1k citations · 1.6k across the 56 of their papers we have counts for
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Sequential Bayesian Learning for Merton's Jump Model with Stochastic Volatility
Eric Jacquier, Nicholas Polson, Vadim Sokolov
Jump stochastic volatility models are central to financial econometrics for volatility forecasting, portfolio risk management, and derivatives pricing. Markov Chain Monte Carlo (MC…
Deep Learning for Short-Term Traffic Flow Prediction
Nicholas Polson, Vadim Sokolov
We develop a deep learning model to predict traffic flows. The main contribution is development of an architecture that combines a linear model that is fitted using regula…
The Market for English Premier League (EPL) Odds
Guanhao Feng, Nicholas G. Polson, Jianeng Xu
This paper employs a Skellam process to represent real-time betting odds for English Premier League (EPL) soccer games. Given a matrix of market odds on all possible score outcomes…
Bayesian Particle Tracking of Traffic Flows
Nicholas Polson, Vadim Sokolov
We develop a Bayesian particle filter for tracking traffic flows that is capable of capturing non-linearities and discontinuities present in flow dynamics. Our model includes a hid…
Bayesian analysis of traffic flow on interstate I-55: The LWR model
Nicholas Polson, Vadim Sokolov
Transportation departments take actions to manage traffic flow and reduce travel times based on estimated current and projected traffic conditions. Travel time estimates and foreca…
Analyzing Risky Choices: Q-Learning for Deal-No Deal
Laszlo Korsos, Nicholas G. Polson
We derive an optimal strategy in the popular Deal or No Deal game show. Q-learning quantifies the continuation value inherent in sequential decision making and we use this to analy…