Forecasting High‐Frequency Risk Measures

This article proposes intraday high‐frequency risk (HFR) measures for market risk in the case of irregularly spaced high‐frequency data. In this context, we distinguish three concepts of value‐at‐risk (VaR): the total VaR, the marginal (or per‐time‐unit) VaR and the instantaneous VaR. Since the market risk is obviously related to the duration between two consecutive trades, these measures are completed with a duration risk measure, i.e. the time‐at‐risk (TaR). We propose a forecasting procedure for VaR and TaR for each trade or other market microstructure event. Subsequently, we perform a backtesting procedure specifically designed to assess the validity of the VaR and TaR forecasts on irregularly spaced data. The performance of the HFR measure is illustrated in an empirical application for two stocks (Bank of America and Microsoft) and an exchange‐traded fund based on Standard & Poor's 500 index. We show that the intraday HFR forecasts capture accurately the volatility and duration dynamics for these three assets. Copyright © 2015 John Wiley & Sons, Ltd.     

Heteroatom-doped graphene for electrochemical energy storage

The increasing energy consumption and envi- ronmental concerns due to burning fossil fuel are key drivers for the development of effective energy storage systems based on innovative materials. Among these materials, graphene has emerged as one of the most promising due to its chemical, electrical, and mechanical properties. Heteroatom doping has been proven as an effective way to tailor the properties of graphene and render its potential use for energy storage devices. In this view, we review the recent developments in the synthesis and applications of heteroatom-doped graphene in supercapacitors and lithium ion batteries.