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We use machine learning methods to forecast individual stock returns and create long-short portfolios in the Brazilian stock market, using a rich data set including technical and fundamental predictive signals. We further develop an algorithm that combines long-short portfolios obtained with various machine learning methods such that (i) the risk c...
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... use an exponentially-weighted moving average estimator with a decay factor of λ = 0.96 to estimate this covariance matrix each month, starting with one year of daily returns. 18 The results are shown in Figure 3. Most of the time, κ t is lower than 1, in order to balance the risk contributions of the long and short legs, due to the higher volatility of the P 1 portfolios. ...
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