists because the mean-variance efficient portfolio changes over time (ii) Investment behavior models 1.BSV model (Barberis, Shleffer, and Vishny, 1998) The BSV model argues that people (Barberis, Shleffer, and Vishny, 1998) The BSV model suggests that there are two error paradigms in making investment decisions: one is selective bias (representative bias), in which investors pay too much attention to the pattern of changes in recent data and not enough to the overall characteristics that generate these data, and this bias leads to an under-reaction of stock prices to changes in returns (under-reaction) and the other is conservative bias ( conservation), where investors fail to correct their forecasting models in a timely manner in response to changed conditions, leading to stock price overreaction (over-reaction) The BSV model starts from these two biases and explains how investors decision models lead to market price changes in securities that deviate from the efficient market hypothesis 2. The DHS model (Daniel Hirsheifer and Subramanyam, 1998) This model classifies investors into informed and uninformed categories uninformed investors do not have judgment bias, informed investors have overconfidence and biased self-attribution (serf-contribution) overconfidence leads investors to exaggerate the accuracy of their judgment of stock value; biased self-attribution makes them The biased self-attribution causes them to underestimate the public signals about stock value As public information eventually overcomes behavioral biases, overreaction to personal information and underreaction to public information lead to short-term continuity and long-term reversal of stock returns So Fama (1998) argues that although the DHS model and the BSV model are based on different behavioral premises, the conclusions of both are similar　　The HS model (Hong and Stein, 1999), also known as the unified theory model, differs from the BSV and DHS models in that it focuses on the mechanism of action of different actors rather than on the cognitive biases of the actors. Under these assumptions, the model uniformly attributes under- and over-reaction to the gradual diffusion of information about fundamental values, without including other factors that may have a negative impact on investors emotional stimulus and the impact of the DHS model. The model argues that the initial tendency of observant newsmakers to underreact to private information leads momentum traders to try to exploit this through hedging strategies, and that doing so leads to exactly the other extreme - overreaction 4. The herd behavior is in line with the maximum utility criterion, is the irrational behavior carried out under group pressure and other emotions, there are two types of models sequential and non-sequential sequential model proposed by Banerjee (1992), in this model, investors through a typical Bayesian process from the market noise and other individual decisions in order to obtain decision information, the most important feature of such decisions is the sequential nature of their decisions but In reality, it is unrealistic to distinguish the order of investors and thus this hypothesis lacks support in the actual financial market. The non-sequential type then argues that regardless of the strong or weak tendency to imitate, the thick-tailed characteristics of the zero-point symmetry and unimodality of the modern financial theory on stocks are not obtained (III) Empirical tests Since the 1980s, empirical studies contradicting the modern financial theory have emerged, mainly in the form of investment The change in strategy The following are a few typical behavioral financial strategies: 1. The small firm effect The small firm effect refers to the higher return of small-cap stocks than large-cap stocks Banz (1981) found a trend of decreasing stock market capitalization with increasing firm size In the same year, Reimganum (1981) also found that the average return of common stocks with the smallest firm size is 18 percent higher than the average return based on the CAPM model More recently Siegl (1998) found that on average small-cap stocks have a 4.7% higher annual return than large-cap stocks and that most of the small firm effect is concentrated in January Since both firm size and the arrival of January are known information to the market, this phenomenon clearly violates the semi-strong efficient market assumption Lakonishok et al. (1994) The study found that stocks with high P/E ratios are more risky, and the inverse relationship between particularly poor performance P/E ratios and returns during broad market declines and recessions poses a serious challenge to the EMH, because this is when known information has a significant predictive effect on returns 2. The contrary investment strategy (contrary investment strategy) is to buy stocks that have performed poorly in the past and Some studies have shown that, for example, choosing stocks with low price-to-earnings (PE) ratios; choosing stocks with low market capitalization to book value ratios and low historical returns can often yield much higher returns than expected, and such returns are a long-term abnormal returns (1ong-term anomalies) Desia, Jain (1997). Jain (1997), Ikenberry, Rankine Stice (1996) also found positive long-term abnormal return behavior before and after the stock split of the company Financial theory considers the inverse investment strategy as a correction of the stock market overreaction, a simple extrapolation 3. momentum trading strategy (momentum trading　The momentum trading strategy is an investment strategy that first sets a filter on stock returns and trading volume, and buys or sells stocks when the stock market returns and trading volume meet the filter. In fact, the US value line rankings are an example of the use of momentum trading strategies. The averaging strategy refers to a strategy in which investors buy stocks in batches according to different prices in order to amortize the cost in case of unpredictability, while the time diversification refers to a strategy in which the proportion of stocks is gradually reduced as the investor ages based on the belief that the risk of stocks will decrease as the investment horizon increases These two strategies are considered to be in clear contradiction with the modern financial theory of expected utility maximization Statman (1995 ), Fisher, and Statman (1999) explain the two strategies using ideas from expectancy theory, cognitive error propensity, and aversion to regret in behavioral finance, pointing out suggestions for improvements to strengthen self-control (iv) Prospects for behavioral finance Behavioral finance originated as an explanation for financial market anomalies Kuhn (1970) points out that, historically, for significant anomalies First, the initial appearance of the anomaly can be explained immediately under the original theoretical framework Second, the existing knowledge is considered unable to solve the problem, leaving it to future researchers Third, the theoretical basis changes, allowing the anomaly to be explained under a new framework It is clear that the research efforts of behavioral finance are the third response Behavioral finance, in trying to explain the anomaly, draws on psychological The study of human psychology and behavior patterns, thus making the premise assumptions of its theory close to reality, i.e., is changing the theoretical foundation of modern financial theory There are few well-formed behavioral finance models, and the focus of research remains on the qualitative description and historical observation of market anomalies and cognitive biases, as well as the identification of behavioral decision attributes that may have a systematic impact on financial market behavior Since the psychology of human decision making is FrankfurterandMcGoun(2002) argue that the rebuttal of behavioral finance is impotent and eventually to be assimilated by modern financial absorption I do not agree with this view because although the current behavioral finance research is relatively loose, it is ultimately to build a unified behavioral finance theory with systematic explanatory power Only after the accumulation of this stage is it possible to eventually establish a unified system. The psychological decision properties that have been identified as having potential axiomatic status include: decision makers preferences are generally multifaceted, open to change, and often formed during the decision itself; decision makers are adaptive, and the nature of the decision and the environment influence the decision process and the choice of decision techniques; decision makers seek satisfaction in the decision. Therefore, it is the general process and development direction of behavioral finance research to continue to apply psychological findings to financial research with the aim of establishing a unified and systematic psychological framework for decision making and developing a complete behavioral finance theory based on this framework and, with the end of this process, behavioral finance will naturally replace modern A clear trend in the development of modern economics is to focus more and more on the microfoundations of theories and the study of individual behavior, as revealed by the development of game theory, information economics and the theory of the firm. The advantages of behavioral finance are obvious and because it is a marginal discipline, its development prospects will be very broad with the further development of other disciplines such as psychology, sociology, behavioral economics, and decision theory.

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