Date: 3/31/2008
Open: $47.42
High: $48.30
Low: $46.31
Close: $47.35
Volume: 2,308,473
Advances: 58
Advances >=4%: 4
Daily Change: -0.01%
Dow: 0.38%
Nasdaq: 0.79%
S&P: 0.57%
Monday, March 31, 2008
Sunday, March 30, 2008
Saturday, March 29, 2008
The Volume Affect
Backtesting Methodology
I want to shift gears a little this week and discuss a study I just wrapped up looking at the affects volume has on a trading system. We’ve all heard how important volume is but I’ve become increasingly skeptical of conventional wisdom and decided to take a closer look at it myself. We will change our data format a little this week as well to better facilitate an analysis of this. As usual, we will compare the results over three separate portfolios to confirm our results are systemic.
The entry system is the same one we have been using to date with one exception, Pradeep’s volume requirement has been replaced and we will be looking at the volume increase as a percentage over the average 10-day volume. I inevitable get asked about entries after each post and will only refer one to Stockbee for more details on the entry criteria. I do not want to take the liberty of detailing his criteria here.
For our average volume calculations, we could use a different time frame but the results will not vary substantially as this number changes. This is an area that is susceptible to curve fitting and in order to avoid this, I will always use a 10-day period for these types of calculations.
We will also look at the results with two sets of exits. The 8% protective+20% profit target and the 8% protective + 25% trailing profit stop. These exits are discussed in more detail in previous posts here and here. While probably not necessary, I’ve decided to test with multiple exits to confirm the results are independent of a particular exit strategy.
Let’s begin by looking at a chart of the expectancy per dollar risk (Avg. Trade/ Avg. Loss) against our different volume requirements followed up by the raw data.
8% Protective + 2o% Profit Target
8% Protective + 25% Trailing Profit Stop
To borrow an analogy from Quantifiable Edges, myth confirmed - sort of. Strong volume does appear to elevate our expectancy and the affect can be quite substantial. Looking at he 20% profit target with the IBD portfolio, a 200% volume increase raises our expectancy per dollar risked by nearly 36% over a 0% volume increase. The Nasdaq portfolio is even more dramatic with a 110% expectancy increase.
There are some interesting exceptions however. Above about a 250% volume increase, things start to get a little catawampus, particularly with the S&P portfolio. Part of this can perhaps be described by the lower number of trades at the higher volume breakouts which may be increasing the margin of error but does not fully explain why the S&P portfolio performance completely falls off a cliff between 250-300%. I can only speculate to why this is but feel it might be related to the nature of the large-cap stocks that make up the S&P500 and an over-reaction to a positive event or news item that would trigger this high a volume surge and the subsequent correction. This is only speculation however.
As usual, I encourage everyone to spend some time with the data and formulate your own conclusions and strategies for incorporating this data into your trading, if at all. To aid in this, I have posted the raw data in spreadsheet form to the following location for download.
20% profit target
http://spreadsheets.google.com/pub?key=prgyYW4ZqFw5nJ2l4JqiKZw
25% trailing profit stop stop
http://spreadsheets.google.com/pub?key=prgyYW4ZqFw4Lmo62uQVxNg
I want to shift gears a little this week and discuss a study I just wrapped up looking at the affects volume has on a trading system. We’ve all heard how important volume is but I’ve become increasingly skeptical of conventional wisdom and decided to take a closer look at it myself. We will change our data format a little this week as well to better facilitate an analysis of this. As usual, we will compare the results over three separate portfolios to confirm our results are systemic.
The entry system is the same one we have been using to date with one exception, Pradeep’s volume requirement has been replaced and we will be looking at the volume increase as a percentage over the average 10-day volume. I inevitable get asked about entries after each post and will only refer one to Stockbee for more details on the entry criteria. I do not want to take the liberty of detailing his criteria here.
For our average volume calculations, we could use a different time frame but the results will not vary substantially as this number changes. This is an area that is susceptible to curve fitting and in order to avoid this, I will always use a 10-day period for these types of calculations.
We will also look at the results with two sets of exits. The 8% protective+20% profit target and the 8% protective + 25% trailing profit stop. These exits are discussed in more detail in previous posts here and here. While probably not necessary, I’ve decided to test with multiple exits to confirm the results are independent of a particular exit strategy.
Let’s begin by looking at a chart of the expectancy per dollar risk (Avg. Trade/ Avg. Loss) against our different volume requirements followed up by the raw data.
8% Protective + 2o% Profit Target
8% Protective + 25% Trailing Profit Stop
To borrow an analogy from Quantifiable Edges, myth confirmed - sort of. Strong volume does appear to elevate our expectancy and the affect can be quite substantial. Looking at he 20% profit target with the IBD portfolio, a 200% volume increase raises our expectancy per dollar risked by nearly 36% over a 0% volume increase. The Nasdaq portfolio is even more dramatic with a 110% expectancy increase.
There are some interesting exceptions however. Above about a 250% volume increase, things start to get a little catawampus, particularly with the S&P portfolio. Part of this can perhaps be described by the lower number of trades at the higher volume breakouts which may be increasing the margin of error but does not fully explain why the S&P portfolio performance completely falls off a cliff between 250-300%. I can only speculate to why this is but feel it might be related to the nature of the large-cap stocks that make up the S&P500 and an over-reaction to a positive event or news item that would trigger this high a volume surge and the subsequent correction. This is only speculation however.
As usual, I encourage everyone to spend some time with the data and formulate your own conclusions and strategies for incorporating this data into your trading, if at all. To aid in this, I have posted the raw data in spreadsheet form to the following location for download.
20% profit target
http://spreadsheets.google.com/pub?key=prgyYW4ZqFw5nJ2l4JqiKZw
25% trailing profit stop stop
http://spreadsheets.google.com/pub?key=prgyYW4ZqFw4Lmo62uQVxNg
Friday, March 28, 2008
3/28/2008
Date: 3/28/2008
Open: $48.26
High: $49.02
Low: $47.17
Close: $47.76
Volume: 1,960,521
Advances: 40
Advances >=4%: 3
Daily Change: -0.75%
Dow: -0.70%
Nasdaq: -0.86%
S&P: -0.80%
Open: $48.26
High: $49.02
Low: $47.17
Close: $47.76
Volume: 1,960,521
Advances: 40
Advances >=4%: 3
Daily Change: -0.75%
Dow: -0.70%
Nasdaq: -0.86%
S&P: -0.80%
Thursday, March 27, 2008
New Trade Evaluation Method coming soon...
A reader, Cam asked about the showing the average number of days winning trades were held in our testing. This got me thinking about a new way of evaluating system performance which I think might ultimately be more revealing than the expectancy per dollar risk method I have used to date.
If we take our expectancy per dollar risk and divide that by the average # of days in our winners, we will get a value I am going to call the Efficient Expectancy Ratio or EER.
EER = (Avg. Trade / Avg. Loss) / Avg.Days per Winning Trade
This number will essentially reveal what our expectancy per day in trade is (per dollar risked) and will serve to evaluate which methods are the most efficient use of capital. I will be revisiting some of the previous studies on this site in the next week or so to re-evaluate things through this new method. We will acknowledge that an expectancy of $1 per $1 risk might not be the best use of capital if a system with an expectancy of 25 cents per $1 risk accomplishes this in less than 1/4 the time.
The original evaluation method, Expectancy per Dollar Risk, or EDR will be more useful for longer term investors who are interested in trading less frequently while the new EER ratio will be the more useful to swing traders and those interested in rolling in and out of trades more frequently.
If we take our expectancy per dollar risk and divide that by the average # of days in our winners, we will get a value I am going to call the Efficient Expectancy Ratio or EER.
EER = (Avg. Trade / Avg. Loss) / Avg.Days per Winning Trade
This number will essentially reveal what our expectancy per day in trade is (per dollar risked) and will serve to evaluate which methods are the most efficient use of capital. I will be revisiting some of the previous studies on this site in the next week or so to re-evaluate things through this new method. We will acknowledge that an expectancy of $1 per $1 risk might not be the best use of capital if a system with an expectancy of 25 cents per $1 risk accomplishes this in less than 1/4 the time.
The original evaluation method, Expectancy per Dollar Risk, or EDR will be more useful for longer term investors who are interested in trading less frequently while the new EER ratio will be the more useful to swing traders and those interested in rolling in and out of trades more frequently.
3/27/2008
Date: 3/27/2008
Open: $48.95
High: $49.72
Low: $47.59
Close: $48.13
Volume: 2,475,981
Advances: 24
Advances >=4%: 5
Daily Change: -1.64%
Dow: -0.97%
Nasdaq: -1.87%
S&P: -1.15%
Open: $48.95
High: $49.72
Low: $47.59
Close: $48.13
Volume: 2,475,981
Advances: 24
Advances >=4%: 5
Daily Change: -1.64%
Dow: -0.97%
Nasdaq: -1.87%
S&P: -1.15%
Wednesday, March 26, 2008
3/26/2008
Date: 3/26/2008
Open: $48.71
High: $49.70
Low: $47.77
Close: $48.93
Volume: 2,275,904
Advances: 47
Advances >=4%: 9
Daily Change: -0.3%
Dow: -0.88%
Nasdaq: -0.71%
S&P: -0.88%
Open: $48.71
High: $49.70
Low: $47.77
Close: $48.93
Volume: 2,275,904
Advances: 47
Advances >=4%: 9
Daily Change: -0.3%
Dow: -0.88%
Nasdaq: -0.71%
S&P: -0.88%
Tuesday, March 25, 2008
3/25/2008
Date: 3/25/2008
Open: $48.50
High: $49.78
Low: $47.64
Close: $49.08
Volume: 2,368,906
Advances: 71
Advances >=4%: 22
Daily Change: 1.83%
Dow: -0.13%
Nasdaq: +0.61%
S&P: +0.23%
Open: $48.50
High: $49.78
Low: $47.64
Close: $49.08
Volume: 2,368,906
Advances: 71
Advances >=4%: 22
Daily Change: 1.83%
Dow: -0.13%
Nasdaq: +0.61%
S&P: +0.23%
Monday, March 24, 2008
3/24/2008
Date: 3/24/2008
Open: $47.17
High: $49.29
Low: $46.70
Close: $48.20
Volume: 2,279,248
Advances: 84
Advances >=4%: 29
Daily Change: 2.76%
Dow: 1.52%
Nasdaq: 3.04%
S&P: 1.53%
Open: $47.17
High: $49.29
Low: $46.70
Close: $48.20
Volume: 2,279,248
Advances: 84
Advances >=4%: 29
Daily Change: 2.76%
Dow: 1.52%
Nasdaq: 3.04%
S&P: 1.53%
Sunday, March 23, 2008
Friday, March 21, 2008
O'Neil's Exception to the 20% Profit Target, Part 1
In his book, How to Make Money in Stocks, William O’Neil advocates the use of a 20% profit target with one caveat.
If we think about this for a second, it means that the 20% profit target only becomes active after eight weeks (40 trading days) because if it reaches the price target before that, we do not exit until our time threshold has expired. The benefit this stop has is that if the stock’s movement is particularly strong, we allow our winner to run beyond the 20% target. As the previous couple of studies have illustrated, this is a critically important concept. The eight week period smells a little arbitrary but we will accept it for now and implement this concept in the following way:
If BarsSinceEntry >= 40 Then Exit with Limit Order at EntryPrice * 1.2
As in the previous tests, we will use the Stockbee IBD200 breakout entry on our 300 stock IBD basket and then use the Nasdaq and S&P components to confirm our results. All tests will also implement an 8% protective stop in addition to the profit-taking stop being tested.
AverageTrade(win and loss)/ AverageLosingTrade = Expectancy per dollar risked
AverageTrade(win and loss) / AverageLosingTrade = Expectancy per dollar risked
AverageTrade(win and loss) / AverageLosingTrade = Expectancy per dollar risked
AverageTrade(win and loss) / AverageLosingTrade = Expectancy per dollar risked
“If a stock was so powerful that it vaulted 20% in less than eight weeks, the stock had to be held at least eight weeks.” Third edition, page 103.He goes on suggest that after eight-weeks, we analyze the stock for a longer term gain but offers very few specifics on how this is to be done. More on this in the future.
If we think about this for a second, it means that the 20% profit target only becomes active after eight weeks (40 trading days) because if it reaches the price target before that, we do not exit until our time threshold has expired. The benefit this stop has is that if the stock’s movement is particularly strong, we allow our winner to run beyond the 20% target. As the previous couple of studies have illustrated, this is a critically important concept. The eight week period smells a little arbitrary but we will accept it for now and implement this concept in the following way:
If BarsSinceEntry >= 40 Then Exit with Limit Order at EntryPrice * 1.2
As in the previous tests, we will use the Stockbee IBD200 breakout entry on our 300 stock IBD basket and then use the Nasdaq and S&P components to confirm our results. All tests will also implement an 8% protective stop in addition to the profit-taking stop being tested.
8% protective + 20% Profit Target Only
These are the results from the earlier set of tests I am repeating here for ease of comparison.
IBD Basket
IBD Basket
AverageTrade(win and loss)/ AverageLosingTrade = Expectancy per dollar risked24.21 / 82.52 = 29.3 cents per dollar risked.
Nasdaq Basket
AverageTrade(win and loss)/ AverageLosingTrade = Expectancy per dollar risked 
AverageTrade(win and loss)/ AverageLosingTrade = Expectancy per dollar risked
Nasdaq Basket
AverageTrade(win and loss)/ AverageLosingTrade = Expectancy per dollar risked AverageTrade(win and loss)/ AverageLosingTrade = Expectancy per dollar risked13.63 / 81.50 = 16.7 cents per dollar risked.
8% protective + 20% Profit Target w/ 40-day time threshold
Now we will test the addition of Mr. O’Neil’s time threshold:
If BarsSinceEntry >= 40 Then Exit with Limit Order at EntryPrice * 1.2
IBD Basket
8% protective + 20% Profit Target w/ 40-day time threshold
Now we will test the addition of Mr. O’Neil’s time threshold:
If BarsSinceEntry >= 40 Then Exit with Limit Order at EntryPrice * 1.2
IBD Basket
AverageTrade(win and loss) / AverageLosingTrade = Expectancy per dollar risked35.83 / 82.45 = 43.5 cents per dollar risked.
Nasdaq Basket
Nasdaq Basket
AverageTrade(win and loss) / AverageLosingTrade = Expectancy per dollar risked25.23 / 82.55 = 30.6 cents per dollar risked.
S&P500 Basket
S&P500 Basket
AverageTrade(win and loss) / AverageLosingTrade = Expectancy per dollar risked19.21 / 81.60 = 23.5 cents per dollar risked.
Conclusions
So we can see that this implementation of Mr. O’Neil’s exception to the 20% profit target is an effective strategy to let our winners run. The simple addition of this time threshold has elevated our expectancy per dollar risked by 48% in our IBD basket, 101% in our Nasdaq basket, and 41% in our S&P500 basket. Part 2 will extend this study through a different interpretation of Mr. O’Neil’s suggestion, as a Rate of Change (ROC) stop.
Conclusions
So we can see that this implementation of Mr. O’Neil’s exception to the 20% profit target is an effective strategy to let our winners run. The simple addition of this time threshold has elevated our expectancy per dollar risked by 48% in our IBD basket, 101% in our Nasdaq basket, and 41% in our S&P500 basket. Part 2 will extend this study through a different interpretation of Mr. O’Neil’s suggestion, as a Rate of Change (ROC) stop.
Thursday, March 20, 2008
3/20/2008
Date: 3/20/2008
Open: $46.61
High: $47.62
Low: $45.13
Close: $46.91
Volume: 3,151,834
Advances: 53
Advances >=4%: 9
Daily Change: 0.25%
Dow: 2.16%
Nasdaq: 2.18%
S&P: 2.39%
Open: $46.61
High: $47.62
Low: $45.13
Close: $46.91
Volume: 3,151,834
Advances: 53
Advances >=4%: 9
Daily Change: 0.25%
Dow: 2.16%
Nasdaq: 2.18%
S&P: 2.39%
Wednesday, March 19, 2008
3/19/2008
Date: 3/19/2008
Open: $49.37
High: $49.93
Low: $46.58
Close: $46.80
Volume: 2,829,142
Advances: 4
Advances >=4%: 0
Daily Change: -5.2%
Dow: -2.36%
Nasdaq: -2.57%
S&P: -2.43%
Open: $49.37
High: $49.93
Low: $46.58
Close: $46.80
Volume: 2,829,142
Advances: 4
Advances >=4%: 0
Daily Change: -5.2%
Dow: -2.36%
Nasdaq: -2.57%
S&P: -2.43%
Testing Ideas
In the right-hand side, there is a section called Future Testing Ideas where I list ideas that I am interested in testing in the future, or have already tested and want to write up. I'd like to invite readers to post any of their own ideas here that they are interested in having tested. I can't promise I'll do it but if it is interesting, unique, and progammable, I will eventually get around to it. I am also going to limit items posted on this blog to concepts that are more structural in nature and not edges that could easily be traded against so please keep that in mind.
Tuesday, March 18, 2008
3/18/2008
Date: 3/18/2008
Open: $48.33
High: $49.81
Low: $47.45
Close: $49.35
Volume: 2,424,077
Advances: 94
Advances >=4%: 61
Daily Change: 4.48%
Dow: 3.51%
Nasdaq: 4.19%
S&P: 4.24%
Open: $48.33
High: $49.81
Low: $47.45
Close: $49.35
Volume: 2,424,077
Advances: 94
Advances >=4%: 61
Daily Change: 4.48%
Dow: 3.51%
Nasdaq: 4.19%
S&P: 4.24%
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