Data Structure & Algorithms

Quantitative Finance

Learn the basics of quantitative analysis, including data processing, trading signal generation, developing trading strategies, and constructing a multi-factor model with optimization. Sentiment analysis with natural language processing to analyze corporate filings to generate sentiment-based trading signals and combing these multiple signals for portfolio management will be covered. Also, We will learn data structure and algorithms to solve various coding test problems at Leetcode and HackerRank.

Deep Reinforcement Learning

Optimal Execution

Learn to develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. We will also learn the combination of sophisticated mathematical modeling, empirical facts, and financial economics to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms.