2. SUBMITTED BY
SANA TAUS & THE GROUP
GROUP VII
GROUPS MEMBERS
SANA TAUS
ANIQA MUSHTAQ
AREEBA MUNIR
FATIMA NOOR
3. MARKET ANOMALIES
Market anomalies refer to persistent patterns or phenomena in financial markets that contradict the
efficient market hypothesis (EMH).
The EMH suggests that
financial markets are efficient, meaning that prices fully reflect all available information, making
it impossible to consistently earn abnormal returns or identify mispriced assets.
However, market anomalies indicate situations where certain investment strategies or patterns have
consistently outperformed the market or have shown consistent deviations from what would be
expected in an efficient market.
4. VARIOUS TYPES OF MARKET ANOMALIES
1. Size Effect:
The size effect anomaly suggests that smaller companies tend to outperform larger companies over the
long term. This contradicts the notion that all companies are equally
efficient and that investors should be compensated solely based on their level of risk.
2. Value Effect:
The value effect anomaly suggests that stocks with low price-to-earnings (P/E)
ratios or other value-based metrics tend to outperform stocks with high P/E ratios or growth
stocks. This contradicts the idea that the market accurately prices securities based on their fundamental
value.
5. TYPES OF ANOMALIES
3. Momentum Effect:
The momentum effect anomaly suggests that stocks that have performed
well in the recent past tend to continue outperforming, while stocks that have performed poorly
continue to underperform. This contradicts the efficient market hypothesis, as it implies that
past price trends provide predictive information about future returns.
4. Post-Earnings Announcement Drift:
This anomaly refers to the tendency for a stock's price
to continue to drift in the same direction as the earnings surprise for a period of time after the
announcement. Positive earnings surprises are associated with positive drift, while negative
surprises are associated with negative drift.
5. January Effect:
The January effect anomaly suggests that stocks tend to outperform in
January compared to other months. This anomaly is often attributed to year-end tax-related
activities, investor psychology, and portfolio rebalancing.
6. TYPES OF ANOMALIES
6. Low-Volatility Effect:
The low-volatility effect anomaly suggests that stocks with lower levels of volatility tend to provide higher
risk-adjusted returns compared to stocks with higher volatility.
This contradicts the efficient market hypothesis, as it implies that lower-risk stocks offer superior risk-
adjusted returns.
7.Dividend Yield Effect:
The dividend yield effect anomaly suggests that stocks with higher dividend yields tend to outperform
stocks with lower dividend yields.
This contradicts the notion that investors are compensated for risk alone, rather than the dividend pay
outs.
8. Weekend Effect:
The weekend effect anomaly refers to the tendency for stock returns to be lower on Mondays compared
to other days of the week.
This anomaly is often attributed to investor sentiment and the accumulation of negative news over the
weekend.
7. TYPES OF ANOMALIES
9. Piotroski F-Score Anomaly:
The Piotroski F-Score is a financial scoring system used to
identify fundamentally strong companies. The anomaly suggests that stocks with high F-Scores
tend to outperform stocks with low F-Scores.
10. Liquidity Anomaly:
The liquidity anomaly refers to the tendency for stocks with lower
liquidity (higher trading costs and lower trading volume) to have higher returns than stocks
with higher liquidity. This contradicts the notion that higher liquidity should lead to more
efficient pricing.
Certainly! Here are a few more market anomalies that have been identified:
11. Earnings Announcement Anomaly:
This anomaly refers to abnormal stock returns that
occur around the time of quarterly earnings announcements. Stocks may experience significant
price movements, both positive and negative, in response to earnings surprises.
8. TYPES OF ANOMALIES
12. IPO Underpricing:
IPO underpricing is an anomaly where initial public offerings (IPOs)
tend to be priced below their intrinsic value, causing them to experience significant price
increases on their first day of trading. This can result in substantial short-term profits for IPO
investors.
13. Seasonality Anomalies:
Seasonality anomalies refer to recurring patterns in stock returns
that are related to specific calendar periods. Examples include the January effect, where stock
prices tend to rise in January, and the "Sell in May and Go Away" effect, which suggests that
stock returns tend to be lower during the summer months.
14. Reversal Effect:
The reversal effect, also known as the "Losers become Winners" anomaly,
suggests that stocks that have performed poorly in the past tend to have higher returns in the
future, while stocks that have performed well in the past tend to have lower returns.
9. TYPES OF ANOMALIES
15. Volatility Skew Anomaly:
The volatility skew anomaly refers to the observation that
implied volatility tends to be higher for out-of-the-money options compared to at-the-money or in-the-
money options.
This violates the assumption of constant volatility in traditional option pricing models.
16. Earnings Quality Anomaly:
This anomaly suggests that companies with higher earnings
quality, such as those with less aggressive accounting practices and more transparent financial reporting,
tend to outperform companies with lower earnings quality.
17. Closed-End Fund Discount/Premium Anomaly:
Closed-end funds are investment vehicles that trade on exchanges like stocks. Occasionally, these funds
trade at a discount (trading below their net asset value) or at a premium (trading above their net asset
value).
The persistence of these discounts or premiums is considered an anomaly.
10. TYPES OF ANOMALIES
18. Long-term Reversals:
Long-term reversals refer to the observation that stocks that have experienced long-term underperformance tend to
subsequently outperform, while stocks that have enjoyed long-term outperformance tend to subsequently
underperform.
19. Sentiment-based Anomalies:
Sentiment-based anomalies suggest that investor sentiment and market psychology can impact stock prices, resulting
in deviations from fundamental values.
Examples include the overreaction effect, where stocks that experience extreme price movements tend to experience
subsequent price corrections, and the disposition effect, where investors tend to hold on to losing stocks for too long
and sell winning stocks too quickly.
20. Earnings Management Anomaly:
This anomaly relates to the manipulation of reported earnings by companies to meet or beat earnings expectations. It
suggests that companies engaging in earnings management may experience abnormal stock returns as the market
reacts to the reported earnings.
These are just a few additional examples of market anomalies.
It's important to note that the existence and persistence of these anomalies can vary over time, and some anomalies
may be subject to changing market conditions and investor behavior.
11. Q2 WHAT IS MEANT BY EFFICIENT MARKETS? DESCRIBE THREE FORMS OF
MARKET EFFICIENCY?
Efficient markets refer to financial markets
where prices of assets fully and quickly
reflect all available information.
In an efficient market, investors cannot
consistently achieve above-average returns by
exploiting mispriced securities because any new
information is quickly incorporated into the asset
prices, leaving little room for arbitrage
opportunities.
Efficient markets are based on the concept of the
efficient market hypothesis (EMH), which
suggests that it is difficult to consistently
outperform the market based on publicly
available information.
12. THREE FORMS OF MARKET EFFICIENCY
1.Weak Form Efficiency:
In weak form efficiency, asset prices fully reflect all historical market data and price movements. This
means that past prices, trading volume, and other technical analysis indicators cannot be used to
predict future price movements or generate abnormal returns. In other words, the weak form efficiency
assumes that historical price data is already incorporated into current prices, and no trading strategy
based on past prices alone can consistently beat the market.
2. Semi-Strong Form Efficiency:
Semi-strong form efficiency includes all information available in the public domain. In addition to
historical price data, it incorporates all publicly available information such as financial statements, news
releases, economic reports, and analyst recommendations. In a semi-strong efficient market, investors
cannot consistently generate abnormal returns by trading on public information since it is quickly and
accurately reflected in the asset prices.
13. THREE FORMS OF MARKET EFFICIENCY
3. Strong Form Efficiency:
Strong form efficiency is the highest level of market efficiency, incorporating all public and private
information. In a strong form efficient market, asset prices reflect not only publicly available
information but also insider information, private company data, and any other privileged
information. This form of efficiency suggests that even insiders with access to private information
cannot consistently earn abnormal returns because the market fully incorporates all relevant
information.
It's important to note that achieving perfect efficiency in real-world markets is challenging, as there
are limitations, such as information asymmetry, transaction costs, behavioral biases, and market
frictions, that can hinder the complete and immediate reflection of information in asset prices.
However, the concept of market efficiency serves as a theoretical benchmark against which the
performance of investors and investment strategies can be measured.
14. Q3: EXPLAIN THE FACTORS USED IN THE BLACK-SCHOLES OPTION VALUATION MODEL.
WHAT IS THE RELATIONSHIP BETWEEN EACH FACTOR AND THE VALUE OF THE OPTION?
The Black-Scholes option valuation model is a mathematical model used to
estimate the value of European-style options. It was developed by
economists Fischer Black and Myron Scholes in 1973. The model takes into
account several factors that influence the value of an option.
15. FACTORS USED IN THE BLACK-SCHOLES
MODEL
1. Underlying Stock Price (S):
The current market price of the underlying stock is a fundamental factor in determining the value of an
option. As the stock price increases, the value of a call option (which gives the holder the right to buy the
stock) generally increases, while the value of a put option (which gives the holder the right to sell the
stock) generally decreases. The relationship is not linear, but rather follows a convex shape.
2. Strike Price (K):
The strike price is the pre-determined price at which the underlying stock can be bought or sold when
exercising the option. The relationship between the strike price and the option value depends on the type
of option. For call options, a lower strike price generally increases the option value, while for put options,
a higher strike price generally increases the option value.
3. Time to Expiration (T):
The time remaining until the option's expiration is a critical factor. The longer the time to expiration, the
greater the probability that the option will end up in-the-money (profitable). Consequently, options with
more time to expiration generally have higher values compared to options with less time to expiration.
F
16. FACTORS USED IN THE BLACK-SCHOLES MODEL
4. Risk-Free Interest Rate (r):
The risk-free interest rate represents the return an investor can earn with certainty by investing in a risk-free asset,
such as government bonds. As the risk-free interest rate increases, the value of call options generally increases
and the value of put options generally decreases. This relationship is due to the cost of holding the underlying
stock versus risk-free investments.
5. Volatility (σ)
Volatility measures the degree of fluctuation or uncertainty in the price of the underlying stock. Higher
volatility increases the potential for large price movements, which in turn increases the value of options. Both
call and put options benefit from higher volatility, as it enhances the probability of achieving higher profits.
6. Dividends (if applicable):
If the underlying stock pays dividends, they can impact the value of options. Generally, higher dividend payments
reduce the value of call options and increase the value of put options, as they reduce the potential for stock price
appreciation. The Black-Scholes model combines these factors to estimate the theoretical fair value of an option. It
assumes constant volatility, efficient markets, and no transaction costs. However, in practice, deviations from these
assumptions and additional factors may influence option prices. It's important to note that the Black-Scholes model is
specifically designed for European-style options, which can only be exercised at expiration. It may not accurately
value options with complex features or those traded in markets with deviations from the model's assumptions.
F
17. FACTORS USED IN THE BLACK-SCHOLES MODEL
The following formula computes the Price of a Call Option
Here;
18. FACTORS USED IN THE BLACK-SCHOLES MODEL
The following formula computes the price of Put Option P
In this equation, N equals the cumulative distribution function
of the standard normal distribution. It represents a
standard normal distribution with m = 0 and standard
deviation = 1
. T-t refers to the maturity period (in years).
. St is the underlying asset’s spot price.
. K denotes the strike price.
. r represents the risk—free rate.
. O symbolizes the underlying assets' return volatility.
19. Q4 DISCUSS THE FED’S MODEL OF MARKET FORECASTING. WHAT ARE THE LIMITATIONS
OF THIS
MODEL?
The "FED'S Model" of market forecasting, also known as the Fed Model or Equity Risk Premium
Model, is an approach used to assess the attractiveness of stocks relative to bonds by comparing
the earnings yield on stocks to the yield on long-term government bonds. The model is based on
the premise that investors should compare the earnings yield (earnings divided by price) of stocks
to the yield of risk-free bonds to make investment decisions. The basic idea behind the Fed Model
is that when the earnings yield on stocks is higher than the yield on bonds, stocks are considered
relatively more attractive and may provide better returns. Conversely, when the earnings yield is
lower than the bond yield, stocks may be deemed less attractive compared to bonds.
20. LIMITATIONS
1. Narrow Focus:
The Fed Model only compares the earnings yield of stocks to the bond yield and does not take into
account other factors that influence stock prices, such as company- specific fundamentals, industry
dynamics, macroeconomic indicators, or market sentiment. It over simplifies the complex nature of stock
market valuation.
2. Flawed Assumptions:
The model assumes that the earnings yield on stocks should be equal to the bond yield for equilibrium,
neglecting the risk premium associated with stocks. It assumes that stocks and bonds have the same level
of risk, which may not be accurate, as stocks are inherently riskier and have greater volatility compared to
bonds.
3. Time Inconsistency:
The model's results can vary over time, making it challenging to rely on it consistently. Market conditions,
interest rates, and investor sentiment can significantly impact the relationship between stock and bond
yields. This time-varying relationship undermines the model's ability to provide reliable and consistent
predictions.
F
21. LIMITATIONS
4. Lack of Consideration for Dividends:
The Fed Model focuses on earnings yield and bond yield but overlooks the importance of dividends, which are a critical
component of total return for stocks. Ignoring dividends can lead to an incomplete assessment of stock market
attractiveness.
5. Market Inefficiencies:
The model assumes efficient markets, where prices accurately reflect all available information. In reality, markets can be
influenced by behavioral biases, market inefficiencies, and investor sentiment, which may lead to deviations from the
model'spredictions.
6. Limited Applicability:
The Fed Model primarily focuses on the comparison between stocks and government bonds, neglecting other asset classes
and investment options. It may not be suitable for assessing the attractiveness of stocks relative to other types of bonds,
commodities, alternative investments.It is important for investors to be aware of these limitations and not rely solely on the
Fed Model for investment decisions. Market forecasting requires a comprehensive analysis that considers a wide range of
factors and incorporates various valuation models and indicators.
22. Q5: DEFINE DOW THEORY OF TECHNICAL ANALYSIS? EXPLAIN ITS THREE TRENDS? WHICH
ONE IS MOST IMPORTANT? CRITICISM OF DOW THEORY?
The Dow Theory is a foundational principle of technical analysis that was
developed by Charles H. Dow, the founder of Dow Jones & Company, in
the late 19th and early 20th centuries. It provides a framework for
analyzing and interpreting stock market trends and making investment
decisions based on price action.
23. DOW THEORY CONSISTS OF THREE TRENDS:
1. Primary Trend:
The primary trend represents the long-term direction of the
overall market, which can be either bullish (rising) or bearish
(falling). According to the Dow Theory, the primary trend is
the most significant and influential trend. It can last from
several months to several years and sets the overall tone of
the market.
2. Secondary Trend:
The secondary trend is a counter-trend movement that
occurs within the primary trend. It is often referred to as a
corrective or countertrend movement, as it opposes the
primary trend. Secondary trends typically last from a few
weeks to a few months and can be caused by factors such as
market corrections, profit-taking, or short-term investor
sentiment.
3. Minor Trend:
The minor trend is the shortest-term trend and is also known
as the daily or noise in the market. It represents the short-
term price movements within the secondary trend. Minor
trends can be influenced by factors such as news events,
economic data releases, or investor sentiment on a given day
or week.
24. CRITICISM OF THE DOW THEORY INCLUDES THE FOLLOWING POINTS:
1. Subjectivity:
The Dow Theory relies on the interpretation of price patterns and trends, which can be subjective
and open to different interpretations by analysts. This subjectivity can lead to inconsistent
conclusions and potentially erroneous investment decisions.
2. Lack of Specific Entry/Exit Points:
The Dow Theory provides a framework for understanding market trends but does not offer specific
entry or exit points for individual stocks or investments. Traders and investors may find it
challenging to translate the theory into actionable trading strategies with precise timing.
3. Limited Use of Quantitative Analysis:
The Dow Theory primarily focuses on price action and does not incorporate advanced quantitative
analysis or statistical models. Critics argue that relying solely on price patterns and trends may not
provide a comprehensive and accurate assessment of market dynamics.
25. CRITICISM OF THE DOW THEORY INCLUDES THE FOLLOWING
POINTS:
4. Lack of Consideration for Fundamental Analysis:
The Dow Theory emphasizes price movements and trends while largely ignoring fundamental
analysis, such as company financials and economic indicators. Critics argue that a holistic approach
combining both technical and fundamental analysis is necessary for a comprehensive investment
strategy.
5. Evolution of Markets:
The Dow Theory was developed in the late 19th century when markets operated differently than
they do today. Critics argue that the theory may not fully capture the complexities of modern
markets, including the impact of algorithmic trading, high-frequence trading, and global inter
connectedness.
It's important to note that while the Dow Theory has its limitations, it still holds significanceas one
of the foundational principles of technical analysis and has influenced the development of various
other technical indicators and theories. Traders and investors often combine the Dow Theory with
other tools and indicators to enhance their market analysis and decision-making processes.
26. Q6: WHAT IS AN INDUSTRIAL LIFE CYCLE? ALSO EXPLAIN DIFFERENT STAGES
OF INDUSTRY LIFE CYCLE?
The industrial life cycle is a concept used to describe the different stages that an industry
goes through from its inception to its decline. It provides a framework for understanding
the dynamics and characteristics of industries over time. Understanding the industry life
cycle is valuable for businesses and investors as it helps them anticipate and adapt to
changes in market conditions. It enables companies to make strategic decisions
regarding product development, marketing, pricing, and resource allocation based on the
specific stage of the industry life cycle.
27. THE STAGES OF THE INDUSTRY LIFE CYCLE ARE AS FOLLOWS:
1. Introduction/Pioneering Stage:
The introduction stage is the initial phase of an industry where a new
product or service is introduced to the market. This stage is characterized
by low market acceptance, limited competition, and high uncertainty.
Companies in this stage focus on product development, market awareness,
and establishing their position in the industry. Profits are typically low or
negative during this stage as companies incur high research and
development costs.
2. Growth/Expansion Stage:
The growth stage is marked by increasing market acceptance and rapid
expansion of the industry. Customer demand and sales volume rise
significantly, leading to increased competition. Companies in this stage
focus on expanding market share, improving product quality, and
enhancing operational efficiency. Profitability improves as economies of
scale are achieved, and market demand continues to rise.
3. Maturity/Stabilization Stage:
The maturity stage is characterized by a stable and saturated market.
Industry growth slows down as market demand reaches its peak and
competition intensifies. Companies in this stage focus on market
differentiation, cost control, and maximizing market share. Price
competition becomes more prominent, and profitability may start to
decline as companies fight for market share.
28. THE STAGES OF THE INDUSTRY LIFE CYCLE ARE AS
FOLLOWS:
4. Decline Stage:
The decline stage occurs when the industry experiences a decline in market demand or becomes
obsolete due to changing technologies, consumer preferences, or other external factors. Companies in
this stage face declining sales, shrinking market share, and increased competition. Many firms may exit
the market, leading to consolidation. Strategies in the decline stage often include cost-cutting,
diversification, or exiting the industry altogether.
It's important to note that the length and characteristics of each stage can vary across industries.Some
industries may experience shorter life cycles due to rapid technological advancements or changing
market dynamics, while others may have longer life cycles characterized by slow market evolution.
29. ASSESSING THE INDUSTRY LIFE CYCLE:
The industry life cycle classification of industry evolvement helps investors to assess the growth potential of different
companies in an industry. Based on the stage of the industry, they can better assess the potential of different
companies within an industry. This helps in estimating the return potential, and the risk, of companies.
There are limitations to this type of analysis. First, it is only a generalization, and investors must be careful not to
attempt to categorize every industry, or all companies within a particular industry, into neat categories that may not
apply. Second, even the general framework may not apply to some industries that are not categorized by many small
companies struggling for survival. Finally, the bottom line in security analysis is stock prices, a function of the expected
stream of benefits and the risk involved. The industry life cycle tends to focus on sales and share of the market and
investment in the industry. Although all of these factors are important to investors, they are not the final items of
interest. Given these qualifications to industry life cycle analysis, what are the implications for investors? The pioneering
stage may offer the highest potential returns, but it also poses the greatest risk.
Several companies in a particular industry will fail or do poorly. Such risk may be appropriate for some investors, but
many will wish to avoid the risk inherent in this stage. Investors interested primarily in capital gains should avoid the
maturity stage. Companies at this stage may have relatively high dividend pay-outs because they have fewer growth
prospects. These companies often offer continuing stability in earnings and dividend growth. Clearly, companies in the
fourth stage of the industrial life cycle, decline, are usually to be avoided. Investors should seek to spot industries in
this stage and avoid them.
It is the second stage, expansion, that is probably of most interest to investors. Industries that have survived the
pioneering stage often offer good opportunities. Growth is rapid but orderly, an appealing characteristic to investors.
