1) What Events Matter For Exchange Rate Volatility ? (with Hedibert Lopes, Submitted)
2) Dynamic copula models with variable selection (with Hedibert Lopes, Draft available upon request)
3) Forecasting using DFM: A sparse principal components approach (with Marcio Laurini)
1) Currency Carry Under Falling Stars (with Mohammed M. Kaebi)
2) Firm Characteristics and Stock Returns in Brazil (with R. Ribeiro, J. Costa, M. M. Kaebi and T. Nobrega)
Published in Entropy, 2024
This paper expands traditional stochastic volatility models by allowing for time-varying skewness without imposing it. While dynamic asymmetry may capture the likely direction of future asset returns, it comes at the risk of leading to overparameterization. Our proposed approach mitigates this concern by leveraging sparsity-inducing priors to automatically select the skewness parameter as dynamic, static or zero in a data-driven framework.In a bond yield application, dynamic skewness captures interest rate cycles of monetary easing and tightening and is partially explained by central banks’ mandates.
Recommended citation: Martins, Igor, and Hedibert Freitas Lopes. 2024. "Stochastic Volatility Models with Skewness Selection" Entropy 26, no. 2: 142.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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