Market making and trading strategies

• Objective: to design optimal option hedging pricing strategies while relaxing the Black-Scholes assumptions• Formulated a Reinforcement Learning(Q-Learning)based Dynamic Hedging & Option payoff replication model• Explored Optimal Control Theory for Portfolio Optimization and derived standard Delta(∆) hedging equations• Derived a novel option pricing model based on Control Theory using Dynamic Programming for optimization• Impact: Portfolios can be hedged more efficiently as the proposed strategies are a generalization to BSM models

– Developed a Computer Vision based Automated Toll System using YOLOv3 object detection alg.– Built a TCP and HTTP based client-server system to automate all the toll lanes.– Implemented a DBMS(MySQL & Redis) and a dashboard for real-time toll-booths monitoring.– Integrated ANPR(Automatic Number Plate Recognition) based on OpenALPR.

Handling the companies who came to the campus for placements and responsible for conducting the tests, GDs(Group Discussion) and interviews for the candidates.