Shock-triggered asymmetric response stochastic volatility

Juan Miguel Marín Díazaraque and María Helena Lopes Moreira da Veiga

DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística

Abstract: We propose a novel asymmetric stochastic volatility model (STAR-SV) in which the leverage parameter adjusts to the magnitude of past shocks. This flexible specification captures both the leverage effects and their propagation more effectively than standard asymmetric volatility models. To estimate the STAR-SV parameters, we implement a data cloning algorithm that approximates the maximum likelihood estimates and their asymptotic variances. In finite-sample simulations, data cloning consistently leads to reliable estimates and small standard errors. Empirically, we fit the model to Bitcoin, Nasdaq and S&P 500 returns and evaluate 1 and 10-day volatility forecasts, using unconditional and conditional tests of predictive ability. STAR-SV using data cloning proves to be the most adequate forecaster, outperforming the most stringent confidence thresholds and weakly dominating in several variance regimes. Finally, we show the performance of the model in predicting the 99% Value-at-Risk. STAR-SV, using data cloning, seems to respond quickly to volatility spikes and passes backtests for both time horizons.

Keywords: Stochastic; volatility; Data; cloning; Value-at-risk; Leverage; effect; Leverage; propagation; Volatility; Forecasting (search for similar items in EconPapers)
JEL-codes: C15 C32 C53 G15 G17 (search for similar items in EconPapers)
Date: 2023-02-14
New Economics Papers: this item is included in nep-ecm and nep-ets
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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:36569

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