The dependence of foreign exchange rates on order flow is investigated for four major exchange rate pairs, EUR/USD, EUR/GBP, GBP/USD and USD/JPY, across sampling frequencies ranging from 5 min to 1 week. Strong explanatory power is discovered for all sampling frequencies. We also uncover...

We exploit full order level information from an electronic FX broking system to provide a comprehensive account of the determination of its liquidity. We not only look at bid-ask spreads and trading volumes, but also study the determination of order entry rates and depth measures derived from...

Most of the existing empirical literature on FX market microstructure uses indicative quote data derived from Reuters EFX Screens. This paper examines the adequacy of such data as proxies for firm, tradeable quotes. We present a comparison of prices (and volumes) derived from Reuters D2000-2...

The quality of statistical risk models is much lower than often assumed. Such models are useful for measuring the risk of frequent small events, such as in internal risk management, but not for systemically important events. Unfortunately, it is common to see unrealistic demands placed on risk...

Accurate prediction of the frequency of extreme events is of primary importance in many financialapplications such as Value-at-Risk (VaR) analysis. We propose a semi-parametric method for VaRevaluation. The largest risks are modelled parametrically, while smaller risks are captured by the...

Large one-off events cause large changes in prices, but may not affect the volatility and correlation dynamics as much as smaller events. In such cases, standard volatility models may deliver biased covariance forecasts. We propose a multivariate volatility forecasting model that is accurate in...

Financial institutions rely heavily on Value-at-Risk (VaR) as a risk measure, even though it is not globally subadditive. First, we theoretically show that the VaR portfolio measure is subadditive in the relevant tail region if asset returns are multivariate regularly varying, thus allowing for...

The experience from the global financial crisis has raised serious concerns about the accuracy of standard risk measures as tools for the quantification of extreme downward risks. A key reason for this is that risk measures are subject to a model risk due, e.g. to specification and estimation...

This is documentation for a C++ implementation of the simulated maximum likelihood (SML) estimation method, where the SML algorithm is applied to the stochastic volatility (SV) model. The algorithm and code can easily be adapted to a richer class of SV models, as well as to more general dynamic...