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Algorithmic Trading Strategy Development and Optimisation

Owen Nyo Wei Yuan, Victor Tan Jia Xuan, Ong Jun Yao Fabian, Ryan Tan Jun Wei

Abstract

The report presents with the development and optimisation of an enhanced algorithmic trading strategy through the use of historical S&P 500 market data and earnings call sentiment analysis. The proposed strategy integrates various technical indicators such as moving averages, momentum, volatility, and FinBERT-based sentiment analysis to improve overall trades being taken. The results show that the enhanced strategy significantly outperforms the baseline model in terms of total return, Sharpe ratio, and drawdown amongst other factors. The findings helped demonstrate the relevance and effectiveness of combining technical indicators, sentiment analysis, and computational optimisation in algorithmic trading systems.

Algorithmic Trading Strategy Development and Optimisation

Abstract

The report presents with the development and optimisation of an enhanced algorithmic trading strategy through the use of historical S&P 500 market data and earnings call sentiment analysis. The proposed strategy integrates various technical indicators such as moving averages, momentum, volatility, and FinBERT-based sentiment analysis to improve overall trades being taken. The results show that the enhanced strategy significantly outperforms the baseline model in terms of total return, Sharpe ratio, and drawdown amongst other factors. The findings helped demonstrate the relevance and effectiveness of combining technical indicators, sentiment analysis, and computational optimisation in algorithmic trading systems.
Paper Structure (51 sections, 6 equations, 7 figures, 1 table)

This paper contains 51 sections, 6 equations, 7 figures, 1 table.

Table of Contents

  1. Introduction
  2. Project Overview
  3. Motivation and Background
  4. Objectives
  5. Enhanced Exploratory Data Analysis (EDA)
  6. Momentum vs Future Returns
  7. Cumulative Returns
  8. 200-Day Moving Average
  9. Average True Range (ATR)
  10. Momentum Decile Analysis
  11. ATR Bucket Analysis
  12. Momentum-to-Volatility Ratio
  13. Data Cleaning and Preparation
  14. Duplicate Removal and Date Standardisation
  15. Handling Missing Price Values
  16. ...and 36 more sections

Figures (7)

  • Figure 1: Baseline vs Enhanced Strategy Comparison
  • Figure A1: 63-Day Momentum vs Forward 21-Day Return
  • Figure A2: Cumulative Returns: Top Momentum Portfolio vs Market Average
  • Figure A3: ATR(14) Volatility vs Forward 21-Day Return
  • Figure A4: Momentum Deciles vs Average 21-Day Forward Return
  • ...and 2 more figures