Transcripts – Textual Data Analytics Over XpressfeedTM

Power Your Portfolio with Metadata – Receive unstructured textual data in machine-readable format with

metadata tagging for quicker analysis.

– Easily combine transcripts of call data from earnings, M&A, guidance, along with special calls and conferences with existing datasets to formulate unique, proprietary datasets.

– Gain a competitive edge and unique insight leveraging unstructured data to fuel your investment strategy.

Alpha Unscripted. Alternative Data for Your Next-Generation Research and Analysis.Gain greater insight into your investment process with powerful textual data, and Textual Data Analytics, delivered on Xpressfeed™, S&P Global Market Intelligence’s data feed management solution. Easily integrate rigorously sourced, reliable transcripts data with your own content and solutions. Leverage metadata to power your research and gain valuable perspective that lets you develop strategies with strong alpha potential. Streamline your analysis with derived sentiment scores to quickly assess and compare the sentiment expressed on earnings calls using Textual Data Analytics. Leverage the power of additional behavioral-based metrics, such as language complexity, for your workflows.

Natural LanguageProcessing (NLP)

The process of leveraging computers and statistics to process and make sense of language in a systematic and sensible way that doesn’t involve human intervention besides coding.

Transcripts on Xpressfeed™

Textual Data Analytics

Positive/Negative Sentiment

Language Complexity

Numerical Tokens

Number of Positive andNegative Words

Caller and AnalystEngagement

Key Developments

Estimates

Speaker Data

Ownership Data

Proprietary Data

Events

Gain Valuable Insight with Textual Analysis – Analyze historical textual data and speaker trends from

management’s discussion to help determine positive or negative tone or sentiment.

– Gain a better understanding of how often specific words are spoken, down to the speaker and context.

– Easily link the Speaker ID to the S&P Global Estimates and Professionals database, to help identify sell-side analysts’ revision changes.

Go One Step Further with Textual Data Analytics

– Implement 39+ sentiment scores and behavioral-based metrics derived from Natural Language Processing (NLP) into your analysis or to use as a benchmark.

– Quickly assess the sentiment expressed on earnings calls of over 9,000 active companies dating back to 2004.

– Leverage provided metrics to measure sections of calls and individuals on calls.

– Receive updates intra-day to stay current on the most recent activity.

Dive Deeper with Reliable, Global Coverage – Extensive, unique metadata tagging for each message

including Company ID, Speaker ID, Key Development ID, among others.

– Rigorously sourced historical transcripts data with robust collection and transcription processes, dating back to 2004.

– Stream XML messages for future eventdata and alerts on upcoming transcripts.

– Enhanced coverage includes 9,000 companies and growing, 100% coverage of the S&P 500®, Russell 1000®, and FTSE 100 with 95% coverage of the S&P Euro 350.

Benefit from Our Convenient and Flexible Delivery Options

– Receive text delimited files via Xpressfeed™ including updates every hour, featuring full point-in-time data from preliminary, edited, scoped, and final.

– Access via Event Driven Alerts, a low latency feed that delivers XML messages of every five words spoken timestamped to the second.

– Leverage EDX FTP with full XML of the transcript in every instance from preliminary, edited, scoped, and final.

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0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160

Sen

tim

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l(N

et P

osit

ivit

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Call Components*

S&P structures uninterrupted speaking by an individual as a ‘component’ within the call

Mor

e P

osit

ive

Less

Pos

itiv

e

(%)

End of PresentationSection Sentiment1.72%

Start of YouTubeQs Sentiment1.03%

End of YouTube Qs andStart of Analyst QsAgain Sentiment0.89%

End of the Q&ASession Sentiment0.59%

Result:Tesla’s stock droppedmore than 6% inafter-hours trading

Tesla’s May 2, 2018 Earnings Call Net Positivity Sentiment Level After each answer from executives during the Q&A Where net positive = (# positive words – # negative words) / total words1

1Loughran, T. and B. McDonald. “When is a Liability not a Liability?Textural Analysis, Dictionaries, and 10-Ks.” Journal of Finance 66, no.1 (2011): 35-63.Source: S&P Global Market Intelligence Quantamental. Research, as of 05/03/2018 and for illustrative purposes

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