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Forecasting value at risk with intra-day return curves

Rice, G., Wirjanto, T., Zhao, Y. (2020) Forecasting value at risk with intra-day return curves. International Journal of Forecasting, 36 (3). pp. 1023-1038. ISSN 0169-2070. (doi:10.1016/j.ijforecast.2019.10.006) (KAR id:93923)

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Official URL:
http://dx.doi.org/10.1016/j.ijforecast.2019.10.006

Abstract

Methods for incorporating high resolution intra-day asset price data into risk forecasts are being developed at an increasing pace. Existing methods such as those based on realized volatility depend primarily on reducing the observed intra-day price fluctuations to simple scalar summaries. In this study, we propose several methods that incorporate full intra-day price information as functional data objects in order to forecast value at risk (VaR). Our methods are based on the recently proposed functional generalized autoregressive conditionally heteroscedastic (GARCH) models and a new functional linear quantile regression model. In addition to providing daily VaR forecasts, these methods can be used to forecast intra-day VaR curves, which we considered and studied with companion backtests to evaluate the quality of these intra-day risk measures. Using high-frequency trading data from equity and foreign exchange markets, we forecast the one-day-ahead daily and intra-day VaR with the proposed methods and various benchmark models. The empirical results suggested that the functional GARCH models estimated based on the overnight cumulative intra-day return curves exhibited competitive performance with benchmark models for daily risk management, and they produced valid intra-day VaR curves.

Item Type: Article
DOI/Identification number: 10.1016/j.ijforecast.2019.10.006
Uncontrolled keywords: Forecasting comparison; Functional GARCH; Intra-day VaR backtesting; Overnight cumulative intra-day return; Value at risk
Subjects: H Social Sciences
H Social Sciences > H Social Sciences (General)
Divisions: Divisions > Kent Business School - Division > Department of Accounting and Finance
Depositing User: Yuqian Zhao
Date Deposited: 17 May 2022 09:39 UTC
Last Modified: 18 May 2022 09:27 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/93923 (The current URI for this page, for reference purposes)
Zhao, Y.: https://orcid.org/0000-0002-5396-3316
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