We develop a discrete-time affine stochastic volatility model with time-varying conditional skewness (SVS). Importantly, we disentangle the dynamics of conditional volatility and conditional skewness in a coherent way. Our approach allows current asset returns to be asymmetric conditional on...

Sharpe style regression has become a widespread analytic tool in the financial community. The style regression allows one to investigate such interesting issues as style composition, style sensitivity, and style change over time. All previous methods to obtain the distribution and confidence...

Hedging of illiquid financial instruments is carried out with liquid instruments that, as a rule, have simpler payoff functions. For example, hedging of Asian or long-dated put options is carried out with vanilla puts, hedging of Bermuda swaptions is done with vanilla swaptions, etc. This kind...

In financial markets, the order flow, defined as the process assuming value one for buy market orders and minus one for sell market orders, displays a very slowly decaying autocorrelation function. Since orders impact prices, reconciling the persistence of the order flow with market efficiency...

We introduce advanced idiosyncratic risk (“AI-Risk”), a parsimonious correlated residual correction to a predictive stress CAPM-like factor model, aimed to get more accurate stock-stock correlations. We find that AI-Risk can be significant for stock portfolios. Inclusion of AI-Risk gives a...

This paper studies a dynamic market microstructure model, in which a strategic market maker competes with an informed trader. We include the presence of noise traders and limit order traders in our setup. Our model is a N-period model. We give necessary and sufficient conditions for an...

The purpose of this paper is to understand how the current financial landscape shaped by the crises and new regulations impacts Investment Banking's business model. We will focus on quantitative implications, i.e. valuation, modeling and pricing issues, as well as qualitative implications, i.e....

Previously we introduced Singular Spectrum Analysis SSA and its multivariate extension MSSA as a powerful tool for cleaning data. Here we compare MSSA with the data filling algorithm M-REM (Multivariate Regularized Expectation Maximization). We compare theoretical methodology, numerical...

We present an exact analytic solution to the two-dimensional correlated default structural Merton model in the form of a local volatility problem using a conformal square-root transformation of the exact solution to a 2D hybrid barrier problem. We also give an approximation and evaluate it...

We showed that Singular Spectrum Analysis (SSA) applied to time series yields better correlations for risk simulations. This involved comparing SSA-based correlations with standard correlations and to noise, a zero correlation Wishart random matrix (WRM). We complete this testing here. We also...