To Munchie
Hi M. Just thought I would post a response to your queries in my shouts here. I am trying to keep away from this addiction mate....so hope this suffices.
I use both EA studio and Strategy Quant for data mining efforts.
EA studio has a powerful workflow process and its speed is facilitated from simply spitting out strategies that operate off the open bar condition. As a result, I tend to reserve its use for longer timeframe strategies such as H4 and D1. It now has the ability to accept longer range data....hence with a solid remote server chugging away constantly....can generate hundreds of robust strategies over time under 24/7 processing. I use it to crunch as much data as I can get my hands on....as I am looking for robust strategies that can survive across a broad range of market condition.
For any queries regarding EA studio.....then use this forum https://forexsb.com/forum/ and ask. They are a helpful bunch here especially the developer Popov.
While Strategy Quant X is still in Beta mode...I restrict my testing to Strategy Quant version 3.8.2. SQX is going to be an amazing piece of testing software when complete...but it is too buggy at the moment to rely on....so stick with version 3.8.2. You can use this to hone in on strategies at the shorter term level such as M30, H1 etc as you have far more freedom in your strategy design than EA studio.
It is very worthwhile signing up for the Quastic Algo-Trading Course run by Zdenek Zanka as he navigates you through the necessary steps to take into account in testing for robustness.
https://quastic.com/courses/algo-trading-course/
Also don't be afraid to use the forum for queries. https://strategyquant.com/forum
In addition, for further assistance...keep your eyes peeled for member Geektrader on this forum and others. He knows what he is doing and has some very good ideas on what is required for workflows with a range of different data mining products such as EA Studio and SQ etc.
In regards to how I use them at the moment........my preference is to use them to simply supplement my divergent EA's which have been developed to target momentum and trend following. The core of my portfolio is based on logic designed to simply capture fat tailed moves which under diversification are much more prevalent than you might think. I develop these very simple solutions myself. Most guys would not look twice at them as on their own they don't appear to deliver bang for buck....but this is where portfolio management and position sizing kicks in. This core portfolio of systems when compiled together offer stunning returns under favorable volatile conditions but the flip side is that they also possess drawdown signatures that need to be filled when conditions are unfavourable.
Now given my penchant for divergence and my distaste of convergence or mean reversion, I use the data mining solutions to find other divergent solutions that fill the gaps. Now the trick for those in the know....is that they do exist using different timeframes, instruments and systems.....but you need to design your workflow within a 'logic space' to find them. Effectively you constrain your solutions through design parameters to fit within criteria needed to 'fill the weak spots' at the portfolio level.
Mate....don't expect success overnight. It takes quite some time to sort the chaff out from the wheat with these techniques but it sounds like you are on the right path.
In regards to 'when do you take these systems live'.....here are some key things to note.
1) You need very broad diversification using these systems and lot's of them. In playing the Law of Large numbers you need to behave accordingly. Ideally you have hundreds of different strategies using very low trade risk per strategy allocated to your finite capital. For example if you allocate $200K of capital towards the portfolio....think in terms of 0.5% trade risk per strategy....that way any failure element has only a very marginal impact on your overall result.
2) Given the vast number of strategies that can be developed very quickly...do not get attracted to the strategy itself. Simply look at how it assists the overall portfolio. If it does not assist in improving the risk weighted return of the overall portfolio....then drop it like hot cakes and choose another.
3) Given that you have tested your strategies over very long time horizons, then speed of implementation is not advised. Put the strategy on demo account from 6 months to a year before considering live implementation. It it fails in demo....then drop it. Do not be sucked in to performance over short term time horizons. Market conditions change....and you do not want to be left holding a strategy with negative skew.
4) You will also need to test your strategy in the live environment with a very small capital allocation to ensure it operates in a similar manner to the demo environment recognizing that slippage and variations in spread and SWAP now enter the equation. You need to parallel test over both demo and live trade environments.
5) If it still stacks up and assists the overall portfolio then commit to an allocation towards it....but monitor, monitor and monitor using your backtest as a blueprint to navigate future uncertainty.
6) Do not be sucked in by linear equity curves and tight Monte Carlo signatures. Robust strategies tested over long timeframes all have volatility cooked in to them. If they don't...then chances are you are a victim to negative skew which will end in tears and certainly not be robust solutions. You smooth the curves at the global portfolio level....not at the individual system level. Each strategy must have 'full risk release' baked in to them. If they don't then you are kidding yourself with methods that retain intrinsic risk and you will not stand the test of time. Each strategy simply needs weak positive expectancy over extended timeframes eg. 20 years plus....and they all will possess high volatility. Under a compiled portfolio you address the drawdown weakness of each strategy and weight your position sizing so that at the 'global' level your positive expectancy of momentum is far more consistent than what an individual return stream can bring to the table.
7) This is a wealth building exercise...not a get rich quick solution. You cannot have predictive cashflow over the long term unless you believe in pink unicorns.
Take heed of Ralph Vince when he says.....
“The key to ensure that you have a positive mathematical expectation in the future is to not restrict your system’s degrees of freedom.
This is accomplished not only by eliminating, or at least minimizing, the number of optimizable parameters, but also by eliminating, or at least minimizing, as many of the system rules as possible.
Every parameter you add, every rule you add, every little adjustment and qualification you add to your system diminishes its degrees of freedom.
Ideally, you will have a system that is very primitive and simple, and that continually grinds out marginal profits over time in almost all the different markets.
Again, it is important that you realize that it really doesn’t matter how profitable the system is [by itself], so long as it is profitable. The money you will make trading will be made by how effective the money management you employ is.
The trading system is simply a vehicle to give you a positive mathematical expectation on which to use money management. Systems that work [show at least a marginal profit] on only one or a few markets, or have different rules or parameters for different markets, probably won’t work real-time for very long…”
I hope this helps mate....now I better leave this infernal addictive forum for good......
Cheers
C
Hi M. Just thought I would post a response to your queries in my shouts here. I am trying to keep away from this addiction mate....so hope this suffices.
I use both EA studio and Strategy Quant for data mining efforts.
EA studio has a powerful workflow process and its speed is facilitated from simply spitting out strategies that operate off the open bar condition. As a result, I tend to reserve its use for longer timeframe strategies such as H4 and D1. It now has the ability to accept longer range data....hence with a solid remote server chugging away constantly....can generate hundreds of robust strategies over time under 24/7 processing. I use it to crunch as much data as I can get my hands on....as I am looking for robust strategies that can survive across a broad range of market condition.
For any queries regarding EA studio.....then use this forum https://forexsb.com/forum/ and ask. They are a helpful bunch here especially the developer Popov.
While Strategy Quant X is still in Beta mode...I restrict my testing to Strategy Quant version 3.8.2. SQX is going to be an amazing piece of testing software when complete...but it is too buggy at the moment to rely on....so stick with version 3.8.2. You can use this to hone in on strategies at the shorter term level such as M30, H1 etc as you have far more freedom in your strategy design than EA studio.
It is very worthwhile signing up for the Quastic Algo-Trading Course run by Zdenek Zanka as he navigates you through the necessary steps to take into account in testing for robustness.
https://quastic.com/courses/algo-trading-course/
Also don't be afraid to use the forum for queries. https://strategyquant.com/forum
In addition, for further assistance...keep your eyes peeled for member Geektrader on this forum and others. He knows what he is doing and has some very good ideas on what is required for workflows with a range of different data mining products such as EA Studio and SQ etc.
In regards to how I use them at the moment........my preference is to use them to simply supplement my divergent EA's which have been developed to target momentum and trend following. The core of my portfolio is based on logic designed to simply capture fat tailed moves which under diversification are much more prevalent than you might think. I develop these very simple solutions myself. Most guys would not look twice at them as on their own they don't appear to deliver bang for buck....but this is where portfolio management and position sizing kicks in. This core portfolio of systems when compiled together offer stunning returns under favorable volatile conditions but the flip side is that they also possess drawdown signatures that need to be filled when conditions are unfavourable.
Now given my penchant for divergence and my distaste of convergence or mean reversion, I use the data mining solutions to find other divergent solutions that fill the gaps. Now the trick for those in the know....is that they do exist using different timeframes, instruments and systems.....but you need to design your workflow within a 'logic space' to find them. Effectively you constrain your solutions through design parameters to fit within criteria needed to 'fill the weak spots' at the portfolio level.
Mate....don't expect success overnight. It takes quite some time to sort the chaff out from the wheat with these techniques but it sounds like you are on the right path.
In regards to 'when do you take these systems live'.....here are some key things to note.
1) You need very broad diversification using these systems and lot's of them. In playing the Law of Large numbers you need to behave accordingly. Ideally you have hundreds of different strategies using very low trade risk per strategy allocated to your finite capital. For example if you allocate $200K of capital towards the portfolio....think in terms of 0.5% trade risk per strategy....that way any failure element has only a very marginal impact on your overall result.
2) Given the vast number of strategies that can be developed very quickly...do not get attracted to the strategy itself. Simply look at how it assists the overall portfolio. If it does not assist in improving the risk weighted return of the overall portfolio....then drop it like hot cakes and choose another.
3) Given that you have tested your strategies over very long time horizons, then speed of implementation is not advised. Put the strategy on demo account from 6 months to a year before considering live implementation. It it fails in demo....then drop it. Do not be sucked in to performance over short term time horizons. Market conditions change....and you do not want to be left holding a strategy with negative skew.
4) You will also need to test your strategy in the live environment with a very small capital allocation to ensure it operates in a similar manner to the demo environment recognizing that slippage and variations in spread and SWAP now enter the equation. You need to parallel test over both demo and live trade environments.
5) If it still stacks up and assists the overall portfolio then commit to an allocation towards it....but monitor, monitor and monitor using your backtest as a blueprint to navigate future uncertainty.
6) Do not be sucked in by linear equity curves and tight Monte Carlo signatures. Robust strategies tested over long timeframes all have volatility cooked in to them. If they don't...then chances are you are a victim to negative skew which will end in tears and certainly not be robust solutions. You smooth the curves at the global portfolio level....not at the individual system level. Each strategy must have 'full risk release' baked in to them. If they don't then you are kidding yourself with methods that retain intrinsic risk and you will not stand the test of time. Each strategy simply needs weak positive expectancy over extended timeframes eg. 20 years plus....and they all will possess high volatility. Under a compiled portfolio you address the drawdown weakness of each strategy and weight your position sizing so that at the 'global' level your positive expectancy of momentum is far more consistent than what an individual return stream can bring to the table.
7) This is a wealth building exercise...not a get rich quick solution. You cannot have predictive cashflow over the long term unless you believe in pink unicorns.
Take heed of Ralph Vince when he says.....
“The key to ensure that you have a positive mathematical expectation in the future is to not restrict your system’s degrees of freedom.
This is accomplished not only by eliminating, or at least minimizing, the number of optimizable parameters, but also by eliminating, or at least minimizing, as many of the system rules as possible.
Every parameter you add, every rule you add, every little adjustment and qualification you add to your system diminishes its degrees of freedom.
Ideally, you will have a system that is very primitive and simple, and that continually grinds out marginal profits over time in almost all the different markets.
Again, it is important that you realize that it really doesn’t matter how profitable the system is [by itself], so long as it is profitable. The money you will make trading will be made by how effective the money management you employ is.
The trading system is simply a vehicle to give you a positive mathematical expectation on which to use money management. Systems that work [show at least a marginal profit] on only one or a few markets, or have different rules or parameters for different markets, probably won’t work real-time for very long…”
I hope this helps mate....now I better leave this infernal addictive forum for good......
Cheers
C
4
he is just human like the rest of us, and is very hard to change our behaviour.
