36-hour competition that exposed participants to machine learning, derivative modelling, and how to apply their knowledge to the real-life problems faced by the Quantitative Research and Data Analytics teams on a day to day basis.
Optimal timing for airline ticket purchasing from the consumer’s perspective is challenging principally because buyers have insufficient information for reasoning about future price movements. In this challenge we simulate various models for computing the best possible expected future prices by constructing new features from the existing features and also introducing new features to make our model more robust.
Simulate Stock Price Movement using historical data
Given Payoff States and Contingency Claims evaluate the fair price of the derivative designed