FastBreak Pro Version 6.x www.edge-ware.
Disclaimer and License Agreement The information that FastBreak Pro provides is only part of the information needed for a good investment program. Consult your investment representative before buying or selling any investment. Read the prospectus to determine whether an investment meets your objectives. EDGE WARE, INC. DOES NOT RECOMMEND SPECIFIC INVESTMENTS SUITABLE FOR YOUR PERSONAL OBJECTIVES BUT IS LIMITED TO PROVIDING INFORMATION FROM THE BEST AVAILABLE SOURCES.
Table of Contents 1.0 Preface ...................................................................................................... 4 2.0 Introduction .............................................................................................. 5 3.0 Upgrade Notes .......................................................................................... 6 4.0 How FastBreak Pro is Different from Standard FastBreak.................... 14 5.0 Installation .....................................................
1.0 Preface Note: A PDF copy of this manual is on your installation disk. We recommend you put a copy on your computer so you will always have a copy available. FastBreak Pro has the look, feel and all the functionality of Standard FastBreak. Where FastBreak Pro is different is that it has the automated system optimizer and builder. The Standard Manual contains explanations and details of all the functions common to both versions.
2.0 Introduction Edge Ware, Inc. released the initial Standard FastBreak version in early 1996 to allow investors to design, evaluate and trade fund rotation investment strategies. An early version of Standard FastBreak was reviewed in the July 1999 issue of Technical Analysis of STOCKS & COMMODITIES, the premier technical analysis investment magazine. Their review, in part, said, “This is easily the most elaborate fund switching software we’ve run across, and it’d be worth the time to check it out.
3.0 Upgrade Notes Maintaining Existing FastBreak Trading Strategies If you have existing FastBreak strategies that you like we recommend that you keep the old version of FastBreak on your computer until you have verified that the strategies produce the same results with the new version. Prior to installing the new version of FastBreak go to the folder where the existing version is located, typically ftbreakp for Pro users, and find the file ftbreakp.exe. Rename this file ftbreakpVx.
build systems that are complementary to traditional FastBreak systems that always buy into strength. This will become clear as each of the new options is explained. Note: The new options will only work with Linear Slope ranking. We will give only a brief overview here in the upgrade notes. More information can be found later in this manual, and details on the new functions can be found in the Appendix in the Standard FastBreak manual.
Release notes for FastBreak Pro Version 6.3 Version 6.3 allows a user to add FNU and Detail files when the best generation systems (DFT files) are saved. Read the “Saving Strategies” section at the end of Chapter 8 to understand how you can take advantage of this new option to more quickly evaluate the ten best trading systems found by the optimizer. It will allow you to quickly compare the equity curves of the top ten best systems. Changes in Version 6.
Details of the Trendline algorithm is provided in the Appendix A of the Standard FastBreak manual, and issues to consider when using Trendlines with the optimizer are discussed in Appendix A of this manual. NOTE: The algorithm to determine trendlines is very computer time intensive. You will notice a long delay at the beginning of the optimization as trendlines are calculated for all trading family members. If the trading family is large, i.e.
Changes in Version 5 The following list of changes covers upgrades from Version 4 to Version 5. Some users may be upgrading from very old versions, and a section follows to cover upgrades from Version 3. You may ask how Version 5 of FastBreak Pro is different from previous versions and if you should reread the manual. The answer is that the changes are extensive and we suggest you read the entire manual to understand the enhancements.
often fail resulting in a whipsaw trades. We saw the need for market timing signals that would keep the trading system out of the very worst of markets. There are numerous market timing signals available but so many of these are not robust and fail the test of time. Also, we wanted to develop our own signals that met our needs, e.g., switches per year, drawdown, markets traded etc. o One disadvantage of the many market signals available is that they are developed for a specific index, e.g., S&P 500 Index.
minimum holding period value. This is now very similar to setting the top % to zero percent. One difference is that if more than one fund can be sold on a given day the Harnsberger option will sell the weakest (as measured by Sell ranking) fund. We now put an H in the Why Detail file column to indicate a Harnsberger sell. Stop loss using a short/long Exponential Moving Average (EMA) crossover. This is similar to the current EMA stop except that the fund NAV is smoothed with a short term EMA.
users have the requirement to hold a fund for a fixed number of days after purchase. They can now start a stop after this number of days. Ability to search the Buy and Sell ranking list by fund symbol. Some users have very large trading families and it is difficult to locate a particular issue in the ranking list. This option allows the user to do an efficient search for the fund symbol.
4.0 How FastBreak Pro is Different from Standard FastBreak Our intent when we designed FastBreak Pro was to automate development of mechanical trading systems. We wanted to provide the capability to build very complex strategies while taking the “grunt work” out of the development process. Edge Ware, Inc. believes that mechanical trading systems are appropriate for most investors, both professional and individual.
to try, and this is why FastBreak Pro uses a very sophisticated genetic algorithm (GA) to evolve the parameter choices. Determining optimized parameters that maximize your investment objectives is only part of the problem. Trading system developers must constantly be wary of “overoptimization” or “curve-fitting” of parameters. FastBreak Pro avoids over-optimization by using various techniques, but the most important technique is automated out-of-sample testing.
5.0 Installation New users should first read the Standard FastBreak manual supplied with your purchase. That manual describes all the parameters and options available and how to operate the basic functionality. It is important that you understand how the various options and parameters in FastBreak Pro operate. This supplemental manual focuses on the automated optimization process in FastBreak Pro. FastBreak Pro installs exactly like the standard version of FastBreak.
6.0 Technical Support and Upgrades Note: Do not call Investors FastTrack for technical support. Do not use the 800 order line number for technical support. This is a commercial order line that only takes orders and they are not equipped to answer any questions. Any messages left with the order line will not be returned. Please read this entire manual and check the FAQ chapter before asking for support. We have tried to make this software and documentation as user-friendly as possible.
Upgrades We provide minor upgrades to FastBreak on our web site, and if you encounter an error, we suggest you download the latest version of the software because this will often solve the problem. The Edge Ware Internet Web site (www.edge-ware.com) always has the latest version for download. FastBreak is constantly improving, and we try very hard to get those improvements in the hands of our users as fast as possible. As we make changes new versions are often placed on our web site for free downloading.
7.0 FastBreak Pro Operation We recommend that you read this manual in the order it was written; however, if you have experience with Standard FastBreak or just can’t wait to see the program in operation, go to the Examples chapter. Note: The way FastBreak Pro looks on your computer may appear slightly different than the views in this manual. This is the result of screen resolution differences or you may have a newer version of the software.
To switch back to the “Standard” FastBreak screens described in the standard manual use the icon on the far right of the icon tool bar: The following icons are used to control the standard FastBreak options.
2nd Note: the Optimize Family option is not available when using trendline Stops or Buy filters. See Appendix A for details. To prevent over-optimization of the trading family, enter a Minimum Family size value: This option will keep a reasonable number of funds in your trading family and prevent finding a final optimized trading family that has too few funds to work well in the future. The minimum family size is the lower limit on your trading family.
Most ETFs have very short histories. FastBreak assumes historical data starts on 9/1/1988 (earliest date in FastTrack database) to adjust the start date. If you use a trading family of funds, stocks that generally don’t have a long history you will need to adjust the IS Start Date to a much later date. This is easy to do by following these steps: 1. Enter all your parameters and let FastBreak adjust the IS Start Date 2. Note how long the IS Start Date occurs after 9/1/1988.
If you want to try Buy and Sell Using Rank, you would check the box and this would indicate to try that parameter option. Next, FastBreak Pro needs a range of parameters to try. In the above example, FastBreak will try Buy Ranking parameters between 10 and 95 days, and Sell Ranking parameters between 10 and 95 days. During optimization FastBreak Pro will search this range to find the optimum set of parameters. Note: The first range of text boxes is listed at Parm1 and the second range of boxes as Parm2.
When using the (NC) alpha ranking method, you need to enter the alpha index to use. The default is the S&P 500 (SP-CP). Short EMA/Long EMA Users of earlier versions of FastBreak Pro found that the optimizer often found an optimum parameter in which the Short EMA was actually a larger value than the Long EMA. This happened because the optimizer found that buying the weakest funds was often the best solution historically. This can be compared to the “buy the dips” technique of the late 1990s.
If you check the Correlation box, FastBreak Pro will try a maximum correlation, between funds to hold, for some strategies: The optimizer will try to find an optimum maximum correlation value along with an optimum period to calculate the correlation values. The best strategies that are found may or may not have the correlation option activated.
You can force FastBreak Pro not to use the option, to use the option, or allow FastBreak Pro to optimize whether to use the option. This option is very effective, and we recommend that you check the Yes box to always use the option. To consider using the BAT function use the following screen options: The parameters and control of the BAT option is very similar to BOOM. The default parameters are reasonable and shouldn’t be changed.
The brokerage STRF minimum holding period, Short Loss and Delay values are set to the user defined values, and these parameters are described in the standard FastBreak manual. To have the optimizer determine the number of funds to hold to meet your performance parameters use the following: In this example, the optimizer will determine if holding 1, 2, or 3 funds is best. If you know you want to hold a specific number of funds, put that number in both range boxes.
If you use Yes, the optimizer will always try the adjustment option. If you check Optimize, the optimizer will “consider” using this functionality. See the standard manual for complete details on this option. If you decide to use the function, you will need to input the Adjustment Index (the default is SP-CP, the S&P 500 Index) as well as ranges for the adjustment factors and the EMA ranges. Remember, an adjustment factor less than 1.
logarithmic and linear trendline options for Buy filters and sell Stops. If the No radio button is chosen then only linear trendlines will be used. If the Optimize option is selected then the optimizer will try both logarithmic and linear trendlines to determine which works best.
Stop Loss Click this icon to bring up the stop parameters page: Stop Begin Day This option is used in the optimization process to suspend all Stops for a user defined period of days after a fund is purchased. We added this feature for a couple of reasons. One, we have users who use fund families that absolutely prevent exiting a fund for a fixed number of days, e.g., 7 and 30 days are quite common, after a fund is purchased.
a minimum number of calendar days is reached. The option is at the top of the screen where Stop optimization ranges are set. There is a single value in the text box. In the above example using 30 would deactivate ALL stops until 30 days after a fund is purchased. The default value is 1 day, which will make all activated stops effective on the day the fund is purchased. Note: A user needs to set the minimum value in the User Min Hold period range to a similar value.
You are not required to use the second period. If you want a single stop value to be found for the entire time period a fund is held, check only the first box and put a large value, e.g., 9999, in both date range fields: Note: It is very important that you understand this concept. Many users have only checked the first stop range and accepted the default Day Range of 10 to 50 days. The effect of this is that the optimizer may select a stop but the stop gets turned off somewhere between 10 and 50 days.
Buy Filters Screen Click on this icon to bring up the Buy Filters screen: Buy filters are checks that can be applied to a fund prior to purchase. See the Standard manual for a complete description of all the available options. To consider a Rate of Return (ROR) Filter on any fund purchased use the following: In this example, annualized rates of return from 4% per year to 10% per year will be tested. The rates of return will be calculated using day ranges from 20 to 40 days.
ROR is to be calculated. For example, FastBreak may determine that the fund to be purchased should be increasing at the rate of at least 8% per year measured over the most recent 31 days. To consider a Parabolic Buy Filter use the following: The guidance for this option is the same as the ROR buy filter. To consider an Exponential Moving Average Buy Filter use the following: In this example, EMA buy filter values between 25 and 100 market days will be considered.
wants to force this filter to be used the Force Use box can be checked. This will make every strategy that the optimizer tries use this option. If the Force Use box is checked, it does not matter if the Correlation Buy Filter box is checked or not. The user may want to force the use of this option if the strategy developed is to have a maximum correlation with a particular market index (See the Genetic Algorithm Screen options soon to be covered).
Genetic Algorithm Screen Note: To better understand the following discussion you may want to go to Appendix A and read the discussion on Genetic Algorithms (GA). To bring up the Genetic Algorithm and investment criteria screen, click the following icon: This screen is used to select the nature of the strategy to be optimized and customize the GA parameters.
Only one of these three parameters can be selected for optimization using the radio buttons. If a parameter is not selected for optimization, FastBreak Pro will try to build a strategy that is acceptable to the user for the other two criteria. You must put a value other than zero into the text box for the non-optimized criteria if you want FastBreak Pro to recognize it.
some genetic algorithm books, but we have not found these large population sizes to result in improved system performance using the 50% Survivor Selection Percentage (see below). It may be that the Survivor Selection Percentage needs to be made substantially smaller, e.g., 25%, to prevent “dilution” of the gene pool. This is an area for future study. 2. You can specify population sizes by entering a value in the Population # field.
described in the Appendix. Note: Activation of the Maximize Robustness option will triple run time; however, we believe it is critical to building good trading systems. If robustness is not activated, the optimized trading systems are very susceptible to overoptimization. We have found that, under some circumstances, strategies with more stop loss and buy filters options activated can lead to non-robust strategies.
database can be used. Note: If using the Minimize Beta option, the Beta Buy Filter should also be used on the Buy Filter screen. For example, if a user wants a strategy that has a maximum beta of 1.5, then a range of 1.0 to 2.0 could be used in the Beta Buy Filter range. The reason that a range can be used rather than just forcing a Beta buy filter of 1.5 is that if the strategy holds many funds, individual funds may have beta values greater than 1.
The information in this file will be covered later when the optimizer is covered. Using this option can result in quite a large file. Use with care. To set the maximum number of generations to be tested, use the following field: A typical value is 15 to 25 generations. When the FastBreak Pro optimizer reaches this value, it will stop. Note: If a Restart file (described later) is reloaded, this value will be ignored in the restart.
FastBreak Pro will look at the Weight% values you have entered and sum them, in the case of our example that would be 80%. FastBreak then assumes the new system to be built will have the remaining 20% weighting (20%= 100% - 80%). You can use one or two existing systems. Just check the box next to the System Name text box to tell FastBreak Pro which system(s) to use.
8.0 Running FastBreak Pro Optimization The GA optimizer works interactively with a special version of Standard FastBreak. Standard FastBreak provides the evaluation of strategies that are built by the GA part of the software. The following information will be clearer after you have run the examples.
The list order for both lists are based on “Adjusted” performance (Adj %). This performance will be based on the option for optimization that the user has selected, i.e., annual return, UPI, or MDD. The actual performance is adjusted according to how well a strategy meets the user criteria, i.e., MDD, UPI, Switches per Year, maximum beta, and robustness. The actual performance for each strategy is shown in other columns: compounded annual performance, UPI, MDD, and Switches per year.
E P R C B X T EMA Buy Filter Parabolic Buy Filter RSI Buy Filter Correlation Buy Filter Beta Buy Filter EMA Crossover Buy Filter Trendline Buy Filter B E Adjust Beta Buy Filter Adjust EMA Buy Filter When you see a “Y” in a column, this means an option was activated for this strategy and “N” indicates the option was not activated. Note: If you are using the Trendline options rather than just a simple “Y” or “N” in the trendline columns there can be an “L” in the column to provide additional information.
For example, here are the graphs for Annual return, MDD, UPI and robustness: 46
Notice that there are two lines on each graph. One line is for the #1 strategy identified by FastBreak Pro (based on Adjusted performance in the Best Results screen) and the other line is the 10th best strategy. You may see the two lines cross over, depending on the options selected. You can continue or stop a paused run by clicking on the buttons at the bottom of the Best Results screen: Note: The graph information is not saved in the restart file.
The Out-of-Sample (OS) Results screen adds a new line at the end of each generation. When we refer to “Average” values, we are referring to a simple average of the ten best systems that have been found. Note: A common misunderstanding is that the ten best systems were all found in the current generation. This is not the case. For example, at the end of generation 8, there are ten “best” systems found and saved. These best systems could have been found in any of the eight generations evaluated.
ANN SD MAX ANN MIN ANN The standard deviation of the Out-of-Sample annual returns for the top ten systems. The larger the value, the larger the variation in Out-of-Sample performance. The maximum Out-of-Sample return for the top ten systems. The value in ( ) after the value is the position in the top ten systems. In the screen print above, the best OS performance at the end of generation 8 was 155.47%.
Saving Strategies The parameters for the top ten best systems can be saved after a run has finished, or the program can be paused during optimization and the systems can be saved. FastBreak will create parameter files (DFT files in FastBreak nomenclature) when you click on the Create DFT files icon: You will be asked to select the generation that you want to save: After you select a generation and click OK, you will be asked to give a root name to these files.
You can then see the specific strategy parameters found and you can execute FastBreak Pro in the standard manner to view Detail results or FNU files. Note: You will need to go to the Output tab to activate and name the detail and FNU files. Once you have done this you can resave the DFT file to capture the file names. There are two additional options at the bottom of the menu that allows the user to elect creation of FNU and Detail files.
9.0 Examples We have included example files on the installation CD. You can use the files directly from the CD, but we recommend copying the files to your FastBreak Pro installation folder. You may need to reset the path to the FastTrack trading family. We use the default paths of C:\ft\ftdef (Trading families defined by FastTrack) and C:\ft\Userdef (Trading families created by you the user).
hold three funds because we set the minimum and maximum range for # funds held to 3. We are optimizing on Annual return, but have specified an MDD goal of 15%. The optimization will have 100 members in the first generation and 50 for subsequent generations. We will optimize for 15 generations. We have specified a nominal mutation rate of 2%. The IS date range is 6/19/1989 through 12/31/1999. The OS date range is 1/3/2000 through 12/29/2000.
future market conditions. The reason we reserve some recent out-of-sample market data is to test the optimized parameters. We are looking for the point that the systems start to become over-optimized. Looking at the screen below we can see that the GA is finding better IS results. The IS ANN column is calculated by taking the ten best systems available at the end of each generation and using the system parameters to test for returns in the OS Date range.
The OS MDD is a little disappointing because we optimized with a 15% MDD, and we see that the OS MDD is typically in the 17-22% range. There are some very good reasons for this to happen. First, we are trading sector funds which can be very volatile. A second reason is that we retained the gold fund, a very volatile fund, in the trading family. For comparison, the NASDAQ was down 40% in this period and the S&P 500 was down 10%.
After you choose the generation number you will be asked to provide a name. We will use the name Exp and FastBreak will provide the extensions (Exp0.DFT, Exp1.DFT … Exp9.DFT) to identify each of the top ten systems. We can now load and execute each of the DFT files in FastBreak Pro and look at specific trading parameters, MDD, S/Y etc. We do this because the Out-of-Sample screen only provides the average values for these parameters for all ten systems.
In this example, we chose system # 10 in generation 9 because it was the best in the Outof-Sample screen. Should we always automatically choose the trading system that was best in the OS time period? Not necessarily. See the next chapter for suggestions on how to choose among the top ten best systems. Note: Here is a shortcut for evaluation of the top 10 best systems. Create a Batch run file (see Standard manual for information on running in Batch mode).
and evaluate them separately, but we will use the FastBreak Pro family optimization option to determine the best combination of funds. We build a trading family in FastTrack that contains all four funds – FSAIX, FSENX, FSESX, and FSRFX. This family has been built and can be found on the installation disk (file name is Myentr.fam). Copy this file from the disk to your FastTrack Userdef folder. This folder contains all the user defined families. Note: You must copy the Myentr.
This trading strategy has very good performance in the OS period. The results are even more impressive compared to the major market indexes during the time period. Again, it is not an exact process to choose the best generation. We chose generation number 19 because it had a good combination of IS, OS and UPI values. We proceed by creating DFT files for the ten best strategies in this generation using the Create Best Results DFT Files icon. We provide the name ET.
We see that all 10 new families (ET0 through ET9) are now available in the Families selection table. At this point we execute the strategy just like any FastBreak strategy. We could use the Output tab to write out detail and FNU files for additional information. One item we want to see is what funds FastBreak Pro used from our original family – remember that we used the Optimize Family option. We could use FastTrack to examine the new custom ET3.
Example 3 – Trading Stocks One of the most exciting and aggressive uses of FastBreak Pro is developing stock trading systems. Note: Trading individual stocks is by its very nature not diversified when compared to trading mutual funds. Stock trading systems are subject to very substantial draw downs. We have found that, in strong markets, stock trading systems can, in general, significantly outperform mutual funds trading systems on a return basis.
an inaccurate indication of performance when performance results are measured over a very short trading period. For this reason, it is important to have an OS period of reasonable length. Also, the problem can be exacerbated if the strategy holds a few stocks. Our example holds five stocks which will help mitigate the problem, i.e., a few big trades are less likely to give an unreasonable indication of performance. This optimization can take a long time (overnight on a Pentium 2.
Create the DFT files for generation 14 using the method in the first two examples. Now, load strategy 5 DFT into FastBreak, change the strategy start and end dates to match the OS dates. Execute the strategy. Here are the results: Annual return 89.6 MDD 18.8 UPI 9.9 Beta 1.5 Alpha 97.8 The S&P lost 12% and the OTC lost 45% over this same period.
Example 4 – Building Market Timing Signal Files Read the chapter on building market timing signals in the Standard FastBreak manual. That chapter will provide background on the logic of how FastBreak builds signal files. FastBreak Pro can be used to optimize and build market timing signals. This example will demonstrate how to build a multi-market timing signal. The object of this example is to build a market timing signal that can be used for stock and mutual fund trading systems.
Each day you can load this DFT file and execute it just as you would any trading system. If there is a market buy or sell, the signal file will be updated. Of course if you use this signal in a FastBreak trading strategy you will need to run the signal DFT each day prior to loading and executing the trading system DFT.
10.0 Suggestions for Building Better Systems The optimization parameter defaults in FastBreak Pro will give you good results. In this chapter we show you the sensitivity to some of the optimization options and give you ideas for doing your own studies. We also provide results from our studies that may help you build better systems. Note: As you will see, many of these studies were performed many years ago. That doesn’t invalidate the concepts and ideas for you to consider.
Keeping Track of Optimization Runs It is useful to keep a simple record of optimization runs. Although it is a simple matter to reload the restart file or optimization parameters file to check parameter choices and ranges, we find it useful to keep a simple spreadsheet record of runs. The spreadsheet can be filled out in less than a minute when an optimization run completes.
improvement in the IS results, and this is a reasonable place to stop and choose the 12th generation for further study. We like to see the best systems found, based on OS performance, between generations 512. If the best system is found early, try increasing or decreasing the mutation rate. Sometimes the system converges too rapidly because there are not enough mutations happening, and other times the systems will not get better because there is too much mutation, i.e.
single fund system has the system with the best OS result but is also the system with the worst OS result. What is interesting is that the “hold 3” systems actually has the best average performance, 32% on average, and the worst system had a very respectable 24%/year return. OS Testing Period How much data should be reserved for Out-of-Sample (OS) testing, and how often should a system be re-optimized? There is not a good general rule.
"Stale" OS months Return, %/year 0 6 18 37.7 40.7 41.8 These results are very encouraging because all systems are comparable and the “older” systems actually have slightly better performance. The results would encourage us to trade systems for a year or more prior to re-optimization. See the Frequently Asked Questions chapter for additional comments on this subject.
Trade Return/B&H 5.0 4.0 3.0 2.0 1.0 0.0 19 19 19 19 19 19 19 19 19 19 20 90 91 92 93 94 95 96 97 98 99 00 End Date What is very clear is that in the early to mid 90’s, it appears that your chance for outperformance was much better. The ratio hit a low in the June 1996 – June 1997 time period where the optimum systems actually under performed B&H. The tide seems to have turned in recent years. There are several theories as to why this change would have happened.
Trading International Funds We built a family of 34 international funds that can be traded with either no, or low transaction fees. We examined the impact of restricting the number of switches per year on trading performance. An investor may want to constrain trading because the brokerage company may have a limitation on trades allowed per year. The strategies were optimized with an IS period of 1/4/1993 to 12/31/1997, OS period of 1/2/1998 to 9/19/1999.
discover ways of choosing from among the “best” trading systems provided by FastBreak Pro at the end of each generation. When FastBreak Pro completes an optimization, it provides you with ten systems that have good IS performance, and good OS performance. It is at this point you would begin to trade the system. Although the OS performance may be good, the data that was used to develop the systems is now even older. The following study was made with an IS period of 5/12/1989 to 10/1/1996.
It can be argued which of the ten systems would have been chosen to be traded. The outof-sample MDD was very similar in all cases. In this particular instance, the best OS strategy, system 9, also happened to be the best Post period case at 45.8%/year. We would like to say this always happens, but that is not the case. The second best case, system 10, had a significantly lower but still impressive return, and the worst OS case, system 3, had a very respectable Post period performance of 32.
System Number 1 2 3 4 5 6 7 8 9 10 Average S&P Family Avg. OS Return FNU OS Post OS FNU Post Annual, % Annual,% Annual, % Annual, % 38.5 44.6 17.7 20 28.7 37.7 23.3 21.1 5.8 33 32.2 32.1 41.7 8.7 23.3 24 27.4 40.9 21.8 31.2 22.8 24.9 24.8 29.7 33.8 19.1 19.9 12.4 29.2 26 37.3 38.2 51.7 34.3 45.8 48.7 45.5 50 24.4 26.9 32.5 37.2 32.6 31.9 37.2 32.6 27 14.7 11.3 28.4 14.7 11.3 On average, using the FNU equity curve to measure performance shows a slight improvement in both the OS and Post OS Period.
Generation 8 was selected for detailed analysis. Here are the results (using FNU equity curves): System Number 1 2 3 4 5 6 7 8 9 10 Average S&P Family Avg. OS Return Post OS Annual, % Annual, % 27.8 51.4 27.8 54.6 12.5 46.1 22.9 58.6 30.7 67.2 36.1 54.8 32.5 58.4 38.6 40.9 36.3 31.2 38.7 51.4 31.5 37.2 11.6 52.1 14.7 6.3 These are outstanding results, especially considering less than four years of data was used for optimization.
Reversing the In-Sample and Out-of-Sample Data Periods FastBreak Pro allows the OS data period to be earlier than the IS data period. The more traditional method is to allow the GA to derive parameters then perform out-of-sample testing on the most recent market data. The advantage to the traditional order is to look at the predictive capability of systems on the most recent history.
history. We found that optimization on this recent bear market data improved risk performance. The Effect of MDD Objectives on Performance All investors want trading systems with a small MDD. Here are the results of a study that looked at how MDD performance objectives affected both IS and OS performance. Annual performance was optimized, but MDD constraints of 10%, 15%, and 20% were also applied. The study used the Select trading family and held three funds.
will now “avoid” trading systems that activate too many stops. The above example using a 10% MDD goal was rerun with this penalty activated. The IS, OS and OS MDD results are shown using an X in the above chart. We see that all three measures of performance were improved using this option.
11.0 Frequently Asked Questions and Common Problems Q) I crashed my hard drive (got a new computer, new laptop etc.) and I need to reinstall FastBreak Pro. A) This is our most common tech support call. You MUST use the installation CD to reinstall. We have had a number of users just try to copy files to the new computer or hard drive. This will not work.
a temporary family file to use. This will create confusion if multiple executions are trying to read and write to this family file. Q) What kind of computer will make FastBreak Pro run faster? A) FastBreak Pro performance all about CPU speed. The best way to do analysis faster is to run multiple copies of FastBreaK Pro at the same time if you have a processor with multiple processors or cores. For example, if your processor chip has four cores then you can run four copies of FastBreak Pro at the same time.
Q) I’m using NCalpha ranking, and the funds ranked highest have recently dropped more in price than any other funds in my trading family. How can funds that have dropped so much be ranked high? A) Look at the formula for NCalpha in the Appendix. Funds that have dropped a lot during a major market sell off can have a very high beta. The high beta combined with a negative index gain over the ranking period can result in a positive alpha.
2. Note how long the IS Start Date occurs after 9/1/1988. This will give you the delta delay you need. Round up to the next month. For example, say FastBreak chooses 3/17/1989 this is a delay of nearly 7 months. 3. Look at your trading family and make an estimate on a date when many of your funds became available. As an example, say 2/1/2000 4. Add the delay found in step 2 (7 months) to the date in Step 3. This will give you a new IS Start Date of 9/1/2000 5.
Appendix A -- Technical Discussion What are Genetic Algorithms? Genetic Algorithms are a mathematical method used to solve hard optimization problems. The method simulates the biological processes of “evolution”, “natural selection” and “survival of the fittest.
Adjusted Performance = 20% x 15/18 x 10/14 = 11.9% This calculation is made for all systems (chromosomes) in a generation. All the adjusted performance values are put in order, from best to worst. At this point, only the best systems are allowed to “survive.” The percentage to survive is controlled by the user, but a good starting point is 50%. The next step is to combine system parameters to produce hybrid offspring.
In this example, the parameter values are all increased by 5%. The strategy performance from this run is saved. Then a second evaluation is made, but this time the trading parameter values are reduced by 5%. The performance results are also saved. At this point FastBreak Pro evaluates robustness in one of two ways.
Since 0.86 is greater than 0.85, no robustness adjustment is made to the original 24% performance. Which method, Average or Lowest, is better? Our research shows both give similar results, but we have a slight preference for the Lowest option. We have experimented with different values for the Robust Factor, and we prefer 10% for the robustness factor. We have experimented with the Maximize Robustness value, and we prefer 0.85. Please feel free to experiment and determine your own value preference.
usually results in a reduction to the variable being optimized (constraints such as MDD, or switches per year have the same effect). We are willing to pay a small price in IS performance if it results in a system that has better OS performance, i.e., better predictive ability. What is probably happening in the above example is that the robustness is preventing the genetic algorithm from converging too rapidly. Trying to satisfy the robustness constraint is similar to the effect of mutation.
The time it takes to build the trendlines is dependent on the following: Number of family members Size range for trendlines to be built. If you use 1 to 20 vs. 1 to 10 it will take twice as long because twice as many trendlines need to be built. Selecting the Optimized logarithmic vs. linear option will double the set up time because both versions of trendlines will need to be calculated.
