Skip to content

Latest commit

 

History

History
32 lines (23 loc) · 1.86 KB

README.md

File metadata and controls

32 lines (23 loc) · 1.86 KB

Can the “Sell in May and Go Away” Strategy Produce Excess Returns in the TSX?

This project was created by Mahir Mehta and Isaiah Sinclair.

Abstract

“Sell in May and Go Away” (also known as the “Halloween Effect”) is a calendar effect which posits that the returns in the stock market from the 6-month period of May-October are outperformed by the returns from November-April. This research investigates the strength of this effect in the TSX with samples from over 20 years of data across the 4 oldest and largest ETFs (by assets) under management. However, we performed most of our research using the XIU ETF, which is well-diversified in the 60 top companies in the TSX. We perform tests on the models for the difference in return between the two 6-month periods. After demonstrating some statistically significant evidence of a Halloween Effect, we construct a Halloween Effect trading strategy, where we buy risk-free assets during May-October, and invest in the stock market during the November-April period. We compare the results of this model with the results of a standard buy-and-hold strategy in the XIU ETF, evaluating if there is a statistically significant alpha value that can be derived using the Capital Asset Pricing Model (CAPM). We also analyze the parameter stability of these models.

Technologies Used

  • Python
  • Pandas
  • Statsmodels
  • Jupyter Notebook
  • yfinance
  • Excel

Other Skills Demonstrated

  • Statistical Analysis
  • Financial Econometrics

Data

The data was downloaded from the Bank of Canada website. It has been included in this repository in tbill_all.csv. Some of the intial rows were removed using Excel for easier data cleaning with Pandas. Please note that the column 'V80691345' represents the 6-month t-bill yield that is used in our empirical research. The data is cleaned by the Python Juypter notebook when it is run.