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您的检索式：作者名="Helder Sebastiao"
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| 1 | Forecasting and trading cryptocurrencies with machine learning under changing market conditions显示文摘This study examines the predictability of three major cryptocurrencies—bitcoin,ethereum,and litecoin—and the profitability of trading strategies devised upon machine learning techniques(e.g.,linear models,random forests,and support vector machines).The models are validated in a period characterized by unprecedented turmoil and tested in a period of bear markets,allowing the assessment of whether the predictions are good even when the market direction changes between the validation and test periods.The classification and regression methods use attributes from trading and network activity for the period from August 15,2015 to March 03,2019,with the test sample beginning on April 13,2018.For the test period,five out of 18 individual models have success rates of less than 50%.The trading strategies are built on model assembling.The ensemble assuming that five models produce identical signals(Ensemble 5)achieves the best performance for ethereum and litecoin,with annualized Sharpe ratios of 80.17%and 91.35%and annualized returns(after proportional round-trip trading costs of 0.5%)of 9.62%and 5.73%,respectively.These positive results support the claim that machine learning provides robust techniques for exploring the predictability of cryptocurrencies and for devising profitable trading strategies in these markets,even under adverse market conditions. | Helder Sebastiao Pedro Godinho | 2021 | Financial Innovation2021，7，1： | 21 |
| 2 | Industry return lead‑lag relationships between the US and other major countries显示文摘In this study,we analyze the lead-lag relationships between the US industry index and those of six other major countries from January 1973 to May 2021.We identify the leading role played by the US internationally by showing that the weekly returns of US industries,especially the US basic materials and energy industries,significantly Granger cause the returns of most other countries’industries,suggesting that non-US industries react with some delay to new information.This delayed reaction is even more notice-able during periods of recession in the US when cross-country correlations are higher.This implies that the ability of the lagged returns of US industries to predict industries’returns from other countries is even more pronounced when the US experienced an economic recession.A similar asymmetric relationship is found between the volatil-ity of US industries and that of industries in other markets.The analysis of causality in the distribution of returns and volatility shows that causality runs mainly from the US to other countries,particularly in the presence of extreme negative shocks.Finally,we demonstrate that our predictions are valuable to real-world investors.Long-short strategies generate sizable and statistically significant alphas,and a constant relative risk-averse investor obtains certainty equivalent returns well above the risk-free rate. | Ana Monteiro Nuno Silva Helder Sebastiao | 2023 | Financial Innovation2023，9，1： | 0 |
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