Exploring Breakouts: Part 2

411 views

Continuing the quest to develop a decent breakout system…

Be sure to read Part 1 for the introductory information. Part 2 (this article) will jump right into things with no background information.

The Rules:

  • Buy the next open after a stock has closed at a new N-day high
  • Hold the stock for X days, selling at the close
  • System can hold a maximum of 20 stocks with capital allocated equally among all
  • If there are more stocks than cash, the system ranks picks by dividing volume by the 50 day average volume. Highest ranked stocks are purchased until the system runs out of cash
  • Only stocks with a close > $5.00/share and 10 day average volume > 300,000 are eligible. No OTCBB.
  • Delisted data was used (no survivorship bias)
  • Test period is from 1.1.2001 to 1.1.2009

Let’s look at the results of the optimization:

In this second test, I tested N day highs of 50 -100 in increments of 5 against an X bar exit of 50-100 bars in increments of 5 bars.

The graph above shows that there are two areas which show promise. The only problem is that the area on the right hand side requires holding the trades almost twice as long as they are held on the left hand side to achieve similar gains. However, the right hand side, representing buying a stock after making a new 90 day high and holding it for more than 95 days appears to be less peaky and therefore more robust.

The graph above shows that the greater the N day high, the greater the potential average trade. I suspect the trade off here is to find a balance between opportunity and potential profit. It is likely that the greater the N day high, the fewer the number of stocks (less opportunity) meeting that criteria. If there is not enough opportunity, the system may not be fully invested, and this will hurt performance.

Note the circled area in the graph above. It is not very smooth, while the raised area to the right that corresponds with 85 bars or better, is more rounded and less peaky. It is likely that holding for greater than 85 days will result in more robust and consistent results.

The Importance of Profit/Bar

The above graphs show that holding trades longer may result in similar but possibly more robust results in real-time than holding them for a shorter amount of time. In order to accurately compare results, we want to divide the average trade by the number of bars the trade was held.

For example, if we use what looks to be the optimum settings (based on the above graphs) of an N day high of 90 and a hold of 65 bars, the average trade is 4.15%. We then divide that by 65 to get 0.063% of profit per day.

Using what appears to be the more robust criteria of an N day high of 85 with a hold of 90 bars yields an average trade of 3.08% and a Profit/Bar of 0.0342%.

Next Up- Ranking

Next, I will re-run these tests but will try out different ranking methods. I’m curious to see if they make much difference at this early stage of testing.

Bonus

Here is the equity curve generated from these optimized inputs: N day high of 90 and a hold of 65 bars.

This equity curve shows a compound annual return of 15.55%

Exploring Breakouts: Part 1

1,542 views

What makes a good breakout? I aim to find out…

It seems that everyone loves breakouts. Perhaps it is because of IBD or the Turtle Traders. Or maybe it is because it is easier to buy a stock that is going up, rather than one that is going down. Whatever the reason, breakouts are consistently featured across a wide range of stock trading outlets on the internet, on the TV, and in the print media.

But do they work? And if they do work, do some work better than others?

Let’s start simple…

The breakout, in the most simplest of forms, is a stock that makes a new high. A simple breakout system can be one that buys stocks making a new N-day high, and holds them for X number of bars. Since I believe that simple systems are generally more robust than complex systems, this simple breakout system is what I will start testing.

The Rules:

  • Buy the next open after a stock has closed at a new N-day high
  • Hold the stock for X days, selling at the close
  • System can hold a maximum of 20 stocks
  • If there are more stocks than cash, the system ranks picks by dividing volume by the 50 day average volume. Highest ranked stocks are purchased until the system runs out of cash
  • Only stocks with a close > $5.00/share and 10 day average volume > 300,000 are eligible. No OTCBB.
  • Delisted data was used (no survivorship bias)
  • Test period is from 1.1.2001 to 1.1.2009

Let’s look at the results of the optimization:

In this first test, I tested N day highs of 10 – 50 in increments of 10 against an X bar exit of 0 – 50 bars in increments of 5 bars.

Observations:

I circled the areas we want to focus on. It appears that a breakout making a new 30 day high and using a 30 day exit might show some promise. However, the blue water line is at approximately 1%. This means that on average, these trades are making ~1.5% after being held for 30 trading days. Really, this is not very good. To contrast, PDS average trades are better than 1% with trades being held on average for only 5 trading days.

There is a ton of work to do here. The next optimization run will test breakouts of a 50 – 100 day high against an exit of 50 – 100 days.

Also, the ranking mechanism will have to be tested. As I posted here, there are a variety of ways to rank breakouts. Beyond ranking, there are stops, position-sizing, etc. and even more to be considered, and that is only for a simple breakout making a new N day high. Imagine the complexity if we start looking at breakouts from certain patterns…

For now, I will attempt to establish baseline variables for a simple breakout system.

Bonus:

Here is the equity curve generated from the system using a 30 / 30 setup: Buy stocks making a new 30 day high and sell after holding 30 trading days.

Based on this equity curve, a moving average filter will eventually be employed in an attempt to reduce that huge drawdown. Results above resulted in a compound annual return of 11.17%.

I use AmiBroker to generate most of the charts and graphs that I use and Norgate Premium Data for my delisted and end-of-day data.

The Market is Going To Rip

29 views

Assuming Libya does not get much worse tomorrow, look for a significant bounce. Today’s high volume doji tells me a reversal is in the works.

Here are 4 great breakouts for tomorrow:

BMO

HSY

PKI

OCR

What Makes a Breakout a Great Breakout?

181 views

In order to backtest a breakout system, I need to be able to rank each day’s breakouts so that when the system has cash available for a new position, it takes only the top-ranked stocks. I have my suspicions about what makes a great breakout, but I’m curious as to what other traders believe.

As I begin backtesting breakouts, I’ll cycle through the factors represented in the poll to see whether the crowd gets it right, or not. If there are other factors that can be used to rank breakouts, I’d love to hear about them in the comments. I can add them to the backtesting.

[polldaddy poll=4588227]

The Secret to Trading Breakouts…

154 views

In contrast to more obscure patterns, breakouts can be easy to find. There are various online resources, and even traders with no programming experience or fancy scanning software can get evening breakout reports from sites like Top Breakout Stocks. (Great site, by the way.)

Like many traders, I got started trading breakouts after discovering William O’Neil and Investor’s Business Daily. It wasn’t long before I realized that trading breakouts was hit and miss. What O’Neil used to preach (not sure if he still does) about needing to cut losses at -8% and taking profits at +20% was very important because many breakouts fail. If your first 3 breakouts fail and you lose -8% each, your 4th breakout needs to be a successful trade with a gain of more than +25% in order to get back to break-even. In short, breakout trading tends to have low win rates (around 40% or so), and this makes trading them very difficult, in my opinion.

Breakout trading is complex enough that sites featuring breakouts seldom discuss sell signals, only entries. In fact, I don’t recall ever seeing a web site that publishes sell signals for open breakout trades. I’m not saying they don’t exist; they just aren’t very common.

Why is it that we don’t often hear about the exit strategy when trading breakouts? The answer is simple…

When trading breakouts, you will not be profitable without a robust exit strategy. The secret to trading breakouts is the exit…

I have dabbled with designing breakout systems over the years, and have always given up on them. I am currently dabbling again. Here are some setups for tomorrow. The entry setup has several requirements. A simple exit that will work for these is a 10 day time stop coupled with a 15% profit stop.

I will update the blog over the coming weeks and months as I work towards a robust breakout system.

NTT

OGE

JAH

FICO

HLX

RJA

APC

ES

CLF

WMB

NANO

NVDA

Exploring Breakouts: Part 2

411 views

Continuing the quest to develop a decent breakout system…

Be sure to read Part 1 for the introductory information. Part 2 (this article) will jump right into things with no background information.

The Rules:

  • Buy the next open after a stock has closed at a new N-day high
  • Hold the stock for X days, selling at the close
  • System can hold a maximum of 20 stocks with capital allocated equally among all
  • If there are more stocks than cash, the system ranks picks by dividing volume by the 50 day average volume. Highest ranked stocks are purchased until the system runs out of cash
  • Only stocks with a close > $5.00/share and 10 day average volume > 300,000 are eligible. No OTCBB.
  • Delisted data was used (no survivorship bias)
  • Test period is from 1.1.2001 to 1.1.2009

Let’s look at the results of the optimization:

In this second test, I tested N day highs of 50 -100 in increments of 5 against an X bar exit of 50-100 bars in increments of 5 bars.

The graph above shows that there are two areas which show promise. The only problem is that the area on the right hand side requires holding the trades almost twice as long as they are held on the left hand side to achieve similar gains. However, the right hand side, representing buying a stock after making a new 90 day high and holding it for more than 95 days appears to be less peaky and therefore more robust.

The graph above shows that the greater the N day high, the greater the potential average trade. I suspect the trade off here is to find a balance between opportunity and potential profit. It is likely that the greater the N day high, the fewer the number of stocks (less opportunity) meeting that criteria. If there is not enough opportunity, the system may not be fully invested, and this will hurt performance.

Note the circled area in the graph above. It is not very smooth, while the raised area to the right that corresponds with 85 bars or better, is more rounded and less peaky. It is likely that holding for greater than 85 days will result in more robust and consistent results.

The Importance of Profit/Bar

The above graphs show that holding trades longer may result in similar but possibly more robust results in real-time than holding them for a shorter amount of time. In order to accurately compare results, we want to divide the average trade by the number of bars the trade was held.

For example, if we use what looks to be the optimum settings (based on the above graphs) of an N day high of 90 and a hold of 65 bars, the average trade is 4.15%. We then divide that by 65 to get 0.063% of profit per day.

Using what appears to be the more robust criteria of an N day high of 85 with a hold of 90 bars yields an average trade of 3.08% and a Profit/Bar of 0.0342%.

Next Up- Ranking

Next, I will re-run these tests but will try out different ranking methods. I’m curious to see if they make much difference at this early stage of testing.

Bonus

Here is the equity curve generated from these optimized inputs: N day high of 90 and a hold of 65 bars.

This equity curve shows a compound annual return of 15.55%

Exploring Breakouts: Part 1

1,542 views

What makes a good breakout? I aim to find out…

It seems that everyone loves breakouts. Perhaps it is because of IBD or the Turtle Traders. Or maybe it is because it is easier to buy a stock that is going up, rather than one that is going down. Whatever the reason, breakouts are consistently featured across a wide range of stock trading outlets on the internet, on the TV, and in the print media.

But do they work? And if they do work, do some work better than others?

Let’s start simple…

The breakout, in the most simplest of forms, is a stock that makes a new high. A simple breakout system can be one that buys stocks making a new N-day high, and holds them for X number of bars. Since I believe that simple systems are generally more robust than complex systems, this simple breakout system is what I will start testing.

The Rules:

  • Buy the next open after a stock has closed at a new N-day high
  • Hold the stock for X days, selling at the close
  • System can hold a maximum of 20 stocks
  • If there are more stocks than cash, the system ranks picks by dividing volume by the 50 day average volume. Highest ranked stocks are purchased until the system runs out of cash
  • Only stocks with a close > $5.00/share and 10 day average volume > 300,000 are eligible. No OTCBB.
  • Delisted data was used (no survivorship bias)
  • Test period is from 1.1.2001 to 1.1.2009

Let’s look at the results of the optimization:

In this first test, I tested N day highs of 10 – 50 in increments of 10 against an X bar exit of 0 – 50 bars in increments of 5 bars.

Observations:

I circled the areas we want to focus on. It appears that a breakout making a new 30 day high and using a 30 day exit might show some promise. However, the blue water line is at approximately 1%. This means that on average, these trades are making ~1.5% after being held for 30 trading days. Really, this is not very good. To contrast, PDS average trades are better than 1% with trades being held on average for only 5 trading days.

There is a ton of work to do here. The next optimization run will test breakouts of a 50 – 100 day high against an exit of 50 – 100 days.

Also, the ranking mechanism will have to be tested. As I posted here, there are a variety of ways to rank breakouts. Beyond ranking, there are stops, position-sizing, etc. and even more to be considered, and that is only for a simple breakout making a new N day high. Imagine the complexity if we start looking at breakouts from certain patterns…

For now, I will attempt to establish baseline variables for a simple breakout system.

Bonus:

Here is the equity curve generated from the system using a 30 / 30 setup: Buy stocks making a new 30 day high and sell after holding 30 trading days.

Based on this equity curve, a moving average filter will eventually be employed in an attempt to reduce that huge drawdown. Results above resulted in a compound annual return of 11.17%.

I use AmiBroker to generate most of the charts and graphs that I use and Norgate Premium Data for my delisted and end-of-day data.

The Market is Going To Rip

29 views

Assuming Libya does not get much worse tomorrow, look for a significant bounce. Today’s high volume doji tells me a reversal is in the works.

Here are 4 great breakouts for tomorrow:

BMO

HSY

PKI

OCR

What Makes a Breakout a Great Breakout?

181 views

In order to backtest a breakout system, I need to be able to rank each day’s breakouts so that when the system has cash available for a new position, it takes only the top-ranked stocks. I have my suspicions about what makes a great breakout, but I’m curious as to what other traders believe.

As I begin backtesting breakouts, I’ll cycle through the factors represented in the poll to see whether the crowd gets it right, or not. If there are other factors that can be used to rank breakouts, I’d love to hear about them in the comments. I can add them to the backtesting.

[polldaddy poll=4588227]

The Secret to Trading Breakouts…

154 views

In contrast to more obscure patterns, breakouts can be easy to find. There are various online resources, and even traders with no programming experience or fancy scanning software can get evening breakout reports from sites like Top Breakout Stocks. (Great site, by the way.)

Like many traders, I got started trading breakouts after discovering William O’Neil and Investor’s Business Daily. It wasn’t long before I realized that trading breakouts was hit and miss. What O’Neil used to preach (not sure if he still does) about needing to cut losses at -8% and taking profits at +20% was very important because many breakouts fail. If your first 3 breakouts fail and you lose -8% each, your 4th breakout needs to be a successful trade with a gain of more than +25% in order to get back to break-even. In short, breakout trading tends to have low win rates (around 40% or so), and this makes trading them very difficult, in my opinion.

Breakout trading is complex enough that sites featuring breakouts seldom discuss sell signals, only entries. In fact, I don’t recall ever seeing a web site that publishes sell signals for open breakout trades. I’m not saying they don’t exist; they just aren’t very common.

Why is it that we don’t often hear about the exit strategy when trading breakouts? The answer is simple…

When trading breakouts, you will not be profitable without a robust exit strategy. The secret to trading breakouts is the exit…

I have dabbled with designing breakout systems over the years, and have always given up on them. I am currently dabbling again. Here are some setups for tomorrow. The entry setup has several requirements. A simple exit that will work for these is a 10 day time stop coupled with a 15% profit stop.

I will update the blog over the coming weeks and months as I work towards a robust breakout system.

NTT

OGE

JAH

FICO

HLX

RJA

APC

ES

CLF

WMB

NANO

NVDA