We present an embarrassingly simple method for supervised learning of SABR model's European option price function based on lookup table or rote machine learning. Performance in time domain is comparable to generally used analytic approximations utilized in financial industry. However, unlike the...

We revisit well-known stochastic volatility models with constant coefficients for single asset driven by one factor stochastic volatility as homogeneous diffusion and demonstrate an alternative to the classifications provided in Albanese and Lawi, and Henry-Labord`ere, to deduce asset price...

We provide a simple and explicit construction of a family of stochastic exponentials with expectation k$/in$(0,1). Our family of stochastic exponentials can be constructed to be either strictly positive of merely non-negative

Contrary to well-known asset pricing models, volatilities implied by equity index options exceed realized stock market volatility and exhibit a pattern known as the volatility skew. We explain both facts using a model that can also account for the mean and volatility of equity returns. Our model...

Share prices fluctuate far more than dividends. In contemporary lit- erature, this excess volatility is usually discussed involving the Camp- bell-Shiller present value identity. In our view, it is more appropriate to model future dividends and prices explicitly as random variables. We refer to...

There are concerns that climate-related physical and political risks are not yet properly reflected in asset prices. To address these concerns, we develop a dynamic asset pricing framework with rare disasters related to climate change. The novelty of this paper lies in linking carbon emissions...

Motivated by the problems of the conventional model in rationalizing market data, we derive the equilibrium interest rate and risk premiums using recursive utility in a continuous-time model. We use the stochastic maximum principle to analyze the model. This method uses forward/backward...

The equity premium puzzle describes the enigma between the theoretical model of consumption behavior and its empirical calibration. We believe, this puzzle is based on a logical inconsistency in which deterministic and stochastic quantities are not precisely separated: The empirical literature...

In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference. We provide a hands-on ap proach which is easily implemented in empirical...

In this article we suggest a new method for solutions of stochastic integrals where the dynamics of the variables in integrand are given by some stochastic differential equation. We also propose numerical simulation of stochastic differential equations which is based on iterated integrals method...