Disliked{quote} How important is the choice of the distance (metric) is nearest neighbor? L1, L2, L∞, Mahalanobis.... Do you have a preference?Ignored
Algorithmic Quant Trading (Machine Learning + Stat-Arb) 25 replies
Forex with Machine Learning Software Project 1 reply
Machine Learning + Retail Forex = Profitable? (Quant) 1 reply
Potential new machine learning style software. 79 replies
My most recent advancements into machine learning 16 replies
Disliked{quote} How important is the choice of the distance (metric) is nearest neighbor? L1, L2, L∞, Mahalanobis.... Do you have a preference?Ignored
Disliked{quote} Well, machine learning methods find relationships that might not be obvious enough to be found through a more transparent method (like those you suggest).Ignored
Disliked{quote} So looking at your result it seems you're a step ahead than Daniel, it's really interesting that your NN could be backtested with the same outcome for different runs! About mining bias problem , I don't know if it's a concept that could be applied to NN, btw a nice question to ask Daniel Will follow with interest your work here ! Cheers, SkylineIgnored
Disliked{quote} Could you please provide an example of this? Something simple would suffice. kIgnored
Disliked{quote} Outside of the trading world there are many. For example think about face and audio recognition. A neural network can find many non-linear relationships that make the prediction of a face or an audio track possible while doing this with transparent methods is much more complicated. Sure, machine learning methods are simply glorified functions (input to target converters) but sometimes achieving a similar result while understanding everything "behind the scenes" (all variable interactions) is difficult. It is also worth considering that machine...Ignored
Disliked@PipMeUp: Thanks for the reference, I will obtain and study the book as soon as I am convinced about the path. (Also, I have a feeling that for the understanding/description of the 6-month drop in eurusd one should probably include the data dating back 2 or 3 years.) @stt: Thanks, I found the paper on arxiv, but in order to understand the language I think I'd better at least read the book PipMeUp recommended. {quote}Ignored
Disliked{quote} i think you can get most of the concepts by doing coursera courses (andrew ng has one for starters). also you can get many online books to get started. Also a lot of open source code in every language (c++, python and R) is available so you really dont need to write a lot yourself. check this reddit for good pointers. with your background, i think it wont take much effort to get started.Ignored
Disliked{quote} Whatever coding solution you consider it is extremely important that you consider how you will simulate and live trade from the start. A mistake I made in the very beginning was to only concern myself with the building of models and simulations while neglecting how I would actually take those to live trading (which was a headache later on). Make sure from the start that you can simulate your systems and live trade the exact same code it will save you a lot of pain later on.Ignored
Disliked{quote} i think you can get most of the concepts by doing coursera courses (andrew ng has one for starters). also you can get many online books to get started. Also a lot of open source code in every language (c++, python and R) is available so you really dont need to write a lot yourself. check this reddit for good pointers. with your background, i think it wont take much effort to get started. http://www.reddit.com/r/MachineLearn..._well_written/Ignored
Down Down => Down 21 Down Down => Up 25 Down Up => Down 26 Down Up => Up 24 Up Down => Down 24 Up Down => Up 25 Up Up => Down 23 Up Up => Up 32
DislikedThere is something fundamentally different when comparing the GBPUSD and the USDCHF. Do you think that it is a matter of tuning the model parameters and inputs? Do you think there is something that makes the GBPUSD fundamentally more difficult to predictIgnored
DislikedHi algoTraderJo I'd like to reproduce your experiment post#10. I don't understand the approach. From what I understand you take the last 200 triplets of days. The first 2 define the input and the 3rd is the target. I took E/U dataset I get these stats up to yesterday: Down Down => Down 21 Down Down => Up 25 Down Up => Down 26 Down Up => Up 24 Up Down => Down 24 Up Down => Up 25 Up Up => Down 23 Up Up => Up 32 The two previous days on E/U were Up. I understand that you enter long because of the 32 chances out of 32+23. How do you apply k-NN or SVM...Ignored
Disliked{quote} U/CHF and E/U are strongly (anti-)correlated. It is no wonder that their results are similar. Why do you conclude there is a fundamental difference between E/U and G/U instead of questioning the validity of the strategy? Isn't it simply by random chance or overfitting that it works on E/U and normally fails on G/U? What are the results on all the other majors?Ignored
Disliked{quote} Also to algoTraderJo, thanks for the thread, a topic that is near and dear to my heart. I'm subscribed and grateful to be along for the ride!Ignored