11

Getting the Information Edge

With News Flow

Peter Hafez

Director of Quantitative Research

RavenPack

What is News Analytics?

2

News analysis refers to the measurement of the various qualitativeand quantitative attributes of textual news stories. Expressing newsstories as numbers permits the manipulation of everyday informationin a mathematical and statistical way. [Source: Wikipedia]

Key attributes include:

Entity Recognition

Relevance

Novelty

Events

Sentiment

1. Entity Recognition

3

Identify entities such as

companies in news stories

using point-in-time sensitive

information:

• Short names

• Long names

• Common abbreviations

• Common misspellings

• Securities identifiers

• Subsidiaries

2. Relevance

4

Calculate the relevance of a

story to a given company:

• Mentions in the text

• Positioning in the story

(headline vs. last paragraph)

• Total number of companies

mentioned

• Detect roles played by

companies in the story

• Represent the context

numerically

3. Novelty

5

Is the news story "new" or novel?

• Elementize the various characteristics of

a news story

• Distinguish between similar vs. duplicate

stories

• Define a time window between stories

100• 2010-01-21 21:20:08 -- PRESS RELEASE: Toyota Files Voluntary Safety Recall on Select Toyota

75• 2010-01-21 21:20:08 -- News Flash: Toyota Files Voluntary Safety Recall On Select Toyota Division Vehicles

56• 2010-01-21 21:21:27 -- Toyota To Recall About 2.3M Vehicles For Sticking Accelerator Pedals>TM

42• 2010-01-21 21:48:10 -- DJ Toyota Recalls 2.3 Million Vehicles For Sticking Accelerators

Example: Toyota’s Vehicle Recall (news flow in the first 30 minutes)

SC

OR

E

M&A Activity

Analyst Ratings

Bankruptcy

Credit Ratings

Dividends

Earnings

Insider Trading

Legal Issues

Price Targets

Regulatory

Revenues

Stock Price Changes

4. Events

6

Company news and events

should be categorized:

• Identify actionable events

• The more detailed the event,

the better

• Differentiate between

scheduled vs. unscheduled

news events

• Distinguish between

explanatory or predictive

inputs

7

5. Sentiment

One size does not fit all!

• Multiple sentiment analysis

techniques is key

• Classify the various

sentiment proxies disclosed

in financial news

• Sentiment strength is as

essential as sentiment

polarity

• Frame of Reference: News

means different things to

different people

Sentiment Reversals

8

Source: Kittrell – Sentiment Reversals as Buy Signals - Jan 2010

Definitions:

+ A sentiment reversal is a news story that

causes a company to emerge from a

prolonged period of negativity, as

determined by at least 30 negative net

sentiment measurements over at least 30

calendar days

+ Monthly measurement periods are used in

order to increase the likelihood that the

reversals are non-accidental

+ Sentiment reversals apply only on

companies with a minimum market cap. of

$500 million (market growth adjusted)

9

Source: Kittrell – Sentiment Reversals as Buy Signals - Jan 2010

Key Observations:

+ It appears there are more sentiment

reversals in bull markets than in bear

markets

+ Based on a set of 10-stock Monte

Carlo portfolios (with different starting

points), the annualized excess return

ranges between 4 - 11%

+ The average 9-year annualized return

with a zero or 4 month entry interval

is 6.5% and 7.3%, respectively

+ In bear markets, sentiment reversals

still outperform the market, however

they do even better in bull markets

Sentiment Reversal Strategy

Event TradingAverage Stock Price Reaction to Negative News Events

10

Source: Macquarie Quant Research – May 2009

Stocks tend to underperform

prior to a negative news

announcementWhen bad news is

released, the price impact

is almost immediate

Stocks tend to rebound after about five days

After the bounce, securities tend to

reverse and underperform for

several months

Event TradingAverage Stock Price Reaction to Positive News Events

11

Source: Macquarie Quant Research – May 2009

Securities tend to outperform

slightly prior to the release of

positive news events

On the news release date,

securities tend to

outperform

There is no short-term reversal following

positive news announcements

Securities only tend to outperform

slightly following positive news

events

12

Source: Hafez - How News Events Impact Market Sentiment – May 2010

US News Sentiment Index

-55.00%

-45.00%

-35.00%

-25.00%

-15.00%

-5.00%

5.00%

15.00%

25.00%

35.00%

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Mar-

05

May-0

5

Jul-05

Sep-0

5

Nov-0

5

Jan-0

6

Mar-

06

May-0

6

Jul-06

Sep-0

6

Nov-0

6

Jan-0

7

Mar-

07

May-0

7

Jul-07

Sep-0

7

Nov-0

7

Jan-0

8

Mar-

08

May-0

8

Jul-08

Sep-0

8

Nov-0

8

Jan-0

9

Mar-

09

May-0

9

Jul-09

Sep-0

9

Nov-0

9

S&

P 5

00 C

um

ula

tiv

e R

etu

rns

Sen

tim

en

t V

alu

e

US Sentiment Index

S&P 500 Cumulative Returns

Simple Approach: Driven By Relevant, Novel, Event-Level News Sentiment On S&P500 Constituents

13

Source: Hafez - How News Events Impact Market Sentiment – May 2010

Cumulative PerformanceS&P 500 News Sentiment Index

Key Observations:

+ Trading based on sentiment

index changes yields double

digit positive returns in 4 out of

5 years of testing

+ With an Information Ratio of

1.75 and a Hit Ratio close to

70%.

They all Matter:

+ Entity Recognition

+ Relevance

+ Novelty

+ Events

+ Sentiment

-20%

0%

20%

40%

60%

80%

100%

120%

140%

May-0

5

Jul-05

Sep-0

5

Nov-0

5

Jan-0

6

Mar-

06

May-0

6

Jul-06

Sep-0

6

Nov-0

6

Jan-0

7

Mar-

07

May-0

7

Jul-07

Sep-0

7

Nov-0

7

Jan-0

8

Mar-

08

May-0

8

Jul-08

Sep-0

8

Nov-0

8

Jan-0

9

Mar-

09

May-0

9

Jul-09

Sep-0

9

Nov-0

9

Cu

mu

lati

ve R

etu

rns

Sentiment Momentum

Price Momentum

14

Let’s look at some other

examples……….

-40%

-20%

0%

20%

40%

60%

80%

100%

120%

140%

160%

Jan-0

5

Mar-0

5

May

-05

Jul-0

5

Sep

-05

No

v-0

5

Jan-0

6

Mar-0

6

May

-06

Jul-0

6

Sep

-06

No

v-0

6

Jan-0

7

Mar-0

7

May

-07

Jul-0

7

Sep

-07

No

v-0

7

Jan-0

8

Mar-0

8

May

-08

Jul-0

8

Sep

-08

No

v-0

8

Jan-0

9

Mar-0

9

May

-09

Jul-0

9

Sep

-09

Cum

ula

tive

Ret

urn

Sector Rotation Strategies Directional Strategy Driven By News Sentiment Indices

15

Price Momentum

Strategy (IR=0.73)

Return Rotation Strategy with

Market Return Overlay

(IR=0.95)

Industry Return Rotation

Strategy with a Market

Sentiment Overlay (IR=1.37)

Industry Sentiment Rotation

Strategy with a Market Sentiment

Overlay (IR=1.80)

Source: Hafez – Sector Rotation Strategies Driven By News Sentiment Indices - Nov 2009

-10%

0%

10%

20%

30%

40%

50%

60%

May

-05

Jul-0

5

Sep

-05

No

v-0

5

Jan-0

6

Mar-0

6

May

-06

Jul-0

6

Sep

-06

No

v-0

6

Jan-0

7

Mar-0

7

May

-07

Jul-0

7

Sep

-07

No

v-0

7

Jan-0

8

Mar-0

8

May

-08

Jul-0

8

Sep

-08

No

v-0

8

Jan-0

9

Mar-0

9

May

-09

Jul-0

9

Sep

-09

No

v-0

9

16

Source: Hafez - How News Events Impact Market Sentiment – May 2010

Key Observations:

+ Ranking industries according to

sentiment yields profitable market-

neutral strategies.

+ The Top/Bottom 5 spread is positive

in 4 out of 5 years with an Information

Ratio of 1.23 and a Hit Ratio of 67%.

Cu

mu

lati

ve

Ret

urn

Top/Bottom 5 Industry SpreadMarket Neutral Strategy Driven By News Sentiment Indices

Multi-Factor Models Correlation To More Traditional Quant Factors

17

Source: Macquarie Quant Research – May 2009

Key Observations:

+ In general, the performance of news

sentiment holds relatively low correlation

with Value, but has higher correlations

with Price Momentum, Earnings

Revisions and Earnings Surprises

+ The correlation is below 40% against

both Momentum and Analyst Sentiment

factors, which indicates that news

sentiment adds value as an additional

factor

Peter Hafez

Director of Quantitative Research

phafez@ravenpack.com

18

Questions?

Visit my blog at:

www.sentimentnews.com

Appendix: Recent Research Papers

19

Macquarie Equity Research:

“Breaking news: How to use news sentiment to pick stocks”: How news-derived quant factors can add value to multifactor alpha models.

“Eventful investing: Harnessing the power of event-driven strategies”: How news events can be combined with quant factors to boost model

performance.

”Momentum Seeking Attention”: How to improve the efficacy of price momentum factors.

Northfield/Carisma Research:

Equity Portfolio risk (volatility) estimation using market information and sentiment”: How news analytics provide better risk estimates for factor

models.

Knightsbridge Asset Management Research:

“Sentiment Reversals as Buy Signals”: How news analytics can be used to construct triggering events based on Sentiment Reversals.

RavenPack Research:

“Detection of Seasonality Patterns in Equity News Flows”: Examples of seasonal patterns present in equity news flow.

“Impact of News Sentiment on Abnormal Stock Returns“: How news sentiment can be used to construct intra-day triggering events.

“Construction of Market Sentiment Indices Using News Sentiment”: How to construct Market News Sentiment Indices.

“Sector Rotation Strategies Driven By News Sentiment Indices“: How News Sentiment Indices can be used in sector-rotation strategies.

“How News Events Impact Market Sentiment”. How to construct Market News Sentiment Indices Based on Company Events.

For more information on news sentiment research go visit: http://www.sentimentnews.com