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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.
Lucena Research to Apply AI to Wall Street Horizon’s Data
March 1, 2019 by Eugene Grygo via FTF News Lucena will utilize their investment research tools to validate Wall Street Horizon's data and then make that data available for assessment and consumption.
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…
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…
Lucena Research and Wall Street Horizon Extract Insights from Event Data
ATLANTA Lucena Research and Wall Street Horizon Integrate Corporate Event Data onto the QuantDesk Analytic Platform. "Wall Street Horizon is excited to make our unique corporate event data available alongside other data types within Lucena's powerful and agile analytic platform,"…
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…
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…
How To Avoid Missing The Obvious In Your Deep Learning Strategy
Erez Katz, CEO and Co-founder of Lucena Research In Deep Learning, Extracting The Right Insights Hinges On Several Key Steps. Here is how to form a thorough deep learning strategy for investment research. To illustrate, here are two examples that were…
Is Your Data Predictive? How to Measure Before Risking Capital
Erez Katz, CEO and Co-founder of Lucena Research Here are the pitfalls data providers and data consumers should be aware of.
Using Machine Learning to Convert Unstructured to Structured Data
One of the alternative data providers we have been working with in the past two years is Prattle Analytics. Prattle applies NLP to central banks’ communications in order to extract macro level sentiment scores. Find New Insights in Alternative Data Through…
Is Your Deep Learning Strategy Robust Enough?
Erez Katz, CEO and Co-founder of Lucena Research. How to test the robustness of a deep learning strategy. Best practices geared to test your quantitative investment strategy before risking capital.
How To Use RNNs and Time Series Data for Forecasting Stock Prices
How to Use Time Series Data and RNNs To Forecast Stock Prices. It’s important to configure deep net infrastructure to accommodate time series data.