Market Design with Blockchain Technology

Katya Malinova and Andreas Park

We first presented this paper in June 2016 ...

... and for 1 year people told us that trading of blockchain "stocks" was years away

 

How did these guys put it ...?

 

Initial Coin Offerings are now a reality

  • Available tokens for trading (Coinmarketcap)
    • August 19:  182
    • Sept 25:      257
  • Capital raised from mid-2016 to date:
    • $1.3B (NYT July 27, 2017);
    • $2.5B (Coinmarketcap, Sept 26, 2017)
  • Market cap (Coinmarketcap, Sept 26, 2017)
    • ~$8B

What is different?

1. Multiple trading protocols are possible

User-facing exchange mask

Fully Decentralized, "OTC",

Peer-to-Peer Exchange

What is different?

2. High Level of Transparency

See transactions between "addresses" (="IDs")

What is different?

3. You can tell who owns what

To sum up: What is different?

  1. Exchange-trading and Peer to Peer is possible
    • current world peer-to-peer -- through intermediaries
      • a dealer/market maker is on one side of trade
      • parties know who they are trading with
    • technology enables frictionless value transfer
  2. Past transactions are visible
    • may be able to see frequent "traders"
  3. Current holdings are visible
    • may be able to tell who the "whales" are

=> Informational environment changes drastically

 Key: wallets/addresses = IDs  but NOT = traders

Research Question

How does the design of ledger transparency and identifier-usage with possible P2P interactions affect trading behavior and economic outcomes?

  • possible ledger transparency regimes:
    • visible to all
    • hidden (from some)
  • possible identifier-usage regimes:
    • mandate single IDs per entity
    • allow multiple IDs
      • allows to obfuscate holdings (Buterin 2015)

Who benefits and loses under which regime?

Model Ingredients

  • Risky asset, value normally distributed 
  • Two large investors
    • Each period one is hit with size Q=1 liquidity shock.

    • Other can absorb the shock at zero cost.

  • ​Continuum of 1/    small investors
    • ​trade with probability       at "public" price
    • each period, mass 1 wants to buy, mass 1 wants to sell
  • Infinitely many trading periods
N(0,\sigma^2)
N(0,σ2)N(0,\sigma^2)
\rho\le1/2
ρ1/2\rho\le1/2
\rho
ρ\rho

Disclaimer:

  • no asymmetric information 
  • => our results need not be applicable to all asset classes
\rho
ρ\rho

Model Ingredients:
Trading and Timing

 

  • When hit with a shock, the "liquidity trader" (LT) may:
    • trade peer-to-peer (OTC)  (with small and/or large peers)
      • other large: "liquidity provider" (LP)
    • trade with a risk-averse intermediary at

       
      • Intermediary's inventory I "shifts" the public price
    • net-trades with intermediary = inefficient transfer of risk 
  • Unfilled positions clear with intermediary at end of stage game.
p(q)=\frac{\kappa \sigma^2}{N}\ (-I+q) \equiv \frac{\ell}{2} (q-I)
p(q)=κσ2N (I+q)2(qI)p(q)=\frac{\kappa \sigma^2}{N}\ (-I+q) \equiv \frac{\ell}{2} (q-I)

Model Ingredients: Costs

  • Data processing/complexity to contact q
  • Quadratic cost to contact mass q of IDs:
    • cost c is a loss to aggregate welfare
    • pay        and trade quantity
  • Linear mining/validation cost:
    • pay       to trade with     IDs
\rho q
ρq\rho q
\frac{c}{2} q^2
c2q2\frac{c}{2} q^2
\gamma q
γq\gamma q
q
q q

Direct

  • LT to LP: Buy quantity Q at price p?
    1. LP buys Q from intermediary and moves the "public price" P to​
       
    2. LP to LT: "sell you Q at price ≫ p?"
  • Front-runner pays validation costs.
P+ \ell/2 \times Q
P+/2×QP+ \ell/2 \times Q

Idea:

  • keep "risk" of transparency within trading model
  • for investors, can think of other costs, e.g., stealing of investment strategies

Indirect

Model Ingredients: Transparency of Ownership

  1. Full transparency = common knowledge of who is large
    • assume single ID (since validation costs increase in # of IDs)
  2. No transparency
    • only single ID allowed
  3. No transparency (ownership cannot be inferred)
    • continuum of IDs (to obfuscate ownership)

Requires a system design choice:

  • allow an entity (individual, investment fund) only a single ID per instrument
  • possible with private blockchain

Benchmark:
fully transparent (single ID) ownership

Options for Large Trader

Trade with small investors and intermediary

Trade with large investor
 

  • costs:
    • complexity + validation
    • intermediation
  • costs
    • reveal info about the trading needs
    • [model choice]:
      LT may get “front-run” by LP.

​​

Repeated setting:

Front-running is punished by “grim trigger” & trade forever with small and intermediary.

Single shot:
LP always extracts all surplus (or would front-run).

The Benchmark Equilibrium

  1. In a repeated game, "social norms" have bite and front-running can always be avoided.
  2. LT always trades with LP.
  3. LT and LP share the cost savings.
  4. Price concession
    • For small discount factor (infrequent interaction) price concession is necessary.
    • For large enough discount factors (≈ frequent interactions), price concession = 0 is an equilibrium.

Opaque single ID ownership

Equilibrium

  • The optimal mass of IDs to contact is independent of the intermediary's inventories/public price.
  • Mass x* depends on:
    •   : probability of small traders accepting the offer
    •   : the (il-)liquidity of the intermediated market
    •   : complexity/data processing costs.
\rho
ρ\rho
x^*=\max\{0, \frac{\ell \rho}{\ell \rho^2+c} - \frac{\rho\gamma}{\ell \rho^2+c}\}
x=max{0,ρρ2+cργρ2+c}x^*=\max\{0, \frac{\ell \rho}{\ell \rho^2+c} - \frac{\rho\gamma}{\ell \rho^2+c}\}
\ell
\ell
c
cc
  • When the  validation cost is not too large,              , the liquidity trader trades with both continuum & intermediaries
\gamma < \ell
γ<\gamma < \ell

Opaque multi-ID ownership

Closest and native to "public" blockchains:

  • anyone can participate anonymously
  • can create as many accounts as I want
  • described by Ethereum founder as simple solution to achieve privacy
  • private blockchains can choose to organize like this

Acceptance Probabilities: depend on LP's decision

small traders

large trader

small traders

large trader

small traders

large trader

filled

unfilled


Opaque Single ID

Opaque Multi-ID: LP accepts

Opaque Multi-ID: LP rejects

\rho
ρ\rho
\frac{2\rho}{1+\rho}>\rho
2ρ1+ρ>ρ\frac{2\rho}{1+\rho}>\rho
\frac{\rho}{1+\rho}<\rho
ρ1+ρ<ρ\frac{\rho}{1+\rho}<\rho

Decision problem LT

accept offer

submit large amount to continuum

  • (small) price concession to entice larger trader (but also paid to and "wasted on" small traders)
  • larger search costs
  • no price concession
  • expensive interaction with intermediary
  • smaller complexity cost

Decision problem LP

submit large amount to continuum

front run

  • incurs validation fee when front-running

Equilibrium & More

Result 1: There exists an equilibrium with no front-running where

  • LP accepts
  • price concession = 0

provided

  • the discount factor is large enough
    • = frequent interactions.
  • or the intermediated market is sufficiently liquid
    • = front running not very profitable (small quantity and low price advantage)
  • or validation costs are sufficiently high
    • = sunk cost for front-running too high.

Equilibrium & More

Result 2 (numerical): For small discount (=infrequent interaction) factors, the equilibrium with no front-running where LP accept does not exist. Then:

  • In equilibrium, LT offers p = 0 to the continuum, and
  • LP's IDs reject the offer.
     

=> over-trading with intermediary

  • Observation: an increase in the validation cost may curb front-running.

 

 

Comparing the designs

Observations

 

  • Trades with intermediary => socially inefficient 
    • better if large traders interact
    • otherwise: intermediary faces imbalance 
  • Small with large traders => complexity costs
  • By construction, payoffs under the full transparency benchmark are highest.
  • The trade-off for opaque regimes are:
    • complexity cost vs
    • intermediation cost

Comparing multi- vs single-ID opaque designs

 

  • Finding 1:
    • When large traders do not trade with each other, the welfare is the same in both opaque systems, irrespective of the ID-ownership setup.
  • Finding 2:
    • When large do trade with one another with multi-ID ownership, the welfare in this setting is higher than in the single-ID setting.

Payoffs to Large Traders

Finding 3:

For the average equilibrium stage payoffs of large traders.

  1. In multi-ID, when large traders do not interact, eq. payoffs lower than in opaque single-ID.
  2. In multi-ID, when large traders interact and p=0, eq.  payoffs larger than in opaque single-ID.
     

Finding 4: (Numerical)

There exist parametric configurations such that large traders trade with each other at p > 0 in the multi-ID ownership setting, but their average equilibrium payoff in the opaque single-ID setting is higher.

 

Summary

  1. "Back office" settlement has important front office implications!
    • with peer-to-peer there are critical design choices
      • Who can see the ledger?
      • How are virtual identities managed?
  2. Findings:
    • Transparent ledger with single IDs is welfare optimal and has lowest wealth redistribution (almost by construction)
    • Between (A) public blockchain solution with multiple IDs and (B) private, non-transparent ledger with single IDs:
      • public blockchain privacy solution has higher aggregate welfare
      • but does not necessarily lead to higher payoffs for large investors.

WHITE: Market Design with Blockchain Technology - Philly Fed Sept 2017

By Andreas Park

WHITE: Market Design with Blockchain Technology - Philly Fed Sept 2017

This is a set of slides that I used for a presentation of my paper with Katya Malinova on our paper "Market Design with Blockchain Technology". This iteration was presented on Sept 29, 2017. The deck has been designed for a 20 minute presentation.

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