A Simple Approach for Multi‐fidelity Experimentation Applied to Financial Engineering

Abstract

In practical applications, information about the accuracy or 'fidelity' of alternative surrogate systems may be ambiguous and difficult to determine. To address this problem, we propose to treat surrogate system fidelity level as a categorical factor in optimal response surface design. To design the associated experiments, we apply the Expected Integrated Mean Squared Error optimal design criterion, which takes into account both variance and bias errors. The performance of the proposed design was compared using three test cases to four types of alternatives using the Empirical Integrated Squared Error. Because of its ability to foster relatively accurate predictions, the proposed design is recommended in fidelity experimental design, particularly when the experimenters lack sufficient information about the fidelity levels of surrogate systems. The method was applied to the case of intraday trading optimization in which data were collected from the Taiwan Futures Exchange. We also calculated the implied volatility from the Merton's Jump-diffusion model via the fast Fourier transform algorithm with three different models of varying fidelity levels.

Expert Refined Topic Models to Edit Topic Clusters in Image Analysis Applied to Welding Engineering

“…Yet, these definitions may seem inaccurate and disagree with expert judgement. Most recently, many researchers have further refined Bayesian mixture models to make the results even more interpretable and predictive [14][15][16][17][18]. This research has generally caused the complexity of the models to grow together with the number of estimated parameters.…”