Behavioral Portfolio 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-diversifiedportfolio. 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 ...

1. Behavioral Portfolio 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

2. 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-diversifiedportfolio. 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 fearis 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. Hopehas 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

3. 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

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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,

10. 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

11. 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

12. 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

13. 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.

14. 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

15. 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

16. 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