The objectives were two-fold: a) To analyse financial market data to understand market microstructure for mid-frequency trading strategies, b) Create data processing libraries and computational modules to be used for specialised data analysis.- Designed an Option Chain for NSE listings, including calculated indicators such as Greeks and IVs. The automated option map generation procedure has facilitated a streamlined process for further analysis.- Formulated a real-time multidimensional Kalman Filter in C++ using the Eigen template library; this module has been integrated into real-time mid and high-frequency trading strategies.- Created and analysed statistical arbitrage techniques on various selected stock pairs listed on the NSE.- Wrote an analysis pipeline in Python and used it to study the prediction power of various indicators. Implemented various supervised learning models, such as Random Forests, for predicting returns.

The objective was to simulate a gamma radiation detector array to research efficiency corrections.• Closely modelled the 4π icosahedron geometry of the gamma-ray detector array using Solidworks, to be used as a mesh for further simulation. • Employed the C++-based OOP toolkit GEANT4 for a particle-in-matter simulations and efficiency calculations.• Utilised CERN-ROOT for data visualisation and created a data analysis module for corroboration.Results • Successfully attained the estimated efficiencies for 511keV and 1275keV emission of 22Na radio-isotope.