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BehavioralPortfolio Theory

Behavioral

portfolio

theory(BPT), introduced by Shefrin and Statman (2000), provides an alternative to the assumption that the ultimate motivation for investors is the maximization of the value of their portfolios. It suggests that investors have varied aims and create an investment portfolio that meets a broad range of goals such as considering expected wealth, desire for security and potential, aspiration levels, and probabilities of achieving aspiration goals.

Traditional finance is based on three concepts: (1) rational behavior, (2) the capital

asset

pricing model, and (3) efficient market. While, the behavioral finance argue that psychological force would change decision maker’s mind make it not rational anymore, besides the market is not always efficient as well.

The BPT theory is not follow the same principle as Mean-Variance theory, Capital Asset Pricing Model, and

Modern Portfolio Theory

.  However, authors developed BPT on the foundation of SP/A theory (Lopes, 1987) and prospect theory (Kahneman and Tversky, 1979) and closely related Safety-First Portfolio Theory.

In behavioral portfolio theory, authors build single account version of BPT -SA and multiple account version of BPT –MA. The theory is described as a single account version: BPT-SA, which is very closely related to the SP/A theory. In multiple account version (BPT-MA), investors can have fragmented portfolios, just as we observe among investors. They even propose in their initial article a 

Cobb–Douglas

 utility function that shows how money is allocated in the two 

mental accounts

.

The BPT efficient frontiers and the mean-variance frontiers do not coincide. Mean- variance investors choose portfolios by considering mean and variance, which means average and risk. However, investors choose portfolios by considering their expected wealth, security level and potential gain, how to achieve goals. Behavioral portfolio theory is also the observation that investors view their portfolios not as a whole, as prescribed by mean-variance portfolio theory, but as distinct mental account layers in a pyramid of assets, where mental account layers are associated with goals and where attitudes toward risk vary across layers.

The CAPM is a model used to determine a theoretically appropriate required 

rate of return

 of an asset, to make decisions about adding assets to a 

well-diversified

 portfolio. The CAPM investors combine the market portfolio and the risk-free security. In contrast, the BPT investors resemble combine bond and lotter tickets.

Safety- First Portfolio Theory (Roy, 1952) is a 

risk management

 technique that allows an investor to select one portfolio rather than another based on the criterion that the probability of the portfolio’s return falling below a minimum desired threshold is minimized. Roy was the first one who recognized a difference in financial decision-making that arose from varying behavioral sensitives according to the magnitude of a potential loss: some small-scale financial decisions may seek some target of return. Although this perception does reject rationality and other economic assumptions, its more realistic to model markets with awareness of this nearly universal human heuristic (Chen, 2016). Shefrin and Statman focus on choice theories where the axioms of expected utility are violated.

SP/A theory is a psychological theory of choice under uncertainty (Lopes, 1987). In Lopes’ framework, risk-taking is balanced between fear and hope. Lopes posits that fear is such a strong factor because fearful people overweight the probability of the worst outcomes, underweight those for the best outcomes. This leads individual to understate the probability of achieving the highest level of expected wealth.  In other words, fearful individuals are pessimistic. Hope has the inverse effect on individuals – optimism causes hopeful investors to overstate the probability of achieving the highest level of expected wealth. The single account version of BPT (BPT-SA) is based on SP/A theory. The BPT-SA investors are same as mean- variance investors, they consider the investment portfolio as a whole but the optimization criteria differ. BPT-SA investors intergrade their portfolio by considering the covariance.

The multiple account version of BPT-MA build on structure of prospect theory. BPT-MA investors overlook covariances and segregate their portfolio into separate mental account layers. Shefrin and Statman (1985) suggest that the original purchase price serves as a reference point in investment decisions. They use prospect theory to explain why investors sell winners too early and hold losers too long. Tversky and Kahneman demonstrate that the decision process for the investors becomes complicated and difficult due to covariance and other properties of joint probability distribution. Investors simplify their choice by use mental account.

BPT explains (1) investors are different from each other in both preferences and beliefs, (2) develop a behavioral portfolio selection model to explain how differences in preferences and beliefs lead to differences in investors’ portfolio decisions. (3) investors behave as if their portfolios consist of several layers, each with different objectives, trading patterns, and types of securities. Shefrin and Statman explored the links between BPT portfolio and mean variance, CAMP and VaR portfolio. They also discovered the similarities between BPT securities and real world securities such as bonds, stocks and options. BPT investors resemble combinations of bonds and lottery tickets. The bonds for the low aspiration mental account resemble risk-free or investment grade bonds while the bonds for the high aspiration mental account resemble speculative bonds.

Do Investors Expect Higher Returns from Safer Stocks than from Riskier Stock?

In modern finance, the relationship between risk and return based on core concepts as the capital market line and the security market line. The graph feature of these two concepts is positive slope, which means risk and expect return are positively related. However, in this article Shefrin and Belotti found that risk and expected return are negatively related. There are 5 questions will be explained.

1) What evidence is there that investors judge risk and return to be negatively related?

Author tracked eight technology companies’ stock for one year, and designed a survey ask the specific return that the companies expect for, and ask their perception of the riskiness of each stock on a scale of 0-10, risk free – extremely speculative. The result of the survey shows that riskier stocks will produce lower returns than safer stocks, risk and return have negative correlation.

2) What psychological forces would lead investors to form such judgments about risk and return?

As traditional finance defined that the expected return is positively related to risk, but why then do investors found the relationship to be negative? The authors suggest those investors rely on the behavioral heuristic representativeness which mentioned by Tversky and Kahneman in 1974. The key is representativeness involves over-reliance on stereotypes. Shefrin and Statman found investors judge that good stock are stocks of good companies by considering these two questions: goodness of a company and soundness of financial position. So, representativeness leads the investors judge that good companies are safe companies and good stocks to be the stocks of financially sound companies.

3) What implications do such judgments hold for the broad debate between proponents of market efficiency and proponents of behavioral finance?

The broad debate between market efficiency theory and behavioral finance is focus on the cross-sectional structure of realized return. Both parties agree with realized returns have a cross- sectional structure, such as size, book-to–market equity, past three-year returns and past sales growth. Supporters of market efficiency argue that these items can represent risk but behavioral finance supporters think those items reflect mispricing stemming from investor bias, particularly overreaction (Shefrin and Belotti, 2001). However, in authors point of review investors always form erroneous judgment about future returns, the key error in investors’ judgments has less to do with the nature of risk and more to do with the perception that risk and expected return are negatively related.

4) How robust are judgments about risk and return to judgments about the expected equity premium?

The authors suggest that the cross-sectional structure of return expectations remained stable in the face of volatile expectations about the return on the overall market. Based on my understanding if overall market is volatile, the cross- sectional structure of return expectations is still stable. However, Wall Street strategist’s think the magnitude of overall returns to the market are also volatile. Even academic economists hold volatile beliefs about the equity premium, the amount stocks are expected to return over and above the risk return. So, specialists predict market too readily, while individual investor project recent trends to readily.

5) To what extent are investors consciously aware of the way they form judgments about risk and return?

The most amazing things that the authors found is professional investors implicitly expecting higher returns from safer stocks, although they all educated in the tradition of risk and return being positively related. They accept the relationship between risk and return is positive, but in the real-world it is negatively related. The human nature is trying to avoid very risky stock

and find a more safer stock then expect higher return from it. So, based on the authors’ view high risk with high return is invalid.

6) How reliable is the evidence on risk and return presented here?

Shefrin and Stanman (2001) analyze the cross-sectional structure of the actual fortune variable value as a long-term investment as the evidence, and they found that the relationship between VLTI and firms’ characteristics parallels the relationship between expected returns and characteristics.

All in all, the biased judgment that investors make about risk and return appear to be robust, even in the face of a highly volatile time varying equity premium.

Behavioral Portfolio Analysis of Individual Investors

Investor behavior has significant influences on portfolio performance, and its analysis offers an eye-opener regarding behavioral biases on outcomes of various trading operations. For instance, findings from the analysis stock market players accordingly. For example, they understand market dynamics properly and increase performance level. In line with the modern portfolio theory, an investor who wishes to improve performance and minimize risks can ensure the following; he or she needs to put together investments which do not have any correlation. This way, they will be able to look at investment decisions objectively based on risks and returns associated. When it comes to investment, usually people are not as rational with money as they think before the money is earned. Therefore, an investor needs to get a good understanding of investment and behavior related to it as defined below.

Firstly, behavioral finance states that feelings, instincts and certain social influences dictate most of the investors’ decisions. On the other hand, investor behavior establishes the way an investor’s behavior affects his or her investment decisions. Also, it looks at the way decisions impacts investors’ portfolio performance during a given period. For instance, investors feeling overconfidence cause them to overestimate the accuracy of the predictions. It is because of an illusion of knowledge and control of anticipated results.

Based on investor behavioral, the following paper is tended to offer a detailed literature review of the article “Behavioral Portfolio Analysis of Individual Investors.” The review captures three most important concepts covered in the article. They include traditional and behavioral portfolio analysis, objectives and strategies of investment. Lastly, it highlights specific segments of investors based on investment objectives outlined.

The Traditional Portfolio Analysis

According to the article, the traditional model assumes that an investor’s subjective probable beliefs are correct objectively and that markets are often efficient. This way, the task of a portfolio involves managing investors’ risk profiles. It is dependent on their consumption history, current wealth status and labor income associated with a particular investment plan. As such, it means that the portfolio is important since it assists to hedge unpredicted labor income to harmonize consumption stream in a period. Certainly, it requires labor income to be highly volatile for trading activities to involve marginal adjustments. It is the main objective of balancing and dealing with individual investors’ liquidity requirements to finance their consumption cost-effectively.

Therefore, based on the article’s findings, the traditional model of the dynamic portfolio includes an expected utility. For example, it maximizes individual investor’s choice at a given time, securities and consumption stream. It is based on their initial stream of labor income, market prices and wealth each possess.

Behavioral Portfolio Analysis

As indicated in the article, the behavioral method as an approach to portfolio investor choice supports motives for trading and balances liquidity. For example, some of the motives for trading emphasized in the following article include reference point impacts on profits or losses and aspirations. Others are the disposition effect, status quo bias, inadequate saving, realization utility and lack of diversification among many investors. For instance, the disposition effect involves a behavior in which investors fear to venture into business containing high risks. Therefore, they often realize losses because of their reluctance to evaluate those risks.

Objectives and strategies for investment

Secondly, the article highlights objectives and consequently appropriate strategies which investors should make and take respectively with regards to their line of investment. Ordinarily, three major reasons for investing include safety, income and sustained growth and development with regards to investment objectives. Comparing these objectives with the article’s findings, the following is evident.

According to the article, investment objectives are usually determined and influenced by individual investor’s expectations within a specified period and preferences. For example, in addition to safety, income and growth needs, preferences and aspiration levels of investors form their investment objectives. In regards to the behavioral portfolio implication, investors with high aspirations show a high tolerance to risks. Consequently, they are likely to select risky portfolios, set aspiration levels and have a high likelihood of achieving them. In this case, risky portfolios regard those ventures are more exposed to market risks than others. Therefore, preferences and aspirations add to the list of investment objectives based on the article. They require certain strategies to achieve highlighted below.

The article asserts that investors who either prefer investing as a hobby or want to speculate have high convictions, tend to make bold predictions and set difficult objectives. As a result, they have to design effective strategies which will see emerge successfully. One of the strategies the article proposes for such investors involve regular measuring of individual investor performance. It is the change per month in the market value of securities with respect to an investor’s account. Also, investors should attribute returns on their portfolios to more than one risk factor achieve both normal and abnormal performance. As pointed in the article, the strategy helps to minimize risks and maximize one’s net returns.

Segments of Investors Based on Investment Objectives

Lastly, an area highlighted in the article worth pointing involves different segments based on the investment objectives explained above. These different groups of investors include capital growth, saving for retirement, hobby, financial buffer, and speculators. They are grouped according to investors’ major investment objective described as follows.

Investors who want to build financial buffer are motivated by the desire to accumulate wealth and thus want to diversify their investments. In regards to one’s hobby, some people invest for fun, and they are not deterred by risks involved. Unlike those investing to save for retirement, they are overconfidence. Additionally, this group of investors includes those who want discover and speculate. By comparing returns that each segment of investors records monthly, the article establishes the following. The highest monthly return and turnover are attained by those in the segment speculation while those saving for retirement record the lowest.

In brief, based on the above literature review on the behavioral analysis of individual investors, investment objectives and strategies stand out for the most part. For instance, without the consideration of a stylized model and segment one falls in, one will require formulating definite investment goals and means to achieve them within a given period. Again, investors seem to have a common desire; they want some level of income in their portfolios which can help them manage inflation rate in the economy. Therefore, based on the article, to increase investment returns and reduce risks, investors need to spend most of their time assessing suitable investment objectives and strategies.

Online Investors: What They Want, What They Do, And How Their Portfolio Perform

In this article, authors investigate 5,500 individual online investors’ attributes and attitudes and collect their transaction record try to understand what they want, what they do and how their portfolio perform. They create eight hypotheses to explain online investors’ investment behavior: (1) the objective of investing as a hobby or to speculate are associated with a higher turnover of stocks and derivatives, higher portfolio concentration, lower gross and net returns, and more risk-taking, (2) the objective to save for retirement is associated with a lower turnover of stocks and derivatives, lower portfolio concentration, higher gross and nest returns, and less risk taking, (3) relying on technical analysis as an investing strategy is associated with a higher turnover of stocks and derivatives, higher portfolio concentration, lower gross and net returns, and more risk-taking , and (4) relying on one’s own intuition as an investing strategy is associated with turnover of stock and derivatives, portfolio concentration, gross and net returns, and risk taking.

It is important to understand investment objectives and strategies shifted over time that effect on investor behavior and performance. In addition, the pension system used affect online investors making decision a lot, but in authors’ survey it seems to have much less appeal to the investors. The explanation on these phenomena will be demonstrate on this literature review.

Shefrin and Hoffmann match survey data to Dutch online discount brokerage clients for the period 2000-2006 and compare their findings to those obtained by Lease, Lewellen, and Schlarbaum for their 1964-1970 dataset of U.S. full-fee commission brokerage clients (Hoffman and Shefrin, 2011). Based on online investors’ survey records, the following paper is tended to offer a detailed literature review of online investors’ investment objective, investing strategies and investor performance. By knowing these relationships may help investors and financial advisers to have a better investment portfolio.

Online investors’ objective

For online individual investors, entertainment and gambling is a driving force of investing in the stock market. In the behavioral portfolio theory, the investors’ portfolios are organized as layered pyramids, well- diversified, secure, but low-potential investments in the bottom layer, and highly concentrated, lottery-like, but high- potential investment in the top layer. So, the different layers in the pyramid are associated with particular goals and attitude towards risk (Shefrin and Statman, 2000). In this respect, the investment attitude or objective is quite different from the investors who is saving retirement money and who mainly invest as a hobby or to speculate. When the objective is to save for retirement life, the investors don’t want to take excusive risk and their portfolio is not trade very actively but with well diversify, even though their diversification strategies likely are naïve (Benartzi and Thaler, 2007).

As result, the online investors’ primary objective is to speculate have a higher turnover of stocks and derivatives and achieve risker returns. In contracts, individual investors who indicate to save for their retirement have a lower turnover of stocks and hold less concentrated portfolio.

Online investors’ strategies analysis

Based on past stock-market data, the individual investors who use technical analysis as an investing strategy display overconfidence about their ability to extract profitable trading patterns (Stantman, 1999). Authors expect these investors to suffer from illusions of knowledge and control which are associated with high turnover of stocks and derivatives as well as increased risk-taking (Hoffmann and Shefrin, 2011). The stock market conditions as a signal affect trading activity whether frequent or not and may also change technical trading rules. If market condition is unstable, technical investors may only invest in a limited number of stocks that they are familiar with, which lead to more concentrated portfolios. As result relying on technical analysis as an investing strategy is associated with a higher turnover of stock and derivatives, , hold more concentrated portfolios, achieve lower gross and net returns, and incur higher level of risk-taking.

Investors may buy stocks of companies that the company names they are able to recognize and have strong positive association with their mind. Intuition corresponds most closely to psychological concepts such as representativeness and affect heuristic. Representativeness refers to overreliance on stereotypes. For instance, the investors judge that good companies are safe companies and good stocks to be the stocks of financially sound companies. Therefore, the investors who use their intuition as an investing strategy display a higher turnover of stocks.

The article asserts that investors with more online trading experience has higher risk appetite, higher aspiration level, more concentrated portfolios, and higher turnover of stocks or derivatives take more risk as indicated by the standard deviation of gross and net returns, while investors with larger portfolios take less risk. Investors with more experience, who consider themselves to be very advance, who hold more concentrated portfolios, or who have a higher turnover of stocks or derivatives takes more idiosyncratic risk, while investors with large portfolios take less idiosyncratic risk.

A Tale of Two Investors: Estimating Optimism and Overconfidence

The article talks about investor confidence based on an exploration of the implication of the person’s perception of the outcome of the judgment. Barone-Adesi, Mancini and Shefrin approach the tasks using the phrase overconfidence and optimism to describe the types of investors. The scholars categorize the individuals as either optimistic or overconfident then allude that the investor’s exploration of the role of sentiment that relies on the psychological anchoring of the beliefs on pricing kernel. The article considers the options and stocks as the foundation in the formulation of a financial model on the optimism. The empirical study indicates that findings of sentiments must align with frameworks such as the Baker–Wurgler index measures, the Duke/CFO survey responses and the Yale/Shiller crash confidence index. The discussion estimate investor confidence using the options and the quoted prices in judging market outcomes. The information affirms that examining the beliefs of the investors is critical in the identification of the motive for the exploitation of a specific strategy in judging investor as either optimistic or overconfident. The writers proceed to describe the concept as reliant on neoclassical pricing kernel and then equate the strategy to the Keynesian economics of estimating risks.

Reading the text gives the idea that the examination of the psychological concepts is fundamental in the identification of the gaps in human reasoning. According to the presentation that infers to the ideas of previous economists, the process of inquiry in the estimation of the volatility of price quotation is becoming the norm in the contemporary times. The scholars identify the distinction between behavioral finance and neoclassical finance in proving their point. The reference to the works of Barberis and Thaler (2003) identifies limits of arbitrage. The identification of the issues related to overconfidence helps in assessing the risk exposure and liquidity that are integral in the determination of the limits of arbitrage. According to the text, lack of the uniformity of the sentiment in the text used as a reference source for evaluating the limits of arbitrate is a critical concern that scholars ought to analyze with caution. The section highlights the significance of the definition of the concepts using proxies of premiums on dividends and fund discounts among others.

The compelling information in the article is that the research identifies the strategies for estimating theoretical sentiment related to overconfidence. The narration indicates that the identification of market returns and prices are the primary determination for the functionality of Baker–Wurgler index. The writer alludes that the link between the realistic estimations and the imaginative assumptions depends on the ability to characterize the analysis. The quotation of two financial investors is necessary for the determination of the sentiment. According to the index, it helps judge excessive optimism that differs from overconfidence. The process commences with the identification of the price set by one investor then comparing with the values suggested. The variation in the values judges the objectivity in the quotation suggested by the rational investor. The rational investor quotation also helps the return on profitability. The utilization of the empirical methods formulated by Barone-Adesi, Engle, and Mancini in their study of markets determine the approach. The restrictions or the estimation of the measures rely on the portion of on the S&P 500. The tool serves as the standards for the utilization in the United States.

The section on methods of estimating empirical pricing kernel indicates that reliance on sentiment measure poses a risk because it highlights the combination of factors that determine the optimism in the estimation of values. Therefore, the scholars imply that varying the measurements is necessary for the identification of the specifics. A person reading the information gets the idea that overconfidence propels price kernel. Hence, the knowledge of sentiments is critical in the measurement of financial issue that conveys the reality about the performance of a commercial venture. The projectors tend to shed light on the progress of a business rather that conveying information about the challenges affecting a commercial venture. The challenge that affects business ventures is the objectivity in the identification of risk that can contribute to overestimation or overconfidence. Baker–Wurgler uses regression concepts in the calculation of the values that depict reality and the imagination in the quantification of the level of confidence. The index suggests that the overconfidence and over-optimism contribute to negative risk gains.

According to Barone-Adesi, Mancini, Shefrin, the modality of assessments suggested by Baker can convey the accurate index measure but failing to point out the exact sentiments and such is a shortcoming in the presentation of contents that dictates the justification for entrepreneurship. The subsequent compelling information in the articles is the urge to identify the connection amid Baker–Wurgler index and the risk-return relationship. The presentation suggests that the calculations are fundamental in guiding the process of justifying the levels of confidence that can encourage investment into a business. The identification of the Tail Event is also helpful in the determination of the levels of investors’ confidence. The process takes the forms of an examination that commences with the identification of tail element then proceeding to identify the appendix components. The examples include right tail, skewness, and kurtosis. The left bias focuses on the risk implication and components overlooked in the quantification of parameters that might affect the confidentiality of an investor. The reading of Gilchrist and Zakrajˇsek that sought to study the correlation between the defaults risks and the measurements used in testing sentiments is helpful in the comprehension of risks that businesses confront.

The process of the measurements of the sentiment has to conclude with the approval of the balance between the estimation and the actual data about the correlation in the rations. The researcher should exploit empirical strategies in defining the robustness of the business beyond the visualized robustness. As a result, the investor will develop the tool for understanding the implication of overconfidence on the financial status of a commercial enterprise. The studies of the economic factors that determine the sentiments suggest that sentiment indicator is not attributable to one factor but a combination of elements. The historical returns guides in the assessments of the empirical measures to prevent inflation and unnecessary adjustments that interfere with the market activities. The presentation of the graphs facilitates the process in the last section. The tentative data representation relies on the mathematical techniques. The time series regression estimates the variation in the values quoted and the estimation generated by the investor. The objective return and the risk ration calculations using intercept and scope indicates the projection in the performance over a given period.

The presentation segmented into sections identified the role of intuition in the judgment of the level of confidence that influences the decision of entrepreneurs. The subsequent part explores the use of empirical pricing kernel in the measurements. The fourth section explores the theoretical framework that guides the quantification of the investor’s sentiment. The display of the estimation follows before the conveyance of the external measurement factors. The section on pricing kernel highlights the idea of the sentiments and the components that scholars rely on the estimation. The cited elements according to the article are option prices, market returns, and risk-free rates. They aid in the valuation of the position of a business in the market. As noted, the psychological process aids in the determination of the correlation between the measures of the objective components and subjective items. The belief of the investor plays a critical role in the determination of the prices, and the competence of a person in judgment is critical in the presentation of information that corroborates psychological measures with factual data.

CONCLUTION

Shefrin, H., & Statman, M. (2000). Behavioral Portfolio Theory. The Journal of Financial and Quantitative Analysis, 35(2), 127. doi:10.2307/2676187

Shefrin, H. M. (2002). Do Investors Expect Higher Returns from Safer Stocks than from Riskier Stocks? SSRN Electronic Journal. doi:10.2139/ssrn.296157