The Percentage Trailing Stop is one way to limit losses and protect profits.  A stop loss order is set a given percentage away from the current price.    As the price moves in the trader’s favor, the stop rachets along with, never giving ground once its protected by the stop.   For example, after buying long, a trader may set a trailing stop 7% below the current price.   As the price moves up, the trader moves up the stop but never moves it down when the price goes down.   Eventually the price does retrace the 7%, the stop is hit, and the trade exits.

Extra Insight:

In backtesting, the same percentage value is applied to all stocks.   This is not ideal because each stock has a different daily price range — some will routinely move 3% in a day while others barely budge.    The percentage trailing stop adapts to the individual stock better than the dollar trailing stop but not as well as the ATR trailing stop.  

As with all trailing stops, the percentage trail never exits at the extreme of a movement.   Hence it always gives back some of the profits.

Click here for BackTesting Reports on Trailing Stops

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Updated 11/12/08.

Tags: exit, long, loss, stop, trading, trailing backtesting

 A Position Trader seeks intermediate-term opportunites.   Like a swing trader, the position trader is ready with a quick exit strategy but more willing to stay with a trade for several weeks or more.   

Extra Insight:  

For backtesting, I use timed 20 day exits to approximate position trading.

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Updated 11/17/08.

Tags: backtesting, exit, position trader, strategy, trading

Productivity refers to how hard your money works under a particular trading strategy.   Both the number of trades and the average hold time impact how efficiently a strategy manages funds.

Extra Insight: 

The number of trades reflects the opportunity to trade.   In general, a higher number is better for a profitable strategy because it means more opportunity to make money.   However, if a strategy is not profitable or breaks even, more trades just means more commissions paid to the broker and more of the trader’s time consumed.  (Even with completely automated trading, a trader still has to deal with record-keeping and other administrative tasks that grow with the number of trades.)

Backtesting short-term strategies over any significant time period generates many more trades than the average trader can afford.    Realistically, traders need to choose which signals to take.   Eventually, I’d like to make the selection criteria part of the backtest so that it can be measured and compared as well.    Right now, my backtesting engine, TradeStation, only tests one stock at a time and cannot simulate a whole portfolio.

All else being equal, the trading strategy with the smallest average hold time is best.   Not all things are equal in practice though.   People may seek out longer or shorter hold times based on their temperment, tax situation, global market views, margin, and a host of other factors.   The average hold time gives insight into which strategies will fit these other requirements.  I also use it to classify different strategies and compare those with similar hold times.

Updated 11/12/08.

Tags: backtesting, hold time, number of trades, productivity, strategy, TradeStation, trading

A trading strategy might have several different types of exits, among them the Profit-Taking Exit.  As the name suggests, the idea is to bag some profits.  Cha-ching!

Extra Insight:

The profit-taking exit won’t necessarily mean selling at the top.  That’s difficult, maybe impossible, to do consistently and its often called a fool’s errand to try.

Some examples of profit-taking exits are price hitting the upper channel boundary or a pre-defined target percentage gain.

Another profit-taking exit is a trailing stop.   A stop (loss) order is put in place below the current price (or above it for a short).   As the stock price moves up, the stop price moves up too.   Different methods of trailing a stop: ATR (average true range), percentage, and fixed dollar to name a few.

I’m just listing a few possibilities here, not suggesting which one to use.

Click here for BackTesting Reports on Exit Strategies

(Backtesting Blog is an Amazon Associate.)

Updated 11/12/08.

Tags: ATR, backtesting, exit, loss, percentage stop, stop, strategy, trading, trailing stop

I previously used Quick Trading as a label for very short-term trading that lasts only a day or two.  I’ve merged this category with swing trading.

Extra Insight:

In my backtesting, the 2day timed exits are most like Quick Trading.

Updated 11/17/08.

Tags: backtesting, day trading, exit, quick in and out, swing trading, trading

The Results Distribution is a graphical way to show the performance of a trading strategy.   The graph above shows the results of backtesting a trading strategy across several thousand stocks over a 3-year period.

Extra Insight:

Let’s take apart a simpler example:

Each trade is assigned to a bin depending on its profit/loss results.   Different people use different measure of results: dollar gain, percent gain, etc.  I use Van Tharp’s R-Multiple which is the gain divided by the amount risked.   I label the bins with the mid-point of the range.  

For example, a trade that gains twice what was risked goes into the “1.5″ bin along with all the other trades that returned between 1 and 2 times the risk amount (R-Multiple).    

The horizontal axis shows each bin and the vertical shows the number of trades in the bin.   The red line is the zero point which separates winning and losing trades.  In some graphs, profitable bins are green and losers red.  

In our example above, we see that 196 trades returned a profit that was less than the amount risked (less than 1 R-Mult) because the bar for the “0.5″ bin is 196 trades high.   Unfortunately for this strategy, even more trades lost money, which we can tell at a glance from this graph.

In general, better strategies have more action to the right of zero on the chart – more profitable trades either in quantity or quality or both!

The Puppetmaster’s article on Redistribution is an excellent illustration comparing the results distributions for two different trading strategies.

Updated 11/12/08.

Tags: backtesting, loss, Puppetmaster, quality, Results Distribution, risk, strategy, trading, Van Tharp

Risk management is crucial because all trading strategies lose sometimes.    By limiting risk, a trader has a chance to survive long enough to find a way to thrive.   The topic is way too big for my little glossary but its here because I want to encourage traders to think about risk.

Extra Insight: 
Funny Carrie Underwood parody reminder to manage risk:

Backtesting trading strategies provides insight into the risk of various trading strategies.   Understanding risk is the first step towards managing it.   A complete understanding includes the knowledge that there’s always the risk of something completely unknown and unforeseen happening.

Different people have different risk tolerance and even the same person will view various risk differently.  That means you have to decide for yourself what to risk.

Here are a few “rules of thumb”:

• Don’t risk more than you can afford to lose.
• Limit the risk on each position.  1% of your trading account risked per stock is a middle-of-the-road estimate.  By risked, I mean the amount lost if the stop is hit.  No stop?  Then limit the size of the whole position to a small fraction of your account.
• Limit the total exposure of your account.   What happens if all your stops get hit?   What happens if the market gaps past all your stops.   Make sure you can handle it.
• “Blowing up” means losing 50% of account value.   Don’t let that happen!

Here’s a link to the book advertised in the video: Mastering the Trade (McGraw-Hill Trader’s Edge).

(Backtesting Blog is an Amazon Associate.)

Updated 11/12/08.

Tags: backtesting, long, management, risk, sizing, stop, strategy, trading

Van Tharp created the concept of R-Multiples which I find useful in evaluating the performance of trading strategies.  Very briefly, an R-Multiple of a trade is the gain divided by the amount risked.  Losses are negative number, profits are positive numbers.

Updated 11/12/08.

Tags: loss, R-Multiple, risk, trading, Van Tharp

A Signal is the specific event that says when to get in or out of a stock. 

Extra Insight:

Some signals are objective, for example price hitting a 52-week high.   Others are more subjective, for example magazine covers depicting emotional extremes can signal the end of a trend.

For backtesting, we need objective signals that can be evaluated by a computer program.

During backtesting, the computer will take every signal promptly. 

A human trader may ignore a signal or delay taking action — particularly if it is painful!  A human trader may also act even in the absence of a signal, buying when they feel like shopping or selling when they feel fearful, regardless of the signals from their trading strategy.   In this case, the profit/loss performance will differ from the backtesting result.

Updated 11/22/08.

Tags: backtesting, loss, selling, signal, trading

Size Matters

Sizing is the rule for deciding how many shares or contracts to buy.

Extra Insight:

Sizing is critical to risk management, worthwhile returns, and also making comparisions between backtesting runs.   For the backtesting runs, I use a very common and straightforward sizing:

• If there is no stop loss for the strategy under test, my backtesting trade size is 1000 shares (and the amount at risk is the total amount of the trade).
• If there is a stop loss, my backtesting trade size is the nominal risk amount of $1000 divided by the distance from the expected entry price to the stop price.   If its a next-day market order then today’s close serves as the expected entry price.   This way, the risk amount is constant for every trade but the trade size varies in both dollar amount and number of shares.

(Backtesting Blog is an Amazon Associate.)

Updated 11/13/08.

Tags: backtesting, expectancy, loss, management, risk, sizing, stop, strategy, trade size, trading