Thrifting Alpha - Revitalizing Tired Alpha Factors Using Ensemble Learning
Finding alpha is a constant search in algorithmic trading. New alpha factors are always exciting, but sometimes you can come up with new trading signals simply by applying novel aggregation techniques to familiar factors. In this talk we will discuss using ensemble learning methods to combine individual weak signals into stronger factors and assessing their predictive power for long-short equity strategies.
Buying Happiness - Using LSTMs to Turn Feelings into Trades
In this talk we discuss how to build a Twitter sentiment model in Python using Word2Vec and long short-term memory networks (LSTMs), comparing and contrasting with more conventional statistical models. We cover basic Natural Language Processing (NLP) techniques, providing different ways to extract features from text data for use in modeling. We describe a potential use of this sentiment model in developing cross-sectional algorithmic trading signals for factor models, expanding upon previous work using Twitter data.
Bayesian Portfolio Optimization
Uncertainty quantified as probability is the rock upon which Bayesian inference is built. The instability of sample covariance matrices leads to major problems in Markowitz portfolio optimization. In this talk, we use probabilistic programming to compute probability distributions on the covariance of a set of assets. This yields a more robust estimate of their variation and adds uncertainty into how we calculate weights for a portfolio of assets.
Factor modeling is a common topic in quantitative finance. "Smart Beta" ETFs and similar financial products abound, providing a wealth of options to investors. Factor portfolios are constructed by ranking stocks with a combination of fundamental factors and price-based signals. The resulting factors can be used for many purposes, from cross-sectional equity models to risk and performance attribution. In this talk, we discuss what factor modeling is and how to make use of it in a typical quant workflow.