In spite of its tremendous economic significance, the problem of sales staff schedule optimization for retail stores has received relatively scant attention. Current approaches typically attempt to minimize payroll costs by closely fitting a staffing curve derived from exogenous sales forecasts,...

We provide a formulation of stochastic volatility (SV) based on Gaussian process regression (GPR). Forecasting volatility out-of-sample, both simulation and empirical analyses show that our GPR-based stochastic volatility (GPSV) model clearly outperforms SV and GARCH benchmarks, especially at...

We describe a general structure allowing to represent in a regular and extensible way all the financial data available in a research laboratory (at present, the Adaptive Computer Systems Laboratory of the Université de Montréal). After an analysis of field, we clarify the XML representation of...

Prior work on option pricing falls mostly in two categories: it either relies on strong distributional or economical assumptions, or it tries to mimic the Black-Scholes formula through statistical models, trained to fit today's market price based on information available today. The work...

We introduce an asset-allocation framework based on the active control of the value-at- risk of the portfolio. Within this framework, we compare two paradigms for making the allocation using neural networks. The first one uses the network to make a forecast of asset behavior, in conjunction with...