ALL THINGS BIG AND SMALL 2.0

Thanks to EODHD.com for the price data that make my posts possible. When you need high quality financial markets data, you can rely on EODHD.com-they are the best.  EODHD clients who are financial modeling enthusiasts or funds are welcome to contact me for writing or analysis tasks:    tiankhean@gmail.com .  I live in Singapore so there may be time zone differences to take into consideration Introduction When we are not using fundamental data for investment analysis, we use price and volume data (Open, High, Low, Close, Volume).   RSI, MACD, Moving Averages, Stochastics and all those TA tools. They may be useful for visualization of momentum, trading range, volatility, reversion to the mean and so on. But when it comes to probabilistic predictions, clustering and classification for arbitrage, portfolio optimization or complex pattern recognition, advanced statistical techniques have a clear edge.   Many of these techniques have always been there, but th...

  What are Ensembles Ensemble methods in predictive modeling are like gathering the opinions of multiple experts to make a final decision. Instead of relying on just one model to predict future market trends or ETF performance, ensemble techniques combine several different models to improve accuracy and reduce the risk of errors. Using a group of models, instead of just one, Ensembles "vote" on what should be the final output, leading to more reliable and balanced predictions. In regression models, ensemble methods typically use averaging to arrive at a final prediction. The final prediction is the average of all the individual predictions from these models. In boosting techniques, models are built sequentially, each improving upon the errors of the previous ones, and their predictions are also averaged to yield a final result. By combining multiple models, ensemble methods smooth out any individual errors, leading to more accurate and reliable predictions in tasks such a...