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Synthetic Data Generation in Finance
In this master class, Stefan shows how to create synthetic time-series data using generative adversarial networks (GAN). GANs train a generator and a discriminator network in a competitive setting so that the generator learns to produce samples that the discriminator cannot distinguish from a given class of training data. The goal is to yield a generative model capable of producing synthetic samples representative of this class. While most popular with image data, GANs have also been used to generate synthetic time-series data in the medical domain. Subsequent experiments with financial data explored whether GANs can produce alternative price trajectories useful for ML training or strategy backtests.
Reference:
1. 2019 NeurIPS Time-Series GAN paper by Jinsung Yoon, et al.
Stefan is the founder and CEO of Applied AI. He advises Fortune 500 companies, investment firms, and startups across industries on data & AI strategy, building data science teams, and developing end-to-end machine learning solutions.
Before his current venture, he was a partner and managing director at an international investment firm, where he built the predictive analytics and investment research practice. He was also a senior executive at a global fintech company with operations in 15 markets, advised Central Banks in emerging markets, and consulted for the World Bank.
He holds Master's degrees in Computer Science from Georgia Tech and in Economics from Harvard and Free University Berlin, and is a CFA Charterholder. He has worked in six languages across Europe, Asia, and the Americas and taught data science at Data camp and General Assembly.
Sri Krishnamurthy, CFA is the Founder and CEO of QuantUniversity. Sri is the creator of QuSandbox, a platform for experimenting analytical and machine learning solutions for enterprises prior to adoption.
Sri earned an MS in Computer Systems Engineering and another MS in Computer Science, both from Northeastern University and an MBA from Babson College.
QuantUniversity is a quantitative analytics and machine learning advisory based in Boston, Massachusetts. QuantUniversity runs various programs and workshops in Boston, New York, Chicago, and online. The company offers online programs in Machine Learning and AI for Financial services
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