Algorithmic and Mechanical Forex Strategies | OneStepRemoved

Contemplating Stops: Are They Hurting Your System?

by Leave a Comment

I tend to be pretty paranoid about risk of ruin. That is why I almost always suggest adding some form of stop-loss protection to the systems I write about. It just makes sense to me that you should do everything possible to protect your trading capital.

Some of the strategies I have profiled seem to leave themselves open to holding large losing positions. My simple solution to this problem is always to add a simple stop-loss component. However, that could be detrimental to the overall performance of the system.

A recent guest post on System Trader Success forced me to take a deeper look at whether stops are actually worth using. The post was written by Rob Hanna from Quantifiable Edges.

stops

The logical idea of adding stops to reduce your risk of ruin my actually hurt your system’s overall performance.

Rob explains that he primarily trades mean reversion strategies similar to the ones that Larry Connors has published in his books. He explains that Connors has written about the tendency of stops to reduce overall performance. Rob has done his own research on the topic as well:

When looking to trade overbought/oversold techniques, stops generally don’t work well.

If the system suggests the security should bounce when it drops to $20 and it continues to $18, then it is REALLY overdue for a bounce. Any level of stop ensures you are selling an extremely oversold security that is making a low.

Those are buying conditions for oversold systems – not selling conditions.

The trend following crowd won’t agree with what Rob is saying about a security being “really overdue for a bounce,” but it will make sense to mean reversion traders. Rob also points out a stop strategy that seems to have the least negative impact on his oversold systems:

Wait until the security bounces for a bar or two. Look for a higher high, higher low, and higher close – or at least 2 of those 3.

Then place a stop under the swing low that was just made. In cases like this even if the security doesn’t hit your target exit price, it still ensures that you won’t have to suffer through the entire next leg down.

While it seems logical and can sometimes help avoid catastrophic trades in the long run, you’re normally better off just waiting for the mean reversion to occur and exiting at your target level.

He also makes the point that position sizing is extremely important and suggests using options to place trades instead of stops:

Not using stops does not equal not controlling risk. Position sizing becomes very important.

Traders could also consider using options to trade their short-term positions. Options provide a natural stop (zero).

Rob closes his piece by reminding us that he is specifically talking about mean reversion systems. He agrees that stops can be very effective when used with trend following systems.

The interesting take-away from this piece is that the type of strategy you are trading should be what influences your choice of stop-loss strategy more than your personal risk tolerance. If you are struggling with the risks your system takes, changing strategies might be a better option than adding stops.

Making Trading Systems More Antifragile

by Leave a Comment

In order to make trading systems more antifragile, we must focus on changing their risk exposure. If your primary concern in trading is your system’s profitability, then you are setting yourself up for an epic failure. The first and foremost concern of any trading system absolutely must be the risk within a system.

Risk of Ruin

In Book III of Antifragile, Nassim Taleb presents the argument that profit is a secondary goal in business. He argues that anyone who primarily focuses on profit is underestimating their risk exposure.

This concept applies directly to trading systems. Far too many traders use potential returns as the measuring stick for a trading system. Following Taleb’s argument, traders should put far more emphasis on the nature of the system.

“This fragility that comes from path dependence is often ignored by businessmen who, trained in static thinking, tend to believe that generating profits is their principal mission, with survival and risk control something to perhaps consider – they miss the strong logical precedence of survival over success.” – Taleb

While generating profits is certainly the end goal of any system, the ability to generate those profits requires the survival of the system. If the system goes bust at any point, then those future profits mean nothing.

Even if the system generates huge profits for years, if there are significant risks that could eventually catch up to it, then the system is just trading on borrowed time. The most important criteria for assessing a system’s fragility is its risk of ruin.

risk reward comparison

Risk and reward should be balanced against the long term objective of continuing to trade.

The least desirable way to protect against risk of ruin is to decrease the fragility of the system. This may sound like common sense, but far too many traders never make the connection.

As I covered earlier this week, there are three way of doing this: increasing the system’s win rate, increasing the system’s profitability, or decreasing trading size. Of these options, the only one that is completely in the trader’s control is the amount of risk their capital is exposed to.

Sensitivity to failure is best analyzed by adjusting the accuracy percentage and payout ratios. If you trade a trending system and the average payout drops by 20%, what happens to the system? Many trending systems completely fall apart.

Sometimes, a difference of 10% between the historical returns and future observations makes the difference between decent profits and huge losses. This is far more true when the expected percent accuracy falls and the payoff falls, too. Minor errors in observation lead to drastically different outcomes.

Fragility is Relative to Upside/Downside Risk

In the preceding chapter, Taleb explains that fragile systems have more to lose than they can gain. The opposite is true for antifragile systems. They have more to gain than to lose. They have a limited downside.

“You are antifragile for a source of volatility if potential gains exceed potential losses (and vice versa).” – Taleb

This further supports the argument that risk of ruin should be the primary concern when evaluating a trading system. Regardless of the system’s apparent upside, if the downside is too great, the system is no good. If the potential exists to lose everything, there is no possible upside that can balance that.

Long Term Capital Management

Taleb uses the example of a gambler to illustrate that no matter how good his strategy is, if he is exposed to the risk of losing everything then nothing else matters. The same can be said of anyone who’s trading system exposes them to too much risk.

It doesn’t matter how efficient the strategy is or how impressive the returns are if the risk of losing everything is too great. Risk of ruin trumps all other factors because it has the ability to end the game.

Long Term Capital Management (LTCM) provided an excellent example of this concept in the late 1990s. The fund was believed to have superior strategies implemented by brilliant traders and many investors expected the strong returns to continue indefinitely. The problem is that no one was concerned with the downside risk, leaving the fund vulnerable to a Black Swan event, which happened in 1998.

The combination of some unexpected events with a big appetite for leverage proved to be disastrous for LTCM and its investors. LTCM believed that it had smoothed out volatility and could provide consistent returns. As we all learned, the short-termist obsession with pretty Sharpe ratios on high leverage came at the cost of making a blowup inevitable..

Evaluating Your System’s Risk of Ruin

by 2 Comments

What are the odds that your system blows up your entire account? Probably a lot higher than you think.

Risk of Ruin

Risk is one of the most important factors in successful trading. The problem with risk is that it comes in multiple levels. Many traders are able to evolve to the point where they are able to determine how much they are willing to risk on any single trade. The problem is that most traders stop there.

Too many traders never even consider the odds of blowing up their account.  This was certainly an issue I dealt with early in my career. When you’re just getting started, you are naive enough to believe that success will be easy to find. I didn’t think I’d ever come close to losing my account. I didn’t even think I’d ever have a losing streak.

risk of ruin

Is it only a matter of time before your account explodes?

As we evolve, we learn that all systems have drawdowns. All traders struggle at some point. The most important lesson in trading is to survive to trade another day. In order to do this, we have to calculate the odds of losing everything and adjust our trading to make sure we are able to survive. This is why we study risk of ruin.

The Three Components of Risk of Ruin

  • Win Ratio – The percentage of expected winning trades based on historical backtesting.
  • Payoff Ratio – The average profit of a winning trade divided by the average loss of a losing trade. Shaun also calls this the R multiple.
  • Percent of Capital Risked – The amount of capital your system puts at risk on any given trade.

How These Components Interact

Once you have these three components, it is easy to determine your risk of ruin using a table. The ideal situation is to have a risk of ruin as close as possible to 0. In the event that your Risk of Ruin is greater than zero, then you can adjust any of the three components in order to improve it.

The component that you have the most control over is Percent of Capital Risked. Simply adjusting down your position size will dramatically reduce your risk. The drawback to this is that you will also be adjusting down your profits.

The other alternative is to tweak your system in a way that improves your edge. This can be done by increasing the percentage of winning trades your system can expect or by increasing the Payoff Ratio. The Payoff Ratio can be increased either by having bigger profits on winning trades or less losses on losing trades. These components are more difficult to adjust because there are more factors outside of your control.

Using My 10/100 SMA System Example

I recently had a simple moving average system backtested. Using the historical backtest data for that system, we can calculate the risk of ruin. The system was set up to have rules that were extremely simple. It establishes a long position when the 10 day SMA crosses above the 100 day SMA and then goes to cash when the 10 day SMA crosses below the 100 day SMA.

Based on the results from historically backtesting this system on the SPY, I discovered that it would be profitable on about 41% of its trades. Its winning trades are a little better than 4 times as large as its losing trades, so I can put it in the 4-1 category.

According to the Risk of Ruin tables, if I was to use this system and risk 1% of my capital on each trade, my Risk of Ruin would be 0. Nothing is ever definite, but there is very little chance that I would go broke trading this system. The problem, however, is that this system also fails to beat out standard buy and hold strategies. There would also be an issue if the system’s Win Ratio fell below 30%. If that were to happen, Risk of Ruin would jump to 100%.