Conveners
CONTRIBUTED Finance
- Miklós Arató (Eötvös Loránd University)
We present a novel deep neural network-based approach for the parameter estimation of the fractional Ornstein-Uhlenbeck (fOU) process. The accurate estimation of the parameters is of paramount importance in various scientific fields, including finance, physics, and engineering. We utilize a new, efficient, and general Python package for generating fractional Ornstein-Uhlenbeck processes in...
Financial fraud detection is a classification problem where each operation have a different misclassification cost depending on its amount. Thus, it fall within the scope of instance-dependent cost-sensitive classification problems. When modeling the problem with a parametric model, as a logistic regression, using a loss function incorporating the costs has proven to result in a more effective...