Elevate Your Journey
Computational finance is the incredibly dynamic field of computer science that deals with applied problems in finance. We broadly use the term to refer to the use of quantitative research techniques and technology by institutional investors, whether machine learning, signal processing, optimization, high performance distributed systems, or other tools, to predict and algorithmically trade the capital markets.
We work with a variety of buy-side institutions, including the leading hedge funds, proprietary trading firms, and market makers in the investment space. These institutions work on solving some of the most complex unsolved problems in capital markets.
For example, the market’s adherence to the Efficient Market Hypothesis is far from absolute. Disparities arise from investors possessing varying levels of risk tolerance and distinctive ideas about market dynamics. Market participant behavior is influenced by a myriad of factors such geopolitical events, economic indicators, and general psychology, creating an enduring unpredictability and random walk due to these differences. Even with sophisticated machine learning models and access to unlimited data, accurately predicting market movement remains a formidable challenge.
Capital markets are dynamic and ever-evolving; complexity is the norm. It is within these intricacies our clients see opportunities for innovation, alpha generation, and growth. The pursuit of solutions for these market complexities drives progress and propels the investment industry forward.
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Recommended Reads
The Quants: How a New Bread of Math Whizzes Conquered Wall Street and Nearly Destroyed It
Inside the Black Box: A Simple Guide to Quantitative and High-Frequency Trading
The Man Who Solved The Market: How Jim Simons Launched the Quant Revolution
A Man for All Markets: From Las Vegas to Wall Street, How I Beat the Dealer and the Market
The Complete Guide to Capital Markets for Quantitative Professionals
How I Became a Quant: Insights from 25 of Wall Street’s Elite