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Data Validation
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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…
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.
Are Financial Analyst Ratings Predictive?
Erez Katz, CEO and Co-founder of Lucena Research How to use Machine Learning to Measure the Predictive Nature of Financial Analyst Ratings The QuantDesk Event Analyzer, can be used to construct a scan that determines which stocks meet or exceed overall…
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…
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 Machine Learning Can Validate Your Data For Stock Forecasting
Erez Katz, CEO and Co-founder of Lucena Research There are many Machine Learning methods that can be used to validate data for stock forecasting. It’s important to understand and distinguish the methods before utilizing AI to validate and predict asset prices.