Dear Keith, which kind of machine learning it is, is actually a more complex question than one would expect. Because the typical approach which is used by JBT (and similar tools) falls a bit through the cracks.. It is roughly a time series prediction problem. - Albeit we do not want to predict the next value, we only want to predict the kind of trade to make. Thus, it can also be seen as a classification problem. If you look at categorizations like in en.wikipedia.org/wiki/ Machine_learning it is supervised learning in a way which is most closely to decision trees (though the tree nodes are parameter values - the ones your optimizer give you). The difficulty are the indicators.. They can be seen as features which are used as the basis for classification by the decision trees.
There are tons of ML approaches, but you / we will probably not implement others, as they fit not well to the kind of JBT-approaches. However, the lessons from testing apply here. You may find it worthwile to look at http://en.wikipedia.org/wiki/Cross-validation_(statistics) and other literature in the same direction. Cheers Klaus On 5 Jun., 20:32, Keith <[email protected]> wrote: > Dear Klaus, > > I am very grateful to you for your indulgence in my ramblings and > thanks again for the rules, I will keep them in mind as I explore JBT. > > Drawdowns are a part of the reality of trading, so I have no problem > with that. I remember witnessing 2 equity curves for the top 2 > competitors in a forex contest. The first trader has small but very > consistent winning trades - very little drawndowns. The second trader > has much fewer trades but has great drawdowns and also greater > profits. > > My personal preference is to emulate the first trader, consistent but > smaller profits, with little drawdowns, with that slight edge - that > is the system I want to build. > > What category of machine learning would you classify JBT's method so I > can google them up. > > Thanks. > > Keith > > On Jun 5, 11:09 am, Klaus <[email protected]> wrote: > > > > > Dear Keith, > > > regarding the overoptimization problem: > > - rule one: don't have to many parameters. (the more parameters, the > > closer you can fit, but the > > less general your rules will become) - it is a similar difference > > between understanding and > > learning word by word. You want the system to generalize > > fundamentals not to memorize the > > training set.. > > - rule two: in order to check: separate between training set and > > test. > > Be sure that both cover very different market situations. > > (e.g., things like the flash crash recently, of course there one > > only, thus it is better to have it in the > > test set) > > => see cross-validation if you want to go more in depth > > - rule three: before you start try to understand what an acceptable > > system might be for you: > > if you dream up the system that has no drawdown, only wins. There > > might be no such system, then > > stop wasting your time :) > > > Regarding machine learning: there is tons of knowledge out there. > > Beyond the primitive rules, given above. > > I am not a guru on it, so I cannot condense it shortly. If you want to > > better understand what you are doing, > > there is a lot of it free on the internet, but also good textbooks. > > A special branch focus on time series prediction (this is what applies > > here), and also many reports > > use some sort of a market data for this.. > > > Cheers > > Klaus > > > On 5 Jun., 19:09, Keith <[email protected]> wrote: > > > > Dear Klaus, > > > > Thank you so much for sharing your experience. > > > > I agree completely with your sentiments especially on money management > > > and control - black swan events do exist and in these very uncertain > > > and bipolar markets, the danger is ever more present. > > > > Based on a short exploration of the code, each strategy is a variation > > > of volality, velocity and the volume impact of the bid and ask prices > > > and the relation to the crossover of a fast and slow indicator. These > > > parameters are optimized through back and forward testing over some > > > time period, which is another parameter which may need to be > > > optimized. Many gurus warn about over-optimization - so how do we > > > know if we have the right optimized parameters? It was mentioned that > > > we may need to optimise the parameters after a time - how and when > > > shall we know that? If this is the wrong thread to discuss this, let > > > me know where to take this because this is very interesting to me. > > > > I appreciate that having a stop loss in the back tested strategies > > > reduces its performance. Were the stop loss points fixed or also > > > optimized. If a market is very volatile, a closer fixed exit will have > > > a higher chance of being hit be it a profit target or a stop loss. > > > Most gurus recommend a closer profit target to a stop loss for > > > futures. > > > > Warren Buffet said once in an interview that he does not trade > > > anything he does not understand. Since you are familiar with machine > > > learning, could you share with us your views on how these strategies > > > function and how do they adapt to changing market behaviours? > > > > Thanks. > > > > Keith > > > > On Jun 5, 7:46 am, Klaus <[email protected]> wrote: > > > > > Dear Keith, > > > > > as you asked me, also my 2c (though nonlinear has MUCH more > > > > experience > > > > on this, so if in doubt take his answers). > > > > > My status is as this: for some time I am following here and played > > > > around.. > > > > For a few weeks now, I am collecting data for my own experiments. > > > > And only recently I became serious about designing strategies, though > > > > this is > > > > purely a hobby. I have some background on machine learning, though. > > > > Thus, > > > > all this is not foreign to me. > > > > > At this point: most of the time the system is in forward testing mode, > > > > for pure recording > > > > (I still want to extend my data basis). Last week, I traded it live > > > > only on friday, as I had > > > > only then time to monitor the system. Currently I do not yet have too > > > > much trust > > > > in the strategies (because you can never be sure how much your tested > > > > strategies > > > > extrapolate to unseen data). > > > > This said, I leave the computer also alone for half an hour or so, but > > > > at this stage not much longer. > > > > In the long term, I hope to increase the time frame, but I am not > > > > sure, whether I will eventually > > > > (can) fully automatic. Besides the quality of the strategies, there is > > > > also the question regarding > > > > stability of the platform (and connection, etc.). For example, last > > > > week while I was forward testing, > > > > I suddenly found TWS dead. In such a situation you are stuck with > > > > whatever position you had before, as > > > > JTB can no longer change it. > > > > If you want to go fully automatic, you must be able to accept this > > > > financially... > > > > > Regarding stop-losses, profit targets. I use them when I trade > > > > manually - why? Because this is a way I > > > > can get basic automatization from TWS. > > > > However, any experiments in autotrading are exactly in order to get > > > > smarter than this! > > > > My personal take on these are: they are very simple approaches to > > > > ensure to get out of the market. > > > > However, any good strategy (in my eyes) defines exactly when to enter > > > > AND when to leave the market. > > > > Because, why should I be very sophisticated wrt whent to enter the > > > > market and extremely simplistic > > > > regarding leaving it? Both contribute in equal manner to the total > > > > system performance. > > > > If you approach strategy design in this way, that you carefully design > > > > both, then you will find, what > > > > (to my knowledge) everyone found so far: typically your performance > > > > gets worse with stop-loss > > > > and profit target attached. Because in such a situation it means, you > > > > replace a sophisticated > > > > exit strategy with an ad-hoc approach. > > > > > Cheers > > > > Klaus > > > > > On 4 Jun., 21:08, Keith <[email protected]> wrote: > > > > > > Hi Klaus, > > > > > > Many thanks for your valuable advice - I will take careful note of it. > > > > > > Just out of curiosity, are you trading live with preset stop losses > > > > > and profit targets? > > > > > > Do you constantly watch the platform trading and do you need to > > > > > manually adjust the trades when needed or have you gone fully > > > > > automated? > > > > > > With the default platform, I have to manage the trades on TWS and exit > > > > > the platform manually to stop it. > > > > > > All the best to your live trading! > > > > > > Keith > > > > > > On Jun 4, 11:01 am, Klaus <[email protected]> wrote: > > > > > > > Dear Keith, > > > > > > > take care: single days don't tell you anything. If you want to use > > > > > > specific strategies: > > > > > > set up a data set for training the parameters. (My experiences with > > > > > > the out-of-the-box parameters > > > > > > for the provided strategies are suboptimal.) > > > > > > > Have a second, non-trivial data set for cross-testing. Any strategy > > > > > > that only performs well on the training > > > > > > data is worth-Less! (Thus, you need this second data set.) > > > > > > You can do this with the data provided with Jbooktrader (don't > > > > > > forget > > > > > > to split it) > > > > > > or with data you record yourself in forward mode (this also helps to > > > > > > analyze any instabilities and issues). > > > > > > > Both training data and validation needs to be a non-trivial amount > > > > > > (a > > > > > > week is not enough, let alone a day says nothing). > > > > > > Even for completely failing strategies, there are very good days, > > > > > > and > > > > > > even for the best strategy, there are loosing days. > > > > > > Ideally both data sets cover different types of days (sideways, up, > > > > > > down, zick-zack..) and after optimizing you should > > > > > > also check how broad the success regions are. Otherwise you end up > > > > > > with strategies that are too brittle.. > > > > > > > Having written this, I am currently live trading with a nice result > > > > > > for the day so far :) > > > > > > (Unfortunately, this does not mean I will even come out + today - or > > > > > > tomorrow.. - after all, > > > > > > it is statistics.) > > > > > > > Cheers > > > > > > Klaus > > > > > > > On 4 Jun., 18:50, Keith <[email protected]> wrote: > > > > > > > > Hi Eugene, > > > > > > > > I am glad to report that when I combine the ProfitTaker and > > > > > > > LossStopper together and only traded that strategy it seems to > > > > > > > work > > > > > > > very well this morning. > > > > > > > > Thanks. > > > > > > > Keith > > > > > > > > On Jun 2, 4:54 pm, Eugene Kononov <[email protected]> > > > > > > > wrote: > > > > > > > > > For those who are anxious to try the "classic" strategies, I am > > > > > > > > attaching > > > > > > > > two sample strategies, LossStopper and ProfitTaker. The first > > > > > > > > one uses a 7 > > > > > > > > point stop. The second one uses a 5 point profit target. These > > > > > > > > are > > ... > > Erfahren Sie mehr » -- You received this message because you are subscribed to the Google Groups "JBookTrader" group. To post to this group, send email to [email protected]. To unsubscribe from this group, send email to [email protected]. For more options, visit this group at http://groups.google.com/group/jbooktrader?hl=en.
