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Abstract
Several hidden risks of factor investing can lead to investor disappointment; even diversified baskets of factors are prone to sharp drawdowns and prolonged periods of underperformance. Accordingly, the authors explore a variety of techniques to improve the risk-adjusted returns of individual factors and factor portfolios. Introducing a new two-step volatility management method that adjusts the length of the estimation window to scale factor returns, the authors find that this technique is effective in improving both risk-adjusted returns and the trade-off between performance improvement and turnover characteristics. Ultimately, coupling this novel two-step approach with an optimization technique that captures both volatility and correlation information leads to improved risk-adjusted performance, lower volatility of volatility, and improved kurtosis and drawdown characteristics.
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