lse: ME319: Machine Learning and Stochastic Simulation: Applications for Finance, Risk Management and Insurance
ME319: Machine Learning and Stochastic Simulation: Applications for Finance, Risk Management and Insurance
Stochastic Calculus for Finance I: Binomial asset pricing model and Stochastic Calculus for Finance II: tochastic Calculus for Finance II: Continuous-Time Models. These two books are very good if you want to apply the theory to price derivatives. Stochastic Differential Equations: An Introduction with Applications Bernt Oksanda.
Nature: Evaluation and recommendation of sensitivity analysis methods for application to Stochastic Human Exposure and Dose Simulation models
Evaluation and recommendation of sensitivity analysis methods for application to Stochastic Human Exposure and Dose Simulation models
Simulation research derives new methods for the design, analysis, and optimization of simulation experiments. Research on stochastic models develops and analyzes models of systems with random behavior ...
JSTOR Daily: On Choosing Parameters in Retrospective-Approximation Algorithms for Stochastic Root Finding and Simulation Optimization
The stochastic root-finding problem is that of finding a zero of a vector-valued function known only through a stochastic simulation. The simulation-optimization problem is that of locating a ...
On Choosing Parameters in Retrospective-Approximation Algorithms for Stochastic Root Finding and Simulation Optimization
We present a stochastic simulation model for estimating forward-looking corporate probability of default and loss given default. We formulate the model in a discrete time frame, apply ...
Stochastic volatility models are increasingly important in practical derivatives pricing applications, yet relatively little work has been undertaken in the development of practical Monte Carlo ...
A stochastic process is a colection of random variables defined on the same probability space. Please explain further what parts of this definition are escaping you.