Click to view my Maximum Adverse Excursion video.  

The Maximum Adverse Excursion or MAE is a measure of how far a trade went against you.   Read this previous post for a definition.   BackTesting Reports measures MAE across thousands of trades, allowing you to use it as a metric to assess and compare trading strategies.

Of course the idea is to pick a strategy with a low Maximum Adverse Excursion.   You can also reduce the MAE (and risk) of a strategy by using a stop loss.

Tags: MAE, risk, stop, strategy

If you’ve ever wondered:

• which MACD sell signal has the best track record
• whether to sell when the MACD Histogram ticks down or wait for the lines to cross
• how far positions have dropped after a MACD by signal
• whether stop losses really reduce risk
• whether using an ATR stop is worth the effort

then you might considering investing in a copy of the MACD Sell Signals BackTesting Report.

The MACD Sell Signal Report builds on two of the MACD Buy Signals to backtest basic exit signals using MACD lines and histograms. This report gives the first look at Maximum Adverse Excursion - how far the position went against you — as a way to measure the risk of each strategy.   It also compares three different types of stop losses to reduce risk.   Read this report to find out how you would have fared by following the MACD and MACD Histogram.

 Subscribe to BackTesting Report Now or order MACD Reports separately

Tags: ATR, backtesting, exit, linkedin, MACD, MACD Histogram, MAE, Maximum Adverse Excursion, risk, selling, stop

With a rally coming together over the past week, I want to review two distinct and important elements of the buying process.   Before I jump in, let me say that I don’t claim to know if this is The Time to buy or not.  I do want to give you two steps to consider when making that decision for yourself.   They are:

• Screening for candidate stocks
• Signaling the time to buy (and sell)

This first, stock screens, is more time invariant - a fancy way of saying the list doesn’t change much day to day. In fact, you may not want to change you stock list much year to year as there is a lot to be said for getting to know a handful of stocks inside and out.   If you’re like me, you itch to scan a huge number of stocks to see offer up the best opportunities.   Of course, you can do both.  I have my screeners delivering new stocks every day and I also have my favorites that I’ve gone back to so many times over the years that I am part of the reason support and resistance works because I know from memory what is a low buying price and when to take the money and run.    On the other hand, a decidedly Bad Idea is obsessively returning to a stock on which you lost thinking that it “owes you”.  This is where an objective plan can really save you.

Sit down at a quiet time and think through the things you want in your candidate stocks.    I consider three categories:  practical matters, fundamentals, and technical screens.   Other folks might want to consider social values, or what their friends say, or worldwide demographics.    I have a hard time making the last three objective myself.

On the bare-bones practical side:

•             Volume is a very measurable criterion that is almost pointless to test.   You need enough volume to get in and out.  Period.  I like to see at least 500,000 shares traded per day.
•             Price is another area where it’s very easy to be objective - at least at the extremes.   If you want to be a penny stock trader - great!  Go be the best.   But most people choose $1, $5, or $10 and say it’s as low as they go.  
•             Your risk limits drive a price/volatility limit.   If you risk only 2% of your account per trade (and that’s being generous), you can’t get into any stock with an average true range bigger than that amount.

Do fundamentals matter or is the sum total of available information reflected in the price?   You will have to make your own decision on that, dear reader, because the fundamental data I had at my disposal last I looked was not clean enough to make a good determination.    Even so, I do use fundamentals as a tie-breaker for the times when I get too many signals at once.   Then I’ll take the signals on the stocks with fundamentals (and story) to my liking.  A better way is to refine the objective rules to come up with just the right number of stocks to fit your account.

Technical stock screens are an important component of your plan.  They can and should be tested thoroughly.   First define what you want, say stocks in an uptrend, or beaten down stocks, or stocks trading in a nice range, whichever.  Then figure out which tool from technical analysis delivers the best candidates for your needs.  This means know how well the various technical analysis tools have performed.  This applies whether you are picking the short list of stocks you will grow with for the next couple years, or setting up a daily screen.   If it’s done right, your technical stock screener can give a solid list of candidates.   Remember, the point is not to go out and buy all of these right away, but instead to stalk them for the right time to make your move.

 For example, a moving average can function as a stock screener, where stocks above the moving average are said to be in an up-trend and stocks below the moving average are said to be in a downtrend.   Many experts recommend buying only stocks which are above their moving average, although some will say you can capture more of the move by getting in well below the averages.  Of course the advice varies on which length of moving average and what you use may depend on whether you have a short- or long-term outlook.    Click here to order your copy of the BackTesting Report on moving average stock screens and find out which moving averages have potential and which have not proven out as a stock screener.

 This post talks about screens stocks to build a candidate list that is bigger than you can use at any one time.   The examples — price, volume, above/below moving averages — showed objective, testable tactics that can identify out a candidate list.  But the stock screener doesn’t pinpoint the time to buy.   For that we need a more precise entry signal which I’ll discuss in the next article.

Tags: backtesting, entry strategy, moving average, risk, signal, Strategy Development

A Drawdown is a dip in account value from its highest point.

Wikipedia has a very rigorous definition here.

Extra Insight:

An open drawdown is calculated by taking the current market value of both open and closed positions.

Two tricky things about drawdowns:  knowing how much you can handle, and estimating how much you might be in for.  That’s the key to pick a trading system (strategy and sizing) that doesn’t risk more than you can afford to lose.

During backtesting, keeping track of adverse excursions, or how far winning trades go in the wrong direction can give some insight into potential drawdowns of a trading strategy.  

To be absolutely sure to avoid devastating drawdowns its necessary to limit the amount of money in play.

Each person must define what level is devastating for themselves however 50% loss is often called “blowing up”.

Last updated 11/11/08.

Tags: backtesting, drawdown, loss, risk, sizing, system, trading

Expectancy measures a trading strategy’s profit potential.   It considers both the reliability or win rate as well as the amount gained by each win.    That way, it can compare trading strategies that often win small gains with strategies that rarely win but win big when they do. 

Expectancy = (win_rate * avg_win) - (loss_rate * avg_loss)

Van Tharp defines expectancy in terms of risk here, as the average of the R-multiples returned by trading or backtesting the system.

Extra Insight:

Over a large number of trades, the expectancy is the expected gain of the trading strategy.  Higher expectancy is generally better.  Always avoid trading strategies with negative expectancy.

Scaling the expectancy by risk is indeed useful, especially when it comes time to compare different systems.  I use the R-multiples as suggested by Van Tharp for ease of calculation.

Expectancy is also known as the Kelly Criterion for the Bell Labs researcher who proved the equation as an upper bound on the amount to risk.     A common language way to say it is to risk an amount proportional to the expected gain.   So if the expectancy is 45%, Kelly advocated risking 45% of the account value.   This may be mathematically optimal over a large number of trades but it can have a very vicious drawdown!   Imagine trading a high expectancy system, say 80% and the first trade is a loss.  For a $100k account, that would leave only $20k in the account and a long road to make a 4x gain to break even.

Expectancy is not the be-all and end-all of a trading system.   The standard deviation or variance of the results is important.  The win rate is too.  Both give insight into how psychologically difficult it is to stick to the trading strategy.

Updated: 11/12/08.

Tags: backtesting, expectancy, Kelly criterion, long, R-Multiple, risk, strategy, system, trading, Van Tharp

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

Shorting is simply selling a stock you have borrowed but you haven’t yet bought.   The idea is to sell when the price is high and buy later when the price is lower.    Buying the stock then closes the short trade as the stock is paid back to the lender (usually the broker).  

Details on how to sell short are in Sell and Sell Short by Dr. Alexander Elder.

Extra Insight:

Short selling is more difficult to model for backtesting because not everything is reflected in the price.  Extra rules are imposed by the SEC such as no shorting until the price ticks up.  The SEC recently removed this one.    The stock also needs to be available to short — meaning someone has to be willing to lend out the shares. Often shares are not available when the price is in free fall.   As we see in the current crisis, new rules are created on the fly such as the one-month hiatus on shorting bank shares.  To be super-accurate, a model would need to have different shorting rules for different dates– something that is beyond the scope of most backtesting engines.   The upshot is that backtesting doesn’t model short strategies as well as it does long strategies.

Risk management is more important for short selling because a short seller loses money when the stock rises without limit.   In contrast, a buyer of a stock can only lose as much as they paid for it.

A portion of the proceeds of a short sale are available immediately.   Some traders (and mutual fund managers) will use the proceeds to buy shares of a different stock thus making their money go farther.

(Backtesting Blog is an Amazon Associate.)

Updated 11/12/08.

Tags: backtesting, Elder, long, management, risk, selling, short, strategy

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