See the press release at the link below for the full announcement:
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.
Updated June 03, 2009…this promotion has ended. Congratulations to Mike T. — the winner of the drawing for a free subscription to BackTesting Report. You can still get the chapter and more in the MACD Buy Signals BackTesting Report.
This chapter is for you if…
You’re not clear on the distinction between the common MACD Histogram and Appel’s Histogram. Don’t worry, you’re not alone. The two different ways of plotting the MACD Histogram confused many people, even experts — see earlier posts for a few examples.
You just want to brush up on the MACD, how its plotted and what signals it gives.
You want to see a little bit of what’s inside a BackTesting Report. The MACD Buy Signals Report sells for $37 but this chapter is yours free.
Enter Drawing to Win a 12-Issue Subscription to BackTesting Report
After you download and read the free chapter of the report above, leave a comment on this post to enter the drawing. If you’ve never commented on a blog before, you just click the comment link at the top of this post and scroll to the bottom to find a form to enter your comment.
On June 3, 2009 at the LA Trader’s Expo, I’ll randomly select a comment and that person will receive a 12-issue subscription to BackTesting Report, a $127 value. You do need to download the report to enter because comment spam is so prevalent that we have to cross-check the comments with the mailing list.You don’t need to be at the Trader’s Expo to win.
(Updated from 5/11 and reposted on 5/15 due to technical difficulties. If you sent a comment before 5/15, please resend.)
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Do you use the MACD indicator or MACD Histogram?
Or follow an expert who does?
If you answered “yes”, you may be leaving money on the table without even knowing it. The most recent BackTestingReport uncovered two mistakes that even experts make with the MACD and MACD Histogram.
After independently researching the report, I sent it to the inventor of MACD, Gerald Appel. Here’s what he said:
“You do seem to have come pretty much to the same conclusions that our research staff has. Most of what you see regarding MACD was arrived at before 1990 by which time I was already advising audiences not to await crossings.”
Mr. Appel is the president of Signalert with hundreds of millions in assets under management, and he has a research staff. If you don’t have quite those resources – or even if you do – you might consider a small investment in an easy-to-read research report.
When you read the MACD Buy Signals Report, you will get an idea how much it cost US stock market participants who waited for MACD lines to cross before buying a stock. Not only that, you will be clued in to a second costly mistake, this time with the MACD Histogram. This one is so widespread, you’ll run into it even on Yahoo Finance charts.
Finally, you get critical data to decide how best to use MACD for your own gain.
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.
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.
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.
Today was an excruciatingly down day in the US stock markets, and me with a new BackTesting Report package on moving average buy signals. The package is a great deal and chock-full of useful information, yet I felt like I had to ask myself whether this was the right time to bring it to market.
But when I reflect on the situation, I quickly realize that I expect to see buy signals of one form or another from my market scans before I see more sell signals. Here’s why:
- Long trades with stops have already been stopped out.
- Long trades without stops (very long-term holdings) are too weak to sell now.
- Short trades are already initiated.
- The market has been falling for 3 weeks, making new short signals unlikely.
In summary, I’m not expecting any fresh sell signals. However, when the market stablizes I’ll be on the look-out for two types of buy signals:
- Cover shorts
- Initiate new long trades
That and I take the lesson from the great ones such as Warren Buffet, Jesse Livermore, Baron Rothschild, and the rest who indicate that success comes from buying when others are selling, being greedy when the masses are fearful. Tempered with patience to avoid falling knives!
So even though its a rare stock that has any sort of a moving average buy signal today, its not such a bad day to be thinking about strategies for the next buying opportunity. Maybe its a good day to read reports about buy signals after all.
Definitely as good a day as any to ask yourself if you have an objective way to figure out what to do in the market without getting carried away by the emotions of the crowd.
BackTesting Report helps you make rational investment and trading choices by giving you the results of rigorous testing of popular technical strategies. It gives you the data without all the effort of backtesting yourself.
Excerpts from the report:
“Establishing a baseline of market behavior helps you tell if a strategy is doing well for good reason or if it’s just plain lucky. For example, it may initially sound great to have an entry strategy that wins 55% of the time. But if our baseline test wins 60% of the time, that entry doesn’t look so good anymore. Likewise, a win rate of 30% might not sound like much, until you learn that the baseline was 25%! The baseline sets the standard for performance. This issue is about entry baselines and it focuses on the win rate more than the other statistics.”
“This report establishes the baseline for comparison with all other trading strategies. This is a crucial step because you need a way to tell if a strategy did well when the market just happened to pull it along, or if the strategy really does signal timely entries and exits. A good baseline shows what happens in the absence of a strategy. Rather than exercise judgment on when to enter, the baseline strategy always enters when it doesn’t have a position and likewise, always exits after a pre-defined number of days.”
Please share this report as you wish. You can email it, link to it, reprint it, or blog about it. Please also include a link back to www.backtestingreport.com and drop me a line so I can publish a link back to you. Thanks!
The actual link to the document is http://www.backtestingreport.com/BackTestingReportBaseline.pdf
(This post and the associated document are licensed this under the Creative Commons License, Attribution 3.0. http://creativecommons.org/licenses/by/3.0/us/ . I am the majority shareholder of Own Mountain Trading Company, the publisher of BackTesting Report. )
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