OWN MOUNTAIN TRADING COMPANY PRESENTS · 2012. 9. 19. · To implement a “Power Tools” strategy for trading divergences, the buy signal depends on the market trend as defined

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OWN MOUNTAIN TRADING COMPANY PRESENTS

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Contents

Contents ...................................................................................................................................... 2

Letter from the Editor ................................................................................................................. 3

The Strategy Evaluation Process ................................................................................................. 4

Strategy Under Test .................................................................................................................... 5

Basic Strategies Tested ........................................................................................................... 5

Backtesting Results – Entry Testing .......................................................................................... 12

Active Investors with 200-Day Timed Exit ............................................................................ 12

Position Traders with 20-Day Timed Exit .............................................................................. 12

Swing Traders with 2-Day Timed Exit ................................................................................... 13

Table of Results for Entry Testing ......................................................................................... 14

Exit Testing Results ................................................................................................................... 15

Win Rates with Real Exits ...................................................................................................... 17

Expectancy ............................................................................................................................ 19

Risk as Measured by MAE ..................................................................................................... 21

Select R-Multiple Distributions ............................................................................................. 23

Conclusions ............................................................................................................................... 26

How to Apply This Strategy ................................................................................................... 26

Resources .................................................................................................................................. 27

Understanding Technical Indicators Made Easy with BackTesting Report .............................. 28

Bibliography .......................................................................................................................... 30

Software ................................................................................................................................ 30

Web Sites .............................................................................................................................. 30

Disclaimer .................................................................................................................................. 31

This report builds upon Issue1. Reading it first is highly recommended.

Download Issue1 – Baseline (it’s free) from http://www.backtestingreport.com/BackTestingReportBaseline.pdf

BackTesting Reports about MACD:

Anticipating the Cross with MACD Buy Signals Catching the Wiggles with MACD Sell Signals The Missing Link with Moving Averages and MACD Finding Big Bottoms with MACD Divergences

HYPOTHETICAL OR SIMULATED PERFORMANCE RESULTS HAVE CERTAIN LIMITATIONS. UNLIKE AN ACTUAL PERFORMANCE RECORD, SIMULATED RESULTS DO NOT REPRESENT ACTUAL TRADING. ALSO, SINCE THE TRADES HAVE NOT BEEN EXECUTED, THE RESULTS MAY HAVE UNDER-OR-OVER COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY. SIMULATED TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFIT OR LOSSES SIMILAR TO THOSE SHOWN.

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Letter from the Editor July 2009 Dear Reader- I have a confession to make: In the course of writing BackTesting Report this spring I became thoroughly obsessed with the MACD. Not that I was a stranger to it to begin with, I have traded MACDH divergences for years. Now with months of detailed research I feel like a photographer who wants to take just the right shot to reveal the heart of my subject. This issue of BackTesting Report focuses on the best of the MACD – the divergences between price and indicator. In truly obsessive fashion, the pages below take apart the MACD divergence, trying it with lines and histogram, standard settings and slow, and a smattering of exits. Even though I had hoped to find the one best way to use MACD, in this issue you will find several good strategies along with data-backed criteria to help you choose the way to apply MACD that appeals most to you. Along the way, I point out a few pitfalls to avoid as well. In his Master’s Class, Gerald Appel, the inventor of the MACD, gives several examples of waiting for a negative divergence to sell. What he doesn’t tell you, but what is laid out in this report – is “Here are the rewards if you do wait for a divergence signal.” I’ve got to admit, in my own trading, I understood the concept rationally but didn’t always wait for the bearish divergences to sell. It always seemed scary as the price fell away from a high and as the MACDH started ticking down – I was out of there. Even coding up the bearish divergence strategies I was shaking my head believing they wouldn’t turn out and thinking up alternate exits to test. Boy, was I surprised! Looking at these backtesting results and also the more recent stock market behavior has renewed my excitement about MACD divergences. See the companion software installation instructions for examples of more recent successes with MACD bullish and bearish divergences. I’ll be setting up forward testing and taking steps to use this data to improve my own trading routines. All in all, this report and the whole series on MACD should give you an arsenal of tools to build your own trading or investment strategies. Self-discipline not included. Sincerely, Jackie Ann Patterson

Editor, BackTesting Report Director, Own Mountain Trading Company

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The Strategy Evaluation Process

You’ll find background information about how to use this report in the grey boxes. Generally it doesn’t change much from report to report. The blue words are usually links to the BackTestingBlog online glossary. If you are already familiar with BackTesting Report, just skip ahead to the next section if you wish.

BackTesting Review Backtesting measures the relative performance of a set of trading strategies on historical price data. Since backtesting relies on past data, it makes no guarantees about future performance and can’t say whether a strategy will do as well in the future as it did in the past. However, if a strategy didn’t perform in the past, there’s no reason to believe it will suddenly turn into a winner. It pays to avoid strategies with a losing track record. Although most traders agree that backtesting is useful, many people don’t do it because of the time, expense, and expertise required. Backtesting Report gives you a leg up on the markets without doing all the work yourself.

How to Compare Entry Strategies Picking entry strategies which have win rates above the baseline is a good start. Also use win rate as a hint on the ease of following a system. For example, consider if you can really stick to a trading plan that only wins 10% of the time. Most importantly, remember that win rate alone doesn’t determine if a strategy is profitable – the size of the wins and losses matters, too. How to Compare Exit Strategies Most complete strategies have two types of exit tactics: taking profits and stopping losses. To keep the exploration to a manageable size, first we will compare profit-taking without stops, with the same criteria to sell the stock as to buy the stock. This also gives a fantastic what-if scenario to see what can happen if you run without limiting risk. Next we add a couple different stops losses and compare them both to the stop-less run and to each other. Keep the following criteria in mind while comparing different exit strategies.

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Strategy Under Test

Basic Strategies Tested

Bullish divergences on the MACD Lines and Histogram are said to be some of the “most powerful signals in technical analysis”1. This Report takes aim at that claim, and examines what works and what really doesn’t with MACD bullish divergences. Before diving in, you need to know the moving parts of the MACD, including the different histogram types. For more information, refer to MACD Buy Signals BackTesting Report which has comprehensive explanations. The basic definition of a bullish divergence is when price makes a lower low but the indicator makes a higher low. Likewise a bearish divergence is said to occur when price makes a higher high but the indicator makes a lower high. We look at two different types of divergences in this issue: MACD Histogram and MACD Lines. Indicator divergences are sometimes squirrely and subjective, however, we need an objective definition to do meaningful automated backtests. The algorithms tested in this issue are necessarily approximations of what a human would pick as MACD divergences. Every effort was made to make them close approximations and to err on the side of missing opportunities rather than including bogus signals. When modeling a subjective heuristic applied by human experts, a key question is which expert to model. This report based the definition of MACD Lines on the Power Tools book2 by Gerald Appel and for MACD Histogram the teaching of Dr. Alexander Elder served as a guide. The upshot is that MACD Histogram divergences are required to “break the back of the bear” by crossing up through zero between the MACDH humps of the bullish divergence, whereas no such requirement is placed on divergences of MACD Lines. To get a clear picture of the various strategies at work and observe an example of MACD’s ability to find important market bottoms, see Figure 1 - Figure 8 depicting the 2003 bottom in SPY and how it’s traded by each strategy. As usual we started testing with timed exits. Then we tested with symmetric exit signals of bearish divergences. The screenshots below are of the final steps in the backtesting process – bullish divergence entry strategies with symmetric exit signals of bearish divergences plus average true range (ATR) stops. We skip ahead to the final strategies because that gives more realistic insight into how a person might use them.


MACD Lines Divergences

Figure 1 - MACD Lines Bullish Divergence Buy Signal with sell signal of a bearish divergence of MACD Lines (from TradeStation)

The MACD Lines (MACDL) rise in between the price bottoms of July 2002 and October 2002, forming a positive or bullish divergence marked by green arrows. Likewise, the MACDL declines between price tops of June and Sept 2003, forming a negative or bearish divergence marked by red arrows. Note that in this case, the price continues upward after the strategy exits.

Figure 2 - Closeup of MACD Lines Bullish Divergence (from TradeStation)


Power Tools MACD Lines Divergences

Figure 3 - BackTesting Report interpretation of Power Tools MACD Divergence strategy (from TradeStation)

To implement a “Power Tools” strategy for trading divergences, the buy signal depends on the market trend as defined by the the 50-day Exponential Moving Average (EMA). For buy signals, the slower 19,39,9 MACD settings – shown in the black histogram at the bottom of Figure 3 -- came into play when the price dropped below the 50-day EMA. The standard 12,29,9 MACD settings – green indicator on Figure 3 -- were employed otherwise. This strategy takes profits on bearish divergences of the slower MACD Lines. Readers of Mr. Appel’s book or the MACD Sell Signals BackTesting Report know that the original “Power Tools” strategy also used the 50-day EMA as a stop. However, setting the stop at a fixed multiple of the average true range (ATR) was used instead for consistency with other strategies in this report and also to reduce whipsaws.

MACD Histogram Divergences

The MACD Histogram (MACDH), defined as the difference between the MACD Lines, moves much more quickly than the MACD Lines, and hence provides more signals. Thus the MACDH may better suit the temperament of short term swing traders. In our chosen example in Figure 4, the MACDH divergence catches the same price double bottom as the MACD Lines strategies, plus several more. Unfortunately, for this example, the additional trades didn’t profit but instead whipsawed. From the fact that the last trade did make good by catching the up move from the eventual 2002 market bottom, we can see the value of persistence in re-entering after being repeatedly stopped out.


Figure 4 - MACD Histogram Bullish Divergence Buy Signal with sell signal of a bearish divergence of MACD Histogram (from TradeStation)

Zooming in on the unsuccessful and successful trades in Figure 5 and Figure 6 respectively gives us some hints on how a human discretionary trader might improve on the mechanical strategy applied in the backtest. Subjective variations such as the slope of the MACDH are beyond the scope of this backtest.

Figure 5 - MACDH Bullish Divergence Whipsaws (from TradeStation)


Figure 6 – Close up of successful entry on MACDH Bullish Divergence (from TradeStation)

Contrast the steady and steep price decline in Figure 5 where MACDH got whipsawed with the double bottom in Figure 6 where the MACDH positive divergence did signal a significant buying opportunity. Another interesting feature of Figure 6 is the gap up on the buy day. Recall that our end-of-day strategy detects a signal after hours and schedules a buy on the open the next day. This is the proper way to backtest with end-of-day data because it prevents us from accidently acting on a signal in hindsight and calling it foresight. A live trader with intraday data might get the buy signal in time to act before the close on the same day. While we can’t test this directly, we can and did post-process the results data to estimate the opening gaps.

Additional Exit Testing for MACD Divergences

In practice, some swing traders buy on a bullish MACDH divergence but do not hold until the same stock gets a bearish MACDH divergence. Instead, they wait for the MACDH to rise above zero and then sell the moment the MACDH ticks down. Figure 7 shows this strategy applied to the same 2002-2003 price data on SPY. Notice how the first trade shown is now profitable whereas before (in Figure 4 and Figure 5) it got stopped out. Also notice the quick exit on the Oct’02 entry and how that allows the opportunity to grab another trade at the Mar’03 bullish divergence. This strategy gives no re-entry signal after that and consequently misses most of the 2003 bull run. Remember we now have 20-20 hindsight -- in the gloom of early 2003, a major rise was not so clearly imminent, and a short term trader might have felt contented to have snagged any profit at all.


Figure 7 - MACDH Bullish Divergence buy signal which exits when MACDH on a MACDH downtick above 0 (screenshot of TradeStation)

Figure 8 – Close up of MACDH Bullish Divergence buy signal which exits when MACDH downticks above 0 (screenshot of TradeStation)

In addition to the strategies presented above, two other runs applied more tactics to limit losses in conjunction with ATR stops. It applied to both the basic MACDL and MACDH divergences. Here’s how it works: The value of the MACDL or MACDH is recorded on the day of the buy signal. If the MACD (lines or histogram respectively depending on the strategy) ever violated its value on the day of the buy signal, the position was sold at the next day’s open. In the results tables, these are called the MACD Div Low+3ASym runs.


Backtesting Setup Details Markets: US Stocks and international stocks represented by ADRs on NYSE, AMEX, NASDAQ including delisted tickers. (Click here for stock lists.) Time Periods: May 1994 - April 2008, divided into three samples to prevent over-optimization. May 1994 – April 2004 denoted by darker blue Ten-year period chosen to include major up, down and sideways movements. May 2004 – April 2007 denoted by medium blue Out-of-sample data for the original period. At 3 years, it’s 1/3 as long as original. May 2007 – April 2008 denoted by light blue Current data. It’s 1/3 of the previous sample and is more out-of-sample data. (Click here for background on time period selection.) Direction: Long Only Entry Strategy: Enter any stock with buy signals as described above, and when volume criterion is met (more than 500,000 shares daily). All entries are next day via Market on Open orders.

Exit Strategy: Exit all stocks according to the signals described above. Profit-taking is done next day via Market on Open orders. Stop losses, where applied, are simulated as stop orders which may be executed intraday. This combination doesn’t exactly model a nimble trader who may grab profits from an exit signal early in a day in which those waiting for end-of-day miss out due to a sell-off before the close. It does model end-of-day trading and investment though. Sizing: Where no stops are involved, size is fixed at 1000 shares. With stops, the risk amount was fixed at $1000 and the size computed as the number of shares that would risk $1000 between the anticipated entry and the stop. Backtesting Engine: TradeStation version 8.6, Build 2525 Data Vendor: CSI Data This data set was specially selected for accuracy after extensive testing. (Click here for background on data preparation.)

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Backtesting Results – Entry Testing

Active Investors with 200-Day Timed Exit

As shown in Figure 9, the win rate varies with respect to the baseline for active investors. In more recent years, the MACD Histogram Bullish Divergence entries beat the baseline.

Figure 9 – Active Investors with 200 day exit

Position Traders with 20-Day Timed Exit

The MACD Bullish Divergence strategies edge past the baseline for Position Traders as shown in Figure 10 on the next page. The differences are slight.

57% 62%

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How to Read the Entry Testing Graphs This section emphasizes Win Rate, which is the metric to beat for entry strategies. Three time periods are tested separately to help guard against curve fitting. In the graphs, each set of bars represents the time period indicated on the horizontal axis. They are also shaded differently for each period with 1994-2004 the darkest and 2007 – 2008 the lightest. The blue bars are from BackTesting Report #1 – the baseline for comparison. The other colorful bars are the results from this particular set of tests. See the legend on the graph to map the color to a strategy.

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Figure 10 – Position Traders with 20-day exit

Swing Traders with 2-Day Timed Exit

MACD divergences do not get off to a winning start for swing traders with a 2 day horizon. We can see in the graph below that the test strategies perform below the baseline for all three time periods. However, the swing trading results improve by estimating how many stocks gap up on the buy day. Our strategy is simply buying at the open on the next day after a signal. However a savvy swing trader might check for signals near the end of the day and enter just before the close. While our data gives no insight into the ultimate fate of the gapping trades, it does show that between 5 to 10% of stocks tested significantly gapped up on the day after the buy signal. Catching the opening gap by entering near the close on the signal day could be enough to take the win rates over 50%.

Figure 11 - Swing Traders with 2-day exit

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Table of Results for Entry Testing Table 1 – Table of Results for Entry Testing

MACD Bull Div Entries Productivity Reliability Probability

Name of Strategy Under Test # Trades Avg Hold %Wins Expect StdDev

Active Investors

MACDH Div 1994-2004 200day 7081 189 53.11% 0.13 1.60

MACDL Div 1994-2004 200day 5224 194 51.97% 0.13 1.79

MACDH Div 2004-2007 200day 2198 181 66.20% 0.12 0.44

MACDL Div 2004-2007 200day 1273 198 61.27% 0.09 0.53

MACDH Div 2007-2008 200day 969 126 37.87% -0.08 0.31

MACDL Div 2007-2008 200day 58 183 20.69% -0.25 0.30

Position Traders

MACDH Div 1994-2004 20day 13035 20 54.16% 0.03 0.47

MACDL Div 1994-2004 20day 9431 20 53.91% 0.04 0.54

MACDH Div 2004-2007 20day 3922 20 56.12% 0.01 0.17

MACDL Div 2004-2007 20day 2715 20 56.28% 0.01 0.21

MACDH Div 2007-2008 20day 2069 19 46.40% -0.01 0.17

MACDL Div 2007-2008 20day 1413 20 44.87% -0.01 0.16

Swing Traders

MACDH Div 1994-2004 2day 22850 2 46.53% 0.00 0.12

MACDL Div 1994-2004 2day 14783 2 44.76% 0.00 0.15

MACDH Div 2004-2007 2day 7245 2 47.58% 0.00 0.08

MACDL Div 2004-2007 2day 4304 2 47.54% -0.01 0.10

MACDH Div 2007-2008 2day 4266 2 48.62% 0.00 0.07

MACDL Div 2007-2008 2day 2572 2 46.07% 0.00 0.08

How to Read the Results Table For Entry Testing The table below summarizes the results for all trader types. In general, potentially profitable strategies have a positive expectancy, shown in green. Losing strategies have their negative expectancies colored red. Yellow indicates that the expectancy was slightly positive, but rounded down to zero – indicating caution. Expectancies are a very rough guideline at this stage because we are using timed exits.

Bullish Divergences on MACD Lines and MACD Histogram did not increase the win rate over the baseline with timed exits. To succeed, MACD Bullish must show larger profits on winning trades and smaller losses on losing trades.

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Exit Testing Results

With exit strategies the key criteria are Expectancy and Maximum Adverse Excursion (MAE), described in detail below. The number of trades measured how often the strategy had an opportunity to trade. The average hold time measures how long each trade went on. Between them you can get an idea of how productively each strategy put its funds to use. Keep in mind that the average hold times are just that – an average. Winning trades tended to go on longer while losing trades were often shorter.

How to Read the Results Table For Exit Testing The table below summarizes the backtesting results for the exit testing. In general, potentially profitable strategies have a positive expectancy, shown in green. Losing strategies have their negative expectancies colored red. Yellow indicates that the expectancy was slightly positive, but rounded down to zero – indicating caution. Note that we compare to 20-day timed exits as the closest to the actual hold times of the strategies with real exits.

How to Use Expectancy When testing a real strategy with exits, expectancy becomes more important than win rate. As the name suggests, expectancy guides you in understanding what to expect by giving you the mathematical average result you could expect from each trade. As with any average, results of any single trade will vary but expectancy shows you how they evened out over time. BackTesting Report scales expectancy by the amount risked to make it possible to compare vastly different strategies across a very broad selection of stocks. A positive expectancy means the strategy was profitable in the past. A negative expectancy flags a strategy that lost money during the time period under test and is something to avoid. For example, an expectancy of 0.09 means an average of 9% of the amount risked was returned per trade. If a stop was employed and the position scaled to limit risk, this will be 9% of the total dollar amount between entry price and stop price. With no stop, we assume the entire position was at risk, and in that case a 9% expectancy implies a 9% return, on average per trade. Again this doesn’t mean every trade returns 9%, a big loss and even bigger gain could amount to an average of 9%. Obviously, bigger is better and you should seek the highest expectancy within your risk tolerance. A key question is: how much is enough? Only you can answer that for sure. As a rough guide, the graphs of results are set up to plot any strategy on a color-coded gradient with a red zone for losses, cautionary yellow zone for strategies which demonstrated a very thin edge, and a green zone for those that performed better. In the graphs below, you’ll notice the color scale is shifted such that strategies with expectancies just above zero are coded red because you need more than break-even to show a real-world profit.


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Table 2 - Table of Results for Exit Testing

MACD Bull Div Exits Productivity Reliability Probability

Name of Strategy Under Test # Trades Avg Hold %Wins Expect StdDev

Baseline 1994 - 2004, 20 days 26049 192 57% 0.15 1.11

MACDH Div Sym 1994-2004 6705 195 65.47% 0.10 0.69

MACDL Div Sym 1994-2004 5222 227 64.86% 0.11 0.65

MACDH Div 2ASym 1994-2004 13508 51 26.93% 0.35 2.72

MACDH Div 3ASym 1994-2004 11669 72 37.25% 0.33 2.16

MACDH Div 3ADownT 1994-2004 17089 7 46.11% 0.05 0.69

MACDH Div Low+3ASym 1994-2004 15660 27 37.85% 0.14 1.22

MACDHMA Div 3ASym 1994-2004 1121 47 42.02% 0.28 1.85

MACDLMA Div 3A Sym 1994-2004 835 20 29.46% 0.23 1.56

MACDL Div 2A Sym 1994-2004 9699 55 25.66% 0.43 3.17

MACDL Div 3A Sym 1994-2004 8598 78 35.07% 0.38 2.47

MACDL Div Low+3A Sym 1994-2004 11075 39 24.73% 0.32 2.62

MACDL Div 2APwr Sym 1994-2004 7219 65 23.38% 0.52 3.81


Baseline 2004-2007, 20 days 41980 20 55% 0.01 0.14

MACDH Div Sym 2004-2007 2269 144 75.80% 0.10 0.36

MACDL Div Sym 2004-2007 1788 159 74.94% 0.11 0.49

MACDH Div 2ASym 2004-2007 4343 48 35.02% 0.57 2.61

MACDH Div 3ASym 2004-2007 3650 67 46.88% 0.53 1.95

MACDH Div 3ADownT 2004-2007 5298 7 46.53% 0.03 0.69

MACDH Div Low+3ASym 2004-2007 4928 27 40.10% 0.20 1.22

MACDHMA Div 3ASym 2004-2007 399 47 49.87% 0.36 1.61

MACDLMA Div 3A Sym 2004-2007 342 18 27.78% 0.04 1.04

MACDL Div 2A Sym 2004-2007 3023 52 34.77% 0.68 3.05

MACDL Div 3A Sym 2004-2007 2628 72 46.00% 0.70 4.91

MACDL Div Low+3A Sym 2004-2007 3310 45 35.29% 0.42 3.13



Baseline 2007-2008, 20 days 12597 20 44% -0.02 0.13

MACDH Div Sym 2007-2008 1030 112 42.43% -0.07 0.30

MACDL Div Sym 2007-2008 872 103 42.43% -0.07 0.26

MACDH Div 2ASym 2007-2008 2540 26 22.32% -0.32 1.52

MACDH Div 3ASym 2007-2008 2230 38 29.87% -0.29 1.25

MACDH Div 3ADownT 2007-2008 3028 7 43.96% -0.05 0.67

MACDH Div Low+3ASym 2007-2008 2872 18 29.46% -0.16 0.86

MACDHMA Div 3ASym 2007-2008 121 44 35.54% -0.20 1.68

MACDLMA Div 3A Sym 2007-2008 86 13 22.09% -0.15 1.50

MACDL Div 2A Sym 2007-2008 1834 25 23.06% -0.31 1.55

MACDL Div 3A Sym 2007-2008 1596 35 30.01% -0.29 1.25

MACDL Div Low+3A Sym 2007-2008 2014 23 24.28% -0.20 1.00

MACDL Div 2APwr Sym 2007-2008 1377 25 23.67% -0.29 1.54

MACDL Div 3APwr Sym 2007-2008 1226 35 30.51% -0.28 1.24

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Win Rates with Real Exits

Figure 12

Graphs of win rates for strategies with exits are shown in Figure 12 - Figure 14. With 13 strategies under test, the graphs get a little crowded. The data label closest to and even touching each triangle identifies the strategy by name. Each data point is presented in the same order left to right as in the data table top to bottom. Interestingly enough, the fully symmetric strategies which buy on a bullish divergence and sell on the next bearish divergence without any stop loss actually beat the baseline. Glancing at Table 2 tells us that the hold times for these fully symmetric strategies were far longer than the others and longer than our chosen baseline for this test – the 20-day timed exit. Let’s reserve final judgment on each strategy until we see the expectancy and risk factors in the sections below.

Baseline

MACDH Symmetric

MACDL Symmetric

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Adding real exits of course changes the win rates for each strategy. While win rate is not as important as expectancy, we still want to know if a strategy wins often enough to hold our attention and not decimate our accounts with losses before the winner finally arrives. It’s not surprising to note that the win rate decreases with the addition of stops. Nor is it particularly cause for alarm. Adding a stop will always reduce the win rate because some trades got stopped out that would have turned around and later become winners. We’ll miss those but that’s okay.


Figure 13

Figure 14

Baseline

MACDH Symmetric

MACDL Symmetric

MACDH, 2ATR Stop

MACDH, 3ATR Stop


MACDH Low +

3ATR Stop


MACDL 200-d MA 3ATR Stop

MACDL 2ATR Stop

MACDL 3ATR Stop

MACDL Low +

3ATR Stop

MACDL Pwr 2ATR Stop

MACDL Pwr 3ATR Stop

15.0%

25.0%

35.0%

45.0%

55.0%

65.0%

75.0%

85.0%

Win

Rat

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MACD Bull Div with Exits 2004-2007

BaselineStrategy

Baseline

MACDH Symmetric

MACDL Symmetric

MACDH, 2ATR Stop


MACDH, 3ATR Stop

MACDH Low +

3ATR Stop



MACDL 2ATR Stop

MACDL 3ATR Stop MACDL

Low + 3ATR Stop

MACDL Pwr 2ATR Stop

MACDL Pwr 3ATR Stop

15.0%

25.0%

35.0%

45.0%

55.0%

65.0%

Win

Rat

e

MACD Bull Div with Exits 2007-2008

BaselineStrategy


Expectancy

Figure 15 – Expectancy of MACD Divergence Strategies

How to Read the Expectancy Graph The colorful graph above plots the expectancy for all of the exit strategies under test plus the baseline. Each strategy occupies one space along the horizontal axis and is in the same order as in the data table. All the data for one strategy is aligned in a vertical column. As shown in the legend, each time period has a particular shape to identify its data point. For example, 1994-2004 is denoted with a diamond. If a shape is not visible, it is hiding behind a larger shape which had roughly the same value. The vertical axis displays the expectancy. Negative expectancies (unprofitable) are color-coded red. Notice that the red extends above the zero line. That is not an accident. A strategy that comes out marginally positive in hypothetical backtesting is unlikely to be profitable in real situations. The colors gently fade to yellow to indicate caution. Then they go on to green to signify strategies that were more profitable in backtesting and have a chance at real-world profitability. As the data points spread apart from the zero line, they reveal that increasing risk goes with increasing returns. It’s relatively easy to find rules and leverage that increases the expectancy in good times but it usually comes at the expense of a greater negative expectancy when conditions deteriorate. Look for strategies that go further into the green zone and less into the red zone than others.

Baseline MACDH

Symmetric

MACDL Symmetric

MACDH, 2ATR Stop

MACDH, 3ATR Stop


MACDH Low +

3ATR Stop



MACDL, 2ATR Stop

MACDL 3ATR Stop

MACDL Low +

3ATR Stop

MACDL Pwr 2ATR Stop

MACDL Pwr 3ATR Stop

-0.40

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Exp

ect

ancy

Strategy

MACD Bullish Divergence with Exits 1994-2004

2004-2007

2007-2008


In Figure 15 the expectancies illuminate the differences between the strategies tested:

Trading on divergences brought outstanding profits in good times (note the 1994 – 2004 and 2004-2007 markers solidly in the green zone)

The same strategies brought losses in the tough years (2007-2008), although less.

MACDL got more green than MACDH for the same red zone behavior. The Power Tools with the longer average hold time hit the highest expectancy of all. When deciding between the MACDH and MACDL however, consider also the Standard Deviation. It is lower for MACDH meaning less violent equity swings which might be easier to stomach.

Applying the 200-day MA to the MACDL unexpectedly hurt results (possibly because a stock trading above its 200-day MA is not at bottom – it either has further to go down, or if the price is already climbing above the 200-day MA, the double bottom signaled by a MACDL divergence already happened while the price was under the 200-day MA and so got filtered out.)

Exiting on the first MACDH downtick above zero succeeded in limiting losses during the tough years, however it also severely limited profits in good times. This strategy did take the most trades with the shortest average hold time which signals productive use of account equity. But its slight edge of 0.05 expectancy leaves no margin for error, slippage or even full-priced commissions.

Curiously, the 3ATR stop did slightly less poorly in the 2007-2008 timeframe than the tighter 2 ATR stop. This held true for both the MACDH and MACDL suggesting that at some point tighter stops possibly bring more losses by getting caught up in the noise and not allowing the stock enough room to move. Or this may be related to the sizing algorithm – see the MAE section for more details on that.

The Low+3 tactic reduced tough year losses while still retaining solid green zone profits. It consisted of monitoring the MACD Lines or Histogram value throughout the life of the trade and exiting if that value was violated.

Effects on Expectancy of Limiting Risk with Stops and Sizing The baseline strategy as well as the symmetric strategies without stops produced results clustered around the breakeven point. With stops, the difference in expectancies between the time periods is accentuated. Clearly the profits in good times make a nice positive jump. The negative expectancies (losses) in 2007-2008 also become more extreme as stops are added. The extreme jump is largely an effect of the change in sizing and risk calculations. It illustrates how reducing your risk can improve profits when the right strategy is employed for the market conditions. However adding stops is not a panacea for a mismatch between strategy and market conditions as shown by the losses in 2007-2008


Risk as Measured by MAE

In all cases, using symmetric exits – bearish divergences -- without stops gave a worse max MAE than the baseline. See Table 3 below. Keep in mind that the 20-day timed exit baseline was chosen because it was closer to the average hold times of the majority of strategies. The majority of strategies employ stops and so have shorter average hold times than the symmetric exits. It’s not entirely fair to compare a 20-day hold time with the 100- to 200- day hold time of the symmetric MACD divergence strategies and that is at least partially responsible for the outsized MAEs on the strategies without stops. Being without stops no doubt contributes. Rather unexpectedly, the 2 ATR stop on the Power Tools run had a worse MAE than the 3 ATR stop. One would think that a wider stop would necessarily lead to a worse MAE. In this case what happened was that they both had the same trade – buy signal on STEM at 11/21/07. Both trades wound up being stopped out when price couldn’t follow through after a strong gap up opened for a buy price higher than expected. The difference between the two stop values was in the sizing. Because the 2 ATR stop was closer to the price of the stock than the 3 ATR stop, to maintain comparable risk amounts on the trades, the size of the 2 ATR stop trade was 5434 shares versus 3623 shares purchased with a 3 ATR stop. The larger size is what pushed the 2 ATR stop to a higher MAE than the 3 ATR stop for that particular trade. With the smaller size, that trade didn’t even have the worst MAE for the 3 ATR stop. Another trade was the “winner” of that contest resulting in different per share MAE values between the 2 and 3 ATR stop runs. MAEs are comparable between Lines and Histogram divergences. The additional exit criteria of MACDH downticks and Low MACD values markedly decreased the MAE, in line with the expectancies in the previous section. What is not in line is the MAE on the MACDHMA. Comparing the trades for MACDHMA to MACDLMA (histogram vs lines) revealed that the MACDHMA had more gaps up on the open which pushed more trades past the expected risk amount of $1000. This undoubtedly contributed to the higher average MAE but it is unclear if gaps up are the sole cause.

How to Assess Risk with Maximum Adverse Excursion (MAE) Equally important to understanding the potential for gain is assessing the risk of loss. Drawdown is frequently quoted in the industry but, because most of us are not managing a portfolio of 7147 stocks, it’s not very useful here. Instead we can gain knowledge of the risks by tracking the Maximum Adverse Excursion (MAE). Don’t let that technical term put you off, it really just means knowing how much the position went against you. MAE is not the same as the biggest losing trade because a stock may wander down for a huge open loss and come back before the exit. To stay in the game, the MAE needs to stay under the size of your account. To be successful, the MAE needs to be limited to a fraction of your account. In the table below, the baseline “no-strategy” strategy shows how far awry trades can go. The 20-day timed exit functions as the baseline because that most closely matches the average number of days that the other strategies held their stocks.




Table 3 – MAE for Trades Sized to Risk $1000-$1200 with stops, or whole position up to $100, 000 without stops

MACD Bull Div Exits Viability Per Share

Name of Strategy Under Test $ MAE Avg $ MAE Max MAE Avg MAE Max

Baseline 1994 - 2004, 20 days $1,953.28 $ 518,000.00 $ 1.95 $518.00

MACDH Div Sym 1994-2004 $5,518.48 $ 621,360.00 $ 5.52 $621.36

MACDL Div Sym 1994-2004 $5,626.58 $ 359,860.00 $ 5.63 $359.86

MACDH Div 2ASym 1994-2004 $ 654.91 $ 1,197.14 $ 1.33 $118.50

MACDH Div 3ASym 1994-2004 $ 658.03 $ 1,191.10 $ 1.96 $154.00

MACDH Div 3ADownT 1994-2004 $ 341.78 $ 1,191.10 $ 0.99 $149.00

MACDH Div Low+3ASym 1994-2004 $ 458.57 $ 1,198.40 $ 1.38 $154.00

MACDHMA Div 3ASym 1994-2004 $ 624.30 $ 1,159.20 $ 2.02 $ 34.81

MACDLMA Div 3A Sym 1994-2004 $ 361.39 $ 1,101.52 $ 0.97 $ 15.00

MACDL Div 2A Sym 1994-2004 $ 653.95 $ 1,197.00 $ 1.22 $ 89.00

MACDL Div 3A Sym 1994-2004 $ 659.83 $ 1,183.70 $ 1.84 $153.00

MACDL Div Low+3A Sym 1994-2004 $ 569.82 $ 1,197.00 $ 1.06 $ 84.90

MACDL Div 2APwr Sym 1994-2004 $ 658.54 $ 1,197.00 $ 1.15 $ 74.00

MACDL Div 3APwr Sym 1994-2004 $ 668.82 $ 1,191.40 $ 1.74 $104.50

Baseline 2004-2007, 20 days $1,643.57 $ 207,600.00 $ 1.64 $207.60

MACDH Div Sym 2004-2007 $3,245.91 $ 181,800.00 $ 3.25 $181.80

MACDL Div Sym 2004-2007 $3,256.36 $ 138,900.00 $ 3.26 $138.90

MACDH Div 2ASym 2004-2007 $ 633.00 $ 1,191.16 $ 0.91 $ 7.72

MACDH Div 3ASym 2004-2007 $ 616.53 $ 1,192.55 $ 1.31 $ 14.60

MACDH Div 3ADownT 2004-2007 $ 332.96 $ 1,155.00 $ 0.70 $ 10.50

MACDH Div Low+3ASym 2004-2007 $ 440.05 $ 1,190.45 $ 0.93 $ 14.60

MACDHMA Div 3ASym 2004-2007 $ 600.65 $ 1,192.55 $ 1.50 $ 8.14

MACDLMA Div 3A Sym 2004-2007 $ 348.60 $ 968.66 $ 0.75 $ 6.56

MACDL Div 2A Sym 2004-2007 $ 634.19 $ 1,164.90 $ 0.87 $ 11.35

MACDL Div 3A Sym 2004-2007 $ 616.68 $ 1,187.62 $ 1.24 $ 11.35




Baseline 2007-2008, 20 days $3,121.15 $ 75,660.00 $ 3.12 $ 75.66

MACDH Div Sym 2007-2008 $6,811.17 $ 82,370.00 $ 6.81 $ 82.37

MACDL Div Sym 2007-2008 $6,535.97 $ 51,570.00 $ 6.54 $ 51.57

MACDH Div 2ASym 2007-2008 $ 672.13 $ 1,195.48 $ 1.36 $ 10.46

MACDH Div 3ASym 2007-2008 $ 687.09 $ 1,666.66 $ 2.11 $ 17.33

MACDH Div 3ADownT 2007-2008 $ 365.95 $ 1,139.84 $ 1.09 $ 10.30

MACDH Div Low+3ASym 2007-2008 $ 481.59 $ 1,174.20 $ 1.46 $ 12.27

MACDHMA Div 3ASym 2007-2008 $ 628.38 $ 1,136.80 $ 2.40 $ 13.22

MACDLMA Div 3A Sym 2007-2008 $ 349.49 $ 1,008.80 $ 1.39 $ 10.40

MACDL Div 2A Sym 2007-2008 $ 673.02 $ 1,195.48 $ 1.39 $ 10.49

MACDL Div 3A Sym 2007-2008 $ 676.95 $ 1,161.60 $ 2.09 $ 15.14






Select R-Multiple Distributions

Distribution of Results Tables of results give a good summary but are necessarily leave out detail. For deeper insight, check out the results distribution graphs. They indicate whether to expect big losses often or a multitude of little hits. Likewise, some strategies will have many small gains and others earn their keep in a few large paydays. Click here for more about distribution graphs. Next page too.

Figure 16 - Results Distributions for MACD Bull Div Strategies running 1994 - 2004: MACDL Power Tools with 3 ATR Stop, MACDH with 3 ATR Stop, MACDL with Low+3ATR Stops (from top to bottom)

http://backtestingblog.com/glossary/results-distribution-definition/


For the 2004-2007 results on the left side of this page, the fat tail of positive R-Multiples is highlighted in green to make it more visible. The Power Tools strategy has the thickest fat tail – meaning that it had the most trades with huge profits. However, the other strategies have more “everyday” trades bringing in 5R or less.

Remember that R is the amount risked per trade, in our test $1000. R-Multiple is the number of times that risk is returned, so +5R is $5000 profit while -1R is a $1000 loss. The trades are sorted into “bins” which correspond to a bar on the graph. The label of the bin is the mid-point of its contents so the 0.5 bar represents all trades that returned between 0 and 1 R. Anything more negative than -1 R means those trades gapped past their stops or jumped the risk limits due to opening gaps.

Figure 17 - Results Distributions for MACD Bull Div Strategies running 2004 - 2007: MACDL Power Tools with 3 ATR Stop, MACDH with 3 ATR Stop, MACDL with Low+3ATR Stops (from top to bottom)


An alarming thing happens with both the MACDL Power Tools strategy and the MACDH strategy: the -1.5R bin is larger than the -0.5R bin meaning that many losing trades jumped their stops! It’s also possible that the risk value was exceeded if the stock gapped up in the morning. These results are “risk limited” meaning that trades that would have increased the risk value more than 20% were thrown out (with negligible impact to expectancy). That leaves many trades where the initial risk between buy price and stop price grew beyond the set $1000 risk. The MACDL Low+3ATR strategy doesn’t exhibit this unruly behavior. Looking at the Zoom graphs on the right side of the proceeding 3 pages, we see how many losing trades are cut short when the MACD (H or L) revisits its “low” value (at the close on the day of the buy signal). These are the taller red bars between -0.85 and -0.05. Those trades are cut short and then don’t go on to either jump stops for a loss or turn around for a profit.

Figure 18 - Results Distributions for MACD Bull Div Strategies running 2007-2008: MACDL Power Tools with 3 ATR Stop, MACDH with 3 ATR Stop, MACDL with Low+3ATR Stops (from top to bottom)


Conclusions

Long trades on MACD Divergences bagged attractive returns in favorable markets and significantly beat the baseline. In the tough years they lost money but not as much as they gained in the good years. Having an indicator to determine general market direction would have been useful to weed out the bad times to take MACD divergence buy signals. The 200-day MA is not that indicator – it didn’t provide the expectancy boost we’ve seen when we paired it with other strategies. If you’re trying to decide between MACDH and MACDL divergences consider these factors: MACDL had: fewer signals higher expectancy more huge winners

MACDH had: more frequent signals decent expectancy a larger number of smaller wins

In a baseball analogy, MACDH was oriented towards more base hits, doubles and triples, while MACDL helped trader swing for the fences to rack up home runs. Both MACDH and MACDL required a trader to let the winners run for weeks and months to achieve the high positive expectancies in this backtest. Attempts to exit the MACDH trades at the first downtick above zero severely limited profits. A nimble trader that can accurately sense the MACD divergence during the day it occurs and enter just before the close might have goosed their expectancy gain capturing gaps up on the morning open. No evidence suggested that this gain affected the expectancy of holding long term, meaning that the big morning gap up trades had about the same chance of long term gain as the trades that didn’t gap. If trading MACD divergences, expect most of your stops to be jumped and size your positions conservatively. Don’t run per-trade risk at your highest threshold. Both the MACDH and MACDL strategies had the majority of their losses grow larger than the initial risk value, either from opening day gaps up or from gaps down past the stop. In either event, you are better off setting a nominal risk value that is well below what you are comfortable losing. That said, MACD divergences did prove out as the most powerful of the MACD signals.

How to Apply This Strategy

Two main approaches: 1) Watch your favorite stocks and when you see a MACD bullish divergence, consider

jumping on it. This might happen once or twice a year.

2) Scan the broad market for MACD bullish divergences on any stock or more realistically any stock that meets your pre-set criteria of volume, fundamentals, etc.

A mechanical or automated strategy relying solely on MACD divergences is not recommended.


Resources

Free Charts

You can simply plot the MACD lines and histogram on a chart. Most tools can do this with built-in functions. For detailed instructions on how to use a free tool, see http://www.backtestingreport.com/MACD_on_BestFreeCharts.pdf . FreeStockCharts.com - free interactive charts made with BATS real-time data

Yahoo.com – free, online stock charts made with CSI Data for historical charts

Automated Scans for MACD Divergences

To save yourself hundreds of hours searching for MACD Divergences, check out the BackTesting Report custom scans for MACD Divergences. Check out BackTesting Report’s package of TradeStation (TS) strategies and functions which highlight MACD Divergences on a chart. The TS strategies generate MACD Divergence buy and sell signals that can be used (at your own risk), with either the TS automated trade execution, the backtesting engine, the scanner, the RadarScreen®, or simply to see the strategy trades highlighted on the chart. For more information visit: http://backtestingblog.com/code/macd-divergences/

Figure 19 - TradeStation screenshot of the MACD Divergence strategy and RadarScreen

http://www.backtestingreport.com/MACD_on_BestFreeCharts.pdf

http://www.freestockcharts.com/

http://www.yahoo.com/

http://backtestingblog.com/code/macd-divergences/


Understanding Technical Indicators Made Easy with BackTesting Report

BTR1: Baseline (Free Bonus Report) Establishes a standard for comparison for the US Stock market from 1994 - 2008. Brief reference filled with background info on backtesting and evaluating strategies.

Buying New Trends Series

BTR2: Trading Above the Moving Averages: Shows you when it made sense to wait for a market ripe for buying by highlighting which MAs

worked and which didn’t. BTR3: Price Crossing the MA: Learn simple ways to trigger an objective buy signal on a rising trend BTR4: Moving Average Crossovers Tests out the buy signals from this classic strategy. Plus a free bonus! Best of Moving Average Buy Signals, comparing the best signals from previous reports plus introducing a new strategy with promising results, especially for swing traders. This bonus is exclusively for BackTesting Report package customers. All four moving average issues are zipped into one download.

Custom Strategies and Scans

EasyLanguage® for TradeStation enables you to scan the markets for opportunities to use the strategies tested by BackTesting Report. Mark charts with the buy and sell signals taken by the most promising strategies. TradeStation strategies also support RadarScreen to scan a symbol list in real time. For example, you can save hours each day in identifying the elusive and powerful MACD divergences on US stocks.


WHAT WORKED, WHAT DIDN’T WORK AND HOW TO AVOID THE MISTAKES EVEN EXPERTS MAKE

BTR5: Anticipating the Cross with MACD Buy Signals Get-started guide explains the moving parts of the MACD, clearing up the mysteries of the multiple histograms. Pits MACD lines versus histograms to choose an entry signal. Popular parameter settings covered as well.

BTR6: Catching the Wiggles with MACD Sell Signals Backtests basic MACD signals - buys and sells - seeking the ways to capture profits from usual end-of-day action in the stock market.

BTR7: Missing Link Between MAs and MACD See how the 12/26 moving average crossover compares. This moving average combination is singled out because it forms the basis of the MACD.

BTR8: Finding Big Bottoms with MACD Divergences Get a handle on divergences between indicator and price. Explore the combination of MACD bullish divergences as buy signals and MACD bearish divergences as sell signals.

Copyright 200-2012. Own Mountain Trading Company. All rights reserved. www.backtestingreport.com

Related Reading The author’s current reading list is posted at http://backtestingblog.com/order/books/

Bibliography

Appel, Gerald. Master Class with Gerald Appel, Financial Trading Seminars, 2003. 2 Appel, Gerald. Technical Analysis: Power Tools for Active Investors, FT Press, 2005. Aronson, David. Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals, Wiley, 2007. 1Elder, Alexander. Trading for a Living, Wiley, 1993. Chuck LeBeau and David Lucas. Technical Traders Guide To Computer Analysis of the Futures Market, The Book Press, 1992. D.R Barton, Chuck LeBeau. Class notes of The Systems Development Workshop. Offered by Van Tharps Institute, 2007. Tharp, Van. Trade Your Way to Financial Freedom, 2nd edition, McGraw Hill, 2007. Wiessman, Richard L. Mechanical Trading Systems: Pairing Trader Psychology with Technical Analysis, Wiley Trading, 2005.

Videos

http://truthaboutmacd.com – free video on MACD technical indicator and in-depth video course

Software

MACD Divergence Detectors – scanners to automatically find several kinds of MACD divergence, see backtestingblog.com/code/macd-divergences/

TradeStation® – the backtesting engine used in this report, see tradestation.com

Web Sites BackTestingBlog.com – background information on backtesting, including glossary Divergence-Alerts.com – daily alerts on MACD Divergences in stocks, ETFs and futures. Also tracks an ETF rotation investment strategy.

http://backtestingblog.com/order/books/

http://truthaboutmacd.com/

http://backtestingblog.com/code/macd-divergences/

http://www.backtestingblog.com/

http://backtestingblog.com/category/glossary/

http://divergence-alerts.com/


Disclaimer By purchasing this report, you are agreeing to the following disclaimer:

Own Mountain Trading Company, its owners, directors, managers and officers, (“Own Mountain”), are not responsible for the success or failure of your decisions relating to any information presented in this report. The information presented in this report should be carefully considered and evaluated, before reaching a decision, on whether to use them.

This report contains comparisons, assertions, and conclusions regarding performance based on backtesting. Backtesting is the process of testing a trading strategy on prior time periods. When you backtest, the results achieved are highly dependent on the movements of the tested period. One should not assume that what happens in the past will happen in the future, and this assumption can cause potential risks for the strategy. Back-testing is not identical to live trading. As such the backtesting performance may differ from the actual performance. Markets are always changing and evolving. The market today can be very different from the market last year. The past performance does not equal future results.

There can be no assurance that any prior successes, or past results can be used as an indication of your future success or results. Results are based on many factors. Own Mountain has no way of knowing how well you will do, as we do not know you, your background, your work ethic, or your skills or practices. Therefore Own Mountain does not guarantee or imply that you will get rich, that you will do as well, or make any money at all. There is no assurance you will do as well. If you rely upon the information presented in this report; you must accept the risk of not doing as well. Any earnings or income statements, or earnings or income examples, are only estimates of what we think you could earn.

You are advised to do your own due diligence when it comes to making business decisions and all information should be independently verified by your own qualified professionals.

All businesses have unknown risks involved, and are not suitable for everyone. You could experience significant losses, or make no money at all. Use caution and seek the advice of qualified professionals. Check with your accountant, lawyer or professional advisor, before acting on this or any information

Own Mountain makes no express or implied claims that you will make money as a result of purchasing this report and using the information presented in this report.

You agree that Own Mountain is not responsible for any success or failure that you or your business may experience as a result of using the information presented in this report. You freely and of your own will risk any and all capital you may choose to spend in using the information. You will do so with skill and common sense. You will not hold Own Mountain Trading Company accountable in any way for any failure of the information to live up to your expectations.

In no event shall Own Mountain have any liability for any special, punitive, indirect, or consequential damages (including lost profits), even if notified of the possibility of such damages.

TradeStation, EasyLanguage, and RadarScreen are trademarks of TradeStation Group, Inc.

OWN MOUNTAIN TRADING COMPANY PRESENTS · 2012. 9. 19. · To implement a “Power Tools” strategy for trading divergences, the buy signal depends on the market trend as defined

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