We propose a machine learning framework to capture the dynamics of highfrequency limit order books in financial equity markets and automate real-time prediction of metrics such as mid-price movementâ€¦ (More)

We use a generalized birth-death stochastic process to model the high-frequency dynamics of the limit order book, and illustrate it using parameters estimated from Level II data for a stock on theâ€¦ (More)

Portfolio credit derivatives, such as basket credit default swaps (basket CDS), require for their pricing an estimation of the dependence structure of defaults, which is known to exhibit tailâ€¦ (More)

It is well-established that equity returns are not Normally distributed, but what should the portfolio manager do about this, and is it worth the effort? As we describe, there are now some goodâ€¦ (More)

Portfolio risk forecasts are often made by estimating an asset or factor correlation matrix. However, estimation difficulties or exogenous constraints can lead to correlation matrix candidates thatâ€¦ (More)

Historical time series of asset returns are commonly used to derive forecasts of risk, such as value at risk (VaR). Provided there is enough data, this can be done successfully even though assetâ€¦ (More)

This paper presents a new structural framework for multidimensional default risk. We define the time of default as the first time the log-return of the stock price of a firm jumps below a (possiblyâ€¦ (More)

We examine market dynamics in a Lucas-style, asset-pricing model with heterogeneous traders who know the distribution of dividends but not the private information of other traders. Agents optimize aâ€¦ (More)

Given a collection of single-market covariance matrix forecasts for different markets, we describe how to embed them into a global forecast of total risk. We do this by starting with any globalâ€¦ (More)

We address the problem of optimal Central Bank intervention in the exchange rate market when interventions create feedback in the rate dynamics. In particular, we extend the work done on optimalâ€¦ (More)