The Efficient Market Hypothesis states that stock prices always reflect all available information and that it is impossible for investors to outperform the market. It has three main assumptions: stocks are traded at fair value, market prices reflect all information, and investors cannot beat the market. There are three types of market efficiency - weak, semi-strong, and strong. The EMH is limited by market crashes, anomalies, and evidence some investors can beat the market. Several anomalies exist, including calendar anomalies like the January effect and turn-of-the-month effect. Fundamental anomalies include the value and size effects. Technical anomalies use techniques like moving averages and trading range breaks.

1. Efficient Market Hypothesis
P R E S E N T E D B Y:
P R A C H I J A I N
M U S K A N B H O L A
A B H I S H E K K U M A R
PA M I S H
S O N A M S H A R M A

2. agenda
Concept of EMH – Introduction
Assumptions
Types
Limitations
Market anomalies:
a) Calendar anomalies
b) Fundamental anomalies
c) Under and overreaction anomalies

3. introduction
It is an investment theory that states it is impossible to "beat the
market" because stock market efficiency causes existing shares to
always incorporate and reflect all relevant information.
According to the EMH, stock always trade at their fair value on
stock exchanges, making it impossible for investors to either
purchase undervalued stocks or sell stocks for inflated prices. As
such, it should be impossible to outperform the overall market
through expert stock selection or market timing, and that the only
way an investor can possibly obtain the higher returns is by
purchasing riskier investments.

4. assumptions
Stocks are traded on exchanges at their fair market values.
The market value of stocks represents all the relevant information.
Investors are not capable of outperforming the market.

5. Types of EMH

6. limitations
Market crashes
and speculative
bubbles
Market anomalies Investors have
outperformed the market
Behavioral
economics

7. Marketanomalies

8. Calendaranomalies
• The phenomenon of small-company stocks to generate more return
than other asset classes and market in the first two to three weeks of
January is called January effect.
January Effect
• The prices of stocks are likely to increase in the last trading day
of the following month, and the first three days of next month.
Turn-of-the-Month Effect
• This anomaly describes the increase in the prices of stocks and
trading volume of stock exchange in the last week of December
and the first half month of January.
Turn-of-the-Year Effect
• The stock prices are likely to fall on Monday. Means the closing
price of Monday is less than the closing price of previous Friday.
Weekend Effect

9. Fundamentalanalysis
Value anomaly occurs
due to false prediction
of investors. They
overly estimate the
future earnings and
returns of growth
companies and
underestimate the
future returns and
earnings of value
companies
The stocks with low
price to book ratio
generate more return
than the stocks having
high book to market
ratio.
Stocks with high
dividend yield
outperform the market
and generate more
return. If the yield is
high, then the stock
generates more return.
The stocks with low
price to earnings ratio
are likely generate more
returns and outperform
the market, while the
stocks with high price to
earnings ratios tend to
underperform than the
index.
The prior neglected
stocks generate more
return subsequently
over a period of time.
While the prior best
performers
consequently
underperform than the
index.

10. Technicalanomalies
Moving average: An important technique of technical analysis in which buying and selling
signals of stocks are generated by long period averages and short period averages. In this
strategy buying stocks when short period averages raises over long period averages and
selling the stocks when short period averages falls below the long period averages.
Trading Range Break: This technique of technical analysis is based upon resistance and
support level. A buy signal is created when the prices reaches at resistance level, which is
local maximum. As investor wants to sell at peak, this selling pressure causes the
resistance level to breakout than previous level. This breaks out causes a buy signal. A
selling signal is created when prices reaches the support level which is minimum price
level. Thus technical analysis recommends buying when the prices raises above last peak
and selling when prices falls below last trough. But this strategy is difficult to implement.

11. Presented by:
Team 6
Topic:
EMH concept and Anomalies to the EMH concept- explanation of different anomalies