Similar Search Results

Return and Risk of Pairs Trading Using a Simulation-Based Bayesian Procedure for Predicting Stable Ratios of Stock Prices

Gatarek, Lukasz T. - 2014

risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one … uncertainty with risk and return of stock trading. In terms of methodology, we show the effect that using an encompassing prior … better results in terms of profit per capital engagement and risk than using a standard linear normalization …

Persistent link: https://www.econbiz.de/10013056713

Predicting Asset Returns in Developed and Emerging Markets

Sharma, Ankit - 2012

This paper investigates the predictability of asset prices among developed and emerging markets. Weekly and monthly stock market indices from developed and emerging market economies are analysed to check the validity of weak-form of Efficient Market Hypothesis (EMH) using various empirical...

Persistent link: https://www.econbiz.de/10013101494

Forecasting Stock Returns : Do Commodity Prices Help?

Black, Angela J. - 2014

This paper examines the relationship between stock prices and commodity prices and whether this can be used to forecast stock returns. As both prices are linked to expected future economic performance they should exhibit a long-run relationship. Moreover, changes in sentiment towards commodity...

Persistent link: https://www.econbiz.de/10013050821

Stock Index Returns' Density Prediction Using GARCH Models : Frequentist or Bayesian Estimation?

Hoogerheide, Lennart F. - 2017

Using well-known GARCH models for density prediction of daily S&P 500 and Nikkei 225 index returns, a comparison is provided between frequentist and Bayesian estimation. No significant difference is found between the qualities of the forecasts of the whole density, whereas the Bayesian approach...

Persistent link: https://www.econbiz.de/10012976219

Quantile Forecasts of Inflation Under Model Uncertainty

Korobilis, Dimitris - 2015

Bayesian model averaging (BMA) methods are regularly used to deal with model uncertainty in regression models. This paper shows how to introduce Bayesian model averaging methods in quantile regressions, and allow for different predictors to affect different quantiles of the dependent variable. I...

Persistent link: https://www.econbiz.de/10013022195

Forecasting Stock Returns Under Economic Constraints

Pettenuzzo, Davide - 2014

We propose a new approach to imposing economic constraints on forecasts of the equity premium. Economic constraints are used to modify the posterior distribution of the parameters of the predictive return regression in a way that better allows the model to learn from the data. We consider two...

Persistent link: https://www.econbiz.de/10013064939

The Information Content of High-Frequency Data for Estimating Equity Return Models and Forecasting Risk

Dobrev, Dobrislav - 2011

estimates lead in turn to substantial gains for forecasting various risk measures at horizons ranging from a few days to a few … underestimation of risk during bad times or overestimation of risk during good times. We assess the attainable improvements in VaR …

Persistent link: https://www.econbiz.de/10013128339

Forecasting Stock Returns : A Predictor-Constrained Approach

Pan, Zhiyuan - 2019

We develop a novel method to impose constraints on univariate predictive regressions of stock returns. Unlike the previous approaches in the literature, we implement our constraints directly on the predictor, setting it to zero whenever its value falls below the variable's past 12-month high....

Persistent link: https://www.econbiz.de/10012900845

Portfolio allocation for European markets with predictability and parameter uncertainty

Jondeau, Eric; Rockinger, Michael - 2010

We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model …

Persistent link: https://www.econbiz.de/10008797745

Latent Common Return Volatility Factors : Capturing Elusive Predictive Accuracy Gains When Forecasting Volatility

Cheng, Mingmian - 2017

In this paper, we use factor-augmented HAR-type models to predict the daily integrated volatility of asset returns. Our approach is based on a proposed two-step dimension reduction procedure designed to extract latent common volatility factors from a large dimensional and high-frequency returns...

Persistent link: https://www.econbiz.de/10012952724