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Full-Text Articles in Law
Commodity Futures Returns And Policy Uncertainty, Deepa Bannigidadmath, Paresh Kumar Narayan
Commodity Futures Returns And Policy Uncertainty, Deepa Bannigidadmath, Paresh Kumar Narayan
Research outputs 2014 to 2021
© 2020 Elsevier Inc. This paper investigates whether economic policy uncertainty is predictable using three sets of commodity futures market variables, namely the equal-weighted average of futures excess returns, the excess returns on a portfolio of going long in backwardated commodities, and the excess returns on a portfolio of going short in contango commodities as predictors. We find significant evidence of both in-sample and out-of-sample predictability. Combination forecasts also reveal strong evidence of predictability. Our findings remain unchanged following several robustness tests.
From The Tree Of Knowledge And The Golem Of Prague To Kosher Autonomous Cars: The Ethics Of Artificial Intelligence Through Jewish Eyes, Nachshon Goltz, John Zeleznikow, Tracey Dowdeswell
From The Tree Of Knowledge And The Golem Of Prague To Kosher Autonomous Cars: The Ethics Of Artificial Intelligence Through Jewish Eyes, Nachshon Goltz, John Zeleznikow, Tracey Dowdeswell
Research outputs 2014 to 2021
This article discusses the regulation of artificial intelligence from a Jewish perspective, with an emphasis on the regulation of machine learning and its application to autonomous vehicles and machine learning. Through the Biblical story of Adam and Eve as well as Golem legends from Jewish folklore, we derive several basic principles that underlie a Jewish perspective on the moral and legal personhood of robots and other artificially intelligent agents. We argue that religious ethics in general, and Jewish ethics in particular, show us that the dangers of granting moral personhood to robots and in particular to autonomous vehicles lie not …
Generalized Correlation Measures Of Causality And Forecasts Of The Vix Using Non-Linear Models, David E. Allen, Vince J. Hooper
Generalized Correlation Measures Of Causality And Forecasts Of The Vix Using Non-Linear Models, David E. Allen, Vince J. Hooper
Research outputs 2014 to 2021
This paper features an analysis of causal relations between the daily VIX, S & P500 and the daily realised volatility (RV) of the S & P500 sampled at 5 min intervals, plus the application of an Artificial Neural Network (ANN) model to forecast the future daily value of the VIX. Causal relations are analysed using the recently developed concept of general correlation Zheng et al. and Vinod. The neural network analysis is performed using the Group Method of Data Handling (GMDH) approach. The results suggest that causality runs from lagged daily RV and lagged continuously compounded daily return on the …