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Kelly, Bryan T.; Xiu, Dacheng - National Bureau of Economic Research - 2023

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

Persistent link: https://www.econbiz.de/10014322889

Comparing Predictive Accuracy

Diebold, Francis X. - 1994

Using research designs patterned after randomized experiments, many recent economic studies examine outcome measures for treatment groups and comparison groups that are not randomly assigned. By using variation in explanatory variables generated by changes in state laws, government draft...

Persistent link: https://www.econbiz.de/10012473994

Stock Market Forecastability and Volatility : A Statistical Appraisal

Mankiw, N. Gregory - 1989

This paper presents and implements statistical tests of stock market forecastability and volatility that are immune …

Persistent link: https://www.econbiz.de/10012475889

Comprehensive OOS Evaluation of Predictive Algorithms with Statistical Decision Theory

Dominitz, Jeff; Manski, Charles F. - National Bureau of Economic Research - 2024

We argue that comprehensive out-of-sample (OOS) evaluation using statistical decision theory (SDT) should replace the current practice of K-fold and Common Task Framework validation in machine learning (ML) research. SDT provides a formal framework for performing comprehensive OOS evaluation...

Persistent link: https://www.econbiz.de/10014512123

Index-Option Pricing with Stochastic Volatility and the Value of Accurate Variance Forecasts

Engle, Robert F. - 1993

In pricing primary-market options and in making secondary markets, financial intermediaries depend on the quality of forecasts of the variance of the underlying assets. Hence, the gain from improved pricing of options would be a measure of the value of a forecast of underlying asset returns....

Persistent link: https://www.econbiz.de/10012474423

Mispriced Index Option Portfolios

Constantinides, George M. - 2017

The optimal portfolio of a utility-maximizing investor trading in the S&P 500 index and cash, subject to proportional transaction costs, becomes stochastically dominated when overlaid with a zero-net-cost portfolio of S&P 500 options bought at their ask and written at their bid price in most...

Persistent link: https://www.econbiz.de/10012454974

Why Has U.S. Inflation Become Harder to Forecast?

Stock, James H. - 2006

inflation process is well described by an unobserved component trend-cycle model with stochastic volatility or, equivalently, an …

Persistent link: https://www.econbiz.de/10012466341

Answering the Critics : Yes, ARCH Models Do Provide Good Volatility Forecasts

Andersen, Torben G. - 1997

Volatility permeates modern financial theories and decision making processes. As such, accurate measures and good … forecasts of future volatility are critical for the implementation and evaluation of asset pricing theories. In response to this …, a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility at the daily …

Persistent link: https://www.econbiz.de/10012472795

The Predictive Ability of Several Models of Exchange Rate Volatility

West, Kenneth D. - 1994

We compare the out-of-sample forecasting performance of univariate homoskedastic, GARCH, autoregressive and nonparametric models for conditional variances, using five bilateral weekly exchange rates for the dollar, 1973-1989. For a one week horizon, GARCH models tend to make slightly more...

Persistent link: https://www.econbiz.de/10012474328

Valuation of Variance Forecast with Simulated Option Markets

Engle, Robert F. - 1990

An appropriate metric for the success of an algorithm to forecast the variance of the rate of return on a capital asset could be the incremental profit from substituting it for the next best alternative. We propose a framework to assess incremental profits for competing algorithms to forecast...

Persistent link: https://www.econbiz.de/10012475683

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