Open: $50.54
High: $51.95
Low: $49.57
Close: $50.77
Volume: 3,331,637
Advances: 66
Advances >=4%: 10
Declines >=4%: 7
Daily Change: 0.43%
Dow: -0.09%
Nasdaq: -0.55%
S&P: -0.38%
Wednesday, April 30, 2008
04/30/08
Date: 04/30/08
Open: $50.54
High: $51.95
Low: $49.57
Close: $50.77
Volume: 3,331,637
Advances: 66
Advances >=4%: 10
Declines >=4%: 7
Daily Change: 0.43%
Dow: -0.09%
Nasdaq: -0.55%
S&P: -0.38%
Open: $50.54
High: $51.95
Low: $49.57
Close: $50.77
Volume: 3,331,637
Advances: 66
Advances >=4%: 10
Declines >=4%: 7
Daily Change: 0.43%
Dow: -0.09%
Nasdaq: -0.55%
S&P: -0.38%
Tuesday, April 29, 2008
04/29/08
Date: 04/29/08
Open: $51.62
High: $52.17
Low: $49.78
Close: $50.55
Volume: 2,862,764
Advances: 20
Advances >=4%: 3
Declines >=4%: 33
Daily Change: -2.52%
Dow: -0.31%
Nasdaq: +0.07%
S&P: -0.39%
Brutal on stong volume. The magnitude of some of the losses today on the list influenced the creation of a new category (see above).
Open: $51.62
High: $52.17
Low: $49.78
Close: $50.55
Volume: 2,862,764
Advances: 20
Advances >=4%: 3
Declines >=4%: 33
Daily Change: -2.52%
Dow: -0.31%
Nasdaq: +0.07%
S&P: -0.39%
Brutal on stong volume. The magnitude of some of the losses today on the list influenced the creation of a new category (see above).
Monday, April 28, 2008
04/28/08
Date: 04/28/08
Open: $52.05
High: $53.04
Low: $50.92
Close: $51.86
Volume: 2,421,054
Advances: 55
Advances >=4%: 8
Daily Change: -0.41%
Dow: -0.16%
Nasdaq: +0.06%
S&P: -0.11%
Open: $52.05
High: $53.04
Low: $50.92
Close: $51.86
Volume: 2,421,054
Advances: 55
Advances >=4%: 8
Daily Change: -0.41%
Dow: -0.16%
Nasdaq: +0.06%
S&P: -0.11%
Sunday, April 27, 2008
Vacation
I will be away on vacation next week so the index updates may not occur on a daily basis. Have a good week.
Percentage Price Action & Volume Breakouts, Part 1
A few weeks ago, we looked at how a volume surge a breakout trading system affects its expectancy with various sets of exits. That study can be found here.
This week, I wanted to take a look at how price action associated with a volume surge changes things. There are a number of ways to look at price movement- as a percentage change, relative to average true range, relative to standard deviation, etc. This week we will look at percentage changes and next week, we will take a look at average true range.
Unlike the last few tests, primarily due to the amount of data involved, we will only look at one exit, a fixed 8% protective stop and a fixed 20% profit target. Neither of these exits are trailing and we allow either exit to be hit before exiting. While we concluded in studies, here and here, that there are other exits with much higher expectancy, the holding times increase substantially. The 25% trailing stop, for example, essentially becomes a more risk-managed alternative to buy-and-hold or a longer-term trading/investing strategy. We can assume that the longer a stock is held, the less entry criteria matter and the more important stock selection and long-term growth become. Therefore we will use our shorter term exit stops for these tests as they place more weight on entries for an increase in expectancy.
As usual, we will run the test on three separate portfolios to increase our confidence that the results are systemic and all tests will be run from 01/01/1998-12/31/2007.
Our entry criteria will a liquidity condition requiring 10-day average daily volume to be greater than 100,000 shares. In addition, we will look at both volume as a percentage surge over 10-day average daily volume using a >= condition, and a percentage price breakout over the previous day’s close in a >= condition. Trades will be entered at open with a market order the day following the entry signal.
I am getting fancy this week with some excel surface charts which allow us to look at two variables tested together simultaneously. Previously, we have tested only one variable at a time and the 2D charts were adequate to represent the results, when testing two-variables, the 3D nature of the surface charts makes it much easier to visualize the results. We will begin by looking at the EDR results for the three portfolios.
EDR=Expectancy per dollar risked. This is my primary evaluation ratio and has been covered extensively in previous posts. It is calculated by Average Trade/Average Loss. The results are in dollars with .28 representing 28 cents per dollar risk.The Price% axis of the charts represents the percentage change in price, while the Volume% axis of the chart represents the volume surge. This is consistent in all tests. The z-axis represents our various evaluation ratios.
Let’s begin by looking at the EDR ratio. The first thing that is immediately evident is that our IBD portfolio is substantially different than our other two portfolios. We will discuss this shortly but let’s first discuss the similarities. In all three portfolios, unlike price action, stronger volume surges generally increase expectancy, irregardless of price action. There is a drop along the 400% volume axis in the Nasdaq and IBD portfolios but the general trend is clearly more favorable as volume increases, particularly up to about a 300% volume increase. This is consistent with our previous volume study.
The price action however is quite a different story. Compared to volume, price action when evaluated as a percentage increase over the previous day has a much smaller affect on expectancy. Remember that the filter operators for these test was a >= operator so by selecting only 2% price increases (for example), we are still taking large price spikes, we just aren’t limiting our selection to those. Furthermore, the IBD portfolio experiences a severe expectancy decline with higher price thresholds. There are several possible ways of explaining this but there are two key points I want to make.
First, if we assume that there is a fair amount of random noise in day-to-day price movement, then a percentage change not only includes a certain unquantified amount of noise, but also derives the percentage change against the previous day which also contains a certain, unquantified amount of noise. It does not acknowledge typical volatility for a given security or how either day’s price movement compares against the average. In some instances a 3% move may be substantial, in other situations it is not. Some of these issues are addressed when using average true range which we will test next week.
The second point relates to selectivity. In reviewing these results, I noticed that the 0%/0% figure represents an interesting condition (indicated by the arrow). This is obviously the least selective but if we think about it for a moment, it is basically taking every trade that has a positive close on average volume, remarkably similar in fact to buy-and-hold but traded through a method that allows us to compare results. If we use this 0/0 point as our baseline, it allows us to evaluate whether or not increased selectivity with a given criteria improves things. Through these results, we can conclude that increased volume selectivity is effective for filtering trades, while increased price movement alone (as a percentage) is not, in fact it can hurt.
One other thing that occurred to me is an idea for introducing an adaptive component into a system that allows it to modify selectivity based on the native performance of the underlying basket of securities being traded. By looking at the 0/0 points for the three baskets, we can see that expectancy on the IBD is the highest natively, and that portfolio suffers the most from over-selectivity. I have also seen the same thing happen with using relative strength to filter NASDAQ stocks during the dotcom boom, nearly anything you did to “slow-down” resulted in reduced expectancy. This is only an idea but putting it here will make sure I remember it. This blog is increasingly going to serve as a development journal of sorts – hope everyone is ok with that.
Below, I will post the EER and DDR results for the tests. I will not comment on them but am making them available for those motivated to dig a little deeper. If anyone has any questions, feel free to ask.
EER=Efficient Expectancy Ratio. This is our EDR/Avg. Days in Winning trades. This number is meant to reveal the most efficient use if capital as it calculates expectancy per dollar risk per day in trade. The results are in dollars with .01 representing 1 cent per dollar risk per day in trade
DDR= Drawdown ratio. This number is calculated by Net Profit/Maximum Drawdown. A higher number is better.
This week, I wanted to take a look at how price action associated with a volume surge changes things. There are a number of ways to look at price movement- as a percentage change, relative to average true range, relative to standard deviation, etc. This week we will look at percentage changes and next week, we will take a look at average true range.
Unlike the last few tests, primarily due to the amount of data involved, we will only look at one exit, a fixed 8% protective stop and a fixed 20% profit target. Neither of these exits are trailing and we allow either exit to be hit before exiting. While we concluded in studies, here and here, that there are other exits with much higher expectancy, the holding times increase substantially. The 25% trailing stop, for example, essentially becomes a more risk-managed alternative to buy-and-hold or a longer-term trading/investing strategy. We can assume that the longer a stock is held, the less entry criteria matter and the more important stock selection and long-term growth become. Therefore we will use our shorter term exit stops for these tests as they place more weight on entries for an increase in expectancy.
As usual, we will run the test on three separate portfolios to increase our confidence that the results are systemic and all tests will be run from 01/01/1998-12/31/2007.
Our entry criteria will a liquidity condition requiring 10-day average daily volume to be greater than 100,000 shares. In addition, we will look at both volume as a percentage surge over 10-day average daily volume using a >= condition, and a percentage price breakout over the previous day’s close in a >= condition. Trades will be entered at open with a market order the day following the entry signal.
I am getting fancy this week with some excel surface charts which allow us to look at two variables tested together simultaneously. Previously, we have tested only one variable at a time and the 2D charts were adequate to represent the results, when testing two-variables, the 3D nature of the surface charts makes it much easier to visualize the results. We will begin by looking at the EDR results for the three portfolios.
EDR=Expectancy per dollar risked. This is my primary evaluation ratio and has been covered extensively in previous posts. It is calculated by Average Trade/Average Loss. The results are in dollars with .28 representing 28 cents per dollar risk.The Price% axis of the charts represents the percentage change in price, while the Volume% axis of the chart represents the volume surge. This is consistent in all tests. The z-axis represents our various evaluation ratios.
Let’s begin by looking at the EDR ratio. The first thing that is immediately evident is that our IBD portfolio is substantially different than our other two portfolios. We will discuss this shortly but let’s first discuss the similarities. In all three portfolios, unlike price action, stronger volume surges generally increase expectancy, irregardless of price action. There is a drop along the 400% volume axis in the Nasdaq and IBD portfolios but the general trend is clearly more favorable as volume increases, particularly up to about a 300% volume increase. This is consistent with our previous volume study.
The price action however is quite a different story. Compared to volume, price action when evaluated as a percentage increase over the previous day has a much smaller affect on expectancy. Remember that the filter operators for these test was a >= operator so by selecting only 2% price increases (for example), we are still taking large price spikes, we just aren’t limiting our selection to those. Furthermore, the IBD portfolio experiences a severe expectancy decline with higher price thresholds. There are several possible ways of explaining this but there are two key points I want to make.
First, if we assume that there is a fair amount of random noise in day-to-day price movement, then a percentage change not only includes a certain unquantified amount of noise, but also derives the percentage change against the previous day which also contains a certain, unquantified amount of noise. It does not acknowledge typical volatility for a given security or how either day’s price movement compares against the average. In some instances a 3% move may be substantial, in other situations it is not. Some of these issues are addressed when using average true range which we will test next week.
The second point relates to selectivity. In reviewing these results, I noticed that the 0%/0% figure represents an interesting condition (indicated by the arrow). This is obviously the least selective but if we think about it for a moment, it is basically taking every trade that has a positive close on average volume, remarkably similar in fact to buy-and-hold but traded through a method that allows us to compare results. If we use this 0/0 point as our baseline, it allows us to evaluate whether or not increased selectivity with a given criteria improves things. Through these results, we can conclude that increased volume selectivity is effective for filtering trades, while increased price movement alone (as a percentage) is not, in fact it can hurt.
One other thing that occurred to me is an idea for introducing an adaptive component into a system that allows it to modify selectivity based on the native performance of the underlying basket of securities being traded. By looking at the 0/0 points for the three baskets, we can see that expectancy on the IBD is the highest natively, and that portfolio suffers the most from over-selectivity. I have also seen the same thing happen with using relative strength to filter NASDAQ stocks during the dotcom boom, nearly anything you did to “slow-down” resulted in reduced expectancy. This is only an idea but putting it here will make sure I remember it. This blog is increasingly going to serve as a development journal of sorts – hope everyone is ok with that.
Below, I will post the EER and DDR results for the tests. I will not comment on them but am making them available for those motivated to dig a little deeper. If anyone has any questions, feel free to ask.
EER=Efficient Expectancy Ratio. This is our EDR/Avg. Days in Winning trades. This number is meant to reveal the most efficient use if capital as it calculates expectancy per dollar risk per day in trade. The results are in dollars with .01 representing 1 cent per dollar risk per day in trade
DDR= Drawdown ratio. This number is calculated by Net Profit/Maximum Drawdown. A higher number is better.
Turnover for week beginning 04/28/08
Turnover this week was not unusually high at 17% - less than last week's 19%. I am not legally permitted to reproduce the IBD100 but I am listing the new and removed industry groups to potentially help identify any new emerging leadership trends. I do not think there is enough data as of now to draw any meaningful conclusions but I will start to post this list on a weekly basis. Also, TraderFeed has some very good posts recently on money flow into/out of various sectors.
New to the list:
Auto Parts
Independent Oil & Gas
Personal Computers
Diversified Machinery
Industrial Metals & Minerals
Industrial Electrical Equipment
Chemicals - Major Diversified
Wireless Communications
Credit Services
Diversified Machinery
Scientific & Technical Instruments
Oil & Gas Refining & Marketing
Management Services
Industrial Electrical Equipment
Business Services
Internet Software & Services
Scientific & Technical Instruments
Removed:
Packaging & Containers
Data Storage Devices
Insurance Brokers
Oil & Gas Equipment & Services
Shipping
Restaurants
Wireless Communications
Oil & Gas Drilling & Exploration
Semiconductor - Integrated Circuits
Farm & Construction Machinery
Gas Utilities
Semiconductor - Integrated Circuit
Diversified Investments
Basic Materials Wholesale
Steel & Iron
Beverages - Soft Drinks
Oil & Gas Equipment & Services
New to the list:
Auto Parts
Independent Oil & Gas
Personal Computers
Diversified Machinery
Industrial Metals & Minerals
Industrial Electrical Equipment
Chemicals - Major Diversified
Wireless Communications
Credit Services
Diversified Machinery
Scientific & Technical Instruments
Oil & Gas Refining & Marketing
Management Services
Industrial Electrical Equipment
Business Services
Internet Software & Services
Scientific & Technical Instruments
Removed:
Packaging & Containers
Data Storage Devices
Insurance Brokers
Oil & Gas Equipment & Services
Shipping
Restaurants
Wireless Communications
Oil & Gas Drilling & Exploration
Semiconductor - Integrated Circuits
Farm & Construction Machinery
Gas Utilities
Semiconductor - Integrated Circuit
Diversified Investments
Basic Materials Wholesale
Steel & Iron
Beverages - Soft Drinks
Oil & Gas Equipment & Services
Friday, April 25, 2008
04/25/2008
Date: 04/25/2008
Open: $51.33
High: $52.73
Low: $50.31
Close: $52.07
Volume: 2,649,245
Advances: 80
Advances >=4%: 23
Daily Change: 2.16%
Dow: +0.33%
Nasdaq: -0.25%
S&P: +0.65%
The IBDIndex managed to play catch up today but not quite enough to finish positive on the week, lagging the broader indexes which were able to finish over last week's close. As I mentioned yesterday, I will pay close attention to the stock rotation as I rebalance the index this weekend, paying particular attention to specific sectors or industry groups that may be rotating into a leadership role. It may just turn out that this week was simply a well-deserved consolidation period, a spring break perhaps, for the majority of the list leaders.
Open: $51.33
High: $52.73
Low: $50.31
Close: $52.07
Volume: 2,649,245
Advances: 80
Advances >=4%: 23
Daily Change: 2.16%
Dow: +0.33%
Nasdaq: -0.25%
S&P: +0.65%
The IBDIndex managed to play catch up today but not quite enough to finish positive on the week, lagging the broader indexes which were able to finish over last week's close. As I mentioned yesterday, I will pay close attention to the stock rotation as I rebalance the index this weekend, paying particular attention to specific sectors or industry groups that may be rotating into a leadership role. It may just turn out that this week was simply a well-deserved consolidation period, a spring break perhaps, for the majority of the list leaders.
Thursday, April 24, 2008
04/24/2008
Date: 04/24/2008
Open: $51.91
High: $52.60
Low: $49.71
Close: $50.92
Volume: 2,828,042
Advances: 28
Advances >=4%: 2
Daily Change: -2.049%
Dow: +0.67%
Nasdaq: +0.99%
S&P: +0.64%
Today was a crazy day. The IBDindex dipped below its 10-day moving average, dropping over 2% on the 3rd highest volume day since I've begun tracking it. All this on a day when the major indexes managed to reverse an early morning sell-off into a moderate sized rally, breaking through recent resistance. The IBD100 simply never followed the broader market rally. It is quite possible we have a sector rotation in the works with new leadership emerging not currently on the IBD 100. It will be interesting to see what the turnover rate on the IBD100 list is this weekend.
Wednesday, April 23, 2008
04/23/2008
Date: 04/23/2008
Open: $52.35
High: $53.08
Low: $50.96
Close: $51.99
Volume: 2,268,786
Advances: 40
Advances >=4%: 5
Daily Change: -0.36%
Dow: +0.34%
Nasdaq: +1.19%
S&P: +0.29%
Open: $52.35
High: $53.08
Low: $50.96
Close: $51.99
Volume: 2,268,786
Advances: 40
Advances >=4%: 5
Daily Change: -0.36%
Dow: +0.34%
Nasdaq: +1.19%
S&P: +0.29%
Tuesday, April 22, 2008
04/22/2008
Date: 04/22/2008
Open: $52.85
High: $53.45
Low: $51.32
Close: $52.18
Volume: 2,525,795
Advances: 20
Advances >=4%: 1
Daily Change: -1.45%
Dow: -0.82%
Nasdaq: -1.29%
S&P: -0.88%
Open: $52.85
High: $53.45
Low: $51.32
Close: $52.18
Volume: 2,525,795
Advances: 20
Advances >=4%: 1
Daily Change: -1.45%
Dow: -0.82%
Nasdaq: -1.29%
S&P: -0.88%
Monday, April 21, 2008
04/21/2008
Date: 04/21/2008
Open: $52.60
High: $53.55
Low: $51.62
Close: $52.98
Volume: 2,285,130
Advances: 66
Advances >=4%: 10
Daily Change: 1.08%
Dow: -0.19%
Nasdaq: +0.21%
S&P: -0.16%
Open: $52.60
High: $53.55
Low: $51.62
Close: $52.98
Volume: 2,285,130
Advances: 66
Advances >=4%: 10
Daily Change: 1.08%
Dow: -0.19%
Nasdaq: +0.21%
S&P: -0.16%
Sunday, April 20, 2008
Trend-following the RSI(2)
I admittedly got a little distracted this week. What started as a little side project for me actually ended up consuming all of my computational resources and ultimately generated 17,485,793 trades. Yea, 17 million. Fortunately I figured out how to program macro scripts for Traders Studio recently so much of the process was automated.
The primary purpose behind this blog is to explore and test trend-following ideas that can be used in conjunction with a CANLIM approach to the markets. With that said, there has been a lot of discussion recently in part of the blogosphere I follow looking at the 2-period RSI as a short-term mean-reversion indicator. Don't let the title fool you, I am only following this “trend” with a little research of my own. Yea, I know - not that funny.
Woodshedder@IBC
The Dogwood Report
Pennings of an Analyst
TradingMarket
This is natural given the recent range-bound market that highlights the need for a trader to be able to adapt to various market conditions. Markets don’t always trend and knowing when to step back or change approaches is critical to stabilizing returns and minimizing drawdowns. I decided to apply my own approach to testing the RSI(2) this week to determine if it had enough meat to serve as the basis for a short-term mean-recursion trading system. I am typically not a big fan of indicators & oscillators for no other reason than I have not found or seen quantifiable evidence backing up the effectiveness of most of them. I even looked at the ADX a few weeks ago on this blog as an obvious candidate for a trend-following system. Unlike that however, the RSI(2) did impress me.
The setup, entry and exit criteria for the test this week was very simple. The setup was only a liquidity threshold requiring 10-day average volume to be above 100,000 shares. Entry was a market order to buy $1000 worth of shares at open on the day following the RSI(2) falling below a certain threshold and exits were simple 1,5 and 10-day timed exits. Not a complete “system” but simple enough to place all the burden on the RSI for the heavy lifting. I did intend to look at shorting overbought as well but simply ran out of time. The test are run for a 10-year period starting on 01/01/1996 through 12/31/2007.
The y-axis of the performance graphs are formatted with my go-to evaluation criteria, EDR (expectancy per dollar risk) which is calculated by Average Trade/Average Loss. The x-axis shows the RSI value that was used as the threshold in a <= operation. I will follow-up the graphs with the raw trade data.
IBD portfolio
NASDAQ100 components
S&P500 components
So I think the results speak for themselves. It looks like an RSI <= 3 is the sweet spot so if we allow ourselves the luxury of perfect hindsight for a moment and use that as our threshold, expectancy per dollar risked on our Nasdaq portfolio, for example, was 242% higher than all trades 1-day out, 140% higher 5-days out, and still 112% higher 10-days out. Remarkable results. Combined with more refined entry, exit, risk management and position sizing rules, I’m quite certain you could increase your win percentage and expectancy much further. Not only that, as these results illustrate, the method is robust enough to apply to larget baskets of stocks which will generate plenty of oppertunities. I am a believer, atleast for now until every computer plugged into the internet starts trading it. Keeps you sharp though, when something stops working, it only means something else is starting to.
The primary purpose behind this blog is to explore and test trend-following ideas that can be used in conjunction with a CANLIM approach to the markets. With that said, there has been a lot of discussion recently in part of the blogosphere I follow looking at the 2-period RSI as a short-term mean-reversion indicator. Don't let the title fool you, I am only following this “trend” with a little research of my own. Yea, I know - not that funny.
Woodshedder@IBC
The Dogwood Report
Pennings of an Analyst
TradingMarket
This is natural given the recent range-bound market that highlights the need for a trader to be able to adapt to various market conditions. Markets don’t always trend and knowing when to step back or change approaches is critical to stabilizing returns and minimizing drawdowns. I decided to apply my own approach to testing the RSI(2) this week to determine if it had enough meat to serve as the basis for a short-term mean-recursion trading system. I am typically not a big fan of indicators & oscillators for no other reason than I have not found or seen quantifiable evidence backing up the effectiveness of most of them. I even looked at the ADX a few weeks ago on this blog as an obvious candidate for a trend-following system. Unlike that however, the RSI(2) did impress me.
The setup, entry and exit criteria for the test this week was very simple. The setup was only a liquidity threshold requiring 10-day average volume to be above 100,000 shares. Entry was a market order to buy $1000 worth of shares at open on the day following the RSI(2) falling below a certain threshold and exits were simple 1,5 and 10-day timed exits. Not a complete “system” but simple enough to place all the burden on the RSI for the heavy lifting. I did intend to look at shorting overbought as well but simply ran out of time. The test are run for a 10-year period starting on 01/01/1996 through 12/31/2007.
The y-axis of the performance graphs are formatted with my go-to evaluation criteria, EDR (expectancy per dollar risk) which is calculated by Average Trade/Average Loss. The x-axis shows the RSI value that was used as the threshold in a <= operation. I will follow-up the graphs with the raw trade data.
IBD portfolio
NASDAQ100 components
S&P500 components
So I think the results speak for themselves. It looks like an RSI <= 3 is the sweet spot so if we allow ourselves the luxury of perfect hindsight for a moment and use that as our threshold, expectancy per dollar risked on our Nasdaq portfolio, for example, was 242% higher than all trades 1-day out, 140% higher 5-days out, and still 112% higher 10-days out. Remarkable results. Combined with more refined entry, exit, risk management and position sizing rules, I’m quite certain you could increase your win percentage and expectancy much further. Not only that, as these results illustrate, the method is robust enough to apply to larget baskets of stocks which will generate plenty of oppertunities. I am a believer, atleast for now until every computer plugged into the internet starts trading it. Keeps you sharp though, when something stops working, it only means something else is starting to.
Saturday, April 19, 2008
Friday, April 18, 2008
04/18/2008
Date: 04/18/2008
Open: $51.82
High: $53.12
Low: $51.06
Close: $52.41
Volume: 2,632,043
Advances: 85
Advances >=4%: 17
Daily Change: 2.15%
Dow: +1.81%
Nasdaq: +2.61%
S&P: +1.81%
This was a solid week for the IBD100. The IBDIndex is up 6.35% this week compared to 4.9% in the Nasdaq. If this rally holds up, it appears we may finally have some growth leadership emerging which marks a clear distinction between previous rally attempts in the past few months.
Open: $51.82
High: $53.12
Low: $51.06
Close: $52.41
Volume: 2,632,043
Advances: 85
Advances >=4%: 17
Daily Change: 2.15%
Dow: +1.81%
Nasdaq: +2.61%
S&P: +1.81%
This was a solid week for the IBD100. The IBDIndex is up 6.35% this week compared to 4.9% in the Nasdaq. If this rally holds up, it appears we may finally have some growth leadership emerging which marks a clear distinction between previous rally attempts in the past few months.
Thursday, April 17, 2008
04/17/2008
Date: 04/17/2008
Open: $51.71
High: $52.38
Low: $50.40
Close: $51.31
Volume: 2,371,967
Advances: 22
Advances >=4%: 2
Daily Change: -1.28%
Dow: +0.01%
Nasdaq: -0.35%
S&P: +0.06%
Open: $51.71
High: $52.38
Low: $50.40
Close: $51.31
Volume: 2,371,967
Advances: 22
Advances >=4%: 2
Daily Change: -1.28%
Dow: +0.01%
Nasdaq: -0.35%
S&P: +0.06%
Wednesday, April 16, 2008
04/16/2008
Date: 04/16/2008
Open: $50.93
High: $52.42
Low: $50.27
Close: $51.98
Volume: 2,773,553
Advances: 95
Advances >=4%: 39
Daily Change: 3.68%
Dow: +2.08%
Nasdaq: +2.80%
S&P: +2.27%
Open: $50.93
High: $52.42
Low: $50.27
Close: $51.98
Volume: 2,773,553
Advances: 95
Advances >=4%: 39
Daily Change: 3.68%
Dow: +2.08%
Nasdaq: +2.80%
S&P: +2.27%
Tuesday, April 15, 2008
04/15/2008
Date: 04/15/2008
Open: $50.03
High: $50.88
Low: $49.04
Close: $50.14
Volume: 1,982,796
Advances: 69
Advances >=4%: 9
Daily Change: 1.06%
Dow: +0.49%
Nasdaq: +0.45%
S&P: +0.46%
Open: $50.03
High: $50.88
Low: $49.04
Close: $50.14
Volume: 1,982,796
Advances: 69
Advances >=4%: 9
Daily Change: 1.06%
Dow: +0.49%
Nasdaq: +0.45%
S&P: +0.46%
Monday, April 14, 2008
Sunday, April 13, 2008
Closing Price and Daily Range
The results of this week’s study really surprised me. Few things are more painful when trading an end-of-day system than to have a stock price drop substantially the morning of your entry. There is obviously no way to minimize this risk completely but anything to reduce the frequency of this would represent a tangible statistical edge, not to mention a major psychological advantage. Conventional wisdom suggest that a closing price in the upper percentages of a stock’s daily range is a sign of strength and narrowing trade selection to these stocks that closed strong could potentially offer a terrific technique to help accomplishing this.
These test will use our “standard” entry criteria discussed last week with the following criteria:
Average Volume = 10-day average not including today - Average(Vol,10,1).
Average Volume >= 100,000 shares
Today’s Volume >= AverageVolume * 2 (100% increase)
Today’s Close > Yesterday’s Close
In addition to this, I am calculating the daily range of each stock on the day of the breakout and will then run a series of tests where we take only closes that fall in the top X% of that daily range. The top 100% represents taking every trade while the top 10% represent only taking trades where the close is in the top 10% of the daily range.
For exits, we will use a simple 1, 5 and 20-day timed exit. As usual, we will run the test on three separate portfolios to increase our confidence in the robustness of the results.
Our primary evaluation ratio will again be our EDR ratio but we will also look at the two other evaluation ratios used previously on this blog. I acknowledge that it may be difficult for a new reader to comprehend my approach by starting here but rather than continuous overly redundant posts, I encourage anyone interested to read through the previous backtesting studies to flush out exactly what we are doing.
EDR=Expectancy per dollar risked. We’ve covered this plenty already but it is calculated by Average Trade/Average Loss.
EER=Efficient Expectancy Ratio. This is our EDR/Avg. Days in Winning trades. This number is meant to reveal the most efficient use if capital as it reveals expectancy per dollar risk per day in trade.
DDR= Drawdown ratio. This number is calculated by Net Profit/Maximum Drawdown. A higher number is better.
I will begin this week by posting the summary graphs followed by the raw data of the tests.
Summary Graphs:
Raw Data:
Conclusion:
If this does not highlight the advantages of backtesting an idea or strategy prior to implementation, I don’t know what does. Using such a strategy, only limiting EOD trade selection to those stocks that closed in the top 25% of their daily range, could have been disastrous. I say “could” because backtesting in no way predicts the future and this could start working terrific tomorrow. Personally however, I am not willing to bet my money on it.
The reduction in expectancy was substantial and consistent in all portfolios. Looking at the Nasdaq portfolio for example, the top 10% of trades when compared to the top 100% (all trades), had an expectancy decrease of 35% 1-day out, 27% 5-days out, and 17% 4-weeks later. I suspect this was perhaps once a profitable strategy but any edge has long been traded away. Skepticism towards conventional wisdom remains a valid strategy for capital preservation.
As we would expect with any entry criteria, the entry criteria itself has less and less of an impact as the time held increases. The underlying fundamentals of price movement ultimately have the largest impact on longer-term expectancy but even after 20-days, there are lingering affects from using this type of entry filter. I would not suggest one reject those stocks that close in the top 25% of their daily range. Often, these are the most powerful movers but limiting ones selection to these is clearly not an advantageous decision.
These test will use our “standard” entry criteria discussed last week with the following criteria:
Average Volume = 10-day average not including today - Average(Vol,10,1).
Average Volume >= 100,000 shares
Today’s Volume >= AverageVolume * 2 (100% increase)
Today’s Close > Yesterday’s Close
In addition to this, I am calculating the daily range of each stock on the day of the breakout and will then run a series of tests where we take only closes that fall in the top X% of that daily range. The top 100% represents taking every trade while the top 10% represent only taking trades where the close is in the top 10% of the daily range.
For exits, we will use a simple 1, 5 and 20-day timed exit. As usual, we will run the test on three separate portfolios to increase our confidence in the robustness of the results.
Our primary evaluation ratio will again be our EDR ratio but we will also look at the two other evaluation ratios used previously on this blog. I acknowledge that it may be difficult for a new reader to comprehend my approach by starting here but rather than continuous overly redundant posts, I encourage anyone interested to read through the previous backtesting studies to flush out exactly what we are doing.
EDR=Expectancy per dollar risked. We’ve covered this plenty already but it is calculated by Average Trade/Average Loss.
EER=Efficient Expectancy Ratio. This is our EDR/Avg. Days in Winning trades. This number is meant to reveal the most efficient use if capital as it reveals expectancy per dollar risk per day in trade.
DDR= Drawdown ratio. This number is calculated by Net Profit/Maximum Drawdown. A higher number is better.
I will begin this week by posting the summary graphs followed by the raw data of the tests.
Summary Graphs:
Raw Data:
Conclusion:
If this does not highlight the advantages of backtesting an idea or strategy prior to implementation, I don’t know what does. Using such a strategy, only limiting EOD trade selection to those stocks that closed in the top 25% of their daily range, could have been disastrous. I say “could” because backtesting in no way predicts the future and this could start working terrific tomorrow. Personally however, I am not willing to bet my money on it.
The reduction in expectancy was substantial and consistent in all portfolios. Looking at the Nasdaq portfolio for example, the top 10% of trades when compared to the top 100% (all trades), had an expectancy decrease of 35% 1-day out, 27% 5-days out, and 17% 4-weeks later. I suspect this was perhaps once a profitable strategy but any edge has long been traded away. Skepticism towards conventional wisdom remains a valid strategy for capital preservation.
As we would expect with any entry criteria, the entry criteria itself has less and less of an impact as the time held increases. The underlying fundamentals of price movement ultimately have the largest impact on longer-term expectancy but even after 20-days, there are lingering affects from using this type of entry filter. I would not suggest one reject those stocks that close in the top 25% of their daily range. Often, these are the most powerful movers but limiting ones selection to these is clearly not an advantageous decision.
Friday, April 11, 2008
04/11/2008
Date: 04/11/2008
Open: $49.81
High: $50.52
Low: $48.67
Close: $49.28
Volume: 1,960,857
Advances: 11
Advances >=4%: 3
Daily Change: -2.1%
Dow: -2.04%
Nasdaq: -2.61%
S&P: -2.04%
Open: $49.81
High: $50.52
Low: $48.67
Close: $49.28
Volume: 1,960,857
Advances: 11
Advances >=4%: 3
Daily Change: -2.1%
Dow: -2.04%
Nasdaq: -2.61%
S&P: -2.04%
Thursday, April 10, 2008
04/10/2008
Date: 04/10/2008
Open: $49.85
High: $50.93
Low: $49.04
Close: $50.34
Volume: 2,104,997
Advances: 73
Advances >=4%: 7
Daily Change: 1.02%
Dow: +0.44%
Nasdaq: +1.27%
S&P: +0.45%
Open: $49.85
High: $50.93
Low: $49.04
Close: $50.34
Volume: 2,104,997
Advances: 73
Advances >=4%: 7
Daily Change: 1.02%
Dow: +0.44%
Nasdaq: +1.27%
S&P: +0.45%
Wednesday, April 9, 2008
04/09/2008
Date: 04/09/2008
Open: $50.34
High: $51.10
Low: $49.09
Close: $49.84
Volume: 2,227,708
Advances: 29
Advances >=4%: 3
Daily Change: -0.82%
Dow: -0.39%
Nasdaq: -1.13%
S&P: -0.81%
Open: $50.34
High: $51.10
Low: $49.09
Close: $49.84
Volume: 2,227,708
Advances: 29
Advances >=4%: 3
Daily Change: -0.82%
Dow: -0.39%
Nasdaq: -1.13%
S&P: -0.81%
Tuesday, April 8, 2008
04/08/2008
Date: 04/08/2008
Open: $49.71
High: $50.89
Low: $49.13
Close: $50.25
Volume: 1,976,005
Advances: 61
Advances >=4%: 3
Daily Change: 0.38%
Dow: -0.29%
Nasdaq: -0.68%
S&P: -0.51%
Open: $49.71
High: $50.89
Low: $49.13
Close: $50.25
Volume: 1,976,005
Advances: 61
Advances >=4%: 3
Daily Change: 0.38%
Dow: -0.29%
Nasdaq: -0.68%
S&P: -0.51%
Monday, April 7, 2008
04/07/2008
Date: 4/07/2008
Open: $50.65
High: $51.48
Low: $49.48
Close: $50.06
Volume: 2,645,222
Advances: 71
Advances >=4%: 6
Daily Change: 0.61%
Dow: +0.02%
Nasdaq: -0.26%
S&P: +0.16%
Open: $50.65
High: $51.48
Low: $49.48
Close: $50.06
Volume: 2,645,222
Advances: 71
Advances >=4%: 6
Daily Change: 0.61%
Dow: +0.02%
Nasdaq: -0.26%
S&P: +0.16%
Sunday, April 6, 2008
Saturday, April 5, 2008
Does an ADX filter work?
This week I set out to determine if there was a way that an ADX filter could be incorporated into a breakout trading strategy that would increase expectancy in an unambiguous way. It seems logical that a system developed to take advantage of a trending market would benefit enormously from an indicator designed to tell us if we indeed had one on our hands.
I’ve also decided to change the standard entry criteria I use as the base for the tests on this blog to something I am comfortable revealing in its entirety. This will hopefully make everything more transparent for everyone. The goal for this was not to create a tradable entry system as much as a simple, generic breakout entry that would (a) take advantage of our volume test from last week, and (b) be simple enough to layer up and test additional criteria with.
The “standard” entry criteria are as follows:
Average Volume >= 100,000 shares
Today’s Volume >= AverageVolume * 2 (100% increase)
Today’s Close > Yesterday’s Close
Average volume is a 10-day average not including today - Average(Vol,10,1).
This is a simple volume breakout. If these 3 conditions are met, buy $1000 worth of shares on the following open with a market order. In all examples, I used a 14-period ADX as it is generally the “default” on most websites and charting software. There are several common ways of using an ADX filter and I tested five layered over the above entry criteria:
ADX > 20
ADX > 30
ADX > ADX 10 days ago
ADX > ADX 10 days ago * 1.5
ADX > 30 and ADX greater than ADX 10 days ago.
These represent the most common uses for the ADX and the basic concepts behind them is to A) buy if the ADX is above a certain level, B) buy is the ADX is rising, C) buy if there is a strong jump in the ADX, D) buy if the ADX is above a certain level and rising.
I also decided to test these with two exits. Confidence in our volume tests from last week was increased with similar behavior over multiple exit strategies so I decided to continue that theme. One exit was the fixed 8% protective stop with a 20% profit target we have used before. The second exit was a simple 1-month timed exit (21-days). This is an unclamped exit and should be more effective at revealing an increase in the average strength or magnitude of breakouts associated with use of an ADX filter, if they exists.
As usual, I will run our test on three separate portfolios of stocks in the hope that any results we see are confirmed over multiple portfolios as I am looking to add only tools with systemic advantages to my trading toolbox.
Last but not least, there are now three evaluation ratios we will now look at instead of the previous one. They are as follows:
EDR=Expectancy per dollar risked. We’ve covered this plenty already but it is calculated by Average Trade/Average Loss.
EER=Efficient Expectancy Ratio. This is our EDR/Avg. Days in Winning trades. This number is meant to reveal the most efficient use if capital as it reveals expectancy per dollar risk per day in trade.
DDR= Drawdown ratio. This number is calculated by Net Profit/Maximum Drawdown. A higher number is better.
Alright let’s get to it.
8% Protective + 20% Profit Target
I’ve also decided to change the standard entry criteria I use as the base for the tests on this blog to something I am comfortable revealing in its entirety. This will hopefully make everything more transparent for everyone. The goal for this was not to create a tradable entry system as much as a simple, generic breakout entry that would (a) take advantage of our volume test from last week, and (b) be simple enough to layer up and test additional criteria with.
The “standard” entry criteria are as follows:
Average Volume >= 100,000 shares
Today’s Volume >= AverageVolume * 2 (100% increase)
Today’s Close > Yesterday’s Close
Average volume is a 10-day average not including today - Average(Vol,10,1).
This is a simple volume breakout. If these 3 conditions are met, buy $1000 worth of shares on the following open with a market order. In all examples, I used a 14-period ADX as it is generally the “default” on most websites and charting software. There are several common ways of using an ADX filter and I tested five layered over the above entry criteria:
ADX > 20
ADX > 30
ADX > ADX 10 days ago
ADX > ADX 10 days ago * 1.5
ADX > 30 and ADX greater than ADX 10 days ago.
These represent the most common uses for the ADX and the basic concepts behind them is to A) buy if the ADX is above a certain level, B) buy is the ADX is rising, C) buy if there is a strong jump in the ADX, D) buy if the ADX is above a certain level and rising.
I also decided to test these with two exits. Confidence in our volume tests from last week was increased with similar behavior over multiple exit strategies so I decided to continue that theme. One exit was the fixed 8% protective stop with a 20% profit target we have used before. The second exit was a simple 1-month timed exit (21-days). This is an unclamped exit and should be more effective at revealing an increase in the average strength or magnitude of breakouts associated with use of an ADX filter, if they exists.
As usual, I will run our test on three separate portfolios of stocks in the hope that any results we see are confirmed over multiple portfolios as I am looking to add only tools with systemic advantages to my trading toolbox.
Last but not least, there are now three evaluation ratios we will now look at instead of the previous one. They are as follows:
EDR=Expectancy per dollar risked. We’ve covered this plenty already but it is calculated by Average Trade/Average Loss.
EER=Efficient Expectancy Ratio. This is our EDR/Avg. Days in Winning trades. This number is meant to reveal the most efficient use if capital as it reveals expectancy per dollar risk per day in trade.
DDR= Drawdown ratio. This number is calculated by Net Profit/Maximum Drawdown. A higher number is better.
Alright let’s get to it.
8% Protective + 20% Profit Target
21-day Timed Exit
Conclusions
I started this section off by attempting to write a very detailed analysis of what was going on. The fact of the matter is that the results are the results and they are there for everyone to see and analyze for themselves. Anything I write is my interpretation of what I am seeing and others will undoubtedly see something else. Unlike many of the previous tests run on this blog, the advantages here are much more subtle and much less consistent.
My own conclusion is that unfortunately, the ADX is not something I personally feel comfortable using as a filter for significantly improving the reliability or expectancy of a breakout system. There are countless people out there who use the ADX, many of whom probably with some degree of success, but the test for me do not reveal a consistency or magnitude of improvement I’m comfortable with.
Friday, April 4, 2008
4/04/2008
Date: 4/04/2008
Open: $49.50
High: $50.66
Low: $48.71
Close: $49.76
Volume: 2,616,662
Advances: 71
Advances >=4%: 11
Daily Change: 0.96%
Dow: -0.13%
Nasdaq: +0.33%
S&P: +0.08%
Open: $49.50
High: $50.66
Low: $48.71
Close: $49.76
Volume: 2,616,662
Advances: 71
Advances >=4%: 11
Daily Change: 0.96%
Dow: -0.13%
Nasdaq: +0.33%
S&P: +0.08%
Thursday, April 3, 2008
4/03/2008
Date: 4/03/2008
Open: $48.64
High: $49.92
Low: $48.07
Close: $49.29
Volume: 2,730,707
Advances: 66
Advances >=4%: 11
Daily Change: 0.87%
Dow: 0.16%
Nasdaq: 0.08%
S&P: 0.13%
Open: $48.64
High: $49.92
Low: $48.07
Close: $49.29
Volume: 2,730,707
Advances: 66
Advances >=4%: 11
Daily Change: 0.87%
Dow: 0.16%
Nasdaq: 0.08%
S&P: 0.13%
Wednesday, April 2, 2008
Trading Cost Calculations
I want to take a moment to remind everyone that the tests run on this blog do not include slippage and broker’s fees. I will only add slippage and transaction costs when testing money management and position sizing strategies in the future.
An easy way to calculate broker’s fees is to subtract your round-trip trading cost from the average trade (win & loss) figure given on the summary report. Remember that these test use $1000 lots so adjust your numbers accordingly with your typical trade size. You will note that MANY of the tests we have run so far would turn to a negative expectancy if you use any of the ~$20 round trip brokers. Please keep this in mind as you review and consider these results. Many of the 8% trailing stop tests generate more in broker's fees than net profit.
To drive this point home, I've decided to use the following example. The system tested here, with the 8% protective+20% profit target, generated 7678 trades over a 10 year period. The difference in commisions alone between TD Ameritrade (for example) and Interactive Brokers would have bought you this...
Aston Martin V8 Vantage
(7678*$20)-(7678*$2)=$138,204 (asuming lots under 200 shares)
An easy way to calculate broker’s fees is to subtract your round-trip trading cost from the average trade (win & loss) figure given on the summary report. Remember that these test use $1000 lots so adjust your numbers accordingly with your typical trade size. You will note that MANY of the tests we have run so far would turn to a negative expectancy if you use any of the ~$20 round trip brokers. Please keep this in mind as you review and consider these results. Many of the 8% trailing stop tests generate more in broker's fees than net profit.
To drive this point home, I've decided to use the following example. The system tested here, with the 8% protective+20% profit target, generated 7678 trades over a 10 year period. The difference in commisions alone between TD Ameritrade (for example) and Interactive Brokers would have bought you this...
Aston Martin V8 Vantage(7678*$20)-(7678*$2)=$138,204 (asuming lots under 200 shares)
4/02/2008
Date: 4/02/2008
Open: $48.60
High: $49.68
Low: $47.77
Close: $48.86
Volume: 2,688,676
Advances: 63
Advances >=4%: 6
Daily Change: 0.59%
Dow: -0.38%
Nasdaq: -0.06%
S&P: -0.19%
Open: $48.60
High: $49.68
Low: $47.77
Close: $48.86
Volume: 2,688,676
Advances: 63
Advances >=4%: 6
Daily Change: 0.59%
Dow: -0.38%
Nasdaq: -0.06%
S&P: -0.19%
Tuesday, April 1, 2008
4/01/2008
Date: 4/01/2008
Open: $47.73
High: $49.07
Low: $46.74
Close: $48.58
Volume: 2,693,675
Advances: 82
Advances >=4%: 29
Daily Change: 2.59%
Dow: 3.19%
Nasdaq: 3.67%
S&P: 3.59%
Open: $47.73
High: $49.07
Low: $46.74
Close: $48.58
Volume: 2,693,675
Advances: 82
Advances >=4%: 29
Daily Change: 2.59%
Dow: 3.19%
Nasdaq: 3.67%
S&P: 3.59%
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