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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.
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.
A Quantamental Approach Using Labeling for Stock Trading
One of our Quants, Tarun Bhatia, reviews Quantamental Investing and Labeling Techniques for ML in Finance.
Finding Tradable Signals in Alt Data
Our new data vendor partner Wall Street Horizon joined us in NYC to host a panel discussion on finding tradable signals in alternative data. On Thursday March 14th, 2019 the Lucena Research team co-hosted a panel discussion with data partner…
Skepticism in the Alternative Data Revolution
Erez Katz, CEO and Co-founder of Lucena Research Investment professionals are finally starting to integrate AI and alternative data into their investment approach. Many however are still cautious and seek additional empirical validation.
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…
Why You Should Be Using A Genetic Algorithm for Feature Selection
Why You Should Be Using a Genetic Algorithm (GA) for Feature Selection At Lucena, our goal is to democratize some of the best kept secrets in the Financial industry. Our team works to refute the “black-box” image often associated with…