Market Design with Blockchain Technology

Katya Malinova and Andreas Park

Why is Blockchain Important? What can it do?

 

  • World Wide Web:

    • frictionless electronic transfer of information

  • Blockchain:

    • ​frictionless electronic transfer of value

Illustration: Money Transfer

Illustration: Stock Trade

Illustration: Money Transfer

Illustration: Stock Trade

A version with an exchange

Illustration: Stock Trade

A version without an exchange but with smart contracts

Native design feature of blockchain: transparency of holdings and actions

 

  • Anton Golub, Lykke Chief Scientific Officer: "[T]he public ledger becomes a valuable source of trading data.

    • While it is not possible to identify the traders [by name],

    • any observer can deduct [...] detailed position data - by tracking tick-by-tick transaction data from the blockchain.[...]"

  • One way for traders to obfuscate their holdings is to use multiple accounts/IDs (Vitalik Buterin 2015)

Take Aways: Native Features of Blockchain

  • Blockchain requires no "accounts", dealers/brokers, only the network is needed
  • Peer-to-peer is possible.
  • Blockchain ledger can be very transparent
    • => design choice.
  • Who is your peer ... ?

For this paper

Also interesting

  • Settlement is immediate
    • implications for intermediaries
    • => paper by Zoican & Khapko (2017)
  • How do you pay for validation?
    • Service by network organizers?
    • Incentives as in Ethereum or Bitcoin?

What do you know and what do you not know in OTC?

What do you know and what do you not know in Peer-to-Peer?

Key Research Question

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

  • different ledger transparency regimes are possible
    • ledger is open to all
    • ledger is hidden
  • different identifier-usage regimes are possible
    • use single IDs per entity
    • use arbitrary number of IDs

Who benefits and loses under which regime?

Key Take Away

  • transparent ledger with single IDs is welfare optimal and has lowest wealth redistribution
    • can be implemented with private blockchains
    • here: optimality arises almost by construction
  • If the choice is between
    • public blockchain with multiple IDs and
    • private blockchain with single IDs and non-visible ledger
  • then the
    • public blockchain has higher welfare
    • but it does have higher welfare transfers from small to large investors.

Model Ingredients

  • Risky asset, 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
  • Direct costs:
    • Data processing/complexity to contact mass q
    • Contact mass q:
      • pay        and trade quantity   
      • cost c is a loss to aggregate welfare
    • Linear mining/validation cost:
    • pay       to trade with     counterparties
N(0,\sigma^2)
N(0,σ2)N(0,\sigma^2)
\rho\le1/2
ρ≤1/2\rho\le1/2
\rho q
ρq\rho q
\frac{c}{2} q^2
c2q2\frac{c}{2} q^2
\rho
ρ\rho
\gamma q
γq\gamma q
q
q q

Disclaimer:

  • no asymmetric information here
  • => not applicable to all asset classes
  • But: equities are probably not the first choice for blockchain-based trading
    • instead: bonds, derivatives, swaps

Model Ingredients:
direct costs

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

Disclaimer:

  • no asymmetric information here
  • => not applicable to all asset classes
  • But: equities are probably not the first choice for blockchain-based trading
    • instead: bonds, derivatives, swaps

Model ingredients:
Intermediated Market

  • Risk averse intermediaries offer demand schedule 
  • Price by market clearing
  • For combined inventory I, sell (combined) quantity q at


     
  • Inventory I "shifts" public price by​
  • Model feature:​
    • net-trades with intermediary = inefficient transfer of risk
    • => welfare reducing.
p(q)=\frac{\kappa \sigma^2}{N}\ (-I+q) \equiv \frac{\ell}{2} (q-I)
p(q)=κσ2N (−I+q)≡ℓ2(q−I)p(q)=\frac{\kappa \sigma^2}{N}\ (-I+q) \equiv \frac{\ell}{2} (q-I)
\ell/2\times(-I)
ℓ/2×(−I)\ell/2\times(-I)

based on Biais (1993)

Model Ingredients:
Timing

 

  • Infinitely repeated stage game
  • Stage game:
    • LT hit with shock
    • contacts other traders (large or small) (only once)
    • other investors reject or accept
    • Unfilled portion filled with intermediaries

Model Ingredients:
Indirect Costs => Front-Running

  • Modelling Mechanics of Front-Running:
    1. LT to LP: Buy quantity Q at price p?
    2. LP buys Q from intermediary and moves the "public price" P to
    3. LP to LT: "sell you Q at price ≫ p?"
  • Note: Front-runner must pay validation costs.
P+ \ell/2 \times Q
P+ℓ/2×QP+ \ell/2 \times Q

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
    • assume only single ID allowed
  3. No transparency (ownership cannot be inferred)
    • assume continuum of IDs (to obfuscate ownership)

Benchmark:
Transparent & concentrated ownership

Requires a system design choice:

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

Transparent, concentrated Ownership

  • Key feature: Large traders are identifiable.

  • Large trader LT may:

    • Trade  with small investors,

    • the intermediary.

    • Approach the other large trader LP.

 

Option 1:
Approach small investors

  • Contact mass x of investors such that 

data cost

current market price paid to small

costly trading with intermediary

validation cost

\max_x -\frac{c}{2}x^2-\rho \gamma x-x\rho\frac{\ell}{2}\times (-I) - (1-\rho x)(1-\rho x -I)\times\frac{\ell}{2}.
maxx−c2x2−ργx−xρℓ2×(−I)−(1−ρx)(1−ρx−I)×ℓ2.\max_x -\frac{c}{2}x^2-\rho \gamma x-x\rho\frac{\ell}{2}\times (-I) - (1-\rho x)(1-\rho x -I)\times\frac{\ell}{2}.

Option 2:
Approach other Large Trader

  • (+) ability to locate/contact the LP

    • escape complexity and validation costs,

    • avoid price impact of trade with risk-averse intermediaries.

  • (-) reveal info about the trading needs
    • [model choice]: LT may get “front-run” by LP.

​

Pros & Cons

Possibility of Front-Running

  • Single shot: LP always extracts all surplus (or would front-run). 
  • In repeated setting: 
    • Front-running is punished in subsequent periods via “trigger strategy” punishment:
    • Deviation → large traders avoid each other; trade as in Setting I forever.
  • Is it realistic? I.e., can we assume memory of deviations, repeated interactions?
    • Most peer-to-peer e-commerce systems have bilateral rating:
      • Ebay, Uber, Airbnb, etc.
    • Also doesn't have to be "personal" - "avoiding large" can just become a social equilibrium

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.

Non-Transparency:
Opaque Holdings & concentrated ownership

Equilibrium

  • The optimal mass of traders to contact x* is independent of the intermediaries 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^*=\frac{\ell \rho}{\ell \rho^2+c} - \frac{\rho\gamma}{\ell \rho^2+c}
x∗=ℓρℓρ2+c−ργℓρ2+cx^*=\frac{\ell \rho}{\ell \rho^2+c} - \frac{\rho\gamma}{\ell \rho^2+c}
\ell
ℓ\ell
c
cc
  • Note: For small validation cost,              , holds that                                         trade with both continuum & intermediaries
0<\rho x^* < 1~\to
0<ρx∗<1 →0<\rho x^* < 1~\to
\gamma < \ell
γ<ℓ\gamma < \ell

Non-transparency II:
Opaque & dispersed ownership

Closest and native to "public" blockchains:

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

Acceptance Probabilities

small traders

large trader

small traders

large trader

small traders

large trader

filled

unfilled

Setting I:
non-transparent, single IDs

Setting III: large accept

Setting III: large reject

\rho
ρ\rho
\frac{2\rho}{1+\rho}
2ρ1+ρ\frac{2\rho}{1+\rho}
\frac{\rho}{1+\rho}
ρ1+ρ\frac{\rho}{1+\rho}
  • LT offers p = 0 to the continuum.
  • Large trader public keys reject.
\frac{2\rho}{1+\rho} > \rho > \frac{\rho}{1+\rho}
2ρ1+ρ>ρ>ρ1+ρ\frac{2\rho}{1+\rho} > \rho > \frac{\rho}{1+\rho}

continuum & large accepts

setting I: non-transparent

continuum & large rejects

"over-trade" with the intermediary

Trigger Strategy:

Decision problem LT

accept offer

submit large amount to continuum

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

Decision problem LP

submit large amount to continuum

front run

  • small wrinkle: may involves paying settlement fee when front-running

Characterizing the Equilibrium

  • Search for equilibrium where LP accepts offers & doesn't front-run.
  • to avoid front-running price concession p>0 may be necessary
    • need to offer p to all peers, large and small.
  • validation costs:
    • do not affect the LT directly: with dispersed ownership, has to pay both for trades with peers and with intermediary.
    • matter for front-runner => has to pay unrecoverable sunk cost to move price

Equilibrium & More

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

  • LP accept
  • 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

 

 

Comparing the three designs

Payoffs with transparent, concentrated ownership are highest.

  • Social norms have the strongest bite when there is full transparency.

Comparing the three designs

Observations

  • trading with the intermediary is socially inefficient 
    • to avoid this cost, large traders must interact
    • if not, there is always an imbalance of traders who trade with the intermediary
  • trades between small and large traders cause complexity costs
  • Thus trade-off for large trader interaction is
    • complexity cost vs
    • intermediation cost

Comparing concentrated vs dispersed

 

  • Finding 1:
    • Equilibrium with multi-IDs where large don't trade with one another has the same payoff as single-ID equilibrium.
  • Finding 2:
    • Equilibrium with multi-IDs where large do trade with one another has strictly higher payoff than single-ID equilibrium.

Payoffs to Large Traders

Finding 3:

The following relations hold for the average equilibrium stage payoffs of large traders.

  1. When large traders do not trade with each other with multi-ID ownership, their equilibrium payoffs in this setting are lower than those the opaque single-ID setting.
     
  2. When large traders trade with each other with multi-ID ownership at p =0, their equilibrium payoffs in this setting dominate those in the opaque single-ID setting.
     

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.

 

Influence of Validation Cost

For dispersed ownership, there exist parametric configurations s.t. 

small increase in validation cost => increase in aggregate payoff   

Idea: Switch from

  • "trigger" equilibrium =
    • no price concession
    • LP rejects
    • overtrade with intermediary 
  • to "co-operate" equilibrium 
    • offer price concession (good for small!)
    • LP accepts

Summary

  1. Known design choices for Blockchains/DLT
    • public vs. private
    • permissioned vs. permissionless
  2. Our paper:
    • "back office" settlement has important front office implications!
    • with peer-to-peer there are further critical design choices
      • Who can see the ledger?
      • How are virtual identities managed?
  3. Findings:
    • transparent ledger with single IDs is welfare optimal and has lowest wealth redistribution (almost by construction)
    • Between (A) public blockchain with multiple IDs and (B) private, non-visible ledger with single IDs public blockchain has higher welfare but it does have higher welfare transfers from small to large investors.

Summary

Anton Golub, Lykke Chief Scientific Officer:

  • "The blockchain makes it possible for every financial instrument to be a listed security in the form of a digital token, the so-called colored coin.
    • Every colored coin can contain International Securities Identification Number (ISIN), thus can be treated as any other financial instrument[...]. "

=> Let’s start talking about market design with blockchain technology!

  • In 2017, ICOs MCap>$300M.
  • several blockchain exchanges already operate (e.g., LykkeX, Godzillion).
  • Overstock.com together with t0 will allow blockchain-based trading by end-2017.
  • NASDAQ has issued securities using Blockchain tech.
  • DTCC will soon offer some form of blockchain settlement.
  • ASX in Australia will soon settle on a blockchain.

Market Design with Blockchain Technology

By Andreas Park

Market Design with Blockchain Technology

This is a set of slides that I used for the presentation of my paper with Katya Malinova on our paper "Market Design with Blockchain Technology". This iteration was presented at a conference at the Cambridge Centre for Alternative Finance, Judge School of Business, Cambridge University, June 2017. This deck of slides is designed for a 30 minute presentation.

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