A Model of Rational Speculative Trade

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Transcription:

A Model of Rational Speculative Trade Dmitry Lubensky 1 Doug Smith 2 1 Kelley School of Business Indiana University 2 Federal Trade Commission January 21, 2014

Speculative Trade Example: suckers in poker; origination of CDS contracts

Speculative Trade Example: suckers in poker; origination of CDS contracts Working theory" of trade

Speculative Trade Example: suckers in poker; origination of CDS contracts Working theory" of trade No trade theorems: Aumann (1976), Milgrom Stokey (1982), Tirole (1982) E[ ν b, ν s ν s] E[ ν b, ν s] E[ ν b ν b, ν s]

Speculative Trade Example: suckers in poker; origination of CDS contracts Working theory" of trade No trade theorems: Aumann (1976), Milgrom Stokey (1982), Tirole (1982) E[ ν b, ν s ν s] E[ ν b, ν s] E[ ν b ν b, ν s] Informed agents only trade if counterparty trades for other reasons. Noise traders must have different marginal value of money or inability to draw Bayesian inference

Speculative Trade Example: suckers in poker; origination of CDS contracts Working theory" of trade No trade theorems: Aumann (1976), Milgrom Stokey (1982), Tirole (1982) E[ ν b, ν s ν s] E[ ν b, ν s] E[ ν b ν b, ν s] Informed agents only trade if counterparty trades for other reasons. Noise traders must have different marginal value of money or inability to draw Bayesian inference Kyle (1985), Glosten Milgrom (1985) study behavior of informed traders, take as exogenous behavior of noise traders

Speculative Trade Example: suckers in poker; origination of CDS contracts Working theory" of trade No trade theorems: Aumann (1976), Milgrom Stokey (1982), Tirole (1982) E[ ν b, ν s ν s] E[ ν b, ν s] E[ ν b ν b, ν s] Informed agents only trade if counterparty trades for other reasons. Noise traders must have different marginal value of money or inability to draw Bayesian inference Kyle (1985), Glosten Milgrom (1985) study behavior of informed traders, take as exogenous behavior of noise traders Interpretation of our paper Possibility of pure speculation (no gains from trade) A model of noise traders

This Paper The motive for trading is rational experimentation You have to be in it to win it!" floor manager

This Paper The motive for trading is rational experimentation You have to be in it to win it!" floor manager Each agent draws a type that she does not observe trading strategy, source of information, skill, etc. Agent s type generates a signal about the value of an asset Trading based on signal informs about one s type If type is sufficiently bad then exit If type is sufficiently good, continue to trade

This Paper The motive for trading is rational experimentation You have to be in it to win it!" floor manager Each agent draws a type that she does not observe trading strategy, source of information, skill, etc. Agent s type generates a signal about the value of an asset Trading based on signal informs about one s type If type is sufficiently bad then exit If type is sufficiently good, continue to trade Main Question: Can the experimentation motive overcome adverse selection in the no-trade theorem?

Example (see handout) Setup

Setup Example (see handout) More General Match of θ 1 and θ 2 generates outcome y = (u 1, u 2, σ) Y zero sum payoffs: u 1 + u 2 = 0 payoff-irrelevant signal: σ set of outcomes Y countable Outcomes stochastic: G(y θ 1, θ 2 ) History after t trades: h t = (y 1,..., y t ) Agent s strategy: A(h t ) {stay, exit}

Learning From Trading Results Inexperienced traders willingly enter an adversely selected market even when there are no gains from trade Higher trading volume when learning takes longer Gains from trade multiplier

Learning From Trading Results Inexperienced traders willingly enter an adversely selected market even when there are no gains from trade Higher trading volume when learning takes longer Gains from trade multiplier Questions Interpretation: model of rational trade vs model of noise traders? Is pairwise random matching a good example? For instance, how about double auction? Assumption that trade is necessary for information is key, how to defend it? Applications: overconfidence, bubbles, others?

Purification Two firms with cost c simultaneously set prices Two groups of consumers both with unit demand and valuation v Measure 1 loyal (visit one store) Measure λ shoppers (visit both stores, buy where cheaper) Only equilibrium is in mixed strategies: f (p) = 1 λ v 1 λ 2 p 2

Purification Two firms with cost c simultaneously set prices Two groups of consumers both with unit demand and valuation v Measure 1 loyal (visit one store) Measure λ shoppers (visit both stores, buy where cheaper) Only equilibrium is in mixed strategies: f (p) = 1 λ v 1 λ 2 p 2 Alternative Bayesian game: cost is uniformly distributed on [c α, c + α] and privately observed For any α > 0 obtain pure strategy equilibrium p (c), get price distribution h(p) Result: lim α 0 h(p) = f (p)