Leveraging approximation properties of neural networks for efficient bond pricing - Samay, Panwar (Nanyang Technological University, 2023)
The purpose of this report is to examine the applications of deep learning-based approxi- mation techniques in the pricing of various financial instruments, with a particular emphasis on bond pricing methodologies. The report seeks to approximate pricing maps for bonds and options on the forward curve. Subsequently, the focus shifts to calibrating the input parameters by analyzing the observed prices. Finally, empirical evidence is presented to enable us to calibrate the input parameters of actual bond yields and observe the drift of these parameters as a proof of concept.