Betting Against Beta

This codebase is based on the paper: Frazzini, A. & Pedersen, L. (2014). Betting Against Beta, available online here. It seeks to implement the work discussed in the paper. Namely:

• Since constrained investors bid up high-beta assets, high beta is associated with low alpha.
• A betting-against-beta (BAB) factor, which is long leveraged lowbeta assets and short high-beta assets, produces significant positive risk-adjusted returns.
• When funding constraints tighten, the return of the BAB factor is low.
• Increased funding liquidity risk compresses betas toward one.
• More constrained investors hold riskier assets.

Data

• Data folder stores the fetched data and Data.py.

• Data.py consists of 2 parts: save tickers, get data. Tickers are processed through website information, data are fetched using 'pandas-datareader'.

Implementation

• main.py contains all the functions.

• figure.py is for drawing plots.

Results

This strategy was back-tested on SP500 stocks and TSX (Toronto Stock Exchange) stocks and compared with two other similar factors presented in the Fama French 3-factor model: one is the SMB (small minus big), the other is the HML (high minus low). SMB and HML data were obtained from Ken French’s data library

Cumulative Return with $1 invested in the beginning in the SP500 (shown as US) equity market (in comparison with the SMB and HML factors)

Cumulative Return with $1 invested in the beginning in the TSX (shown as CAN) equity market (in comparison with the SMB and HML factors)

Evaluation

• Portfolio construction

• Hedging

• Trading cost: Looking at the actual weights the strategy puts on stocks with different market cap, we find out small-cap stocks are overweighted, causing significant implementation issues because the smallest stocks usually have limited capacity and are expensive to trade.

Further Development

• Set some threshold regarding the market capitalization when assigning weights

• Mitigate risk using diversification

• Explore the relationship between the strategy and market states, and refine it by incorporating the judgment of market trends into the strategy

Reference

1. Andrea Frazzini and Lasse Heje Pedersen. Betting against beta. Journal of Financial Economics, 111(1):1–25, 2014