Скачать с ютуб 3.2) Has your optimization overfitted your trading system? The two reasons you WILL be over-fitting в хорошем качестве

3.2) Has your optimization overfitted your trading system? The two reasons you WILL be over-fitting

Over-fitting in optimizations happens for two primary reasons: Over-fitting to noise, and over-fitting to events. This video will look at each in turn. Brought to you by Darwinex: https://www.darwinex.com/?utm_source=... Price Action Noise: By attempting to model the overall price action too closely with a large number of parameters means that the model is forced to adapt to the noise and random action to a degree that is to the detriment of being able to model the thing we really need to - the purposeful price action – the outcome is that the model has reduced predictive power for this purposeful price action on future data. Events in the Price Action: Did your backtest results appear successful because of great parameter values of a generalized model, or is it because of the pure chance of benefitting from a few major news events? If the parameters are fitted to the past data, the probability that these values will continue to take advantage of news events in the future is pretty low. We start to dig deeper into the implications of both of these issues. For viewing the whole series in one place, visit https://community.darwinex.com/t/vide... ----------------------------------------    • Algorithmic Backtesting & Optimizatio...   #AlgoTrading, #AlgorithmicTrading, #Backtesting, #Optimization, #Overfitting, #Overoptimization, #PriceAction, #Noise, #EconomicNews, #News Price Action Noise: By attempting to model the overall price action too closely with a large number of parameters means that the model is forced to adapt to the noise and random action to a degree that is to the detriment of being able to model the thing we really need to - the purposeful price action – the outcome is that the model has reduced predictive power for this purposeful price action on future data. Events in the Price Action: Did your backtest results appear successful because of great parameter values of a generalized model, or is it because of pure chance of benefitting from a few major news events? If the parameters are fitted to the past data, the probability that these values will continue to take advantage of news events in the future is pretty low. We start to dig deeper into the implications of both of these issues. ----------------------- IMPORTANT REQUEST: Please please please.. if you find this content useful, please do consider liking and sharing it on YouTube, Twitter, Facebook, LinkedIn and whatever other social networks you have circles in. Darwinex relies almost exclusively on organic growth, primarily through recommendation via informative content. YouTube’s algorithms measure the quality of Darwinex content on the basis of: Reach Engagement and several other related variables With seemingly small actions such as: Clicking the Like button Clicking the Subscribe button Clicking the Share button (on YouTube) and distributing our content etc … YOU inform YouTube’s algorithms of your sentiment towards Darwinex, thereby directly helping Darwinex MASSIVELY in achieving organic growth. Thank you very much for your kind consideration! ----------------------- Risk disclosure: https://www.darwinex.com/legal/risk-d... ** Fancy joining a vibrant community of algorithmic traders, quants and data scientists focused on financial hacking? Join the Darwinex Collective Slack Workspace: https://join.slack.com/t/darwinex-col... #overoptimization,#priceaction,#algorithmictrading,#backtesting,#algotrading,#optimization,#overfitting,#noise,#news