High Frequency Trading: Should it remain legal in our financial markets?

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Introduction

The evolution of markets has brought a significant set of investors and traders

along with it; new technologies allow agents to harness an advantage over each other in

order to make more profits. One increasingly controversial methodology is the use of

algorithms and its extensive application in high frequency trading. Simply put, high

frequency trading (HFT) is the process of transmitting trading orders in large quantities at

rapid speeds (Smith, 2015). Essentially, the use of these algorithms strips the human

intervention on orders in the markets and allows trades to be placed at speeds unmatched

by investors acting manually. Michael Lewis’ recent book Flash Boys: A Wall Street Revolt

has brought HFT into widespread public knowledge (Hull, 2014), and thus stirred

controversies and has given rise to opposition from non-HFT investors, and regulators

(Securities Exchange Commission, Ontario Securities Commission, etc.). HFT firms and

advocates are now on the defensive, and their arguments for benefits of HFT have been

tested and evaluated numerous times through research and studies. After the Flash

Crash of May 2010, regulators have come under scrutiny for their failures to properly

assert HFT regulations, on whom the SEC officially placed the blame on through a

published report in June 2010. The report also highlighted the need for regulators to

extend their regulatory duties to this mysterious and unregulated segment of the market

(Serritella, 2010).

HFT firms claim they provide benefits to the market, but opposition argues that

their disadvantages (some allegedly illegal) far outweigh these benefits and therefore

HFT should be banned from the financial markets. The benefits they claim to provide are;

liquidity in the financial markets, lower bid-ask spreads for certain securities, and lower

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price volatility in the overall financial market (High Frequency Trading: Emergence and

Evolution of High Frequency Trading, 2012). Through the use of topics in law and

economics, such as; the principal-agency problem, externalities, normative Hobbes

theorem, moral hazard, and others, we will go through some arguments against HFTs. I

also present some arguments which defend HFTs to conclude whether or not it should

be legal in our financial markets, and what the future might hold for this trading

methodology and its interaction with the market.

Arguments against HFT

The most common stance against HFT by non-HFT investors has been, and still

is the use of front running (Mckenna, Marketwatch, 2015). Front running is the act of using

non-public material information to execute a trade in a professional account before a

client’s account, and is deemed illegal in the financial markets. I believe this statement,

or rather the term, is wrongfully prescribed to HFT as they have no clients and act solely

as agents of their own assets. What actually happens is that HFT access price affecting

information much faster than other players in the market and the execution of a trade

based on this information is not front running, it is called flash trading, a major difference

(because unlike front running, flash trading is predatory but legal) (Bogoslaw, 2009). HFT

traders acquire information with the use of extremely fast networks that are connected to

an exchange’s data centre (for example; NYSE, or the CME). The cost to build a fast

network with the use of the latest technology is not a small cost by any means, and can

cost hundreds of millions of dollars (depending on the distance between the firm’s data

centre and the stock exchange) (Philips, Bloomberg Technology, 2012). For non-HFT

investors, it would be in their best interests to file a class action lawsuit against an HFT

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firm, this would make it relatively cheaper for the individual investors to file a claim (using

economies of scale). A strong basis of the lawsuit would be the violation of the SEC rules

and contract that HFTs have presumably agreed to follow when they establish themselves

and participate in the financial market(s). However, previous attempts of class action

lawsuits have been dismissed by federal courts because of lack of evidence provided by

the investors that they were being defrauded on trades by HFTs, this case was based on

Michael Lewis’ book (Rohan & Conner, 2016).

Despite the difference between front running and flash trading, retail investors are

still up in arms with regulatory authorities which allow HFT firms participate in the financial

markets, in fact, Italy is the only country in the world where HFT firms are taxed, in an

effort to reduce this practice (Stafford, 2013). Non-HFT investors allude to the fact that

HFT firms are in a way, trading predatorily in the markets, by snatching up orders before

the bulk of the investors get there first. The speed advantage that HFTs have allows them

to bid up prices of securities in different equity exchanges by miniscule amounts. This

process of buying and selling in the exchange leads to a strategy used by HFTs known

as latency arbitrage. Latency arbitrage is when a firm uses the time discrepancies

between market orders on different exchanges to buy stock at a lower cost and then sell

them for slightly more (sometimes by just a cent) to institutional firms that have placed

“buy” orders in the market before the HFT, and process the opposite for a “sell” order.

The HFT firms anticipate these orders by what is known as pinging, which basically allows

the HFT firms to decipher what institutional traders are buying or selling in large orders

and at what price (Scopino, 2015). Pinging is the process of sending multiple lots of orders

(100 shares) at different prices into an exchange only to cancel it once they are notified if

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one price they placed the order at has interested the opposite party of the transaction, the

remaining lots of orders with different prices are cancelled fairly quickly. A large order is

dispersed to be filled at different exchanges, and the difference in time that it takes for an

order to reach each exchange is all the time that is needed for HFT to use latency

arbitrage to profit. For example, let’s say that an institutional investor places an order to

buy 100000 of XYZ stock to exchange 1 (ex. NYSE). But at exchange 1 there were only

45000 shares that could be bought at the price the investor ordered them at. The

remainder of the order goes to different exchanges to continue the purchase of 55000

XYZ stocks that are needed to complete the investors order. Through the use of pinging,

HFT see that 45000 stocks of XYZ were bought at $X at exchange 1 and quickly race to

other exchanges to buy more of stock $XYZ at price $X. When the slower technology-

equipped order from the institutional investor arrives at the other exchange(s), the HFT

firms sell the XYZ stock at $X plus additional cents on the dollar. This time discrepancy

allows for a risk free trade for the HFT firms. The process of pinging has been studied

and is considered a manipulative practise (Scopino, 2015). The intention of sending in an

order of a security just to cancel the order can affect prices of the security while signalling

false information to other investors in the market. HFTs can alter the prices through this

practise in their favour and thus profit with virtually no risk. As for latency arbitrage, this

practise is not considered illegal in the financial markets but is controversial. It allocates

the distribution of wealth by extracting income from the non-HFT investors and

transferring it to HFT firms. In this scenario, the non-HFT firms are directly financially

injured by the practises of HFT firms, and they do not gain anything from it.

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Apart from competing against non HFT firms, HFT firms also compete grudgingly

against each other. The race to harness information from the exchange nanoseconds

earlier is done through what is known as colocation. Colocation is a method used by HFT

firms to situate their trading servers as close as possible to the exchange on which they

wish to trade from. This is because the closer they are to the trading data centre, the

faster their speed advantage will be over other investors, leading to better margins for

latency arbitrage. Frequently, HFT firms are able to colocate their equipment inside the

actual exchange, for large fees to the exchange. Most investors are excluded from this

transaction because of the very high cost of colocation. For this reason, investors

complain that HFT firms are essentially buying their rights to arbitrage, an economic

phenomenon with compensation that should be awarded to the most skilled players, and

the method of fee-for-service colocation seems like a shortcut to the regular arbitration

methods. The act of colocation does bring up some moral hazard on part of the exchange.

For one, the intricate “black boxes” that are colocated inside the exchange act as the data

centres for the HFT firms, but they cannot be fully monitored by the exchange because

of their complex structure. Essentially, the exchange cannot always know how these black

boxes operate and whether they perform the actions they claim to perform (CBS, 2010).

If any monitoring method does exist, it comes at a cost to the exchange, which would be

passed onto the HFTs collocating and thus would trickle down to non-HFT players, yet

again. This private agreement between the exchange and the HFTs can also be

dangerous if the agreement to cooperate fails. The normative Hobbes theorem states that

the law should be designed to minimize the harm caused by failed private agreements.

Since even regulators do not know the full capabilities of HFT computers, it is hard to

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design law to adhere to the normative Hobbes theorem, let alone minimize the harm

caused by a failed agreement. Just as the unpredictable Flash Crash of 2010, we cannot

comprehend the damages caused by a possible failed agreement between an HFT and

a financial exchange.

The opposition also argues that the securities exchange (ex. NYSE, TSX) is not

performing its fiduciary duty to all market players by allowing HFT firms to operate on their

exchanges. The basis of the argument is evident in one of the stipulations in the contract

of a listing agreement for the NYSE which states that a “fair marketplace for all players”

is what is to be expected of the exchange (NYSE IPO Guide, 2013). If the plaintiff is able

to prescribe an appropriate definition to “fair marketplace” and prove that the presence of

HFT firms make it unfair, they have reasonable grounds for claiming negligence and or

breach of duty by the financial exchanges. Although if breach of duty were the grounds

for legal action, a standard care of precaution by the exchange would then have to be

established as well. These processes and transaction costs (price of discovery, exchange

of information between lawyers) are apparent reasons that non-HFT firms and players

hesitate pursing legal action against HFT firms individually. Rather these investors may

find it beneficial to point out enough evidence for regulatory authorities to take further

action (as SEC has done after the release of Flash Boys, 2014) as it would be part of the

authority’s obligatory duty to investigate. Eric Hunsader, CEO of Nanex LLC conducted

his own research after the Flash Crash and found that the NYSE had violated SEC rules

by sending out data to its proprietary feed and public feed at different times. His research

led to an investigation by the SEC and resulted in a fine of $5 million to the NYSE

(Mckenna, Marketwatch, 2016).

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Even after all the studies that have been conducted on HFTs, they still present a

realm of unknown attributes that has not been comprehended yet. Since the SEC had

focused mostly on manual trading and some forms of computerized trading, it has lagged

in terms of regulation of the far more advanced algorithmic trading, especially HFT. In

other words, they were not fully capable of regulating HFT firms until after the Flash Crash

of May 2010 forced them to do so, and still lack considerably. This is also a problem,

because without proper regulation, it is hard to determine the faults and cracks that were,

and still may be present with HFT. Another reason to add regulation is to estimate

expectation damages; what can go wrong with an HFT, and if it does, what will the

damage be, how much will it cost, and who will bear the burden of these costs? The

incomprehensible nature of HFT firms definitely invites much opposition, and from all

fronts (market players, market regulators, etc.). During the Flash Crash of May 10, 2010;

the DJIA, S&P, and other indexes crashed and fell several thousand basis points

(aggregate) when an order was placed by a mutual fund to sell off $4.1 billion of E-Mini

S&P contracts (Treanor, 2015). As mentioned, the official report of the Flash Crash, which

was released in June 2010, placed the blame of this bizarre and unprecedented behavior

in the hands of HFT. Additionally, the report stated that HFT firms then pulled their capital

and their orders out from the market in order to prevent further losses (to themselves)

(Philips, Bloomberg, 2013), a time when liquidity must have been of high demand. Now,

consider the fact that equity exchanges provide HFT firms with liquidity rebates

(PricewaterhouseCoopers, 2015), which is compensation for providing liquidity in the

financial market(s). If a contract was in place at the time of the Flash Crash, the respective

exchanges would be able to seek damages from HFTs, not only would the threat of legal

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action deter other HFTs from pursing the same strategy under a similar scenario, it would

also help negate the economic effects these type of events would have on other investors.

We can use Gary Becker’s (Cooter & Ulen, 2011) model to gauge what the effects of

these events might be. If a legal battle were to ensue, and HFT firms were found guilty,

this would establish a sense of crime deterrence, and lead to the two effects stated above.

The regulatory authority would play the role of applying extra policing resources (through

regulation, fines, etc.) in addition to the crime deterrence as well.

Aside from allowing latency arbitrage, alleged front running, and lightly regulated

practise, the exchanges in fact earn revenue by allowing HFT firms to trade on their

exchange. This is when colocation comes into the picture again. On the NYSE, the fee is

said to be $30000 a month, and in exchange for this fee, the HFT firms gain the ability to

access market information faster than others. The first and foremost idea that comes to

mind is the conflict of interest in which the exchange has many clients but discriminates

the speed of access to its’ information based on monetary exchanges. In essence, it could

be said that the exchange has used discriminatory pricing in order to reap benefits from

its users, and the fact that exchanges are for-profit organizations does not help this

situation either in terms of the regular investor’s perception. Ideally, the exchange(s) will

act as any profit maximizing firm as simple economic theory suggests and look for ways

to increase profits, but this comes at the cost of their other consumers (non-HFT

investors).

As mentioned before, HFT firms pay a high fee (not only to exchanges, but also to

laborers) to construct their networks and connect to exchanges to shave milliseconds off

of their trades. This race against time is a form of competition and innovation in the HFT

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industry, an industry that just has a far simpler and better way of making money than non-

HFT players. If the business model allows HFTs to remain profitable and encourage

innovation in the markets, they should be able to use this model to generate profits. The

number of middle class workers employed by large HFTs to construct their networks

exceeds the thousands (over the past decades) and can be seen as a consumer surplus

in the employment spectrum. There have been accusations of HFTs hurting others in the

market by explicit price manipulations (unlike pinging where price manipulation was a by-

product of the practices of HFTs) (Geiger & Mamudi , 2014), but studies have debunked

this allegation. Other than that, HFTs are not really hurting any players in the market,

rather they increase liquidity and efficiencies in the markets.

There are HFTs that have reported profits for consecutive months at a time, that

is, making a net profit every day for a few months (CBS, 2010). This is (or has been)

unheard of in the investment industry, and the implication is that HFT traders are not

traders, but cheaters. To be “correct” about trades at such a high rate is unfathomable by

traditional investors (buy and hold, short, etc.), and the fact that HFTs are able to

accommodate these profits without fundamental research without consequences

changes the perception for non-HFT players in the market to one that is in favor of HFT

firms.

Apart from non-HFT institutional investors, there are other externalities that result

from the presence of HFTs in the financial market. Retail and small (mom and pop)

investors have come to a certain understanding of HFT firms from the acclaimed Michael

Lewis’ book. Lewis explains that HFT firms are a source of markets being rigged in favor

of the bigger players, and that mom and pop investors are losing out to these bigger

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players (Lewis, 2014). This drawdown of investment from the markets hurts not only the

mom and pop investors, but also all financial intermediaries that manage their money

through the markets, as well as firms in need of capital. Mutual funds, pension funds, trust

funds and others report that smaller investors do not trust the market as much as they did

before because they feel that they are being cheated (Schack, 2013), and therefore

instruct their money managers to invest in other assets. As for the firms, especially new

firms considering IPOs, it is harder to gain the trust of investors on a wide scale

(institutional, retail, mom and pop) because of the changed perception of the financial

markets. This hinders the possibility of an IPO being as successful as it could have been,

or for a well-established firm; the probability of new shares being distributed at a fair price.

Essentially, the prices of securities would be discounted in general (for overvalued, and

undervalued securities). This is undesirable for undervalued securities, because their

prices will be discounted even further than the value that is already established in the

financial markets.

A different perspective to look at the externalities of the actions of HFT is the

relationship between the institutional investor and their client(s) that incur losses from

latency arbitrage conducted by HFT. When clients invest their money with said investors,

they are guaranteed fair market prices, and best execution of orders in their account(s).

However, because of latency arbitrage, the best execution price is not possible for

securities which are exposed to HFT arbitrage. The client may have the substantial

evidence to prove that the institutional investor is not fulfilling its fiduciary duty and

performance according to contracts signed in the opening of an account with the

incumbent’s firm. The principal-agency problem models this exact relationship, and the

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problem of moral hazard (through the investor not taking precaution on trading securities

exposed to HFT) is evident and can be significant if a good portion of equities in a client’s

portfolio are affected of latency arbitrage.

Defending HFT Trading

HFT firms gained traction in the markets at the beginning of the 21st century, and

at first transacted 10% of the orders in the markets. Fast forward to today and that

percentage has grown to about 65%, even though they encompass less than 20% of the

investment firms in the market.

So why, or how can HFT traders be good for the market? Despite the “flaws”

described previously, HFTs provide a variety of sources that are valuable to investors

across all levels in the financial markets. The main advantage HFT provides is liquidity,

using high volume and frequency to buy or sell securities that there is a demand for in the

market. HFTs act as market makers and fill orders when they see an opportunity, but

other investors have problems with how HFTs fulfill these orders (latency arbitrage). We

can say the by-product of the HFTs actions are good and valuable to investors, but the

main purpose of their business is frowned upon in the markets.

HFT firms also provide investors with price efficiencies, through the result of

lowering bid-ask spreads on securities they trade in. Lower bid-ask spreads make it

cheaper for investors to trade securities, but again the problem arises when we look at

the method HFT firms use to do this. HFTs have been accused of shaving some cents off

of these spreads and pocketing them. At the end, the non HFT investor would have been

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able to buy or sell the security for 2 cents cheaper, but the HFT pockets 1 cent so now it

is only 1 cent cheaper, but cheaper nonetheless.

There are certain legal problems that arise when talking about HFT methodology.

The first obvious one is the problem of front running, or the alternative term flash trading.

As previously mentioned, HFT firms use pinging to decipher what price of a security would

be efficient to buy or sell at. When they find out this price, the algorithms put in orders to

buy all available stocks of this security, then send out an order to sell these securities at

another exchange with a higher price. The small benefits add up and can accrue millions

of dollars in profits per year, if not more. To use a good analogy, imagine that you are

shopping and see an item you would like to purchase but wait for it to go on sale, but

there are “scalpers” (HFT) that pay the store to find out what the sale price of this item

will be. As soon as the item goes on sale, those scalpers buy the item for $X and sell it to

you for $X plus an additional dollar amount (fractional). Even though you purchased the

item, and may have got it on sale, you did not get the best price that it was offered for by

the principal. Now imagine the same process happening simultaneously to thousands of

people in thousands of locations. This example is a simplified resemblance of how HFTs,

non-HFT, and financial exchanges interact in the market, and the profits (although

miniscule per security/good) shave off valuable savings from other investors, which go

directly into the pockets of the HFTs engaging in the said securities. This type of

“predatory trading” resembles the distribution of income being unfairly adjusted for the

non-HFT investors.

Economic principles

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Given the currents state of the financial markets, I suggest that we are in a Pareto

efficient market. Pareto efficiency states that the markets are allocative efficient if no

player can improve their position in the market without worsening the position of another.

If we eliminate HFT players in the market, the bid-ask spreads would rise for many

investors participating in markets in which there were HFTs. If HFT players persist,

latency arbitrage still will exist but so will liquidity and lower bid/ask spreads. To go in any

one of these directions, another player in the market will be made worse off, therefore

economic theory suggests that we are in a Pareto optimal state in the markets. However,

the possible introduction of regulations may change this status in the coming years.

Robert Cooter’s book states an important part of information economics; “An

economic innovation provides a better way to make something or something better to

make” (Cooter & Ulen, 2011, p. 113). A better way to make something lowers the cost of

production and increases the supply of this good, and therefore decreases the price of

this good in the market. HFT is that type of innovation, which has provided a better way

of transacting orders in our financial markets, therefore cutting costs, increasing the

supply of trades and lowering the price the consumer pays for the trades to be made. A

simple diagram below shows us the additional consumer surplus in the market because

of lower prices and higher quantities that are potential outcomes of a higher supply of

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trades:

Using simple economic theory, it is easy to see why some non-HFT investors do

not oppose HFT practises, it is because they gain consumer surplus (below the original

price in blue dotted area) and access to lower spreads and the investors that do oppose

HFTs weigh their disadvantages more than their advantages. But as we saw earlier, there

is a loss of consumer surplus through the practise of latency arbitrage. To determine the

net gain or loss, we would have to figure out which effect is more significant and whether

the existence of HFTs benefits the consumer overall.

Another simple economic theory we can use to dissect the long-term impact of

HFTs stems from competitive and absolute advantage. As of now, all HFT firms have

absolute advantage against non-HFT firms. The excessive profit margin attracts new

+Consumer Surplus

D

S’

Price of Trades

(Bid/ask)

Quantity of Trades

S

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players into the HFT market, and doing so increases the supply of HFT firms. As the

number of suppliers increases, the profit margins will decline. This has already been

occurring over the past few years as evident by the lower profit margins of current HFT

firms. This effect has the potential to make all HFT firms become marginally profitable in

a few years, if not earlier. This undesired profit level will cause more innovation, one that

will hopefully be less controversial in the financial market(s) and encompass more profits

for the pioneers of said innovation. But as we progress now, the emergence of more HFTs

will cause more upheaval in the financial markets until a strong approach is taken up by

the regulators.

Based on the research that has already been done on HFT and their practises, I

believe a reform in the financial markets is required. Although, I believe HFT firms will still

persist at a steady rate, the widespread opposition cannot go unheard by the regulators.

Alternatives have already been introduced and initiated in hopes of limiting the effects of

HFT practises. Eric Budish, Peter Crampton, and John Shim suggested the use of

frequent batch auctions (Budish, Crampton, & Shim, 2015), which changes the

continuous time frame of trading to discrete intervals, thus reducing the latency that HFT

firms gain from speed advantage and the amount of times they would be able to use this

strategy. A whole new equity exchange has been introduced to limit the effects of HFT; it

is the IEX (The Investors Exchange) platform, founded by the acclaimed protagonist of

Lewis’ Flash Boys; Brad Katsuyama (Schmidt & Michaels, 2016). IEX already

accommodates 1.54% (IEX, 2016) of the market share of trades that are conducted in the

market, proving that there are investors that value the service and mandate of limiting

HFT practises. The benefits provided by HFTs cannot go unnoticed either, for this reason

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it is highly possible that HFT remain legal, but only with the addition of regulations. As for

the HFT firms, their industry is declining along with their profit margins, and with the

possible introduction of market regulation and other ATS (alternative trading systems) like

IEX, these profit margins would decline even further and discourage others to launch

more HFT firms. In a few years, it is possible that we may have a monopoly of HFT firms

that accommodate trades in all of our markets with regulation enforced by authorities, but

until then we have to accept being the turtles in the race.

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