Negatively Skewed Trading Strategies (Thin Right Tails And Fat Left Tails)

Last Updated on June 11, 2021 by Oddmund Groette

Some years ago I traded propritary with Echotrade. I remember what one of its principals said about new pair traders that started trading with them: oh no, he’ll make a lot of steady money, but ultimately he’ll lose it all, and perhaps even more. His experience was based on the objective numbers from the firm: pair traders did not last long.

The reason is that their strategies are usually negatively skewed/distributed. Why is that? The majority of them play the Martingale strategy*: they add to losers. Problem is, you get away with this most of the time. However, once in a while you get stuck into a pair that does not mean reverse. The loss simply gets bigger and bigger until the account is wiped out or you are being asked for more margin.

When I started trading in 2001, I remember one trader doing merger arbitrage. The spread grew bigger and bigger but he kept on adding new positions. Later the deal was called off. In the end, he lost five years of profit and gave up trading.

What is a negatively skewed distribution?

Skewness has a probability distribution that is not normally distributed.

Distribution refers to the profit and loss distribution of a strategy. When it’s negatively distributed, or skewed, there are more observations on the right side of the y-axis, but the left side of the y-axis is longer and thus contains many more big losers than comparatively winners on the right side.

What does a negatively skewed histogram look like?

The chart below is a good example of how such a negatively distributed/skewed profit distribution:

Mean-reversion strategies are not normally distributed: they have thin right tails and fat left tails.

The chart shows many winners, but it has only 19 winners of more than 10% compared to 46 losers bigger than 10%.

Such a distribution is quite common in mean-revertive strategies. It doesn’t let the profits run and stop-losses don’t tend to work. The price you pay for this is many winners, but also few really big winners.

Opposite we have trend-following strategies that fewer winners, but they tend to be big.

Is negative skewness good?

As you could imagine, it’s not good. You trade happily for a long time until you have a rare, but big loser that wipes out many months, or years, of trading profits.

Moreover, it’s also problematic psychologically. After a big loss, you are more likely to commit behavioral mistakes. Perhaps you stop trading the strategy completely, or the effects might spill over to other parts of your trading.

Another problem with negative skewness and distribution is that most of the time we feel good. Most behavioral tests confirm that we continue hopeless strategies as long as we win frequently. We ignore the fat left tails, unfortunately.

Long-term Capital Management

Even “geniuses” don’t understand fat and long left tails. Perhaps the best example in financial history is the demise of Long-Term Capital Management:

Beginners luck (in trading)

The worst that can happen to a new trader, is to make much money from the start. The chances are that he’s just being lucky. It will feed his ego and increase his risk. He’ll not learn. I have yet to see a trader that does not experience significant losses from time to time. The more you learn, the better you can handle those losses.

A personal anecdote:

Some of my strategies are automated. And I know for sure: sometimes a fat finger or a program error will come and hit me like a boomerang. However, unlike most other traders I’m aware of the skewness and have it in the back of my head all the time. I make sure that my losses are limited in case it happens. Because I know it will happen.


*If it’s part of the strategy I see nothing wrong Martingale. However, that is only to add small units to get a full unit. For example, if you want to build a position of 100 000 USD as a part of a larger portfolio, you can add three units of 33 333 each. There is no way you can pick tops and bottoms, therefore I see nothing wrong with adding to losers if done this way.


Disclosure: We are not financial advisors. Please do your own due diligence and investment research or consult a financial professional. All articles are our opinion – they are not suggestions to buy or sell any securities.