A Note on Forecasting Daily Peruvian Stock Market Volatility Risk Using Intraday Returns

  • Mauricio Zevallos University of Campinas
Keywords: High frequency data, Quantile Regression, Value-at-Risk

Abstract

In this paper I present a model to forecast the daily Value at Risk (VaR) of the Peruvian stock market (measured through the general index of the Lima Stock Exchange: the IGBVL) based on intraday (high-frequency) data. Daily volatility is estimated using realised volatility and I adopted a regression quantile approach to calculate one-step predicted VaR values. The results suggest that the realised volatility is a useful measure to explain the Peruvian stock market volatility and I obtained sound results using quantile regression for risk estimation.

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How to Cite
Zevallos, M. (2019). A Note on Forecasting Daily Peruvian Stock Market Volatility Risk Using Intraday Returns. Economia, 42(84), 94-101. https://doi.org/10.18800/economia.201902.004