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Predictive Analytics
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Using Big Data to Forecast KPI
Erez Katz, Lucena Research CEO and Co-founder During our panel event in NY I referenced how deploying big data in a consumable and actionable format is a critical need for most investment professionals. In order to serve this need, our team has…
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…
Cognovi Labs Partners with Lucena Research to Forecast KPIs and Tradable Assets
Atlanta, GA Cognovi Labs, the leading provider of AI-extracted consumer emotions and behavioral insights, joins the list of Lucena Research data providers. Today, the two companies announced they have partnered to bring new signal-based data offerings to the financial markets.…
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…
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.
A Quantamental Approach Using Labeling for Stock Trading
One of our Quants, Tarun Bhatia, reviews Quantamental Investing and Labeling Techniques for ML in Finance.
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…
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…
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 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…
Applying Deep Reinforcement Learning to Trading
Lucena Research Co-Founder Dr. Tucker Balch provides an introduction to machine learning, specifically applying deep reinforcement learning for stock trading.
How To Use Deep Neural Networks To Forecast Stock Prices
Erez Katz, CEO and Co-founder of Lucena Research How To Use Deep Neural Networks To Forecast Stock Prices