It has been documented in academic white papers and other websites that bear market volatility is always greater than the bull market volatility. Is this one of the reasons why it has always been better to stick to a long only strategy for stocks?
For a given interval of time and with the right environmental variables, we usually don’t see panic buying. On the other hand, all else equal, there are myriads of examples where panic selling occurs. One such example of the modern creation is the flash crash of May 9th 2010. This is true for the equities market.
Can we extend our rationale to futures? How has a long only strategy performed compared to long short? Does this apply to a variety of trend following systems? In this little study I set upon with an hypothesis that shorting brings forth volatility to a trading strategy due to the fundamental idea in buying and selling. I will be coming from a trend following perspective with 3 sample systems and compare their performance across parameters and time to ensure validity of my findings.
For the entire set of simulation I will be using ratio adjusted futures contracts. Test range will be from first trading day of 1980 to 5 months in to 2011. 56 markets will cover all sectors to ensure diversification and robustness of results. No commission is used.
For the first system I will be testing a Donchian N-Day breakout. It will take on one parameter, the breakout day. The exit day will be the same as entry. Sizing is Fixed fractional 1%.
In the above chart, I’ve parameter stepped the system from 20 days to 300 days in increments of 10. This is to ensure that conclusions can be drawn for breakout systems in general rather than just 1 parameter. I’ve recorded the annual Sharpe ratio of both the Long only strategy and Long/Short version of it. As you can see form the results, short to intermediate term breakout days show (40 to 180) consistently higher Sharpe.
Here is another view, showing the excess Sharpe generated for Long only compared to Long/Short. Does this simple test show that long only breakout strategy of intermediate term is better and less volatile compared to Long/Short? If so how come?
To ensure that the period between 40-180 is no fluke, I used a random number generator (numbers generated from atmospheric noises) and picked 10 integers between 40-180 and tested it Long vs Long/Short. The results..
In this, I also incorporated the daily Sharpe ratio (second graph) to show if its consistent with my earlier findings in a different time frame. The excess Sharpe for both graphs were all above zero.
In this simple test, evidence suggest breakout strategies do seem to consistently performance better when they are traded long only rather then long short. I’ve also tested the breakout strategy trading the short side, the results show that it had higher volatility, DD, and lower return.
I thought i'd post this on the forum to get peoples take on it. (my methods of analysis, conclusions, etc) Post was inspired by a short discussion here..
viewtopic.php?t=9284
Long Vs Long/Short Futures
I am very sorry to do this in the first reply, but I have to torpedo the merit of your futures analysis:
1)you are identifying the possibility of a 5-10% improvement in a noisy annual sharpe statistic. In the context of the amount of data available, annual sharpe is a very low sample rate figure and would will have an error term a mile wide, but more importantly, in the game of backtest-to-actual implementation, 5-10% is really splitting hairs. Daily sharpe on the other hand is possibly to short. Sharpe is scale dependant, so try to correlate it with the time horizon of your decision making. Even then , in reality, most seasoned traders will agree that sharpe hides more than it really tells.
2) following on from above....is sharpe even the right type of metric to be using, given it's inherent bias against the very type of "good upside volatility" that TF derives profits from?
3) Even if there is a sharpe ratio benefit to long only, further investigation might find that lack of any short exposure enhances the equity curve phase difference between global upswing and global downswing....one may as well just do leveraged mutual fund investing if you replicate their cyclical performance? There are quite a few threads in this forum on the merits of adding return sets that are negative in average total outcome, but anti-correlated with your other return delivering data sets.
4)You are looking for a reason why long only might be better than long/shorts? Let me take you to your likely conclusion in one sentence: Longs are logarithmically expanded in upside whereas shorts are logarithmically compressed in their upside.
When longs grow so does the price scale, the opposite is the case for shorts. This impacts their Return:risk potential assymetrically , outside of the very short-term.
5)ratio adjusted series is not the way to do it. at all.
6)In my opinion equity market bull/bear volatility assymetry is because the majority of sellers are not actual shorts, but merely offloading ownership to another party; so when they are wrong, the only pain they feel is an opportunity cost one, as opposed to a hard loss in their trading account. As a result upside moves are robbed of 40-45% of their impetus compared to symmetric markets like F/X as sellers are disproportionately made up of people going flat over people initiating actual shorts.
Commodities are assymetric like stocks, but (more than)make up for the bias due to factors like consistent downstream supply chain obligations that must be fulfilled, and inflexibilty of upstream supply in the short-term. These deliver hard dollar losses to sellers who make poor choices and thus promote more equivalent covering/buying impetus and volatility in either direction like a symmetric market.
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I hope that is food for thought.
1)you are identifying the possibility of a 5-10% improvement in a noisy annual sharpe statistic. In the context of the amount of data available, annual sharpe is a very low sample rate figure and would will have an error term a mile wide, but more importantly, in the game of backtest-to-actual implementation, 5-10% is really splitting hairs. Daily sharpe on the other hand is possibly to short. Sharpe is scale dependant, so try to correlate it with the time horizon of your decision making. Even then , in reality, most seasoned traders will agree that sharpe hides more than it really tells.
2) following on from above....is sharpe even the right type of metric to be using, given it's inherent bias against the very type of "good upside volatility" that TF derives profits from?
3) Even if there is a sharpe ratio benefit to long only, further investigation might find that lack of any short exposure enhances the equity curve phase difference between global upswing and global downswing....one may as well just do leveraged mutual fund investing if you replicate their cyclical performance? There are quite a few threads in this forum on the merits of adding return sets that are negative in average total outcome, but anti-correlated with your other return delivering data sets.
4)You are looking for a reason why long only might be better than long/shorts? Let me take you to your likely conclusion in one sentence: Longs are logarithmically expanded in upside whereas shorts are logarithmically compressed in their upside.
When longs grow so does the price scale, the opposite is the case for shorts. This impacts their Return:risk potential assymetrically , outside of the very short-term.
5)ratio adjusted series is not the way to do it. at all.
6)In my opinion equity market bull/bear volatility assymetry is because the majority of sellers are not actual shorts, but merely offloading ownership to another party; so when they are wrong, the only pain they feel is an opportunity cost one, as opposed to a hard loss in their trading account. As a result upside moves are robbed of 40-45% of their impetus compared to symmetric markets like F/X as sellers are disproportionately made up of people going flat over people initiating actual shorts.
Commodities are assymetric like stocks, but (more than)make up for the bias due to factors like consistent downstream supply chain obligations that must be fulfilled, and inflexibilty of upstream supply in the short-term. These deliver hard dollar losses to sellers who make poor choices and thus promote more equivalent covering/buying impetus and volatility in either direction like a symmetric market.
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I hope that is food for thought.
Rabidric,
First and foremost, thank you so much for your detailed feedback, it really helps my learning!
Initially, I found that this to be counter-intuitive. If the short side was a losing proposition, how can it improved the result when combined together? One explanation I felt was acceptable was just the underlying nature of the entire system. From the smoothing nature of the moving average, the number of bars and the magnitude of each bar required to reverse a signal is greater compared to a breakout system. Given this, we can also infer that the number of false breakout of MA strategy is less than a pure breakout strategy. Therefore the MA strategy with lower false signals and less trades (due to less whipsaws) will have a short side that is less volatile. Aggregating long short together will nevertheless improve performance.
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Thanks so much,
First and foremost, thank you so much for your detailed feedback, it really helps my learning!
Initially, I was thinking about this similar matter of what other factors in the error term may be correlated with what I am trying to isolate and measure as it will bring in measurement error and cause effect mixup. I tried to overcome this with more sample data to check for consistency, but the amount of stepping required would take a hours. But your feedback may be right in the idea that such small improvements is not worthy of any conclusions. I actually went further to incorporate two more systems, dual ma and bollinger breakout and found consistently higher sharpe making me reject my alternative hypothesis that sharpe when incorporating shorts would fall for trend following systems. Rather I concluded that it's rather system specific but more sensitivity analysis would be required again to check such conclusions. So to sum up, I agree that long short is more robust.1)you are identifying the possibility of a 5-10% improvement in a noisy annual sharpe statistic. In the context of the amount of data available, annual sharpe is a very low sample rate figure and would will have an error term a mile wide, but more importantly, in the game of backtest-to-actual implementation, 5-10% is really splitting hairs. Daily sharpe on the other hand is possibly to short. Sharpe is scale dependant, so try to correlate it with the time horizon of your decision making. Even then , in reality, most seasoned traders will agree that sharpe hides more than it really tells.
I knew this was gonna "torpedo" me and come back and haunt me. no excuse here but there is merit with my selection as the entire industry uses sharpe and an entire essay can be written of the advantages and disadvantages of it. Nevertheless I whole heartedly agree with you!2) following on from above....is sharpe even the right type of metric to be using, given it's inherent bias against the very type of "good upside volatility" that TF derives profits from?
a bit confused with what you are saying here, are you referring to the fact that the  " lack of any short exposure enhances the equity curve phase"? Nevertheless inferring on the mean I agree from further analysis that short exposure do indeed help diversification, but it depends on the system. I wrote something like....3) Even if there is a sharpe ratio benefit to long only, further investigation might find that lack of any short exposure enhances the equity curve phase difference between global upswing and global downswing..
Initially, I found that this to be counter-intuitive. If the short side was a losing proposition, how can it improved the result when combined together? One explanation I felt was acceptable was just the underlying nature of the entire system. From the smoothing nature of the moving average, the number of bars and the magnitude of each bar required to reverse a signal is greater compared to a breakout system. Given this, we can also infer that the number of false breakout of MA strategy is less than a pure breakout strategy. Therefore the MA strategy with lower false signals and less trades (due to less whipsaws) will have a short side that is less volatile. Aggregating long short together will nevertheless improve performance.
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I think thomas stridsman talk about this in his book about the long term uptrend biases the data and risk/return profile due to the fact that the scale changes. Here im confused as to how it affects whether long and short differs in there risk reward..4)You are looking for a reason why long only might be better than long/shorts? Let me take you to your likely conclusion in one sentence: Longs are logarithmically expanded in upside whereas shorts are logarithmically compressed in their upside.Â
When longs grow so does the price scale, the opposite is the case for shorts. This impacts their Return:risk potential assymetrically , outside of the very short-term.Â
can you please explain your reasoning? what method of contract concatenation will fit this type of analysis?5)ratio adjusted series is not the way to do it. at all.Â
There are many explanations and yours will definitely contribute to my analysis. In my observations, it intuitively makes sense to me from the idea behind panic sell verses panic buying.6)In my opinion equity market bull/bear volatility assymetry is because the majority of sellers are not actual shorts, but merely offloading ownership to another party; so when they are wrong, the only pain they feel is an opportunity cost one, as opposed to a hard loss in their trading account. As a result upside moves are robbed of 40-45% of their impetus compared to symmetric markets like F/X as sellers are disproportionately made up of people going flat over people initiating actual shorts.Â
Commodities are assymetric like stocks, but (more than)make up for the bias due to factors like consistent downstream supply chain obligations that must be fulfilled, and inflexibilty of upstream supply in the short-term. These deliver hard dollar losses to sellers who make poor choices and thus promote more equivalent covering/buying impetus and volatility in either direction like a symmetric market.Â
Thanks so much,