Category: Momentum

Momentum in SA equities over different lookback periods

Momentum in SA equities over different lookback periods

It’s been a while since a posted the previous post in which we looked at momentum in SA equities over a 6 month look back period (skipping the latest month). We also showed how the volatility of the highest stock momentum portfolio looked reasonably predictable (or at least wasn’t random noise). Is 6 month’s optimal though for a lookback period? That’s something we want to address in this post.

In general we keep the portfolio construction process the same as in the previous post:

  • At the end of each month calculate the momentum (over a specific lookback period) of the top 80 stocks (skipping the most recent month).
  • Rank the stocks from highest to lowest momentum placing each stock in one of five portfolios based on this ranking (highest to lowest).
  • Equal weight each stock using closing prices of the following trading day (i.e. we are assuming the we readjust the portfolio at the end of the next day).
  • Allow the weights to float until the next formation/month (this replicates an actual portfolio – each stock is equal weighted at the beginning of the month but price changes will change the weights during the month).
  • Returns are net of dividends and capital adjustments and exclude transaction costs.

 

Going long the top momentum stocks

First we look at portfolios that go long the top quintile of momentum stocks (equal weighted and re-balanced at the end of each month). Below are the cumulative returns (on a log-scale):

Momentum over different lookbacks - long only

It’s a bit messy but we have highlighted the top and bottom two.  Interestingly 6 months’ is a rather “middle-of-the-pack” performer. The more longer-term, 12 and 24 month portfolios seem to do better (and consistently so). As expected the longer the lookback period the lower the returns, although too short and the returns are even worse as highlighted by the 2 month portfolio.

We have shown the total return (annualised) and Sharpe ratios below. This further illustrates this “polynomial” relationship – if the lookback period is either too short or too long a (long-only) momentum portfolio’s return degrades. The 12 to 24 month period again seems to be fairly optimal.

Long only - share and cagr

 

A long-short portfolio

The above analysis was only for a long-only portfolio (long the top momentum stocks). Here we look at a long-short portfolio: long the top momentum stocks and short the lowest momentum stocks. This will give us a good idea of how sustainable momentum is at different lookback periods and whether mean reversion is more prevalent at specific periods.

 

Momentum over different lookbacks - long-short

We have to be careful here, since the period above only stretches from 2004. Momentum worked really well since 2011 – so no matter which lookback period we used we would have done well. Clearly this isn’t going to continue forever and so we need to contrast post-2011 performance with pre-2011 performance.

The 36 and 48 month portfolios seem to be the worst performers and returns are actually negative until 2011. The best performer is once again the 12 month portfolio (even pre-2011).

The annualised returns and Sharpe ratios highlight a similar relationship to the lookback period, although the 6 – 12 month portfolios seem to be fairly optimal. Returns decline from the 12 month lookback onwards.

Long short - share and cagr

Conclusion

You can never be sure what the future will hold in terms of optimisations and how these parameters will evolve going forward. However, from both the long and long/short portfolios it seems like 12 months has done pretty well both pre- and post-2011. However, from the charts of the annualised returns and Sharpe ratios it seems like anything between 6 and 12 months is a decent pick as a lookback period.

 

Although every effort is made to ensure accuracy in the data and analysis presented on this site, this cannot be guaranteed. Nothing on this site constitutes investment advice, nor should it be taken as such. And obviously, past results do not guarantee future performance.

Momentum in South African equities

Momentum in South African equities

Momentum has proven to be one of the most pervasive factors out there in the investing/trading world. A number of academic papers (beginning with the seminal Jegadeesh and Titman paper) have shown momentum to be a persistent and somewhat unexplained (at least by traditional market theory) factor. In South Africa there have been a few academic papers on the subject. A comprehensive paper by Muller and Ward, for example, looked at a variety of factors and found 12 month momentum to be one of the strongest (amongst a few others). They found a momentum portfolio formed on the prior 12 month returns and held for 3 months outperformed the ALSI by roughly 9% per annum over the period (1984-2012).

Lets take a closer look at momentum portfolios, specifically in the South African equity space. We start off by narrowing down the universe to the top 80 stocks on the JSE (data from Bloomberg) from 1 Jan 2000 to 22 March 2016. That is, in our analysis, the top 80 stocks as at the end of each month are taken as our universe with everything else excluded (for that period). We then form 5 portfolios based on 6 month momentum (we will play around with the formation period in a later post). We also exclude the most recent month when calculating momentum due to some evidence that strong momentum stocks exhibit a reversal effect in following next month (this was found in the original Jegadeesh and Titman paper and further elaborated on in a follow up paper – the impact has sometimes been found to be rather marginal).

To summarise:

  • At the end of each month calculate the (6 month) momentum of the top 80 stocks (skipping the most recent month).
  • Rank the stocks from highest to lowest momentum placing each stock in one of five portfolios based on this ranking (highest to lowest).
  • Equal weight each stock using closing prices of the following trading day (i.e. we are assuming the we readjust the portfolio at the end of the next day).
  • Allow the weights to float until the next formation/month (this replicates an actual portfolio – each stock is equal weighted at the beginning of the month but price changes will change the weights during the month).
  • Returns are net of dividends and capital adjustments and exclude transaction costs.

 

Momentum portfolio returns using 6 month momentum

We show the returns for each quintile (i.e top 8 stocks by momentum in quintile 1, and so on). There appears to be quite a good separation – especially between quintile 1 (high momentum) and quintile 5 (low momentum).

Momentum quintiles (6m)

 

Below we show the relative returns of the highest momentum and lowest momentum stocks which highlights the long-term success of momentum. This equates to roughly a 22% outperformance of the low momentum portfolio per annum on average (by the high momentum portfolio).

Q1-Q5 (6m)

When does high momentum underperform?

Most of this outperformance is actually only due to two periods: 2001 – 2007 and 2012 – 2015. High momentum actually underperformed low momentum by roughly 30% during the initial stages of the recovery (2009/2010). The underperformance during the initial stages of the recovery in 2009 is an effect described in the paper Momentum Crashes (Daniel & Moskowitz).

They find that the loser (low momentum) portfolio has much higher beta following a large market decline. Therefore, if you go long high momentum and short low momentum stocks you end up with a large negative beta position (high momentum portfolio’s beta minus a much larger low momentum portfolio’s beta). This means as the market recovers as a whole, higher beta stocks (which are more likely to be in the low momentum portfolio) will do better (thereby outperforming the high momentum portfolio). Daniel & Moskowitz also explain the long-short momentum portfolio as a written call option on the market just after a large decline (due to the large negative beta of the long-short portfolio). Therefore, as the market recovers the call option goes into the money and you (as the writer of the call option) start to accrue losses.

The analogy to written call options is useful, because with a written call option you become short volatility. That is, as volatility increases (all else being equal) the value of the call option rises (and consequently your losses increase). This makes sense if you think about the market conditions which a momentum strategy would thrive in or conversely in which it woudl struggle. A momentum strategy would do struggle with whipsaws, which are present during heightened volatility (hence the whipsaw). A momentum strategy would do well when a stock grinds higher (or lower) at a consistent pace (i.e. when experiencing low volatility).

Daniel & Moskowitz find there is an inverse relationship between volatility and the long-short portfolio’s returns, but only during bear markets. More importantly though, they find that the volatility of the winners portfolio is relatively predictable and using this they are able to scale in and out of the momentum strategy and improve returns and Sharpe ratios.

 

Rolling 6M volatility

In the chart above we plot the rolling 6 month volatility of the high momentum (quintile 1) portfolio for SA equities. The volatility does seem to follow a pattern that reverts to some short-run mean over the short-term and some long-run mean in the long-term – something we may be able to model.

The role of volatility in relative performance

Below we show the short-run mean against the relative return of high momentum against low momentum (long high, short low momentum). Keeping in mind that there is some lag in the smoothed rolling 6M volatility, there does appear to be some relationship. Over the long-term, as volatility increased from 2003 to 2008, the relative return declines until eventually the high momentum portfolio underperforms the low momentum portfolio over 2009-2010.

Volatility vs 12M Rel Returns

Over the period 2011-2014 volatility has declined significantly to near all-time lows, benefiting high momentum. However, of late, markets have experienced heightened volatility, something momentum strategies do not enjoy. The key question is: will these conditions endure and see momentum strategies reverse gains? Momentum has not done well YTD (at least in South Africa) as evident from the sharp decline in relative returns in the chart above. Perhaps volatility declines in the short-term, but it seems as though in the long-term volatility may increase – something to keep in mind when dealing with momentum strategies.

Conclusion

We are, arguably, in the midst of a regime change. We have experienced low interest rates and “easy money” but this era is likely at an end. We should therefore be wary of strategies that have worked over the past five years and whether these will continue in the future.

Momentum as a strategy seems to have done well in South African equities over the past 15 years and more recently from 2012 – 2015. Should we expect this to continue? To address this we have looked at the role volatility has played in momentum strategy returns. Both in academic research and in our own analysis we have found volatility often has an inverse relationship with momentum strategy returns.

The volatility of the highest momentum portfolio does appear to follow some structure – reverting to short-run mean in the short-term and a long-run mean in the long-term. Volatility may decline in the short-term, but it does appear that long-term volatility is on the rise and this is likely to prove a headwind to any momentum strategies.

Some additional questions and points we may want to address in the future:

  • The performance of momentum over lags other than six months and over different holding periods
  • The impact of skipping the most recent month
  • Can we model the volatility of the past winners portfolio?
  • What are the implications for a market cap index (seeing as this is merely a long-only momentum strategy)?

 

Although every effort is made to ensure accuracy in the data and analysis presented on this site, this cannot be guaranteed. Nothing on this site constitutes investment advice, nor should it be taken as such. And obviously, past results do not guarantee future performance.