Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 9 of 9 for “"return prediction"”.
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Artificial Neural Networks in Stock Return Prediction: Testing Model Specification in a Global Context
… and technical factors can accurately predict the returns of a sample of several large-cap stocks from various markets across the globe. This study also explores which hidden layer configuration leads to the best network predictive performance. Furthermore, this research identifies which …
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Essays on Real Estate Finance and Machine Learning
… significant out-of-sample improvement in the return prediction of U.S. REITs. I find that return predictability is improved and REIT investors experience significant economic gains when using machine learning forecasts as compared to traditional OLS forecasts. I also discover that REITs are …
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Research and Development of risk arbitrage trading systems
… We utilized this information to develop a merger return prediction model that predicts a merger's return given various deal characteristics. We constructed several portfolios, one using a trading strategy in which we invest equally in every announced deal, one where we invest only in deals that …
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Cash Flow as a Predictor of Share Returns: Evidence from the Johannesburg Stock Exchange
… traditional asset-pricing models can model share returns. Despite this, there is limited empirical evidence on cash flow metrics as anomalies, and less so on cash flows as a predictor of share returns. The aim of this study is to provide a new insight into the South African equity market by …
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Essays in Empirical Asset Pricing and International Finance
… R², gains in average excess portfolio returns, and a range of risk-adjusted metrics such as the Sharpe ratio, Sortino ratio, Calmar ratio, and gain-to-pain ratio. Moreover, the rolling out-of-sample R² underscores sDOC's adaptability under both calm and turbulent market conditions, …
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Multiple nonlinear prediction of S&P500 returns using an ANFIS
Diese Arbeit präsentiert mit dem ANFIS ein Konzept aus dem Machine Learning mit dessen Hilfe die Rendite des S&P500 nichtlinear vorhergesagt wird. In Anlehnung an Welch and Goyal (2008) wird als Vergleichsgröße zur Renditevorhersage der historische Durchschnitt der Rendite verwendet. Das ANFIS wird …
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Essays in Financial Economics and Asset Pricing
… finding is that precision is priced in excess returns, but the relation between precision and risk premiums is not linear. The main channel for precision to take effects is marginal utility. The sensitivity of a trader's marginal utility to her trading quantity is determined by her risk …