ViniyogIndia ๐Ÿš€ Momentum Investing smallcase to beat the market

Momentum Investing Strategy Basics

The basic idea of momentum investing is intuitive. A stock or any other asset, that has been trending strongly for a while is likely to continue doing so a little bit longer. That is the core concept, rest are details.

Nobel Laurette economist Eugene Fama, who propounded the Efficient Market Hypothesis (EMH), described momentum as a โ€œpremier anomalyโ€ and termed it a โ€œpervasiveโ€ phenomenon. EMH states that as markets are efficient, therefore, past prices cannot predict future returns. Momentum strategies do exactly that, and has been doing so for 100 years or more.

There is no universal explanation as to why price momentum works. Some potential explanations attribute it to investors tendency to initially under-react and subsequently over-react to news affecting stock prices โ€“ a behavioral bias often described as initial under-reaction and delayed over-reaction.

Momentum remains an extensively researched subject in finance which papers documenting evidence of momentum in stock prices dating almost a century back.

ViniyogIndia ๐Ÿš€ Momentum smallcase by ViniyogIndia

Academic research on Momentum Investing Strategy

Momentum is one of the most well researched topics in finance over the past 20 years. Hundreds of papers exits internationally, as well as in India, covering multiple countries and asset classes. We discuss some of the key papers below.

Seminal research by Jegadeesh & Titman

Seminal research on momentum was conducted by Jegadeesh & Titman (1993).

Using data from 1965 through 1989 they observed that winning stocks on the NYSE & AMEX over past 6 to 12 months continued to outperform losing stocks on average over next 6 to 12 months by approximately 1% per month.

Following this paper, their findings have been separately confirmed by many other academic studies, some even going back to the 19th century.

Narshiman Jegadeesh was an IIT/IIM graduate who earned his PhD at Columbia University.

In 1993, Jegadeesh, along with Sheridan Titman (UCLA) published a study showing that intermediate term momentum can be used to generate excess portfolio returns. This paper was described as a “bombshell” against those who glorified the Efficient Market theory.

(Narshimhan Jegadeesh, left, with Sheridan Titman)

52 week High-Low strategy

Similar study was performed by George and Hwang (2004) who developed a strategy that selects stocks based on the ratio of the current price relative to its past 52-week high.

Using data from January 1963 to December 2001 they showed that the long-short portfolio generates 0.45% excess returns per month, with the winnerโ€™s portfolio averaging 1.51%, about 50% more than the loserโ€™s portfolio average return of 1.06%.

Momentum is Persistent and Pervasive

Following Jegadeesh & Titman’s seminal research, hundreds of studies have followed making momentum one of the most well researched topic in finance over the past 20 years

Geczy and Samonov (2012) showed that momentum has worked for US equities for 212 years all the way back to 1801!

Multiple researchers [Antonacci (2012), Asness (2013), King, Silver & Guo (2002)] have established that momentum works over a dozen asset classes and more than 40 countries.

No wonder, Fama & French dscribed momentum as a โ€œpremier anomalyโ€ and a โ€œpervasiveโ€ phenomenon.

The premier market anomaly is momentum… It has been the biggest embarrassment to the Efficient Market theory and I hope it goes away! ๐Ÿ™‚

Eugene Fama

Nobel Laurette Economist for Efficient Market Hypothesis (EMH)

Dual Momentum Investing

Gary Antonacci published two papers [7, 8] and a book titled Dual Momentum Investing on multi-asset momentum. His Global Equity Momentum (GEM) strategy is based on 3 index funds โ€“ 1. Barclays US Aggregate Bond Index for bonds, 2. S&P 500 Index to represent US Equities & 3. ACWI โ€“ Ex US to represent Global Equities. The logic is simple: if equity returns are less than T-bills then invest in bonds, else choose between US & Global Equities based on Relative Strength.

Between 1974 & 2013, GEM returned 17.43% annually, compared to 12.34% for S&P500 and 8.85% for ACWI.

Momentum investing research in India

In the context of Indian stock markets, one of the most well-known study was published by IIM-Ahmedabad, where they computed the Fama-French and momentum factor returns for the Indian equity market for the October 1993 – December 2013 period.

Based on this study, the average annual return of the momentum factor was 21.9%; the average annual return on the value portfolio (HML) was 15.3%; that of the size factor (SMB) nearly 0%; and the average annual excess return on the market factor (MRP) was 11.5%. You can read more on Factor Investing here.

momentum investing in India
Cumulative log-returns of four factors in India, adjusted for survivorship bias. Results suggest that the momentum earns significant positive returns (cumulative return of 341%) in the Indian market.

The Nifty200 Momentum 30 Index

The Nifty200 Momentum 30 Index is a strategy index that tracks the performance of 30 stocks from the Nifty 200 Index having high normalized momentum scores.

This index has significantly outperformed the benchmark returning 18.6% annualized since inception against 12.7% for its parent.
Returns outperformance is consistent – it has outperformed its parent Nifty 200 Index 13 out of the last 16 calendar years, 98.3% times on a rolling return basis for 5 year investment horizons and also outperformed the Nifty 200 during the pandemic in CY 2020 till August 31, 2020.

ViniyogIndia ๐Ÿš€ Momentum smallcase by ViniyogIndia

ViniyogIndia ๐Ÿš€ Momentum Investing smallcase

ViniyogIndia ๐Ÿš€ Momentum Strategy smallcase invests in a portfolio of high momentum stocks picked from the NSE. Key portfolio construction rules are:
  • Portfolio of top 20-25 stocks picked from the NSE universe demonstrating strong uptrend
  • Further refined using combination of secondary factors to maximize risk adjusted returns
  • Mathematical model to control market exposure for risk management
  • Illiquidity filter to remove low volume/ turnover stocks
  • Rebalanced once a month in order to keep % turnover low

ViniyogIndia ๐Ÿš€ Momentum smallcase Performance

ViniyogIndia Momentum Investing Smallcase
YearNifty200Nifty200 Mo30ViniyogIndia Mo
FY2182.10%67.28%155.50%
FY20-27.88%-17.59%-13.65%
FY197.09%8.30%-14.10%
FY1810.67%20.24%55.96%
FY1723.76%37.37%36.11%
FY16-8.83%-7.80%-12.26%
FY1533.35%57.54%94.45%
FY1417.00%19.32%7.74%
FY134.51%14.17%11.61%
FY12-9.01%-1.42%11.06%
FY115.83%11.10%27.94%
FY1085.54%62.02%68.85%
FY09-40.17%-34.45%-1.84%
FY0825.58%45.25%56.29%
FY075.76%0.54%-2.63%
FY0661.21%76.57%72.90%
CAGR12.75%18.41%28.56%
Between 2005 – 2021, ViniyogIndia Momentum strategy generated a compounded return of 28.6% compared to Nifty200 return of 12.8% and Nifty200 Momentum 30 Index returns of 18.4%.

Further, our strategy had a reduced draw down, with worst year returns of -14.1% compared to -40.2% for Nifty200 and -34.5% for Nifty200 Momentum 30 Index.
Nifty200Nifty200 MO30ViniyogIndia MO
-40.17%-34.45%-14.10%

ViniyogIndia ๐Ÿš€ Momentum smallcase returns analysis

To interpret the sources of return for our strategy, we perform a regression analysis using Carhart 4 Factor model. The results are shown in the following table.
 AlphaMKTSMBHMLWML
Factor Premia0.8560.6560.1070.1450.394
p-value0.003~0.00.110.018~0.0
The above data shows that the strategy generates significant alpha that is statistically significant.

Monthly alpha or excess return for the strategy is 0.856%. This is generated using a combination of secondary factors and asset allocation strategies that tries to enhance momentum returns while reducing risks.

Additionally, standard factors, such market beta, momentum and value also add to the overall strategy returns. Returns from the size factor isn’t statistically significant.

It is important for the investors to understand the sources of return for their funds in order to appreciate the value provided by the fund manager, as in many cases managers fail to generate alpha despite charging hefty fees. What they generate instead are betas, which can be easily obtained by exposure to the standard risk factors.

In such cases where an analysis of the fund’s performance reveal that the manager isn’t generating any alpha, investors would be better off buying low cost index funds or ETFs which provide exposure to one or more of the betas such as value, momentum or size. In case of momentum for example, one such low cost fund is the UTI Nifty200 Momentum 30 Index Fund whcih basically mimics the Nify200 Momentum30 Index.

ViniyogIndia ๐Ÿš€ Momentum smallcase by ViniyogIndia

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