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Znevnzonol07

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The thesis must be 40-45 pages. Deadline:. The Theme is "Fama and French 3 and 5 on German Equities". Attached you can find the 1) Thesis Proposal that I sent to my supervisor and he accepted it. It says what I will do in my thesis..Just to say that it requires Econometrics and programming skills (python, Stata etc..). I will also need progress updates every 5 days - very important

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THESIS PROPOSAL Research Question How suitable is the Fama, French model on one EU market (Dutch, Greek, English etc..) and how well will it capture the cross-sectional differences in stock returns for the pre-crisis and crisis period of 20002020. Furthermore, I will also add the Carhart’s momentum factor to witness firsthand the difference in the alpha. There has been some research on EU equities, but I haven’t found one that covers the above period. Relevance of the subject Proving if a significant alpha still exists after controlling for the Size and Value factors is a big point of interest, and if there is, then also add the momentum factor to see the difference. The underlying theory for answering the problem Use of research papers that have been taught in class. The Size and Value factors will capture some cross-sectional differences and if there is still a significant alpha then with the addition of momentum, I would expect it to become insignificant, but this is something that needs to be proved. Research methodology and Data I will make use of all the stocks enlisted in the chosen market and then I will create a custom market portfolio to play the role of the proxy. I guess that would be a better choice than to use for example the AEX or the CAC40. As for the SMB and HML, I will follow the procedures listed on the Fama & French papers, though I think I will have to use different sorting methods because I guess I will have fewer stocks. At the end, I will perform a GRS test as developed by Gibbons, Ross & Shanken (1989). Planning I will be done by the end of March. I know how to execute all the above. I think I will use the Dutch or the French market or the one that I find best data for.
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Fama- French Three and Five Factor Model 1

Fama and French 3 and 5 on German Equities

Student's Name
Institution
Instructor's Name
Course
Date of Submission

Fama- French Three and Five Factor Model 2
Table of Contents
CHAPTER 1: INTRODUCTION ................................................................................................ 4
(rm – rf) = market risk premium ............................................................................................ 9
SMB (Small minus big)........................................................................................................... 10
HML (High minus Low) ......................................................................................................... 10
CHAPTER 2: LITERATURE REVIEW ................................................................................. 13
Factors predicting stock returns............................................................................................ 17
Fama & French factors .......................................................................................................... 18
Macroeconomic factors .......................................................................................................... 20
Evaluation of the five-factor model ....................................................................................... 20
CHAPTER 3: METHODOLOGY ............................................................................................ 21
Portfolio formation ................................................................................................................. 21
Issues surrounding selection of an appropriate sample size ............................................... 23
Any sample selection bias ....................................................................................................... 24
Market proxy ............................................................................................................................. 24
Preparing CRSP Data in R .................................................................................................... 27
Preparing CRSP/Compustat Merged Data in R .................................................................. 27
Constructing Stock Sample in R............................................................................................ 27
Size Sorting .............................................................................................................................. 28
Value Sorting ........................................................................................................................... 28

Fama- French Three and Five Factor Model 3
Constructing Factor Portfolios .............................................................................................. 28
Result replication. ................................................................................................................... 28
Correlation............................................................................................................................... 29
GRS Test .................................................................................................................................. 29
REFERENCES............................................................................................................................ 30

Fama- French Three and Five Factor Model 4
CHAPTER 1: INTRODUCTION
Fama-French is an asset pricing model that expands the capital asset pricing model
(CAPM) by integrating the market risk element. Unlike the CAMP, which only considers
investment risk and measures market risk, the Fama-French considers additional factors that may
impact the yield on stock portfolios. Many practitioners now embrace the Three Factor Model
that Fama and French introduced in 1996 and the consequences that flow from it. Fama and
French (1992, 1996) developed the Three Factor Model using US data, and most other published
research also pertains to US portfolios. Therefore, it is essential to keep this in mind. Outside of
the US market, little information is provided on the Three Factor Model's reliability. The FamaFrench 3-factor model makes an effort to describe why diversified government bond stock
returns differ from market returns.
Eugene Fama and Kenneth French proposed it in 1992 as a development of the
conventional Capital Asset Pricing Model (CAPM), which only considers one market exposure
element. This paper aims to demonstrate whether a powerful alpha can be found after accounting
for the Size and Value variables, which is a significant point of interest; if it can be found, then
the momentum element will be added to determine how much of a difference it makes. The Size
and Value factors will capture some cross-sectional differences. If there is still a significant
alpha, then adding momentum would render it insignificant; however, this is something that
needs to be proven first. The Size and Value factors will obtain some of the cross-sectional
differences.
The model takes into account the fact that small-cap companies and value routinely
outperform the market. Integrating these elements into the model used to price capital assets
helps the manager make better portfolio decisions, which ultimately results in improved

Fama- French Three and Five Factor Model 5
performance. The Fama-French model employs three criteria to characterize proceeds: the
outperformance of firms with low book-to-market value compared to companies with high bookto-value; large companies compared to small-cap companies; and market volatility (Womack et
al., 2003).
Eugene Fama, winner of the Nobel Prize in Economic Sciences, and Kenneth French, a
researcher and a former professor at the University of Chicago Booth School of Business,
collaborated on an effort to improve the accuracy of measuring market returns and discovered,
through their research, that value stocks surpass investment strategy. Similarly, the performance
of small-cap stocks is often superior to that of large-cap equities. As an assessment tool, the
success of portfolios that include a significant number of small-cap or value companies would be
smaller than the CAPM result. This is because the Three-Factor Model adjusts accordingly for
the actual outperformance of small-cap and portfolio allocation. However, the research question
for this paper is;
How suitable is the Fama, French model on one EU market (Dutch, Greek, English, etc..), and
how well will it capture the cross-sectional differences in stock returns for the pre-crisis and
crisis period of 2000- 2020.
The Fama and French model considers three variables: the ratio of a company's book
value to its market value, the model's capital appreciation on the market, and the company's size.
To put it another way, the three elements that are taken into consideration are "small minus
large," "high minus low," and "the return on the portfolio less the risk-free rate of return." The
term "SMB" refers to significant corporations with small market caps that generate higher
returns. In contrast, the term "HML" refers to value stocks with high book-to-market ratios that
produce positive outcomes compared to the market as a whole (Blanco, 2012).

Fama- French Three and Five Factor Model 6
There is a great deal of discussion on whether or not the trend toward outperformance can
be attributed to efficient market operation. The additional risk often justifies the outperformance
that value and small-cap companies experience due to their higher cost of capital and more
business risk. This is done to promote the notion that the market is operating efficiently. The
outperformance is justified by market members erroneously pricing the worth of these
enterprises, which gives the extra return in the long term when the value resets, lending credence
to the hypothesis that the market is inefficient. The Efficient Markets Hypothesis (EMH)
provides evidence, and investors who adhere to this substantiation are more inclined to agree
with the economic side of the argument (Blanco, 2012).
Both the three-factor and the five-factor asset pricing models underlined the importance
of value and velocity as risk variables that shape the cross-section of asset returns. The factor
models assign portfolio returns to risk drivers, which reduces the return attributed to alpha and,
accordingly, management competence. The "logical extension of portfolio attribution analysis,"
that is, "factor-based asset allocation," which became popular during the financial crisis that
lasted from 2007 to 2009, places an emphasis not on asset class segregation but instead on
portfolio selection along health conditions. Sharpe is credited for popularizing the concept of
portfolio correlation analysis, which aims to ascertain an investor's proper asset mix by
"measuring exposures to fluctuations in returns of key asset classes" and assessing the manager's
capability (Blitz, 2014).
The capital asset pricing model (CAPM) can explain the cross-section of stock returns by
analyzing the assets' relationships to the market portfolio. Returns are broken down into an active
component known as alpha and a passive factor known as beta. Fama and French have shown

Fama- French Three and Five Factor Model 7
that the CAPM fails to account for a significant portion of the excess return share for US equities
between 1941 and 1990, which results in high alpha values (Blitz, 2014).
Fama and French emphasized the importance of an investor's capacity to withstand the
additional instability and occasional underperformance that can take place over a short period.
Investors with a time horizon of 15 years or more will be compensated for losses incurred in the
near term, even if they will still experience losses in the long run. Fama and French tested their
model using thousands of random stock portfolios. They discovered that when the size, value,
and beta factors were integrated, the three elements could clarify as much as 95% of the return
on a differentiated stock portfolio (Lawrence, 2007). This was discovered through studies by
Fama and French using thousands of spontaneous stock investments. Suppose investors are given
the capacity to understand 95% of a portfolio's return in comparison to the performance of the
market as a whole. In that case, they are able to create a portfolio in which they earn an
anticipated average return that is proportional to the relative risks that they incur in their
portfolios. The primary elements that drive predicted returns are responsiveness to the market,
sensitivity to size, and sensitivity to value stocks, as evaluated by the book-to-market ratio. Any
higher average projected return may be ascribed to risk that is not currently priced, or that is not
accounted for by the system (Lawrence, 2007).
Lam (2005) uses two different data sets to evaluate the effectiveness of two financial
models: the Fama-French three-factor model and the Capital Asset Pricing Model (CAPM). A set
of portfolios is created based on industry, while another pair of portfolios are made based on size
and the book-to-market profitability ratios. The time series and cross-sectional tests are carried
out across two distinct periods using these two sets of portfolios as the data sources. The results
of the tests do not allow for a conclusion that is free from all doubt that the three-factor model is

Fama- French Three and Five Factor Model 8
superior to the CAPM. In addition, the outcomes of the tests vary depending on the data sets and
periods used (Lam, 2005).
Mark Carhart gave a presentation in 1997 that was devoted to analyzing mutual funds.
The empirical results of the research were based on a model consisting of three factors. Carhart
began with the traditional three-element model and then added a fourth component, which he
referred to as the impetus element. According to his research findings, adding a fourth element
improved the accuracy of calculating portfolio returns compared to the model that only included
three factors (Bello, 2008). The idea of momentum is fascinating in economics, and it may help
provide insights into the potential future returns of an asset. To mathematically describe
momentum, let us suppose that an asset's recovery depends on a term of random error and a
significant covariance with its prior return. This will allow us to model momentum. In other
words, the return on the asset in the next year will be determined by the error term, and it will be
related to the dependent variable across the asset's standard deviation, in addition to having some
kind of autocorrelation that is tied to the return from the year before. Even when autocorrelation
is relatively low, there is still the possibility of a significant influence on the price of the asset:

The following connection is discovered when applying this model to the returns on assets:

If

, the coefficient and

will increase linearly as time passes. In other words, even if the

pattern may seem minor in the near term (

and

), they expand and become

Fama- French Three and Five Factor Model 9
increasingly significant after 48 months (

and

). Investors can then use this

momentum concept to build portfolios and capture returns. Investors may then use the idea of
momentum to construct portfolios and generate rewards (Bello, 2008).
The following is the formula for the Fama-French three-factor model:
Expected rate of return = risk-free rate of return + market risk premium + SMB + HML
The formula may be expressed using the following mathematical notation:
r = rf + β1 (rm – rf) + β2 (SMB) + β3 (HML) + ε
Where; r = estimated rate of return
rf = risk free-rate
β = coefficient for the factors
(rm – rf) = market risk premium
SMB = small-cap company’s return minus large-cap company’s return
HML = high book-to-price returns minus low-book-to-price returns
(rm – rf) = market risk premium
The difference between the risk-free rate and the projected return on the market is what is
meant to be referred to as the market risk premium. It is a figure that indicates the profit an
investor expects to get as compensation for the unpredictability gained above and above the riskfree rate. According to the graphical depiction of the capital asset pricing model, the market risk
premium is comparable to the slope of the security market line (SML). Because the actual trends
in the marketplace determine the value, the one-time price premium is standardly established to
be the same for all investors.

Fama- French Three and Five Factor Model 10
SMB (Small minus big)
Small minus Big, also known as the "small firm effect," is a factor that determines the
size of a company based on the market capitalization of that company. This number specifies the
historical advantage that smaller enterprises have over their bigger counterparts. The beta
coefficient, β1, is the result of linear regression and may have either a positive or a negative
value depending on the circumstances. To put it another way, over time, small-cap firms often
generate more significant returns than big businesses.
HML (High minus Low)
HML is the term used to describe the difference in return between companies with low
and high book-to-market value ratios. Linear regression, which may have positive or negative
values, can be used to get the model's beta coefficient or β2; the primary justification for this is
that high book-to-market ratio stocks generate more returns than low book-to-market ratio
stocks.
A lower sample size results in a fewer number of stocks being represented in each
portfolio, which is a negative. The use of large sample size may be credited for the improved
stock performance of the portfolio. It is essential to remember that small companies tend to react
differently to the circumstances of the market relative to extensive stocks. During the selection
process, information on the book value, market value, monthly pricing data, and other essential
details should be easily accessible (Chung et al., 2006). The stock chosen based on the Fama–
French three-factor model should be able to make it through the rest of the year. During the year,
the returns on the stocks should be greater than zero for at least 85 percent of the trading days. In
addition to stock value, stock price, and momentum, several other aspects influence the
forecasting of stock prices.

Fama- French Three and Five Factor Model 11
The outperformance of companies with a low book-to-market value relative to those
with a high book-to-value, the outperformance of giant corporations comparable to those with a
small market capitalization, and the danger of the market are the three factors that the FamaFrench model chose to explain proceeds. The difference between the risk-free rate and the
projected return on the market is what's meant to be referred to as the market risk premium. The
term "Small minus Big" (SMB) refers to a measurement comparing smaller businesses' success
against that of more significant firms. The term "High minus Low" (HML) describes the
difference in returns generated by companies with a high book-to-market value ratio and those
with a low book-to-market value ratio. When opposed to huge companies, small stocks tend to
react differently to the circumstances of the market. There is a danger of measurement errors, a
strong predisposition for managers to always choose trading systems with an excellent track
record, and there is the choice of the trading system. These all contribute to sample bias. The
graphical and numerical correlation representations are impacted when outliers are present.
The application of the model to the Dutch market provides benefits not just to the
academic community but also to practitioners working in the area of finance. If systematic risk,
company size, and the book-to-market ratio are valued in the Dutch market, it will offer insight
into what those factors are worth. This has repercussions for Dutch companies in terms of
choices about their capital budgets and discount rates. People who intend to invest in Dutch
equities may consider these findings before making any investing choices.
The Fama and Macbeth approach is used to analyze the results of the Three Factor Model
(1973). According to the findings of the time-series regression, often known as the "first-pass
regression," company size and the ratio of book-to-market equity seem to affect returns.
However, the systematic risk does not appear to impact returns. If this is the case, the cross-

Fama- French Three and Five Factor Model 12
sectional regression, also known as the second-pass regression, will demonstrate this. The crosssectional regression results reveal that the market does not price risk premiums, but they also
show that company size is not priced. The proportion of book capital to market equity seems to
be the sole element that makes a difference. Therefore, the CAPM is not enough to describe the
returns of the Dutch market. There is a quality discount and a size impact, although the size
effect is negligible and very modest. Therefore, shares of stocks with a high book-to-market ratio
perform better than those of companies with a low book-to-market ratio. In addition, the model's
alpha is positive and statistically significant, which means that a portion of the returns cannot be
explained.
Researchers have recently modified the Three-Factor model to incorporate extra
components in addition to the original three. A few examples of this include the terms
"momentum" and "quality," as well as "low volatility." In 2014, Fama and French modified their
model so that it would take into account five different criteria. The new model incorporates not
just the three components included in the model's predecessor but also the idea that firms that
forecast greater future profits may expect better returns on the stock market. This idea is alluded
to as the profitability factor. The fifth component, referred to as "investment," is related to the
notion of internal investment and returns. This factor suggests that businesses that funnel their
profits into significant expansion initiatives are more likely to suffer financial losses on the stock
market.
The new Fama–French five-factor model will probably become the new standard for
research on asset pricing. Even though the theoretical underpinnings of the five-factor model are
noticeably higher than that of its predecessor, the traditional three-factor model, the authors
highlight five issues with the new model. First, it maintains the association between market beta.

Fama- French Three and Five Factor Model 13
It returns what the capital asset pricing model predicts, despite the growing body of data
indicating that the true relation is either nonexistent or negative. Second, it remains to disregard
the momentum influence, which is now well-acknowledged across the scientific community.
Third, there are a variety of worries about the strength of the two new elements, investment and
profitability. Fourth, whereas risk-based explanations were essential to support the components
in the three-factor model, the economic basis for the two additional factors is much less
noticeable. This is in contrast to the risk-based arguments, which were essential. Fifth, and to
conclude, it does not seem plausible that the five-factor model will resolve the critical asset
pricing arguments or lead to consensus. Instead, these debates seem more likely to continue
(Blitz et al., 2018).
CHAPTER 2: LITERATURE REVIEW
The asset valuation method that was developed by Sharpe (1964), Lintner (1965), and
Black (1972) was used for a considerable amount of time to describe the disparities that may
occur between returns and risk. According to the SLB model, the anticipated returns on equities
are a linear function of the stocks' susceptibility to market risk (also known as β). This risk may
also be referred to as systematic risk. Because non-systematic risk may be mitigated by
diversification, only this particular risk should be reflected in the price of the asset on the market.
According to this model, market risk is the only variable that can explain the cross-section of
predicted values.
On the other hand, this model cannot explain the so-called "anomalies" of stock returns.
The SLB model has been shown to contain inconsistencies by several distinguished scholars.
Banz (1981) discovered that there was a side effect. The cross-section of predicted returns may
be better understood with more information about the firm's size. Using a company's market

Fama- French Three and Five Factor Model 14
equity as a yardstick, he discovers that tiny businesses have an anticipated return that is
disproportionately high given their size.
In contrast, big businesses have a disproportionately low expected return, given their size.
Another inconsistency was discovered by Stattman (1980) and Rosenberg, Reid, and Lanstein
(1985). According to what they say, the ratio of book equity to market equity positively
correlates with average returns.
According to Chan, Hamao, and Lakonishok's research, similar evidence may be found in
the Japanese market (1991). In addition, Bhandari (1988) discovered that the amount of leverage
a company uses is connected to the risk it takes and the projected return it receives. In
conclusion, Basu (1983) demonstrates that the earnings-price ratio is another factor that might
contribute to an explanation of variances in the cross-section of stock returns. The SLB model
suggests that market risk should be the sole factor that accounts for the cross-section of predicted
stock returns; however, it is abundantly evident that this is not the case in practice.
The field of finance theory has resulted in the production of several models that provide
readers with some insight into the context of the circumstances in which financial choices are
made. Typically, an empirical approach to finance will begin with a theoretical model by
determining whether or not its implications are validated by the facts (Pastor, 2000). The model
is either found to be acceptable or found to be unacceptable based on the results of a test of the
hypothesis. On the other hand, it is not entirely apparent what the implications of the findings are
in terms of how effective the model is for decision-making. Is the model automatically accepted
as correct if it is not challenged in any way? Should it be considered useless and thrown away if
it is turned down? A strategy as rudimentary as this one, based entirely on the outcome of a

Fama- French Three and Five Factor Model 15
hypothesis test, does not take into account many features of the model or the data that may be
helpful to a person in charge of making a decision.
On the other hand, it is possible that it is realistic to presume that financial models are
neither flawless nor completely worthless. In any event, a model is only a simplified
representation of the actual world. Therefore, even if the facts do not provide sufficient evidence
to refute the model, the person responsible for making a choice may not necessarily choose to
accept the model as a dogma. At the same time, the idea that the models suggested by financial
theory may be completely devoid of value seems somewhat excessive. Therefore, even if the
facts do not support the model, the person in charge of making a choice could still wish to utilize
it, at least to some extent (Pastor, 2000).
According to Fama and French (1993), small-cap equities and value stocks have a higher
risk level than big, well-established companies with promising development potential. In light of
this reasoning, Fama and French (1993) include the small company risk premium and the value
risk premium in contrast to the market risk premium in their attempt to explain returns on
portfolios created based on various empirical anomalies. It has been discovered that the Three
Factor Model can appropriately explain most abnormalities.
The validity of the Fama–French Three Factor Model in describing portfolio returns is
well recorded by research evidence; however, tests of the Fama–French Three Factor Model
have not yet been conducted on sector-based portfolios. The market risk premium, the small
company premium, and the value risk premium have varying impacts on the returns received
from various sectors. The coefficients generated from the 3-factor model give helpful
information on these influences. It is thus possible to determine the combined impacts of market

Fama- French Three and Five Factor Model 16
risk, company size, and value effect, which can then be compared to the univariate findings that
Hsieh and Hodnett (2012) found on category portfolios of global stocks.
Roll and Ross (1980), authors of seminal empirical research, state: "We assume that in
many discussions of the CAPM, experts were thinking about the APT and of the process with
only a single element." Xue (2003) contended that in recent times in the asset pricing literature, it
could be substantively recommended that academics may have genuinely considered a multi-beta
analysis of the CAPM in many APT discussions. This is because there have been recent
developments in the asset pricing literature. A great deal can be stated in favor of both of these
viewpoints since a single paradigm is developing that includes essential characteristics of both
the CAPM and the APT.
These findings were used by Fama and French (1996) in a subsequent study, which
resulted in the creation of the Three Factor Model. They developed a model capable of
accurately describing the cross-section of projected returns. Three distinct factors are relevant to
the returns. The additional return generated by a market portfolio (Rm-Rf), The difference in
recovery between a portfolio of small stocks and a portfolio of large stocks; the difference in
return between a portfolio of stocks with a high book-to-market value and a portfolio of stocks
with a low profitability and liquidity value; and the difference in return between a portfolio of
stocks with a high book to market value and a portfolio of stocks with a low book to market
value.
The value premium may be calculated using the high-minus-low factor. If it is positive,
this shows that value companies (those with a high book-to-market ratio) have beaten growth
stocks during the last year (low book-to-market ratio). To become publicly traded, businesses
must first attain a specific minimum size. If they subsequently have a high book-to-market

Fama- French Three and Five Factor Model 17
percentage, their market value has decreased. It is conceivable for this to occur due to adver...


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