Exit Strategies and MACD at MoneyShow Las Vegas Workshops

moneyshow las vegas 2010

Please join me at the Las Vegas Money Show, Tuesday May 11, 2010.

You can learn the past performance of key buy/sell strategies in my two sessions: 
07:45 AM – 08:30 AM   Exit Strategies for Active Investors
Here we focus on SELL strategies including stop losses, profit targets, MACD negative divergences and more.  I’ll present highlights from the Exit Strategies reports which are not recorded anywhere outside this $100 series of reports.  This session is geared towards active investors who like to hold for weeks, months or even years but do plan on selling  stocks someday and want to leverage technical trading skills to pick a good time to get out.   The real bonus for attending live is real-time analysis.   Please bring the tickers of any stocks you are considering selling so we can check exits for them in the session.
 
02:15 PM – 03:00 PM    The Truth About MACD
Highlights from the Truth About MACD series, focusing on BUY signals.  We’ll cover important patterns such as the MACD divergence.    Audience participation is welcome as we check the end-of-day charts for your stocks.
 
Click this link for complimentary registration for you (and spouse) today:

MACD Sell Signals

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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

BackTesting Moving Averages

Why Moving Averages

As a trader or investor, the only reason to investigate moving averages is to gain knowledge to increase profits. Like many other technical indicators, moving averages are meant to help us objectively tell the market status at any given time. This helps us see through the emotions of the day and make rational decisions, which we’re told will lead to greater profits and/or fewer losses over the long run. Moving averages (MAs) smooth the series of prices for a stock. MAs are most often used to identify the trend of market direction, and are classed as a trend-following indicator. This doesn’t mean that MAs are only for long-term investors – short term traders use them also. Moving averages can be used to screen stocks for good candidates, signal buying opportunities, and offer sell signals.

Why Backtest – A Story

The goal of backtesting is to find out if moving averages really do lead to better results and what are the most promising ways to apply MAs. Let me tell you a short story. While I was putting together the results for one of the moving average BackTesting Report issues, I happened to visit a friend. At her house, I came across some reading material from a well-advertised discount stock broker. In it was an article that advising its customers to use a particular moving average length applied in a certain way to get the best results. I had my comprehensive tests right in front of me and I can tell you that broker’s method did not get the best results although they did mention a MA length that is useful in other ways. I had in my hand test results that showed that the way that broker applied the moving average had a win rate worse than the baseline when tested on 7147 stocks over 14 years of stock market data. Clearly the broker wasn’t running that kind of testing. It’s up to the customers – us! – to fend for ourselves and find out what works versus what doesn’t.

How to Calculate MAs

When backtesting moving averages, the first decision is how to calculate the moving average. Do you want a simple moving average (SMA)? Or something designed to track price better such as an exponential moving average (EMA)? You might consider an experiment to compare the win rates of the two different averages. I did just that a couple years ago, and while I don’t have the results to publish, I came away with the notion that it didn’t make a big difference whether I chose SMA or EMA — just pick one and use it consistently. So for this project, I choose to use simple moving averages because I see them mentioned in commentary most often. To actually do the calculation, I relied on the built-in function which came with TradeStation. (The choice of backtesting engine is another decision which is general enough to write about in another post.)

How to Use MAs

Next you need to pin down how exactly you want to apply moving averages. How will you interpret the relationship between price and moving average? What rules will you use to decide when to buy and sell? You don’t have to read long about stocks before coming across a bullish reference to a stock trading above its 200-day moving average or its 50-day moving average, or even the 10- or 20-day MA. Or advice about buying stocks as they cross their 50-day or 200-day moving average. These are important rules to test in the backtesting engine. And then there’s the moving average crossover – a classic method of technical analysis. That makes three distinct ways of using moving averages to test.

Going more in-depth, some trading texts talk about the slope of a moving average. If you hark back to algebra and consider the MA as a line, to find its slope you would pick two points on the line and apply the usual formula ((x2-x1)/(y2-y1)). This brings up the question of how far apart to pick the two points which can make a difference to results. Really, since the MA is being used to identify the trend, we just want to know if it is sloping up or down. Then we can simplify the whole calculation by noticing that if the price is above the moving average, it must be pulling the average up, and a price below the MA pulls it down. Thus another reason to test the efficacy of price above the moving average.

Parameter settings

Once you decide on how to use the MAs, you need to pick a selection of various lengths to test. Beware of over-optimizing. Somewhere out there is a guy with backtesting results showing 3895% gain or whatever using just the right moving average. Too bad he doesn’t know what MA will produce those results in the future. That said, you need to try more than one length to make sure that your results aren’t a fluke. Stick with defaults settings or the ones you hear about most in the media. Finding the one perfect parameter setting is not going to make you rich. Finding a cluster of good, robust settings just might do you a great deal of good though.

As a practical matter when backtesting allow enough data lag before measuring. All tests must begin measuring at the same place for apples-to-apples comparison among different MA lengths. For example, if you’re testing a 200-day moving average, it will take the first 200-days of data to calculate the first point of that moving average. That means that the first day you could possibly have a signal is 200-days into the data set. To make a fair comparison with, say, the 10-day moving average, you need to make sure not to count any signals from the 10-day moving average before the 200-day is ready to go. Fortunately TradeStation has a way to set the “Maximum number of bars study will reference” in “Properties for All” strategies which forces the backtesting engine to wait that long before tabulating data.

More Profit from Buying or Selling?

Moving average rules, and in particular moving average crossover rules, are often discussed as a reversal system. This means that one signal, say the MAs crossing upwards is a buy signal and then its opposite, say MA lines crossing down, is not only a sell signal but also the trigger to go short. Theoretically, that’s just fine but many people are not interested in shorting the market. They are looking for techniques to help them buy and maybe sell. Even a person who regularly sells and sells short might use different techniques for buying and selling. For these reasons, it’s wise to test the buy signals separately from the sell signals.

This poses a dilemma because it’s hard to evaluate a buy signal in isolation. One way to do this is to use timed exits – that is, exit the trade or sell the stock after a certain amount of time elapses. I chose to run each backtest three times with three different times exits because different people have different styles and different needs. To produce backtesting results useful to swing traders, I exit after 2 days. To model position traders, 20 days. To meet the needs of active investors, backtesting holds each position for 200 days. This gives a way to isolate the buy signals and find out just how useful the moving average is to stock buyers of various temperaments.

Need to Define Goodness

One more very important thing to consider if you are backtesting moving averages to find out how well they do in the stock market: How will you know what is good? You need objective criteria for success. That means identifying the key statistics such as win rate, expectancy, hypothetical equity gains, etc. It also means setting standards for acceptable performance in each of these areas.

An example illustrates why this is important and why it’s not as easy as it first appears. Say your tests show a win rate of 55% for a particular indicator. That may might not be so good if, say, 62% of all stocks went up during the same period of time. Or if only 25% of stocks rose during that time period, your 55% win rate would be spectacular. What is good depends on how it compares to baseline market performance under the same conditions.

You can download a free copy of the BackTesting Report Baseline issue by clicking here.

Test Set

For a meaningful backtest, you need to have enough data to make a statistically valid comparison. At the minimum, that means 30 trades. Even if you are trading just one instrument – just one stock or just one currency pair – I think it’s important to test your trading strategy on many different instruments to prove its robustness. I went over the top with an extremely large test set — 7147 stocks over 14 years — to make sure my results would apply in a wide variety of market conditions.

You can get your copy of my backtesting reports on moving average buy signals by clicking here.

Adverse Excursion Definition

An Adverse Excursion is the amount that a trade goes in the wrong direction after entry and before exit.   The Maximum Adverse Excursion (MAE) is the worst over the life of the trade.

For example, say a stock is bought at $30, then drops to $28 before rising to $38 then settling back to an exit at $35.   The drop to $28 is the adverse excursion.    The Maximum Adverse Excursion (MAE) is then $2.

For more information see Maximum Adverse Excursion: Analyzing Price Fluctuations for Trading Management by John Sweeney.

(Backtesting Blog is an Amazon Associate.)

ATR Trailing Stop Definition

The ATR Trailing Stop is one way to limit losses and protect profits. A stop loss order is set a multiple of the Average True Range (ATR) away from the current stock price. As the price moves in the trade’s favor, the stop rachets along with, always calculated from a better closing prices and never from worse closing prices.    This mostly keeps from giving ground once its protected by the stop, except in the case of increasing volatility as measured by the ATR.

Click here for Back Test Performance of Trailing Stops 

Chuck LeBeau popularized the method of trailing a stop loss order a few ATRs below the recent high price for a long trade. This method became known as the Chandelier Stop.    LeBeau’s Book covers other aspects of ATRs.   The best description of the Chandelier exit is in Come Into My Trading Room: A Complete Guide to Trading by Alexander Elder.

The ATR Trailing Stop is also known as a volatility stop.

Extra Insight:

In backtesting, the ATR Trailing Stop reflects each stock’s unique daily price range.  Hence it can fit each stock better than a dollar trailing stop or even a percentage trailing stop.

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

The ATR stop amount can be subtracted from either the high, the close, or the low of the day.    Each variation gives slightly different results.    The important concept is to match the stop distance to the stock’s volatility and to move it along with improving prices.

ATR stops are not offered by brokers, to my knowledge.   They are also tedious to calculate by hand.   The only realistic way to use an ATR stop is with software support.   Programmable software packages such as TradeStation can be programmed to display (and backtest!) an ATR stop.   

Click here for BackTesting Reports on Trailing Stops

(Backtesting Blog is an Amazon Associate.)

Last updated 11/11/08.

Dollar Trailing Stop Definition

The Dollar Trailing Stop is one way to limit losses and protect profits. A stop loss order is set a given dollar amount away from the current stock price per share. As the price moves in the trade’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 $1 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 $1, the stop is hit, and the trade exits.

Extra Insight:

In backtesting, the same dollar stop value is applied to all stocks. This is not ideal because each stock has a different daily price range.  For example, setting the stop $1 away from the price of a $10 stock makes a fairly wide stop but the same $1 stop on a $100 stock is very tight.

As with all trailing stops, the dollar 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

(Backtesting Blog is an Amazon Associate.)

Last updated 11/11/08.

Exit Strategy Definition

 The Exit Strategy is a well-defined plan specifying the conditions to get out of a trade.  

 For a long trade, exiting means selling the stock. For a short trade, exiting means buying a stock.

Extra Insight:

Having a strategy for exit allows a trader to plan with a cool head rather than getting caught up in the heat of the moment.   Backtesting the exit strategy gives a trader insight and confidence in the plan.

Most traders have two purposes for exiting:  taking profits and cutting losses. 

Sometimes both ends are served by one exit order, such as a trailing stop.    Other times, they are two distinct orders, such as a fixed stop loss and a target limit order.

A third goal of an exit strategy may be the efficient use of capital.    In that case, the exit strategy may have rules to exit a trade that isn’t going anywhere in order to redeploy the resources elsewhere.

Click here for BackTesting Reports on Exit Strategies

(Backtesting Blog is an Amazon Associate.)

Updated 11/12/08.

Forward-Testing Definition

Forward-testing, means trading a strategy live with very small size to see how well the strategy (and the trader!) perform in real life.   

Forward-testing is typically done after backtesting to make sure the trading strategy is not the over-optimized result of curve-fitting or data mining.  It also gives a chance to try out the mechanics of entering, tracking and exiting trades.

Extra Insight:

I’ve heard varying advice on the size of trades for forward-testing ranging from smallest possible size – think 1 share – up to just enough to engage the trader’s emotions.

For more insight into this topic, Design, Testing, and Optimization of Trading Systemscomes highly recommended.

(Backtesting Blog is an Amazon Associate.)

Updated: 11/12/08.

Market-on-Close Definition

Market on Close (MOC) order is entered before the market closes and the transaction takes place at the day’s closing price.  

The US stock exchanges process these orders.  Check with your broker for exact instructions on how to enter them.

Extra Insight:

Due to using historical end-of-day data, a “this bar at close” order in backtesting behaves similar to a Market-on-Close order because it takes today’s closing price.   A key difference is that the backtest actually “sees” the closing price before placing the order.   I wish I could do that in real life!

I use the MOC or “this bar at close” order in backtesting only for timed exits because the decision to exit in this case doesn’t depend on the closing price, only the number of days in the trade.

For large orders in thinly traded markets, a live market order might move the live market, resulting in a different closing price than would have occurred without the order — an effect that’s not modeled with historical end-of-day data.

Read a professional’s report here that live MOC orders often execute at the published closing prices.

A small private trader is unlikely to move a large liquid market.   By sticking to high volume stocks, its not only possible to backtest market orders, its also possible to understand more about the differences between market orders and limit orders via backtesting.

Updated: 11/12/08.

Naming Convention Definition

My trading strategies follow this Naming Convention:

[Direction]_Entry_TestPeriod_[Dataset]_Exit

where:

  • Direction is either L for buying long or S for selling short.   Direction is optional and if missing defaults to L.
  • Entry indicates the entry strategy used.
  • TestPeriod is the abbreviated years of the test data.   The data runs from May to April.  So 0407 means May 1, 2004 to April 30, 2007.
  • Dataset indicates the data vendor.   It is optional and defaults to CSI Data if not used.
  • Exit indicates the exit strategy used.

If one of the above field’s parameters are varied during the test, the exact settings for the run are shown next to it.   If settings are not given, then the commonly used settings apply.

For example, L_All_9404_CSI_Timed_200day

  • Trades Long (enters by buying stock)
  • Enter always
  • Spans the time period  May 1, 1994 – April 30, 2004
  • Runs on CSI Data
  • Exits on a specific time setting of 200 days

Another example, MACDH_0407_ATR3

  • Trades Long (enters by buying stock)
  • Enter when MACDH ticks up, settings 12, 26, 9
  • Spans the time period  May 1, 2004 – April 30, 2007
  • Runs on CSI Data
  • Exits on a trailing ATR stop of 3

Updated 11/12/08.