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Losing to Win: 3 Reasons I Focus on Average Loss

Today’s world is driven by data analytics, not just by big business and marketing firms, but by our own demand in our daily lives, from workout stats and footsteps, to resting heart rates and sleep quality. As a self-directed trader, I crave the same analytical ability to analyze and take ownership of my own habits and ultimate performance. However, for a long time I struggled to glean meaningful and actionable feedback from the two traditional sources of measuring performance: overwhelming amounts of individual transaction data, or a single point of comparison from index bench marking.  

While index bench marking can be a valuable tool for comparing personal performance with the market over a specific time, it only depicts relative performance against an index like the S&P 500.  As an active trader, I’m more interested in tracking my own absolute performance: How am I progressing toward my own goals and targets, and what, specifically, can I do to positively impact my results?  

Over the past several years, I’ve discovered ways to convert my own aggregated realized gain/loss data into insightful and actionable feedback. Below, I share some of this feedback and how I’ve used it to consistently exert more control over my trade results.

How efficiently am I turning trading capital into trading profits?

In order to understand what is driving my results, I prefer to break down my performance into the following ratios:

While many traders look at their net gain or loss over a period (total gains minus total losses), fewer consider the ratio of gains to losses and the breakdown of each component. The higher the ratio of total gains to total losses, the greater the “velocity” of capital accumulation.

If my gains are three times my losses, I’m essentially taking three steps “forward” for each step backward. On the other hand, if my gains are only half of my losses, I’ve effectively taken one step forward but two steps backward.

When planning a trade, this would be referred to as a risk/reward ratio for the trade – how much I’m willing to risk in losses (“backward steps”), for the chance of reaching my profit target (potential steps forward). The gain/loss ratio provides a historical look at realized risk (historical losses) and realized reward (historical gains).

What factors impact my Gain/Loss ratio?

Let’s examine the component ratios of the equation above. The first ratio is the number of profitable trades (net result > $0) to unprofitable trades (net result ≤ $0). As a self-directed trader, the decision to enter a trade in the first place should be the result of research, analysis, and planning on the part of the trader. Did I assess the corporate, fundamental, and/or technical conditions accurately?

Did I identify the profit potential, risk factors, and timing considerations appropriately? These, along with many external factors, beyond my control, can determine the initial trade direction. Therefore, I think of the first ratio, the sheer number of profitable and unprofitable trades, as generally (though not entirely) attributable to Entry:

I consider it a general reflection of how effectively I’m executing my pre-trade strategy – screening, analyzing and setting up potential trades – with the recognition that unpredictable events will sometimes affect the ultimate outcome. The key here is to focus on the day-to-day habits, so that the occasional, unpredictable events have less impact on overall, longer-term results.

The other ratio, composed of average gain and average loss, reflects the magnitude of the ultimate outcome, and I therefore attribute it primarily to Exit – how effectively I’ve managed and closed out the positions:

Did I execute my exit strategy as planned? If the trade was profitable, what influenced my decision to exit? If I incurred a loss, was it within my planned risk parameters, or did I hold on to it too long, letting emotions interfere with my exit plan? This figure considers an average based on total gains and losses, rather than specific trades, so I can focus on my overall habits over a time period, rather than individual results.

I like to think of the average gain/loss ratio as an historical “coverage” factor. Gains are great, until a loss comes in and wipes them out. On average, how many average losses was I able to tolerate before it wiped out one of my average gains? For example, if I had an average gain of $1200 and an average loss of $600, I was able to have two losing trades for every one winner, based on my past performance.

Although I cannot control whether a stock price will rise high enough to reach any profit target I may set, I can control how low I let the price go or retrace, before closing the trade and moving on to the next opportunity. This aspect of trading makes average gain a bit tougher to control; as a self-directed trader, I would rather focus on elements I can more easily control, such as average loss, and exert my influence there.

Though at first it might seem pessimistic, focusing on average loss per trade can provide a host of actionable insights and opportunities for improving overall performance

Here are three reasons this irksome little guy transformed my entire trading existence:

Reason #1:  It’s highly controllable

The Average Loss figure is the single most controllable factor in the above equation. Consider this:

You can do all of the screening, fundamental, corporate, and technical analysis in the world before you place your trade; however, once the order is executed, the initial direction of the trade includes a fair amount of chance. There are inherent risks in the market we have little influence or control over, from geopolitical or government risks, to sudden environmental catastrophes; unpredictable events can and do impact stock prices. Sometimes we can manage to salvage small profits when we sense a change in direction, and keep them from turning into small losses, but even that is more a mixture of talent, chance, and timing.

If you subscribe to the notion of letting profits run and cutting losses short, it is unlikely that you would want to proactively limit the profit potential on a stock moving in your favor, before changing conditions warrant a partial or complete exit. If that is the case, it may not be in your best interest to try to exert too much control over the upper potential of a profitable trade. If you do use profit exits, you could effectively enforce a profit “ceiling” by closing out once price reaches a certain point, but you still cannot control whether the price will ever actually reach that price level. A small profit may end up remaining a small profit (or become a small loss).

That brings us to average loss. It’s highly controllable because, while no one can predict how high a stock price can actually go, we can control how low we allow the price to fall, before closing out the position and moving on to the next potential opportunity. You can also set a retracement plan to preserve profits when favorable conditions begin to change, which some traders do automatically using trailing stops.

Reason #2: It takes away some of the pressure to be right

Another way to interpret the average gain/average loss ratio is to look at how much of an average gain is wiped out by one of your average losses. Suppose I’ve placed 19 trades, as follows:

For comparison’s sake, here is the same performance expressed in equation form:

Looking at it this way, I can see that an average loss of $154.50 (1700 ÷ 11) wiped out a whopping 88% of one of my $175 (1400 ÷ 8) average gains.

In contrast, consider the following tweak and its impact to the equation:

Notice the only thing that changed in the second equation was a reduction of the average loss to $100 per trade. In this scenario, each average loss only wiped out 57% of an average gain, allowing almost two losses before an average gain was wiped out.

By proactively cutting off my losses before they hit my existing average loss amount, I was able to positively impact my overall equation, all else being equal.

The goal isn’t zero loss or risk; rather, the goal is to manage risk such that it’s a fraction of the potential gain. Since I’m looking at my past performance here, which is of course no guarantee of future performance, I simply use my current average gain figure as a guideline, and adjust my average loss target to be a fraction of whatever my average gain is (perhaps a half, or third, whatever makes sense for my own risk tolerance).

Reason #3: It feels awesome.

The figures in the example above were not made up – these were my own results from a continuous set of trades. Before I began tracking my performance, I thought I’d been doing pretty well; I had some good trades, some bad ones, but didn’t realize how much of a treadmill I was on – making trades, but not converting capital into profits.

In retrospect, I had two bad habits that were contributing to this result:

1. I’d hurry up and close out profitable trades to try to “lock in” even a modest profit, just to call it a win. This was fear talking, specifically, the fear of being wrong. As a result, I was focused on the quantity of profitable trades, rather than the quality of the gain.

2. I’d hang on to unprofitable trades longer than I should, simply hoping to recoup some of the loss (which occasionally paid off, but often didn’t). This was greed talking: I didn’t want to sell at the current, lower price; I wanted to get back up to the higher breakeven price to save myself from “having been wrong.”

By simply exiting each losing trade before it reached my average loss ($154.50), I noticed an immediate improvement in the overall equation. I was exerting proactive control to decrease the denominator (average loss), thereby lowering its overall impact on my overall results.

The simple practice of consistently closing unprofitable trades for smaller losses (using my average loss amount as a guide) empowered me to feel more in control of my trading results. There are sectors and stocks that will outperform or underperform their benchmarks, but it’s how we manage our trades that will determine the ultimate impact of the trade on the bottom line. I share my more recent 6-month results below – notice that I still am not over 50% on the number of profitable trades.

I did, however, create much higher quality gains, compared with my losses. I was able to focus my energy on screening and technical analysis techniques, and less energy waiting around on stagnant or lagging trades.

Ultimately, regardless of how much research you do upfront, and which trades you choose to take on, one thing you can absolutely count on is that the markets will do what they will. Have a plan for managing profits and taking losses, and stick with it; keep your eye on your trading goals, and try not to let emotions get in the way.

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Schwab does not recommend technical analysis as a sole means of investment research.

Past performance is no guarantee of future results.

The information provided here is for general informational purposes only and should not be considered an individualized recommendation or personalized investment advice. The investment strategies mentioned here may not be suitable for everyone. Each investor needs to review an investment strategy for his or her own particular situation before making any investment decision. Commissions, taxes and transaction costs are not included in the examples used in this discussion, but can affect final outcome and should be considered.

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