Forecasting KPI: Using ML and Big Data for Investment Decisions

Erez Katz, CEO and Co-founder For us at Lucena, applying machine learning to the financial markets has taken an interesting turn in recent years. In theory, fitting a model to historical time series data and forecasting a KPI should be similar to how…

Trending Topics in Alt Data and Machine Learning for Investment

Webinar Overview On June 13th we will host a webinar dedicated to an open Q&A surrounding trending topics in Alt Data, Machine Learning, and Data Science for Finance. An emerging and rapidly evolving technical domain can cause great confusion and…

Testing Multi-Factor Models in QuantDesk

Jonathan Moreland, Director of Research, InsiderInsights.com Jonathan Moreland discusses how Insider Intelligence has been proven most valuable using QuantDesk's multi-factor model.

Live Portfolios From Alt Data

Alternative-Data-Based Long and Short Portfolios In Action Earlier this year we announced a partnership with Wall Street Horizon.  Our partnership will highlight how quality alternative data combined with predictive technology can benefit deploying successful investment signals.

How to fight the commoditization of Alt Data

Erez Katz, CEO and Co-founder Lucena Research The challenge of prolonging alternative data relevancy is on many data provider's mind. Increased competition, and wide distribution could quickly turn into alpha decay and commoditization.

Pre-Earnings Alternative Data for Stock Forecasting

ATLANTA, GA / ACCESSWIRE / February 20, 2019 /  Wall Street Horizon and Lucena Research Partner to highlight pre-earnings corporate event data for use in investment strategies and stock forecasting. Buy side consumers can access Wall Street Horizon's data in multiple…

Feature Engineering for Trading: Art or Science?

Erez Katz, CEO and Co-founder Lucena Research How Feature Engineering Extracts Signals from Data for Trading Those of us who work with big data and the applications of deep learning are often conflicted where human intellect is applied. Utilizing feature…

How to minimize overfitting in your quantitative investment research

Erez Katz, CEO and Co-founder Lucena Research How Cross-Validation and Grid Searching Strengthen Your Model  As new datasets enter the predictive analytics world, streamlining their evaluation and deployment is becoming increasingly essential. Combining multiple, independent datasets into a single predictive model…

How Dynamic Models Prolong An Investment Strategy

Erez Katz, CEO and Co-founder Lucena Research The benefits of dynamic models and how they prolong your investment strategy in a volatile market. One of the biggest fallacies of quantitative strategy development is the belief that a successful model will…

Data Science: A Prerequisite To Machine Learning and Investment Research

Erez Katz, CEO and Co-founder of Lucena Research Is your data research ready? Here are several key concepts for quantitative investment research. Data science is the crucial first step before machine learning can be applied.

How to Use Arbitrage Trading for Foreign Exchange Strategies

Erez Katz, Lucena Research CEO and Co-founder Cointegration is an excellent time series analysis geared to identify a high conviction trade such as arbitrage trading strategies for foreign exchange. A Scientific Approach to Arbitrage Trading in Foreign Exchange   Cointegration…