Hi, regarding DTN2 issue on price change indeed, most of the times the system fails is because relative volatility is low, performing better on more volatile environments, that's why I was thinking that the ranges of succesful trades would be about 3 times higher those losers. That difference between volatility plays in favour of winners. I have quite good knowledge of different trading systems and several years os testing those. But this approach based on risk and a stochastic analysis is a something new I have developed entirely. That's why I ask about this issue provided that other statisticians or mathematicians employ similar approaches. I could implement a testing system as well, but I think asking is smarter initially.
The other real problem is filling at the price you think you will get. There are timing and liquidity issues that most people ignore or underestimate.
51% should be enough but this ratio only can't decide whether you can make consistent profit in the long run
You can be profitable with 40% success rate. What matters is how much you make and lose each time you’re right or wrong! And to know that you need to test.
Everything in the stock market is variable, you should advise very well with your broker since he is the one who has the last word in terms of the development of the market. It also counts on your part to train yourself in the market.
%% Good points; since stuff happens, op would well advised , not that this is investment advice,, but money management helps.Without getting to cryptic, some people did fine early paying for pineapple-$8,000 per pineapple.I seldom sell outside the channel as IBD suggests; but since i like the idea/ institution of James Dole Pineapple, i could lose my position + still eat well . NOT a stock tip.
Sounds like an amateur/inexperienced question -- try it, and you'll see the much deeper, dynamic, complex answer,
Hello all. I have concluded this stage of the study. There are a few conclusions got from this model: - Since the model predicts correctly in average the variation of price for next day 75% of the times, it is especially useful to understand when price should not change and when price may or will change even if it should not do it. - By studying where the predictions for next day fail, you can get interesting insights about price action reliability. - The technical indicators improve the model, so they are still good tools. Before using non-linear models I was not able to introduce technical indicators and volume, but after using models based on decision trees and neural networks, those predictors suddenly started to contribute to the accuracy of the models. - The ability to understand price action and interpret charts is a skill superior to this model. This model, as mentioned, may only help to improve the knowledge related to price action, but not to define a system. Finally, I have published a couple of related artifacts: - One is a brief introduction to the system I have developed to generate the model. It is not the model since it targets open prices, not close prices and it does not include any technical indicator to make it more accessible to the general public interested in machine learning applications. It does not include model optimization, feature selection, etc... Just the basic idea to get it quickly. You will see it is quite simple, but it took months of research to understand what to analyze and how to do it exactly. The model used does not require data regularization nor normalization. I have smoothed the data the minimum possible (2 day SMA) to get predictions from it. http://gonzalopla.com/predicting-stock-exchange-prices-with-machine-learning/ - The other is a tool I have developed and it is still quite basic to test price action strategies. It allows to load any financial time series data (stocks, forex, etc.) to generate ticks and simulate orders executions. You can trade several years of real market data in less than one hour with it. I think it is very useful before beginning demo trading to test strategies. It's also free. http://gonzalopla.com/excel-trading-trainer/ Thank you for all the responses you gave for my previous posts.