ViniyogIndia Momentum Investing smallcase

ViniyogIndia.com Momentum Plus strategy invests in a portfolio of high momentum stocks from NSE that are making 52 week highs. Portfolio construction steps are:

  • Long only portfolio of up to 40 stocks picked from NSE universe exhibiting strong uptrend.
  • Further enhanced by proximity to 52-week highs
  • Illiquidity filter to remove low volume/ turnover stocks
  • Balanced once every month in order to keep % turnover low.
  • Risk managed by limiting exposure to any single stock.
  • This strategy has beaten the markets by a wide margin in past (both in India & globally).

The underlying strategy construct comprise of two factors: a) momentum & b) proximity to 52-week highs. Both has been extensively researched, a brief summary of which is provided below.

*Returns shown are absolute returns since launch, in February 2021

Momentum Investing Strategy  

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.

Nobel Laurette economist Eugene Fama who propounded the Efficient Market Hypothesis (EMH) described momentum as a “premier anomaly” and termed it a “pervasive” phenomenon.

There is no universal explanation for why the momentum factor works. Some potential explanations attribute this to investors tendency to initially under-react and subsequently over-react to news affecting stock prices – a behavioral bias often described as initial under-reaction and delayed over-reaction.

Momentum remains an extensively researched subject in finance with papers documenting evidences of momentum dating almost a century back.

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.

The concept of momentum extends beyond the stock market which is why it is often described as a ‘pervasive’ anomaly. It has been documented across asset classes, geographies and over long periods of time in academic literature. For example, Geczy and Samonov (2012) showed that momentum has worked for US equities for 212 years through out-of-sample testing all the way back to 1801!

Momentum investing research in India

In the context of Indian stock markets, one of the most well-known studies on Four factor model in Indian equities 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, during this period, 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%.

Results suggest that the momentum earns significant positive returns (cumulative return of 341%) in the Indian market.

momentum investing in India
Cumulative log-returns of four factors in India, adjusted for survivorship bias.

Long only momentum

While majority of momentum research focus on Long-Short studies, there is ample literature and evidence of momentum anomaly in the long side.

For example, the Nifty200 Momentum 30 Index tracks the performance of 30 stocks that are part of 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.

Enhancing Returns on momentum stocks

Researchers have studied factors that can be used to enhance momentum returns, and data exists for India as well as global markets. Of these, nearness to 52-week high is amongst the primary.

52 week high low

In fact the 52-week factor was independently studied 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.

Results show that the long-short portfolio generates 0.45% per month, with the winner’s portfolio averaging 1.51% which is about 50% more than the loser’s portfolio return of 1.06%.

This paper also demonstrate that the nearness to the past 52-week high price can be a better predictor for future returns than the past 6-month return used by Jegadeesh and Titman (2001), and, that the return from this 52-week strategy does not reverse in the long run, as was the case in the results of Jegadeesh and Titman (1993, 2001).

Combining momentum with proximity of 52w highs has been found to generate higher returns. We have also validated this in our own tests.

Historical returns of Momentum+ Strategy

Past 10 year back-tested returns for the strategy is over 29% compared to around 12% for Nifty 50 TRI and Nifty 500 TRI

Year-by-year returns are as follows:

Risks

As evident from the back-tested data, this strategy performs extremely well in bull-markets, for example 2014, 2017 and recently 2020 – when it significantly out-performed benchmarks by a wide margin. In side-ways markets, the strategy performs average. In bear markets however, strategy may underperform the benchmarks.

Although, this strategy has significantly outperformed the benchmarks over long-term, in between, there has been dull periods stretching 1-2 years when the returns have been flat. Sticking to your guns during these periods is key for the strategy to play out and generate market beating returns over long-term.

From risk management perspective, strategy put limits on maximum exposure in any single stocks. In down markets, it automatically moves to cash if no suitable opportunities could be found. Further, we filter by 30-day average daily turnover to remove illiquid stocks, and rebalance once a month to reduce turnover and contain impact cost.

*Returns shown are absolute returns since launch, in Feb 2021

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