BeFi Web Seminar for April 25, 2007
Applications of Fluency to Investment
© BeFi Forum 2007
by Danny Oppenheimer
Princeton University
Applications of
Fluency to Investment
Danny Oppenheimer
Princeton University
Fluency
The metacognitive experience of the ease
with which information is processed.
Perceptual Fluency
Linguistic Fluency
Retrieval Fluency
Embodied Fluency
Spatial Fluency
Fluency
Ease of processing information is associated
with many positive dimensions:
• Truth (Reber & Schwarz, 1999)
• Confidence (Norwick & Epley, 2002)
• Liking (Reber et. Al, 1998)
• Intelligence (Oppenheimer, 2005)
• Frequency (Kahneman & Tversky, 1973)
Basic Fluency Effects
The Stock Market
Alter & Oppenheimer
(2006) PNAS
Artificial Stocks
NAME
DIFF. (1-4)
PERFORMANCE
Xagibdan
4.0
-10.71%
Yoalumnix
3.9
-10.71%
Creaumy
3.5
-12.50%
Barnings
1.3
11.79%
Vander
1.4
10.36%
Hillard
1.3
9.29%
Artificial Stocks
Predicted change
in value over 1
year (%)
Predicted Performance of Stocks
Based on Name Complexity
6
+3.90%
4
2
-3.86%
0
-2
-4
-6
Simple name
Complex name
Stock Name Complexity
Real World Performance
• 89 randomly selected NYSE stocks
• IV: ease of pronunciation (1-10).
• DVs:
–
–
–
–
% change in price after 1 day.
% change in price after 1 week.
% change in price after 6 months.
% change in price after 1 year.
Real World Performance
• 1 day: β = -.23, p < .05
• 1 week: β = -.21, p = .05
What does this mean practically?
FLUENT
10
DISFLUENT
VERSUS
10
Real World Performance
Return on $1000
Return on $1000
1400
1350
1300
1250
1200
1150
1100
1050
1000
1358.9
Fluent 10
Disfluent 10
1153.1
1040.5
1 day
1025.9
1 year
Real World Performance
Ruling out alternative causes:
– Industry naming practices.
Super-duper-tronics vs. Donk’s Coal Dredging
– Company size.
Citigroup ($1000bn+) vs. “Nanocap” Market (<$50m)
– Home bias.
All American Telecommunications Co vs. Magyar Tavkozlesi
Resevenytarsasag
– Outliers and log transform.
Ticker Codes
• All stocks in NYSE (665) and AMEX
markets (116) with complete data.
• IV: pronounceability of ticker code.
– KAG vs. KJG
• DVs:
–
–
–
–
% change in price after 1 day.
% change in price after 1 week.
% change in price after 6 months.
% change in price after 1 year.
1 day
% price change after 1 day
Ticker Codes
NYSE
pronounceable + 13.41%
unpronounceable + 9.41%
–t (663) = 2.40, p < .02.
16
14
Pronounceable
Unpronounceable
12
10
8
6
4
2
0
NYSE
% price change after 1 day
Ticker Codes
20
18
16
14
12
10
8
6
4
2
0
Pronounceable
Unpronounceable
AMEX

pronounceable + 18.37%
unpronounceable + 5.30%

t (114) = 1.74, p < .10.

AMEX
Summary
Fluency is a cue towards judgment:
- Fictional stocks
- Real world stock behavior
- Ticker codes and company names
Implications
- Psychological variables and the stock market
-Other types of fluency
- Retrieval fluency
- Perceptual fluency (small stock listings in
newspapers…)
Cue Weighting
Renting an Apartment:
- Number of bedrooms
- Price
- Location
- Does it have a roof (important cue)
- How many blue cars drive by (useless cue)
Cue Weighting
Does fluency influence WHAT information we
take into account when making stock purchasing
decisions.
Stimuli
Linguistic Fluency Manipulation
Participants rate the Growth potential (7 pt
scale) and rank a number of fictional stocks.
Neutral Cues: Location of Headquarters, #
of employees, Date stock went public
Key Cues: Two Fictional Stock Indices
Stimuli
Goldin Index
vs.
BxCd3n Rating
The Financial Group’s assessment of the
stock, on a scale from very weak to very
strong, used to advise stock trading
A composite of multiple business and
financial factors calculated weekly for all
stocks. It runs from a low of 0 to a high of
100.
Results
Evaluations of Fictional Stocks
after Receiving Positive Cue
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
Fluent
Disfluent
Growth
Stimuli
Stimuli
Results
5
4.5
4
High Rating
Low Rating
3.5
3
2.5
Fluent
Disfluent
Summary
Fluency impacts what information people
consider:
-- Linguistic Fluency
-- Perceptual Fluency
Implications
Company Logos
Company Names
Shareholder Reports
Ease of filling out paperwork
Questions?
PRESENTED BY
Shlomo Benartzi
Co-Founder, BeFi
Associate Professor Co-chair of the
Behavioral Decision Making Group
The Anderson School at UCLA
Warren Cormier
© BeFi Forum 2007
Co-Founder, BeFi
President, Boston Research Group