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Live Portfolios Powered by Alt Data

Live Portfolios Powered by Alt Data

April 17, 2019 | Alternative Data, Model Portfolios,

Alternative-Data-Based Long and Short Portfolios In Action

How to fight the commoditization of Alt Data

How to fight the commoditization of Alt Data

April 9, 2019 | Alternative Data, Data Provider, data science,

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.

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Lucena Research to Apply AI to Wall Street Horizon’s Data

Lucena Research to Apply AI to Wall Street Horizon’s Data

April 3, 2019 | Press Release,

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

A Quantamental Approach Using Labeling for Stock Trading

March 27, 2019 | Quantitative Investing,

One of our Quants, Tarun Bhatia, reviews Quantamental Investing and Labeling Techniques for ML in Finance.

Finding Tradable Signals in Alt Data

Finding Tradable Signals in Alt Data

March 20, 2019 | Alternative 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

Skepticism in the Alternative Data Revolution

March 13, 2019 | Alternative Data,

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?

Are Financial Analyst Ratings Predictive?

February 22, 2019 | Alternative Data, quantdesk,

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

Pre-Earnings Alternative Data for Stock Forecasting

February 20, 2019 | Alternative Data, Press Release,

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?

Feature Engineering for Trading: Art or Science?

February 12, 2019 | Ai driven investment strategies, data science, quantitative analysis, stock market,

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

How to minimize overfitting in your quantitative investment research

February 8, 2019 | Ai driven investment strategies, data science, quantitative analysis, Quantitative Investing,

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

Lucena Research and Wall Street Horizon Extract Insights from Event Data

February 1, 2019 | Alternative Data, Data Provider, Press Release,

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

How Dynamic Models Prolong An Investment Strategy

January 29, 2019 | Ai driven investment strategies, Quantitative Investing,

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 for Feature Selection

January 18, 2019 | Ai driven investment strategies, machine learning, Quantitative Investing,

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

Data Science: A Prerequisite To Machine Learning and Investment Research

January 18, 2019 | Alternative Data, data science, data validation, machine learning,

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

How to Use Arbitrage Trading for Foreign Exchange Strategies

January 14, 2019 | Ai driven investment strategies, data science, Event Analyzer, Model Portfolios,

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

How To Avoid Missing The Obvious In Your Deep Learning Strategy

January 12, 2019 | deep learning, machine 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

Is Your Data Predictive? How to Measure Before Risking Capital

January 10, 2019 | DAS, data science, machine learning, Predictive Analytics, quantitative analysis, Quantitative Investing, strategy,

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

Using Machine Learning to Convert Unstructured to Structured Data

January 10, 2019 | Ai driven investment strategies, Alternative Data, data science, machine learning, Predictive Analytics,

  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?

Is Your Deep Learning Strategy Robust Enough?

January 9, 2019 | backtest, big data, deep learning, forecast, investment strategies, quantdesk, Quantitative Investing,

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 RNNs and Time Series Data for Forecasting Stock Prices

January 9, 2019 | Ai driven investment strategies, machine learning, neural networks, quantitative analysis,

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.

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