High-Frequency Risk Measures

Denisa Georgiana Banulescu (1, 2) , Gilbert Colletaz (1) , Christophe Hurlin (1) , Sessi Tokpavi (3)

1 LEO - Laboratoire d'économie d'Orleans [2008-2011]
2 Maastricht University [Maastricht]
3 EconomiX - EconomiX

This paper proposes an intraday high-frequency risk (HFR) measure specifically designed for HFR management and high-frequency trading (HFT). The HFR measure is a conditional joint measure of market risk and liquidity risk for irregularly spaced high-frequency data. It combines two well-known risk measures, i.e., value at risk (VaR) and time at risk (TaR). We propose a forecasting procedure for both measures, which complies with HFR management requirements, particularly in terms of the information set. We also differentiate between three concepts of intraday VaR: total, marginal (or per time unit) and instantaneous VaR. Finally, we propose a backtesting procedure specifically designed to assess the validity of the VaR and TaR forecasts for each trade or other market microstructure event. The performance of the HFR measure is illustrated in an empirical application to two stocks (Bank of America and Microsoft) and an exchange-traded fund (ETF) based on Standard and Poor's (the S&P) 500 index. We show that the intraday VaR and TaR forecasts accurately capture the volatility and duration dynamics for these three assets.

Mots clés: Backtesting.; High Frequency Risk Measure; High Frequency Trading; Value at Risk; Time at Risk; Backtesting

Domaines: Economies et finances

Denisa Georgiana Banulescu, Gilbert Colletaz, Christophe Hurlin, Sessi Tokpavi. High-Frequency Risk Measures. 2013. ⟨halshs-00859456v2⟩