Devices for Dissonance:

Slides:



Advertisements
Similar presentations
David Stark Columbia University Moscow 28 October 2012 Peripheral Vision in Financial Markets.
Advertisements

Knowledge Construction
Hansons Market Scoring Rules Robin Hanson, Logarithmic Market Scoring Rules for Modular Combinatorial Information Aggregation, Robin Hanson, Combinatorial.
AACEI Contingency Forum Contingency Management
Controversies Over Value An STS approach to the capital markets Daniel Beunza “Does STS Mean Business?” Workshop August 2007.
Ron Rhodes Accelerating Growth and Avoiding “Surprises”
I.T. Works Principal Investigator: Peter D. Blanck, Ph.D., J.D. Project Director: James L. Schmeling, J.D. Co-Investigator: Kevin M. Schartz, Ph.D., M.C.S.
Personalisation Implications for the workforce. On the internal workforce –What does the new agenda mean for social care staff? –What changes will we.
Review important principles
Systems Analysis and Design, 7e Kendall & Kendall
1 AFDC MAFC Training Program Shanghai 8-12 December 2008 Value at Risk Christine Brown Associate Professor Department of Finance The University of Melbourne.
WILL BIG DATA CHANGE EVERYTHING IN ACCOUNTING AND AUDITING? Miklos A. Vasarhelyi Rutgers University.
COMPUTER SIMULATION MODELS AND MULTILEVEL CANCER CONTROL INTERVENTIONS Joseph Morrissey, Kristen Hassmiller Lich, Rebecca Anhang Price, Jeanne Mandelblatt.
Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets Charles R. Plott, Shyam Sunder.
Peter Bishop, Futures Studies, University of Houston Support for Scenario Statements Dr. Peter Bishop Futures Studies University of Houston Expert Knowledge,
SMEs’ Finance and Participation in Global Markets Koji ITO Centre for Entrepreneurship, SMEs and Local Development (CFE) Organisation for Economic.
GODFREY HODGSON HOLMES TARCA
Copyright ©2010 Pearson Education, Inc. publishing as Prentice Hall 9- 1 Basic Marketing Research: Using Microsoft Excel Data Analysis, 3 rd edition Alvin.
Market-Risk Measurement
Artificial Intelligence
0 Software as a Service in Finance Date: 15 May 2007 Produced by: Chris Swan The materials may not be used or relied upon in any way.
Breakout 6: Financial Networks, Agent-Based Simulation, and Large- Scale Computation secretary: Michael Wellman moderator: William Rand.
Evaluating Hypotheses
Monty Hall and options. Demonstration: Monty Hall  A prize is behind one of three doors.  Contestant chooses one.  Host opens a door that is not the.
Options and risk measurement. Definition of a call option  A call option is the right but not the obligation to buy 100 shares of the stock at a stated.
Asset Management Lecture 19. Agenda Behavioral finance (Chapter 12) Challenges to market efficiency Limits to arbitrage Irrational investors.
©2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
OPTIONS MEISTER Module 5 –Standard Deviation and Its’ Relationship to Probabilities.
Stock Valuation – Technical Analysis Essentials of Corporate Finance Chapters 7 and 10 Materials Created by Glenn Snyder – San Francisco State University.
ISSUES IN CORPORATE MERGE By: Dr. Salem M. Al-Ghamdi.
COURSE OVERVIEW COURSE REQUIREMENTS KNOWLEDGE AND SKILLS STUDENT EXPECTATIONS Global Business.
Chapter 17 Nursing Diagnosis
 Don’t Fence Me In: Fragmented Markets for Technology and the Patent Acquisition Strategies of Firms Ziedonis, Rosemarie H. Management Science, 50 (6):
Environmental Futures Emile Servan-Schreiber, Ph.D. NewsFutures.com.
Health Promotion Theory. Definition of Health Promotion control over : the act or fact of controlling; power to direct or regulate; ability to use effectively.
World Health Organization A Conceptual Framework for Social Determinants of Health: which theory is the basis of a tool for Health Impact Assessment Prepared.
Chapter 14 Inference for Regression © 2011 Pearson Education, Inc. 1 Business Statistics: A First Course.
Data Integrity and Quality, and Operational Risk Scribe: H. V. Jagadish Moderator: Anthony Tomasic.
1 1 Ch11&12 – MBA 566 Efficient Market Hypothesis vs. Behavioral Finance Market Efficiency Random walk versus market efficiency Versions of market efficiency.
1 Lesson 4 Attitudes. 2 Lesson Outline   Last class, the self and its presentation  What are attitudes?  Where do attitudes come from  How are they.
Assessing the efficacy of structural merger remedies: choosing between theories of harm? Steve Davies and Matt Olczak, ACLE EC Competition.
Cognitive Behavioral Interventions. SOCIAL SKILLS TRAINING: TWO TYPES OF INTERPERSONAL COMPETENCE Cognitive Competence  Knowledge about relationships.
Introduction to Statistics Osama A Samarkandi, PhD, RN BSc, GMD, BSN, MSN, NIAC Deanship of Skill development Dec. 2 nd -3 rd, 2013.
Investor Sentiment and Price Discovery: Evidence from the Pricing Dynamics between the Futures and Spot Markets SWJTU, Chengdu, 2015 Robin K. Chou National.
Unless otherwise noted, the content of this course material is licensed under a Creative Commons Attribution - Non-Commercial - Share Alike 3.0 License.
Cooperative Strategy Cooperative Strategy
Marketing Education: Foundations & Functions.. Mission of Marketing Education  The Mission of Marketing Education is to enable students to understand.
A project called has recently started in Genoa. The project is about the prevention of alcohol and other psychotropic substances,
MATERI #13 Perubahan Transorganisasional
Chapter 2: The Research Enterprise in Psychology
PRIMARY DATA vs SECONDARY DATA RESEARCH Lesson 23 June 2016
Market-Risk Measurement
Chapter 9 Cooperative Strategy Student Version
Cooperative Strategy Cooperative Strategy
ZIKMUNDBABIN CARR GRIFFIN BUSINESS MARKET RESEARCH EIGHTH EDITION.
Chapter 4 Attitudes.
GODFREY HODGSON HOLMES TARCA
Behavioral Finance Unit II.
Foreign Exchange Market and Risk
Uses & Advantages of Derivatives
Customer Relationship Management
Chapter Six Training Evaluation.
The Six Essential Elements of Geography at mrdowling.com
Week 11 Knowledge Discovery Systems & Data Mining :
Part III Exchange Rate Risk Management
Product moment correlation
Marketing Education: What is it?
Trading Live Online Annual Mastery Program Probabilities and Trade Execution High probability of pot knocked over.
The Six Essential Elements of Geography at mrdowling.com
MGT601 SME MANAGEMENT.
Presentation transcript:

Devices for Dissonance: Reflexive Modeling and Systemic Risk Daniel Beunza & David Stark

Dissonance Dissonance fosters discovery by prompting reflexivity.

Dissonance Dissonance fosters discovery by prompting reflexivity. Disagreement about what is valuable makes it possible to discover new resources of value.

How do traders deal with the fallibility of their models?

In the literature, disasters are traced to the behavior of traders, depicted as 1) reckless

In the literature, disasters are traced to the behavior of traders, depicted as reckless and as 2) overly cautious (“herding”)

Processes that provoke doubt can lead to overconfidence

Reflexivity about Models

This is a pipe organ in largest hall of Moscow House of Music. Posted by Irina at 20:55 Labels: instuments, theatre

This is a pipe organ in largest hall of Moscow House of Music. [a declarative speech act] This is a pipe organ in largest hall of Moscow House of Music. Posted by Irina at 20:55 Labels: instuments, theatre

“I apologize.”

“I apologize.” [a performative speech act]

Performativity in economic sociology: Financial models are not representations. They are interventions that format, shape, perform markets. Their use brings new economic objects (markets) into being. Models are market making.

“This is the way that people get from point A to point B.”

A model is performative when its use increases its predictive capabilities.

This is a pipe organ.

A financial model is not a representation;

A financial model is not a representation; it is an intervention.

The arbitrage traders we studied do the same.

The trading room is populated with devices for doubt The trading room is populated with devices for doubt. Traders do not simply use models and devices that perform the market. They also create and use devices for reflexivity. This reflexivity is not exterior to (or above) the structures of socially distributed calculation but is an integral part of it.

Arbitrage is a (reflexively) skilled performance. And this reflexivity is not of the individual but is social and material.

Epistemic challenges of using models in arbitrage

Methodological constraint: a single morning at a single desk in an abritrage trading room.

Calculation in merger arbitrage involves the dissonance between two sets of probability estimates: probability estimates derived at the desk using proprietary models, databases, and instrumentation. 2) “implied probablity” – the aggregate probability estimates of the trader’s rivals

a given trading desk makes probability estimates based on models, proprietary databases, and instrumentation

V= (1-)PNS +PS

The trader’s models and instrumentation are powerful scopes for viewing the markets.

But scopes that reveal can also conceal But scopes that reveal can also conceal. If you take your model for granted, you can lose your shirt.

To avoid cognitive lock-in, the traders turn to socio-technical networks outside the trading room.

relation between the trader and his rivals

The spread plot in merger arbitrage I feel I have not seen enough visualizations so far. So I’d like to start with the visualization that I am going to discuss today. This is a spread plot. I won’t explain what a spread plot is. But I will tell you what it does. This visualization allows users to see the invisible. Now let me give you the background of when I saw this, the research that I made and what I found.

The spread plot is a representation of an economic object that does not have a price and is otherwise not observable, co-produced by the positioning of actors who use it to confront their interpretations and re-evaluate their positions.

Decoding the spread plot time $ Target Acquirer Here, make the case of the difference between the spread plot and the price plot. It gives an advantage “Backing out” implied probability

The spread plot instantiates the diversity of dispersed anonymous actors.

dissonance

Reflexive modeling Dissonance disrupts. It prompts reflexivity. Each of the (materially mediated) relations provokes reflexivity about the other.

?

re-search

Reflexive modeling Differs from ‘herding’ Here, dissonance prompts re-search

Reflexivity is not self-awareness or conceptual transcendence. So as not to be captive of an epistemic trap, traders use devices for dissonance.

?

? ?

WARNING

The same devices for doubt can also be devices for overconfidence, leading to arbitrage disasters. WARNING

The strength of reflexive modeling is based on the fact that it leverages the cognitive independence among dispersed and anonymous actors.

The strength of reflexive modeling is based on the fact that it leverages the cognitive independence among dispersed and anonymous actors. But this same process suggests the possibilities of cognitive interdependence among the rival traders in the professional arbitrage community.

Just as reflexive modeling can typically be a source of correction, so this same cognitive interdependence among traders can, in rare but dramatic instances, lead to the amplification of error.