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The Science Behind Stop-Loss & Target Gain – Learn When to Exit a Position
Co-Authored by: Erez M. Katz (CEO & Co-Founder) and Stuart Colianni (Quant)
Selecting Features with Permutation Importance
Authored by: Stuart Colianni / Quantitative Analyst @ Lucena Research.
A Dynamic Labeling Approach for Financial Assets Forecasting
Authored by: Tarun Bhatia, Stuart Colianni, Taylor Korf, and Erez Katz
Clustering for more effective model training
Stuart Colianni, Quantitative Researcher at Lucena Research
Creating a Multi-Strategy Fund Using Big Data and Machine Learning
Erez Katz, CEO and Co-founder of Lucena Research In order to create a diversified portfolio, our team combined five uncorrelated, best of breed strategies into a single fund named: The Fabulous 5.
Dynamically Retraining Models for Stock Forecasting
Erez Katz, CEO and Co-founder of Lucena Research Dynamic retraining is an important aspect of AI & Big Data for quantitative investing.
Lucena Research and Equifax to Deliver Consumer Credit Data Offerings
Erez Katz, Lucena Research CEO and Co-founder Lucena teamed up with Equifax® to create predictive signals derived from consumer credit analysis for actionable investment deliverables.
Betting on US Defense Stocks
Erez Katz, Lucena Research CEO and Co-founder QuantDesk can research, validate and construct an aero-space & defense stocks portfolio.
Stock Forecasting with Transformer Architecture and Attention Mechanism
Erez Katz, Lucena Research CEO and Co-founder In our stock forecasting research, our goal is to identify meaningful patterns within a noisy construct of time series data.
Mitigating Risk for Event-Driven Investing
Erez Katz, Lucena Research CEO and Co-founder As data and information become more accessible, the market has become more efficient. Consequently, the required lead time for event-driven investing has also grown longer. In other words, investors are seeking early entry…
Mean Reversion: Identify and forecast stocks before they move
Erez Katz, Lucena Research CEO and Co-founder How to use mean reversion to forecast constituents on the verge of moving below or above their peers.
Cracking the Code: Applying Alternative Data to Investment
Erez Katz, Lucena Research CEO and Co-founder On Sept. 26th Lucena Research hosted a panel event for data providers and investment professionals to discuss alternative data for investment. Watch the panel discussion with Q&A here.
Using Big Data to Forecast KPI
Erez Katz, Lucena Research CEO and Co-founder During our panel event in NY I referenced how deploying big data in a consumable and actionable format is a critical need for most investment professionals. In order to serve this need, our team has…
Capsule Networks or CNNs: Which is best for stock predictions?
Erez Katz, Lucena Research CEO and Co-founder Here I’d like to touch on some of the main points that motivated us to explore CapsNet.
New Enterprise Level Portfolio Construction and Execution Services
Atlanta, GA Lucena Research and Data Capital Management announced they are collaborating to bring to market AI-based portfolio construction and execution services. “We’re excited to partner with experts in portfolio construction and management. Together, we present unique offerings, that package data science, machine…
Murky Outlook for Oil
Erez Katz, Lucena Research CEO and Co-founder Oil Volatility: How to Identify a Statistical Arbitrage Opportunity Opposing forces are holding oil prices in a tight range and delicate balance. Excessive US production and oversupply is countered by growing demand. Add…
Perpetually Monitored Strategies derived from Alternative Data and AI
Erez Katz, Lucena Research CEO and Co-founder At Lucena, we connect investment professionals with actionable and validated alternative data. Over the past two years, we’ve added new datasets to our list of validated data partners. To further advance the reliability…
Repurposing Alternative Data for Various Investment Paradigms
Erez Katz, CEO and Co-founder Lucena Research A review of current challenges with alt data adoption and how to overcome them. With our data providers, we are able to provide empirical evidence of the underlying data’s predictive value. Value is…
Capsule Networks: Next Gen Deep Learning Computer Vision for Stock Forecasting
Erez Katz, CEO and Co-founder of Lucena Research Capsule Networks are a fascinating, relatively new technology for image classification. Compared to CNNs, capsule networks have many benefits and phenomenal potential for image classification tasks, specifically time series forecasting.
Consumer Emotion Signals for Forecasting Tradable Assets
An Interview with Cognovi Labs How consumer behavior can provide signals for forecasting tradable assets. Announcing a new partnership with Cognovi Labs, a leader in consumer behavioral science powered by AI.