Seasonal Predictability of Stock Market Returns

This paper focuses on the seasonal predictability of stock market returns. we investigate the statistical significance of predicting stock returns from several calendar dummies. Our main findings, using monthly stock market returns from Belgium. Germany, the Netherlands, UK and US, are that the January effect disappears over time, but a strong support is found for the Sell-in-May effect. This implies that for each country, the returns are on average significantly higher in the winter than i the summer periods. Finally, we only find moderate support for a decennial cycle. Years ending in five have historically been the best years to invest in US stock, but this cycle effect is not found in the other countries.

The Economic Value of Predicting Stock Index Returns and Volatility

In this paper, we analyze the economic value of predicting index returns as well as volatility. On the basis of fairly simple linear models, estimated recursively, we produce genuine out-of-sample forecasts for the return on the S&P 500 index and its volatility. Using monthly data from 1954-1998, we test the statistical significance of return and volatility predictably and examine the economic value of a number of alternative trading strategies. We find strong evidence for market timing in both returns and volatility. Joint tests indicate no dependence between return and volatility timing, while it appears easier to forecast returns when volatility is high. For a mean-variance investor, this predictably is economically profitable, even if short sales are not allowed and transaction costs are quite large.Predicability of stock returns and volatility

Do Macroeconomic Announcements Cause Asymmetric Volatility

multivariate GARCH;volatility;macroeconomics;garch models;stock markets;bond markets

The Economic Value of Predicting Stock Index Returns and Volatility

In this paper, we analyze the economic value of predicting index returns as well as volatility. On the basis of fairly simple linear models, estimated recursively, we produce genuine out-of-sample forecasts for the return on the S&P 500 index and its volatility. Using monthly data from 1954-1998, we test the statistical significance of return and volatility predictably and examine the economic value of a number of alternative trading strategies. We find strong evidence for market timing in both returns and volatility. Joint tests indicate no dependence between return and volatility timing, while it appears easier to forecast returns when volatility is high. For a mean-variance investor, this predictably is economically profitable, even if short sales are not allowed and transaction costs are quite large

Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning

CT Perfusion (CTP) imaging has gained importance in the diagnosis of acute stroke. Conventional perfusion analysis performs a deconvolution of the measurements and thresholds the perfusion parameters to determine the tissue status. We pursue a data-driven and deconvolution-free approach, where a deep neural network learns to predict the final infarct volume directly from the native CTP images and metadata such as the time parameters and treatment. This would allow clinicians to simulate various treatments and gain insight into predicted tissue status over time. We demonstrate on a multicenter dataset that our approach is able to predict the final infarct and effectively uses the metadata. An ablation study shows that using the native CTP measurements instead of the deconvolved measurements improves the prediction.Comment: Accepted for publication in Medical Image Analysi

The link between market orientation and performance in the Australian public sector

Marketing academics and practitioners assume a direct link between market orientation and performance and argue that this applies to both business and non-business organisations. While this aspect has been studied in the business sector, this paper discusses the concepts of market orientation and performance and investigates this relationship in the Australian public sector. The conceptualization of market orientation used is that by Jaworski and Kohli (1993) on which basis MARKOR was developed. This instrument together with an instrument to measure the perceptions of performance of senior managers in the Australian public sector are used to investigate the hypothesized link. The findings confirm a positive relationship between market orientation and performance. The size and type of public sector organisation involved are also found to affect the levels of market orientation together with its components and performance. From the findings, implication are drawn and directions for future research discussed.peer-reviewe