Out-of-Sample Performance of Jump-Diffusion Models for Equity Indices: What the Financial Crisis Was Good for

Frey, Roman; Rodrigues, Paulo; Seeger, Norman

doi:10.2139/ssrn.2021818

“…The figure reveals substantial instability in absolute and relative out-of-sample VaR forecast accuracy from the lens of the Correct Conditional Coverage criterion (18), which endorses our dynamic forecast evaluation scheme; see also Frey et al (2013). For the small-cap portfolio, with the exception of the initial part of the out-of-sample period that captures the brunt of Lehman's debacle, the p-values of the DQ test tend to be the largest (leading to less rejections) for the proposed bivariate model; this finding is aligned with the relatively low rejection rates reported for this model in Table 3.…”

Section: Var Predictions Combining Overnight and Intraday Informationsupporting

confidence: 59%

Overnight News and Daily Equity Trading Risk Limits

Ahoniemi¹,

Fuertes

²

,

Olmo

³

2012

SSRN Journal

4

0

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractThis paper proposes a new bivariate modeling approach for setting daily equity-trading risk limits using high-frequency data. We construct one-day-ahead Value-at-Risk (VaR) forecasts by taking into account the different dynamics of the overnight and daytime return processes and their covariance. The covariance is motivated by market microstructure effects such as price staleness and news spillover. Among the competitors we include a simpler bivariate model where the overnight return is redefined by moving the open price further into the trading day, and a univariate model based on the close-to-close return and an overnight-adjusted realized volatility. We illustrate the different approaches using data on the S&P 500 and Russell 2000 indices. The evidence in favour of modeling the covariance is more convincing for the latter index due to the lower trading volumes and, relatedly, the less efficient price discovery at market open for small-cap stocks.

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Overnight News and Daily Equity Trading Risk Limits

Ahoniemi¹,

Fuertes

²

,

Olmo

³

2015

JOURNAL OF FINANCIAL ECONOMETRICS

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractThis paper proposes a new bivariate modeling approach for setting daily equity-trading risk limits using high-frequency data. We construct one-day-ahead Value-at-Risk (VaR) forecasts by taking into account the different dynamics of the overnight and daytime return processes and their covariance. The covariance is motivated by market microstructure effects such as price staleness and news spillover. Among the competitors we include a simpler bivariate model where the overnight return is redefined by moving the open price further into the trading day, and a univariate model based on the close-to-close return and an overnight-adjusted realized volatility. We illustrate the different approaches using data on the S&P 500 and Russell 2000 indices. The evidence in favour of modeling the covariance is more convincing for the latter index due to the lower trading volumes and, relatedly, the less efficient price discovery at market open for small-cap stocks.

show abstract