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We propose a nonparametric method to study which characteristics provide incremental information for the cross section of expected returns. We use the adaptive group LASSO to select characteristics and to estimate how they affect expected returns nonparametrically. Our method can handle a large...
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on subsequent stock market returns and exacerbates stock market volatility. Furthermore, stocks with large, negative …
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This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of unknown underlying … sensitive to start value. Hence, two-stage QML has been suggested. In empirical estimation on two stock transaction data for …
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We plot aggregated daily stock returns with absolute value less than x against x and show empirically that this produces a typical spoon-shaped pattern which indicates a special type of asymmetry which has not been discussed before. This pattern disappears when individual returns are averaged; it...
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for volatility, correlation and covariance using high frequency financial data. It also implements complementary … paper first presents the issues associated with exploiting high frequency financial data. We then describe the volatility …
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