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Momentum

Momentum Strategies and Indicators
by

Amir Ghods

on 22 July 2015

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Transcript of Momentum


MOMENTUM
Buying Winners and Selling Losers ?
Industry Momentum
Price Momentum
Earnings Momentum
Traditional Finance Theory
Equilibrium Asset Pricing Models
The Efficient Market Hypothesis
Behavioural Finance
Momentum
Investor Psychology
Limits to Arbitrage
Why
In the mid 1980’s an extensive body of finance literature, however, documents that future stock prices are, at least somewhat, predictable based on past returns. For example, De Bondt and Thaler (1985, 1987).
In 1993, Jegadeesh and Titman add a new angle to the above literature by documenting that, over an intermediate horizon of 3 to 12 months, past winners, on average, continue to outperform past losers.
Methodology
European Markets
Asian Markets
Worldwide
Emerging Markets
American markets
Empirical Findings of Momentum
Decile versus Weighted Relative Strength Strategy
Equally-Weighted versus Value-Weighted Portfolios
Full versus Partial Rebalancing
RANKING
10 Decile
Ranks stocks based on their past returns over a given period and divides them into ten portfolios.
stocks in a value-weighted portfolio are weighted according to their market capitalisations so that large cap stocks have the greatest influence on the portfolio return.
Holding Period
Formation period
K
J
t-K
Start
Close
The Momentum Effect
Narasimhan Jegadeesh; Sheridan Titman
Sources of Profits
return on security i
expected return on security i
firm-specific component of return at time t
dispersion in expected returns
potential to time the factor
compensation for bearing systematic risk
need not be an
indication of market inefficiency
suggest market inefficiency
unexpected return on a factor mimicking portfolio
covariance of index is negative (-0.0028 )
+
-
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(period 6-6)
(Decomposition)
Robustness Tests
(subsamples)
Size and Beta
FAMA - FRENCH (FF)
3 FACTOR MODEL
past winner
Past loser
Size
Volume
Value
High Book to Market
Low Book to Market
Growth Stock
Value Stock
Strategy
RETURN
~
~
RETURN
RETURN
Past Loser
Past Winner
Past Winner
Past Loser
SUB-PRIOD SAMPLES
SAMPLE PERIOD
Back Testing

Momentum Explanations
Past loser
Past winner
Risk-Related Explanations
Jegadeesh and Titman ,They find that the beta of the portfolio with past losers is higher than the beta of the portfolio with past winners; with beta values of 1.38 and 1.28, respectively .
Jegadeesh and Titman (2001), who find the losers to load more heavily on Fama and French’s SMB factor; with loadings of 0.55 and 0.41 for losers and winners, respectively.
Jegadeesh and Titman (1993) They find the stocks in the winner portfolio to be larger than the stocks in the loser portfolio, with the average market capitalisation of the winners being twice as large as the average market capitalisation of the losers, thus suggesting that the momentum return cannot be explained by the stocks in the winner portfolio being smaller than stocks in the loser portfolio.
Chan, Jegadeesh and Lakonishok (1996) find that the portfolio of winners tend to include growth stocks with low book-to-market values, whereas the portfolio of losers tend to include value stocks with high book-to-market values.

In other words, the winner portfolio loads negatively on the HML factor, whereas the loser portfolio loads positively on the HML factor, indicating that the book-to-market value as a risk measure is unable to account for the momentum effect.
Due to lack of better explanations some researchers have reached the conclusion that the documented momentum effect is merely a statistical fluke, which is unlikely to work out-of-sample.

For example, Fama (1998) argues that adjusting methodology and performing out-of-sample testing, in general, tend to eliminate observed anomalies.

The many studies across different markets and time periods documenting the momentum effect
Data Snooping and Flawed Methodology
Explanations Based on ?

Behavioral Finance
Momentum
overreaction
underreaction
Momentum Caused by Underreaction
The Gradual Information Diffusion Model
The Disposition Model
Momentum Caused by Overreaction
The Positive Feedback Trader Model
News Watchers
Momentum Traders
1
Private information diffuses gradually across the news-watcher population
UNDERREACTION
trend-chasing
First Momentum Traders
New Momentum Traders
overreaction
Momentum traders base their trading decisions on past price changes only
Rational investors
Disposition investors
The fundamental value of a stock either increases or decreases due to some good or bad news about the company.
Fundamental Value
The stock price rises, based on good news
Sell the Stock Quickly
hold on to the losing stock
The stock price falls, based on bad news
The Fundamental Value
The Fundamental Value
This underreaction on its own does, however, not explain the momentum effect.
The Fundamental Value
The Fundamental Value
Buy
short-selling
The model does not account for long term reversals in stock prices.
Investors that buy securities when prices rise and sell when prices fall.
positive Feedback Traders
Rational Investors
0
1
2
3
fundamental news.
+
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Buy
Sell
period 0 merely provides a benchmark against which the positive feedback traders can measure the appreciation or depreciation of stock prices from period 0 to periods 1 and 2.
+
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0
1
2
3
1
2
Buy
Sell
0
1
2
3
More Buy or Sell
Fundamental News.
Fundamental Value
They realise that the stock in period 2 is either overvalued or undervalued, and thus start betting on reversion to fundamentals. If they have bought in period 1, they sell, if they have sold in period 1, they buy.
In period 3 no trading occurs. Investors pay each other according to the positions they hold.
George Soros’ , description of his own investment strategy, in which he states that his success comes from betting not on fundamentals but on future herd behaviour.
The Overconfidence Hypothesis
Overconfidence refers to the tendency of individuals to overestimate their own abilities in various contexts; so, for example, an overconfident investor will tend to overestimate the precision of own value estimates of companies.
According to Daniel et al., investors are especially likely to be overconfident about signals or assessments with which they have greater personal involvement.

Thus, Daniel et al. define an overconfident investor as one who overestimates the precision of private information signals, but not of information signals publicly received by all. This, in turn, leads to overreaction on private signals but underreaction on public signals.
The evidence regarding the self-attribution bias suggests that people tend to credit themselves for past success, while blaming external factors for past failure.

As a consequence, the self-attribution bias has a tendency to reinforce
overconfidence.
Thanks
Prospect
Daniel Kahneman
information (Earnings Announcements)
firm
analysts
investors
sell rank
revenue
manager

dismissal
stock
analysts
ownership
many stocks
_
want to buy stock
neutral
investors
analysts
employers
in favour of
in favour of
Underreaction to Earnings Announcements
Pessimism Bias
Optimism Bias
analysts
investors
revisions in earnings forecasts
0.004%
average monthly revision
-2.138%
-0.180%
past winners
past losers
-1.843%
1-6
7-12
medium term momentum effect
Model of Investor Sentiment
the conservatism bias
individuals are too slow to change their beliefs when confronted with new information; in other words, new information is underweighted. in a financial context, is that prices only gradually adjust to new information.
representativeness heuristic
judgement based on stereotypes.In a financial context people often seem to find patterns in sequences that are in fact random so that, for example, a small increase in stock prices is likely to resemble previous bull markets.
It is the forecasted future earnings by this investor alone that affect prices and returns.
In reality, earnings streams follow a random walk; however, the investor does not know that.
next period
+
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investor
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+
surprise
the conservatism bias
new information
next period
the medium term momentum effect
representativeness heuristic
+
+
+
+
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-
-
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+
+
+
+
surprise
the long term reversal effect
reverting
random
trend
Rational Speculators versus Rational Investors
A person who trades derivatives, commodities, bonds, equities or currencies with a higher-than-average risk in return for a higher-than-average profit potential. Speculators take large risks, especially with respect to anticipating future price movements, in the hope of making quick, large gains.
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