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Forecasting Stock Prices using XGBoost (Part 3/5)

Augmenting Features using Technical Indicators

This article repeats the analysis in Part 2, but here we add technical indicators into the list of features for the stock price prediction model. The aim is to observe if technical indicators will improve the performance of the model.

Problem Statement
Feature Engineering with Technical Indicators
Training, Validation, Test split
Hyperparameter Tuning
Applying the Model
Findings

Problem Statement

Here, we aim to predict the daily returns of Vanguard Total Stock Market ETF (VTI), using data from the previous N days. In this experiment, we will use 6 years of historical prices for VTI from 2013–01–02 to 2018–12–28, which can be easily downloaded from yahoo finance. After downloading, the dataset looks like this:

Downloaded dataset for VTI. The column ‘daily_ret’ is computed.

Altogether, we have 1509 days of data to play with. Note that Saturdays and Sundays are not included in the dataset above. A plot of the adjusted closing price in the…