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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…

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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? Key concepts for quantitative investment research and why 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.

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,

Using Machine Learning to Create Structured Data from Unstructured Communications One of the alternative data providers we have been working with in the past two years is Prattle Analytics. Prattle applies natural language processing on central banks’ communications in order to extract…

How to Measure Your Investment Portfolio Performance and Optimize

How to Measure Your Investment Portfolio Performance and Optimize

January 5, 2019 | Ai driven investment strategies, Company Blog, data science, Portfolio Optimization, Quantitative Investing,

Measuring and optimizing your portfolio’s performance depends on three key factors.  Investors often look at Sharpe ratio to  measure investment portfolio performance and determine strength. Sharpe ratio measures a portfolio’s risk adjusted return. The goal of Sharpe ratio is to…

“The Journey of an Alternative Data Signal” Webinar

“The Journey of an Alternative Data Signal” Webinar

January 4, 2019 | data science, Predictive Analytics, Quantitative Investing, Webinar Videos,

The AI and big data revolution have energized the financial market in ways not seen since the introduction of electronic trading in the 1980’s.

How Machine Learning Can Validate Your Data For Stock Forecasting

How Machine Learning Can Validate Your Data For Stock Forecasting

December 28, 2018 | Ai driven investment strategies, Alternative Data, big data, DAS, data science, data validation, DME, DQE, machine learning, Predictive Analytics,

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.

How to Empirically Measure Alternative Data’s True Value

How to Empirically Measure Alternative Data’s True Value

December 28, 2018 | Ai driven investment strategies, Alternative Data, backtest, DAS, Data Provider, data science, DME, DQE, Predictive Analytics, quantdesk,

Erez Katz, CEO and CoFounder of Lucena Research How to Empirically Evaluate Alternative Data Through Backtest and Model Portfolio Performance  The growth of alternative data has driven data consumers to seek efficient methods of sifting through vast amounts of information.…

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