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

StdDev is an abbreviation for Standard Deviation – a widely used mathematical formula.   The Wikipedia entry contains a section on finance about halfway down.   In one sentence, StdDev gives an idea how much the trade results vary and a smaller StdDev is generally better.

Extra Insight:

In the backtesting results, I apply the Excel formula Stdev.

Smaller standard deviations generally make for  better trading strategies, provided the strategy also has a positive expectancy to indicate potential profits.

Updated 11/13/08.

Tags: backtesting, expectancy, indicator, risk, standard deviation, strategy, trading

A Swing Trader tries to capitalize on short-term price movements.  A swing trader will hold overnight, possibly for several days, which distinquishes swing trading from daytrading.   Of course some exit strategies are open-ended so the trade may last as long as the stock is running.  After backtesting a few we can see the average hold time for the different trading strategies and settings.

Extra Insight:

In my backtesting, the 2day timed exits apply to Swing Trading.   At that point, its clear if the entry strategy has the trade off to a good start.

Swing Trading Books at Amazon

(Backtesting Blog is an Amazon Associate.)

Updated 11/17/08.

Tags: backtesting, day, entry, exit, long, strategy, swing trader, trading

TradeStation Strategy

A Trading Strategy is the collection of rules about when to enter and exit trades as well as the size of each trade.

Extra Insight:

Sometimes people say “trading system” instead and I do it too.   I really think trading system is larger than just the entry/exit strategies and includes things like record keeping, etc.

TradeStation is a software tool for analysis and backtesting with facilities for creating custom trading strategies.    The image at the top of this article is a screen shot of a very simple entry strategy that buys whenever the stock meets minimum volume requirements.    This obviously is not a tradeable strategy but is something I use as a baseline for comparison.

Updated 11/13/08.

Tags: backtesting, entry, exit, sizing, strategy, system, TradeStation, trading

Trading System refers to the whole set of rules, practices, and habits that make up the process of trading.    This includes market selection, portfolio selection, when to trade, which trading strategies to use when, entry signals, exit signals,  sizing, record-keeping, risk management.   The whole enchillada.

Extra Insight:

Even though I often use the terms interchangably, I think Trading System is bigger than Trading Strategy.

A Trading System is said to be either mechanical, discretionary, or a mixture of the two. 

Most mechanical systems are run by a computer, but they need not be.  A person could conceivably make manual calculations and monitor trades according to rigid rules.   Even in a fully automated mechanical system, the human element is present — someone must decide which system, when to turn it on, how to keep the computers running, etc.   However, backtesting is an obvious step in the development of a mechanical trading system. 

For discretionary traders, modern trading also relies on computers acting according to fixed rules.  For example, many people, wheither they consider themselves traders or investors, fundamental or technical, consult stock charts populated with their favorite analysis techniques and indicators.   Backtesting can inform the judgement of a discretionary trader by outlining the potential performance of various strategies and indicators.

Ed Seykota often says that a trader’s system is really the set of emotions he/she is unwilling to feel.  (See Sat, 17 July 2004 in his Trading Tribe FAQ).   I feel like dodging by saying the emotional side is beyond the scope of this blog.  

Now that I think about it, its not so hard to backtest a general example with software.    For example, the Rational Choice book cites a few studies that prove our human tendency for loss aversion.  To codify that, write a system with: 

• no stops in order to avoid the pain of taking a known loss,
• close targets to avoid the pain of giving profits back, and
• quick file deletion to avoid the pain of knowing its unprofitable. 

(Backtesting Blog is an Amazon Associate.)

Updated 11/13/08.

Tags: backtesting, behavioral finance, discretionary s, Ed Seykota, entry, exit, indicator, loss, mechanical s, Rational Choice, risk, signal, sizing, strategy, system, technical, trading