July 19, 2019

This week there was this interesting notebook presented in a Quantopian forum. It is worth reading first so that what follows could be better understood. It is based on a free paper on momentum with volatility timing (link provided in the first post). 

What I observed was that there was something in there that could apply to any wannabe market-neutral trading strategy. However, it still depended on the premises made about the market in general.

Here, a trend-following assumption is made by assigning more potential upside to the top 10% of momentum stocks while giving more downside to the lowest 10%.

In the presented notebook, its figure #1 does show the strategy breaking down and bad. Here is a copy with the extended time interval.

(click to enlarge)

The poor performance is attributed to a change in behavior during the financial crisis when in reality, the market had not changed. It did what it usually does after a market meltdown, it recovers. And from there, it becomes a simple math problem.

A 10% decline requires an 11.11% rebound to recover. It is not much. While a 50% drop will need a 100% rise to get even. During the 2008-09 financial crisis most stocks declined, few were there to carry the upside torch. While the bottom momentum stocks were plentiful and a lot exceeding the minus 50%. Enough, in fact, to carry a lot of heavy short positions in the seemingly worse-performing stocks.

After the financial crisis, the majority of stocks recovered in the next few years and some more since then (over 300% for the general market lows). It meant that the stocks that declined by 10, 20, 30, 40, 50 or 60% saw their respective prices increase by 11.11, 25.00, 42.85, 66.67, 100.00, and 150.00% just to get even.

Therefore, for sure, it was not a good idea to have big shorts at the very bottom of their respective downfalls. The more the stocks went down, the heavier the short positions were and this right at the bottom of the cycle where they maxed out.

An important number in that trading strategy is the 0.27 constant used in its threshold function. A number that could be known, or set, only after doing many simulations. Increase this threshold to 0.50 and there will be no trades at all. Reduced it to 0.20, and you will skip the period from mid-2007 to mid-2012 with no trades for the W10-Timed. Make the threshold 0.10 and there will be no trading at all for W10-Timed. That is how critical this number is. It is a number you would not have known or optimized before doing any of these simulations.

Another assumption that is made is about the method of determining what is the trend. Here, it is defined based on the last year momentum compared to 1 month ago. Meaning that you are already late by one month over the past year. Making you somewhat over 6 months late to the party. Thereby basing your trading decisions on 6+ months lagging data and out of phase by at least one month. The impact being that the program did not see the recovery coming and was quite late to notice it had happened and was still piling on shorts.

Nonetheless, you can increase the strategy's performance by giving it some alpha. Since the strategy is operating on returns, its basic equation is: F(t) = F_0 ∙ Π_d (1+r_(d,j)) and to achieve more, the equation needs to be transformed into: F(t) = F_0 ∙ Π_d (1 + r_(d,j) + α_(d,j)).

I opted to give the strategy more time since my first interest is to determine if such a strategy can last. And I added some tiny alpha to the picture. This transformed the original figure #1 above into:

(click to enlarge)

By treating the winning and losing returns separately, and giving them small alpha numbers, it was possible to push even further and give even better numbers. Each was awarded the same initial capital and then combined as illustrated in figure #2.

You could push for slightly more alpha, but then, the credibility factor would be put into play. Here, like in other trading strategies, the understanding of the pressure points within a strategy gains its importance. It is with this understanding that you can push on what at first appears as limits when in fact they were just lines in the sand.

On the other hand, you could allocate half of the capital to each of the winners and losers sides. This would be more like the following where less capital would be used:

(click to enlarge)

Again, it is a matter of choices and preferences.

Created. July 19, 2019, © Guy R. Fleury. All rights reserved.