Security Markets

Security Markets#

High Frequency Trading Arms Race#

In 2010, Spread Networks invested $300 million to create a new straight-line optic fiber cable from Chicago to New York, reducing latency from 16ms to 13ms. High frequency traders race to make trades first, which is why they value the decrease in latency. However in 2011, microwaves brought latency down to 10ms.

Is this a market failure? From Spread Network’s perspective, the cable might have made back its investment (and then some profit), but even then the opportunity cost of the investment might have been high as well. Furthermore, does high frequency trading in and of itself even benefit society?

Stock Markets#

We build on the definitions introduced in Section 11 (Prediction Markets and Information Cascades).

Definition 42 (Naive Investors)

Individuals who want to buy/sell stock as a means to store or liquidize assets. Naive investors do not have a primary goal of profiting from private information.

With just naive investors, there can be market frictions: there may not be stocks to buy or sell when a naive investor wants to buy or sell. Furthermore, the no-trade theorem does not apply as these investors derive value from the act of buying or selling itself instead of purely caring about the monetary value of their assets.

As before, liquidity providers leave resting orders and buy low, sell high. They provide an intermediary for naive investors to trade with, but naive investors lose the spread that liquidity providers gain. As such spread is part of naive investors’ transaction costs.

A stock’s “true” value represents aggregate beliefs about the stock’s returns. In equilibrium, a stock’s true value is between the stock’s bid and ask prices (otherwise, some agents have a profitable deviation to buy or sell the stock). True value may vary depending on external events. For example:

  1. Correlated Stocks/Securities: If someone buys gold in Chicago, the price of gold in New York increases. If there is demand for security \(X\) increases and security \(X\) is correlated with security \(Y\), then the price of \(Y\) will go up.

  2. Fed announcements: Fed made announcement on Sept 18, 2013. Markets reacted faster than the speed of light.

  3. Twitter: Trump tweets (about tariffs, the Fed, covfefe) changed stock values.

  4. Reddit: wallstreetbets and Gamestop stock.

Definition 43 (Snipers)

Agents that wait for changes in stock values and rush to trade with liquidity providers’ standing orders before those standing orders can be canceled. As such, being faster than competitors can be profitable.

In response to snipers, liquidity providers might increase spread to decrease sniping opportunities. However, this hurts naive agents by increasing their effective transaction costs.

Market Failure Fixes#

How can we resolve these market failures?

  1. Symmetric Speed Bumps: all orders get delayed by the same amount.

    • Doesn’t solve the speed arms race, nor does it remove sniping risk for liquidity providers.

  2. Random Speed Bumps: each order is delayed by some random amount.

    • Mostly solves the speed arms race (as luck in random difference is more important than speed differences), but makes the sniping risk worse: if a single sniper gets lucky, then the sniping succeeds.

  3. Sniper-Only Speed Bumps: only delay snipers.

    • If implemented, this would resolve the speed arms race and sniping risk, but it is difficult to determine who is a sniper and who is not.

  4. Frequent Batch Auctions: batch orders for some short interval and find the market-clearing price at each batch.

    • Everyone now has time to react to value-changing events as orders are prioritized by price instead of arrival (as long as the order arrives in the same batch).

Blockchain Flashboys#

Definition 44 (Smart Contracts)

Agreement between two agents for one transaction (borrowing) in the current period and a second transaction in some future period (paying back, perhaps with interest). If the second transaction does not happen, some collateral promised by the first agent is given to the second agent.

The collateral needs to be sent simultaneously with the first transaction (otherwise one agent can abort after getting money).

Definition 45 (Atomic Transaction)

A transaction such that either all steps are executed successfully or all steps are canceled.

One application of smart contracts is in decentralized finance (DeFi): cryptocurrencies, stocks, and contracts are traded. Limit order books and automatic market makers can be automated via smart contracts.

Definition 46 (Arbitrage)

Simultaneously buying low in one market while selling high in another.

Arbitrage is especially attractive with decentralized finance:

  1. Risk-Free Atomic Arbitrage:

    • In centralized finance, the arbitrageur takes takes risk (if they buy low first, then the high price they wanted to sell at may drop before they get to selling).

    • However, bundling buy and sell actions into a single atomic transaction resolves this risk.

  2. Cryptocurrencies are highly volatile, leading to more sniping opportunities;

  3. Information (code) is made public so full code and state of smart contract automated market makers are available. As such, it is easy to exploit bugs.

Definition 47 (Front-Running)

Transacting right before another agent to take advantage of the distortionary effects of the latter’s transaction.

In general, this is illegal in centralized finance. In decentralized finance however, all transactions are made publicly known before blocks are mined. Now, suppose miners are also traders and an arbitrageur finds an opportunity. If the arbitrageur broadcasts this transaction, then miners can execute the same trade on their own account. Miner includes the arbitrageur’s transaction on their block but after the miner’s own transaction.

Miners’ Extractable Value (MEV)#

In DeFi, arbitrageurs compete to be at the top of the next block via transaction fees. Then, a miner’s MEV is how much they can charge an arbitrageur. Miners receive rewards for each block they mine and additional transaction fees. Originally, the value for mining the block itself is greater than the MEV, but in recent years block rewards have went down (bitcoin rewards halve every 4ish years) while MEVs have gone up (arbitrageurs increasing demand for transactions). When MEVs come into play, not all blocks are created equal.

As such, miners can access a new type of fee-sniping attack: if block \(\hat{b}\) has a larger MEV than block \(b\), then miners would prefer to mine \(\hat{b}\) over \(b\). Then, a miner with fraction \(\alpha\) of computing power profits from a fee-sniping attack if

\[\alpha^2 \cdot \text{higher MEV} > \alpha \cdot \text{lower MEV} \iff \alpha > \frac{\text{lower MEV}}{\text{higher MEV}}.\]

Success probability is even higher if other miners also try to attack instead of extending \(b_t\).

With selfish tie-breaking, miners want to extend the block with higher MEV opposed to the block that was seen first. Furthermore, a miner can incentivize other miners to help extend their block by leaving some MEV leftover in the next block (known as undercutting). Some possible ways to undercut these issues:

  1. Transaction fees distributed among miners that mine the next \(k\) blocks;

  2. Capped transaction fees;

  3. “Burn” transaction fees instead of giving them to miners.

However, arbitrageurs and miners can always make side payments.

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