2. Momentum Strategy
• A trading strategy that buys stocks that have performed well in
the past and sell stocks that have performed poorly in the past
would be profitable if momentum exists.
• Over a horizon of three to twelve months, past winners on
average continue to outperform past losers by about one
percent per month, showing that there is “momentum” in stock
prices.
Term 2 Session 1 2
3. Objectives of the study
• Procurement of all the listed companies’ prices.
• Calculation of liquidity.
• Choosing the top 200 liquid stocks
• Ranking these 200 stocks based on momentum
• Formulation of 10 portfolios based on momentum.
• Measure the performance of these portfolios.
• Review the thesis by checking the performance of the
portfolios.
Term 2 Session 1 3
4. Limitation of the study
• Momentum strategy cannot be applied for all kind of
investment.
• It can only be applied for short term investment.
• When the market is in descending the strategy doesn’t work
and gives negative return.
• Due to lack of awareness about momentum strategy customers
would react late which results in sub par performance.
Term 2 Session 1 4
5. Literature review
• Momentum has shown itself to be quite robust across U.S. and
foreign equity markets, within industries and countries, and
across many different asset classes such as stocks, currencies,
commodities, and bonds.
• In 1993, UCLA professors Narasimhan Jegadeesh and
Sheridan Titman (1993)found strong evidence, over the 1965–
1989 periods, that stock prices trend—at least in the “short-
term” of up to two years.
Term 2 Session 1 5
6. Contd..
• Other academics confirmed that momentum is at work in
international equities, emerging markets, industries and
sectors, mutual funds, and asset classes. In fact, commodity
trading advisors (CTAs) have built a profitable business
around trading momentum.
• Empirical studies have shown the momentum effect to be
strong, but financial theory hasn’t definitively explained why
momentum exists
Term 2 Session 1 6
7. Research Methodology
Term 2 Session 1 7
• Quantitative research
• Qualitative Research
• Conceptual study
• Hypothesis
• Sampling
• Tools for data collection
• Method of data analysis
9. Qualitative Research
• Dealing with only 200 liquid
stocks.
• Consideration of top 200 stocks
on the basis of return generated.
Conceptual study
• Ranking of stocks based on
momentum.
• Calculation of return over a
period of 10 years to see the
momentum effect.
• Ranking of stocks based on
return.
Term 2 Session 1 9
10. Hypothesis
• Momentum Stocks outperformed
general market index
• Momentum has sticky behaviour.
• Momentum tends to be persistent
in the market.
Sampling
• Whole stock market data
from National Stock
exchange.
• Total of 1600 companies
from 2002-2012
Term 2 Session 1 10
11. Data Collection Tools
• Meta- Stock software for the
extraction of the data.
• Purchase of data from
Viratech software
Data Analysis Method
• Use of Excel functions like
Pivot table, Lookup value
• Return Matrix and
Performance matrix
Term 2 Session 1 11
19. SWOT Analysis
Strength: –
• Momentum is a better measure
than general market index for
short term.
• The strength of momentum
strategy is its performance when
the market is in upward trend.
Weakness :–
• Portfolio holding period for few
months, not tested for a longer
investment .
• Higher trading cost due to
readjustment of portfolio every
month.
Term 2 Session 1 19
20. Opportunities: –
• Use of this strategy for long term investment.
Threat: –
• Presence of variety of other strategies & portfolios.
• At times it didn’t perform well.
Term 2 Session 1 20
21. Findings
• Performance of the portfolios are not
better than the general Market Index.
• Out of the top 10 Portfolios only 5 of
them are performing better than the
Market Index.
• The companies performing very well
more consistent than the average
performers.
• The return on investment by the top
performer was much better than Nifty
return.
• Amount generated by portfolio-2 is
18.5 lakh and by nifty is 5.5 lakh over
10 year period.
• The difference between the highest
and the lowest performer is 16 lakh.
Term 2 Session 1 21
25. • From the graph it is clear that momentum based portfolios can generate
alpha though these portfolios have higher risk and higher return.
• The incremental increase in risk is more than compensated for incremental
increase in the return.
• The graph also demonstrates that portfolios based on strong momentum are
outperforming the average index after adjusting for the risk. Portfolios
based on weak momentum are underperforming and also constitute of
higher risk.
Term 2 Session 1 25
