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First of all, I finished the last page of your book and it was really helpful! Great work!
I hope you can answer to some questions which I have about WFO:
1. How do you discover if a parameter is stable? What I mean is, with a "conventional optimization" I can see all the results
(i.e. Net Profit) of my parameter and pick the "most stable" one which is close to each other with a still acceptable Net Profit even if it's not that one with the highest profit, but in WFO I only know which parameter is the "best one"?
2. If parameter x for the first IS Period is 500 and for the second one is 1500, how do you determine how big of the Range is acceptable?
3. I guess, the most important thing is to avoid over-optimization, so i thought to take the years 2014-2017 as my "IS Period" and plot the optimization results to 2000-2013 to see if the equity curve is roughly similar to my IS Period. What do you think about that?
Thanks!
Can you help answer these questions from other members on NexusFi?
Hello @kevinkdog, I hope all is well with you and family.
I am currently still reading your book, practicing coding some simple strategies, just getting organized.
On page 85, regarding Entry Rules:
Few questions to make sure I understand:
1. If I use Market Orders to entry trade once the trade setup signal is True, does this mean my parameter is 0? So nothing to optimize for entry.
2. If I use Limit Order to enter trade at X ticks from close of recent bar once the trade setup signal is True, does this mean I now have 1 optimizable entry parameter?
Thanks for the kind words - glad you enjoy the book!
1. You are right, stability is harder to determine with walkforward. So, normally I check parameter stability during preliminary testing (the 70% rule), and then during walkforward I look at a few different combos of IN/OUT. The second method is not as effective as the first.
2. I pick ranges long before walkforward testing. It is a mistake to do so afterwards, in my opinion. Sometimes it is hard to pick suitable ranges, so I rely on early testing to help me determine what is appropriate. Eventually it becomes more of a feel thing ("i want a short term indicator, so that means my range should be XX-XX")
3. I have never tried that, so I can't say it would work or not. Many times there is no right answer with this stuff. I suggest you try it, and if it works with real money, then go for it it.
1. Not sure I understand. The parameters would be associated with the setup signal. For example, you could enter at an y bar high close:
If close=highest(close,y) then buy next bar at market;
"y" would be your only parameter to optimize
2. This would be a parameter you could optimize, yes. But you might have others, with rule #1 shown.
Kevin, was just reading the intro to your book and if that story is true then you have more intestinal fortitude than me and are more of a man than I will ever be (and I mean that). Having said that, I trust your judgment based on what I've listened to of you on Better Sys Trader podcast and I have two questions.
What do you think of System Parameter Permutation, and would you be willing to a do a webcast seminar discussing it? Or do you think its rubbish? Or is it not something you've looked into? My understanding of SPP is highly limited but it appears the simplest form of SPP is to split your backtest data into x samples (which would all be in-sample) and then optimize over each sample. Then run linear regression analysis on the optimization results for each sample to determine if there is a similarity in the opti results (by "results", I mean the parameters that perform best according to whatever your fitness function happens to be). However, my research (random googling while sipping bourbon) indicates SPP can be applied in a much more complicated form where not only the parameters are changed, but also some the underlying rules of the system are changed slightly...or perhaps I am misunderstanding something when I say that. Anyway, I would love to hear your thoughts if you got time.
This question is a fishing expedition for thoughts (ignore if needed). I seem to be good at developing automated systems that excel in finite market conditions (regimes), but of course suck in anything other than what it was designed for. So the difference between what happens vs what I would prefer to happen seems to be whether I can accurately predict what type of regime will occur...I should state that my systems are usually intraday that perform better in one "type of day" versus another (think: market profile day types). I think it is important to understand that I'm not talking about a simple regime filter that acts to turn off/on a particular strategy because any "filter" is usually going to be too laggy to be effective for what I'm after (which might mean I'm trying to hard for too much!!). I know I'm not giving enough info here (tho I'm not trying to hide anything either), but it seems to me that my problem is in my approach to coming up with new ideas. Or maybe it's something else. Like I said...ignore this if needed, just looking for food-for-thought.
Thanks for the questions, and thanks for saying you trust my judgment - in an industry full of scumbag educators, I cherish my reputation, and I am glad others see it too.
As far as intestinal fortitude, I think it was more stupidity. I mean seriously, what kind of idiot (besides me) wires margin call money so frequently that he gets gifts for the grandchildren of the bank wire transfer lady?!?!?! Crazy, but true!
To answer your questions:
1. I have looked at SPP, tried it out a bit, but definitely am not someone who should give a webinar on it. The creator of it should do that, as he knows it best and won an award for it. My only concern with SPP, or really any new technique or approach in trading, is that I want to see real time proof that it works. That was lacking in the SPP paper I read. So, it may indeed have validity, you just should prove it to yourself via real time results.
2. Market Wizard Dr. Van Tharp, who has a lot of good info, suggests this approach. By having different strategies for different market regimes, you always will be ready to turn on the applicable strategy.
Sounds like a great concept, but the devil is in the details.
To do this, you need a "controller" or "switcher" strategy that turns on/off the appropriate strategy at the right time. So far so good. The problem is by the time you know the market regime has changed, it is always late. As you say, it is laggy.
So, what you want to do is predict the regime before it happens.
I think it is a great idea, but VERY hard thing to do in practice. How would you propose doing it?
Give me some time to mull it over a bit more and write a semi-cogent response. I've been thinking about it and the more I think about it, the more I think I need to think. Lol.