In a previous post on FamaFrench factors we have discussed Market, HML (returns of High B/M stocks over low B/M
stocks) and SMB (returns of small market cap stocks over large market cap
stocks) factors. In this post we will discuss two factors which are very
popular among the Quant traders. These factors have been religiously studied by academicians as well.
Momentum factor (MOM):
This factor represents returns
continuation over medium term horizon. In simplest terms, stocks which have
outperformed over the last year are going to continue outperforming in recent
future. This factor was first discussed by Jegadeesh and Titman in 1993. Since
then a lot of research has been done on this factor. Numerous studies have
claimed that over long horizon, this factor tends to generate considerable
alpha.
Volatility factor (VOL):
This factors talks about future
performance of stocks based on their historical volatility. Stocks with high
level of volatility under perform stocks with low level of volatility. This
factors goes against the traditional wisdom that high returns is compensation for high risk (volatility). In my view this is a very useful factor for stock selection strategies.
Methodology for factor calculation:
 Everyday top 200 stocks( in terms of market capitalization) are chosen. This is done to avoid survivorship bias.
 These chosen stocks are sorted based on their past 252 trading day returns. Top and bottom quartile of stocks are selected from this list.
 The equal weighted out performance of the top stocks (highest returns) over bottom stocks (lowest returns) for the next day is the return of MOM factor for the next day.
 Above three steps are repeated for all the days to get a time series of MOM daily returns.
 The cumulative sum of these daily returns is the MOM index.
Factor perfomance in Indian stock market:
Following is the behavior of
these factors since 2006. First 253 days show zero returns due to the look back
needed to compute these factors.
MOM has not generated
any significant alpha over the last 6 years. There is a big draw down in the in 2009 when the market was recovering from the 2008 crash. This
post crisis failure of momentum strategies is a well known phenomena known as Momentum Crashes.
VOL has been consistently generating alpha over the last 6 years. Similar to MOM factor, VOL factor tends to suffer whenever there is a spike in the market.
VOL has been consistently generating alpha over the last 6 years. Similar to MOM factor, VOL factor tends to suffer whenever there is a spike in the market.
Randomness tests:
Following are the result of some randomness
tests on these factors:
Test

Parameter

Random Walk

MOM factor

VOL factor

ACF

Lag 1

0

0.25

0.15

Runs test

Number of runs

913

794

803

Variance ratio test

Variance ratio(period=2)

1

1.25

1.15

Variance ratio test

Variance ratio(period=5)

1

1.55

1.28

Why bother with these factors?
The most important use of these factors is in alpha generation. With proper modifications these factors can be used to generate considerable returns in a capital neutral fashion.
These factors can be used for market regime identification. They can be also be used to affirm bullish or bearish trends in market(due to negative cross correlations with market). In a true bull market, these factors are going to show a drawdown.
Returns of various trading strategies can be regressed against the returns of these factors to understand if the strategies are betting on a specific type of risk to generate alpha.
These factors show significant positive autocorrelation. So money allocation to the strategies which use these factors can be dynamically altered based on their recent performance. So a VOL factor long strategy should be allocated less money when VOL factor is falling as the trend is likely to continue.
Hi, Any research papers on VOL factor?
ReplyDeleteAre there any other factors apart from these two which are common knowledge among the quant traders?
ReplyDeleteHi I have read your post this is very helpful for me. This article have awesome topics that I want.
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