1. Summary
In the previous Barra model series articles, we constructed the Size factor, Beta factor, Momentum factor, Residual Volatility factor, NonLinear Size factor, Book-to-Price factor, Liquidity factor, Earning_Yeild factor and Growth factor, and created corresponding The single-factor strategy, in which the Size factor and NonLinear Siz factor have strong profitability. This section of the article is the last factor in the series, Leverage factor, also known as leverage factor.
2. Model theory
The calculation method of the Leverage factor of the Barra model is as follows:
The Leverage factor is composed of three sub-factors, including the market leverage factor MLEV, the asset-liability ratio factor DYOA and the book leverage factor BLEV . The weights of the three factors are 0.38, 0.35 and 0.27 respectively. The leverage factor mainly measures the ratio of a company's liabilities to equity.
3. Factor Analysis
Use alphalens to analyze the Leverage factor (2022-April 14, 2023).
Based on the income analysis, the annualized alpha income of the three groups is 3%~4%, and the beta income is negative, and the greater the frequency of rebalancing, the smaller the beta income; the group with the largest leverage factor value and the smallest group both contribute positive returns .
From the perspective of information coefficient, the absolute value of the average IC of each group is less than 0.01, far less than 0.05, indicating that the factor stock selection ability is weak.
From the perspective of grouping income, there is no stable monotonicity between groups, and the changes between groups are irregular.
4. Backtest analysis
Backtesting time: 2022-01-01 to 2023-04-30 (share exchange at the end of the month) Backtesting species: All A shares (excluding ST shares, suspended shares and sub-new shares within one year) Initial capital: 1 million Handling fee: 0.0007 (bilateral 10,000 commission + unilateral 1,000 stamp duty, a total of 1,400, that is, bilateral 1,000 7) Slippage: 0.00123 (two-sided 1,23) Maximum number of positions: 30
During the backtest period, the strategy achieved an annualized rate of return of 8.25%, barely realizing a positive return. During the period, the return of the CSI 300 Index was -18.07%, and the maximum retracement was 20.46%, which occurred after March 2022.
Although this strategy can greatly outperform the index and obtain better positive returns, in the factor analysis, the factor does not show stable monotonicity, and the average IC value is also low. The returns of this strategy may have greater randomness.
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The strategy source code of this issue has been shared with the Nuggets Quantitative Community .
You can get it yourself through the link below.