Estimation and simulation of risk premia in equity and foreign exchange markets

There is substantial evidence to reject constant-risk-premia financial models. While time-varying risk premia are often mentioned as an alternative, the literature has yet to produce an example that accounts for the important time-series properties of asset returns. We inquire whether mean-variance...

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Published in:Journal of international money and finance 2000-08, Vol.19 (4), p.561-582
Main Authors: Kim, Inbae, Salemi, Michael K.
Format: Article
Language:English
Subjects:
Foreign exchange
Foreign exchange markets
Hedging
Hypotheses
Mathematical models
Mean-variance optimization
Real income
Risk premiums
Securities markets
Statistical analysis
Studies
Time-varying risk premium
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description There is substantial evidence to reject constant-risk-premia financial models. While time-varying risk premia are often mentioned as an alternative, the literature has yet to produce an example that accounts for the important time-series properties of asset returns. We inquire whether mean-variance optimization models can do so. We model asset risk with an absolute-error version of the ARCH-in-mean hypothesis and model hedging motives that derive from variation in future real income and inflation to account for agent heterogeneity. We consider a three-country-and-two-asset world. Our model predicts values for five excess returns relative to the US bill rate. We use a systems approach to estimate the model parameters and then simulate the estimated model to determine if it can account for the important time-series properties of risk premia.
doi_str_mv 10.1016/S0261-5606(00)00020-6
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source International Bibliography of the Social Sciences (IBSS); Elsevier
subjects Foreign exchange
Foreign exchange markets
Hedging
Hypotheses
Mathematical models
Mean-variance optimization
Real income
Risk premiums
Securities markets
Statistical analysis
Studies
Time-varying risk premium
title Estimation and simulation of risk premia in equity and foreign exchange markets
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