首页|Reports from Charles University of Prague Highlight Recent Findings in Machine L earning (Multi-horizon Equity Returns Predictability Via Machine Learning)
Reports from Charles University of Prague Highlight Recent Findings in Machine L earning (Multi-horizon Equity Returns Predictability Via Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Machine Learn ing have been published. According to news reporting originating from Prague, Cz ech Republic, by NewsRx editors, the research stated, "We investigate the predic tability of global expected stock returns across various forecasting horizons us ing machine learning techniques. We find that the predictability of returns decr eases with longer forecasting horizons both in the U.S. and internationally." Our news editors obtained a quote from the research from the Charles University of Prague, "Despite this, we provide evidence that using firm -specific characte ristics can remain profitable even after accounting for transaction costs, espec ially when we consider longer forecasting horizons. Studying the profitability o f long -short portfolios, we highlight a trade-off between higher transaction co sts connected to frequent rebalancing and greater returns on shorter horizons. I ncreasing the forecasting horizon while matching the rebalancing period increase s risk -adjusted returns after transaction costs for the U.S. We combine predict ions of expected returns at multiple horizons using double -sorting and a turnov er reducing strategy, buy/hold spread."
PragueCzech RepublicEuropeCyborgsEmerging TechnologiesInvestment and FinanceMachine LearningCharles Univer sity of Prague
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