Predicting time series quantities has been an interesting domain in predictive analytics. Many traditional Quantitative forecasting methods like ARIMA, SES, SMA are time tested and widely used for things like predicting stock prices.
The short time I have spent on Kaggle, I have realized ensembling (stacking models) is the best way to perform well. Stacking is a Model Ensembling technique that combines predictions from multiple models and generates a new model.