The approximate agents' wealth and price invariant densities of the prediction market model presented in Kets et al.(2014) is derived using the Fokker-Planck equation of the associated continuous-time jump process. We show that the approximation obtained from the evolution of log-wealth...

We investigate market selection and bet pricing in a simple Arrow security economy which we show is equivalent to the repeated prediction market models studied in the literature. We derive the condition for long run survival of more than one agent (the crowd) and quantify the information content...

We consider a Volume Weighted Average Price (VWAP) trading algorithm in which instead of following the static curve passively, the algo may adjust its participation rate in each interval. We propose a framework in which the adjustment only makes use of the expected value of the price...

This paper studies the discriminatory power and calibration quality of the structural credit risk models under the 'exogenous default boundary' approach including those proposed by Longstaff and Schwartz (1995) and Collin-Dufresne and Goldstein (2001), and 'endogenous default boundary' approach...

Climate change is predicted to substantially alter forest growth. Optimally, forest owners should take these future changes into account when making rotation decisions today. However, the fundamental uncertainty surrounding climate change makes predicting these shifts hard. Hence, this paper...

We analyze the value of foresight in the drybulk freight market when repositioning a vessel through space and time. In order to do that, we apply an optimization model on a network with dynamic regional freight rate differences and stochastic travel times. We evaluate the value of the...

Climate change is predicted to substantially alter forest growth. Optimally, forest owners should take these future changes into account when making rotation decisions today. However, the fundamental uncertainty surrounding climate change makes predicting these shifts hard. Hence, this paper...

In the data mining and machine learning fields, forecasting the direction of price change can be generally formulated as a supervised classfii cation. This paper attempts to predict the direction of daily changes of the Nasdaq Composite Index (NCI) and of the Standard & Poor's 500 Composite...

Enrollment rates to higher education reveal quite large variation over time which cannot be explained by productivity shocks alone. We develop a human capital investment model in an overlapping generations framework that features endogenous fluctuations in the demand for education. Agents are...

Motivated by the short-lived arbitrage model, we jointly imply volatilities and virtual interest rates of options to develop minimum variance hedge ratios. We use artificial neural networks to capture the dynamics between the underlying asset price and correlated state variables, which improves...