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On the Directional Predictability of Equity Premium Using Machine Learning [pdf]
- Bostonian 7y agoNow published in the Journal of Forecasting: https://onlinelibrary.wiley.com/doi/abs/10.1002/for.2632 https://onlinelibrary.wiley.com/doi/abs/10.1002/for.2632 . The data is at http://www.hec.unil.ch/agoyal/docs/PredictorData2018.xlsx http://www.hec.unil.ch/agoyal/docs/PredictorData2018.xlsx . The classification models aim to predict whether the monthly stock market return is positive or negative. I wonder how you modify a classification problem when some errors are more costly than others (other than just treating it as a regression problem). Predicting the stock market goes up is more costly when it falls 10% than when it falls 1%. The working paper "Predicting Stock Market Returns with Machine Learning" at https://sites.google.com/site/albertorossifrb/research https://sites.google.com/site/albertorossifrb/research attacks the same problem using machine learning regression models.