NEWS AND RESEARCH

Alexandria Technology Selected by FactSet for Earnings Call Search Capabilities

RESEARCH

Alexandria Technology, the leading Natural Language Processing (NLP) technology for the investment industry, today announced it is working with FactSet, a global provider of integrated financial information, analytical applications, and industry-leading service, to bring corporate Earnings Call Sentiment analysis to FactSet users.

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SOCIETE GENERALE: OUTSOURSE CALLS TO A MACHINE

RESEARCH

Societe Generale finds Alexandria Earnings Calls NLP to be stronger than traditional quantitative factors with significant residual.

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Comparative Analysis of NLP Approaches for Earnings Calls

RESEARCH

This research paper compares popular NLP approaches in the investment industry: Machine Learning, FinBERT, Loughran McDonald. Download the white paper to explore the nuances of each approach and get performance and correlations of each for the past 10 years. Additionally, see how these have performed historically vs. traditional investment factors (Value, Profitability, Quality, Momentum and Growth).

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J.P. Morgan:Social Media Sentiment

RESEARCH

J.P. Morgan finds value in Alexandria Chat Room sentiment over daily and weekly horizons. All performance metrics improved including returns, Sharpe ratio, drawdowns, and Skew.

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Sentiment Applied to Multi-Factor Models

RESEARCH

Monthly sentiment can be included as a factor within a multi-factor model to increase returns. It can also be used as a qualitative screen to time purchases and sales, improving portfolio returns and reducing risk.

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Empirical Research Partners: Robot Newsreaders

RESEARCH

Computing net sentiment for economic topics helps investors see what is directly driving episodes of panic or euphoria, allowing them to position their portfolios over 12-month horizons.

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Risk Systems That Read

RESEARCH

Northfield measures how the present is different from the past and, therefore, how the near future is also likely to be different from the past — something missing from nearly all financial models.

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Maximizing Returns with Alexandria Event Tags

RESEARCH

Alexandria’s NLP engine identifies 23 events within news. Identifying these events improves the return profiles for news-based strategies for one-month and three-month intervals.

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Sentiment v. Momentum: A Comparative Factor Analysis

RESEARCH

Sentiment outperforms 9-month Momentum, when Alexandria sentiment from Dow Jones news articles is aggregated to create net sentiment metrics for a universe of stocks.

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