Handbook of Asian Finance || The Regulation of High-Frequency Trading: An Asian Perspective

Handbook of Asian Finance, Volume 2 2014 Elsevier Inc. All rights reserved.http://dx.doi.org/10.1016/B978-0-12-800986-4.00008-X 153

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The Regulation of High-Frequency Trading: An Asian PerspectiveImad Moosa and Vikash Ramiah445 Swanston St., Melbourne, Vic 3000, Australia

8.1 INTRODUCTION

High-frequency trading (HFT), also known as high-speed trading, has been defined in so many ways that it is invariably confused with other forms of computer-based trading, which often leads to arguments directed against HFT when in fact the subject of criti-cism should be something else. HFT can be defined in terms of its characteristics as a data-intensive, latency-sensitive, high-volume, low-margin activity where holding peri-ods are extremely short and positions are rarely held overnight.1 Thus HFT is a trading activity or style characterized by: (i) rapid analysis of huge amounts of data on prices, volumes, spreads, etc; (ii) high volumes of trading to make non-negligible profit out of very small differences between selling and buying prices; (iii) sensitivity to latency in the sense of involving rapid execution of transactions; and (iv) extremely short holding periods, hence it is basically an extreme version of intra-day trading. HFT is all about doing things quickly and frequently, and this is why Armstrong and Subhedar (2011) describe HFT as the practice of using complex, automated strategies to execute trades within the space of 10 millionths of a second. This is how quick HFT can bespeed is required for frequency, and frequency is essential for making handsome profit from tiny margins.2

High-frequency traders are made up primarily of international banks and large hedge funds, because there are barriers to entry represented by the high cost of obtain-ing tick data and acquiring sophisticated technology. HFT is often characterized as trading with less people as emphasis is placed on computer technology. In the jargon of microeconomics, HFT is a capital-intensive rather than labor-intensive production process. Technology is used to hunt for temporary inefficiencies, distortions, and deviations in the market and trade in ways that can make them money before the underlying phenomenon disappears. High-frequency traders compete on the basis of

1 According to Baumann (2013), rapid trading has reduced the average holding period from 8 years half a century ago to 5 days at present.2 Baumann (2013) expresses this idea as follows: Buying a stock at $1.00 and selling it at $1.0001, for example. Do this 10,000 times a second and the proceeds add up.

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http://dx.doi.org/10.1016/B978-0-12-800986-4.00008-X

Imad Moosa and Vikash Ramiah154

speed with other high-frequency traders, not with long-term investors who look for opportunities over long periods of time.

While HFT has been a common practice in US and European markets for some years, albeit with recurring controversy and mixed feelings, the trend is being replicated in Asian markets. However, HFT has been growing slowly in Asia for several reasons including cultural factors as Asian investors tend to adopt a more conservative funda-mental approach to investment. There are also regulatory issues, emanating from the dilemma of choosing between embracing the practice despite the potential (or alleged) problems associated with it and being left behind the markets that have accepted it as a common practice. After all, HFT may have emerged as a natural outcome of the rapid development in information technology, as financial practices have, throughout history, developed alongside technology particularly communication and information technology. Furthermore, turf battles between exchanges may prevent the kind of inter-connected market approach that provides fertile ground for HFT. Traditional brokers and institutions, whose positions are threatened by upstart trading houses, contribute to the erection of barriers, thus impeding the growth of HFT. In general, the spread of HFT is hampered by inadequate infrastructure, heavy regulation, and opposition from entrenched interests.

The objective of this chapter is to provide a brief exposition of the growth of HFT in Asian markets and evaluate the arguments for and against the practice in general terms and from an Asian perspective. It will be argued that HFT is not the evil practice and that high-frequency traders are not the villains typically portrayed to be by the media and by competing firms that are not willing to or capable of engaging in this activity. Our conclusion is that Asian markets should embrace and welcome HFT as an offshoot of technological progress.

8.2 THE GROWTH OF HFT IN ASIA

After years of resistance, HFT is growing across Asia, driven by market demand, stock exchange consolidation, and greater acceptance among regulators. The move by Asian exchanges to open up to computer-driven trading has led to increasing numbers of high-frequency traders setting up shop across Asian markets. One of the barriers to the spread of HFT in Asia has been the lack of infrastructure because the practice requires rapid execution of transactions. In 2010 Tokyo, Bombay, Hong Kong, and Singapore lagged behind London and New York (NASDAQ) in terms of the time it takes to execute a trade in millisecond as shown in Figure 8.1.

However, things have changed since. Japan led the move to the introduction of HFT into Asian markets when the Tokyo Stock Exchange launched its Arrowhead trading system in a bid to reduce latency and boost trading volumes. As a result, the number of HFT firms trading Japanese stocks is expected to grow significantly. It is also

The Regulation of High-Frequency Trading: An Asian Perspective 155

likely that Arrowhead will spur other innovations and compel more US and European firms to locate trading applications closer to the exchange matching engines in Tokyo. The Singapore Stock Exchange has invested $200 million in its new trading engine, Reach, which provides rapid execution of trades. While it is doubtful if the exchange has a high enough turnover of stocks to become a major HFT player immediately, it is expected to start experiencing a growing proportion of high-speed trades in the com-ing years. Markets such as Indonesia and Malaysia are witnessing a growing number of high-frequency traders starting business and establishing presence. While these markets are not deep or fast enough to support full-blown HFT, the growth of computerized trading is a step on the path toward the accomplishment of this objective.

The rising popularity of HFT in Asian markets would not have been possible a few years ago when regulatory suspicion of automated trading techniques meant that exchanges and authorities shied away from giving brokers direct access to the market. However, regulators still have mixed feelings about giving high-frequency traders a free hand. Concerns linger about the possibility that a flash crash, like the one that hit US exchanges in May 2010, could wreck havoc across Asian markets. On that occasion, the Dow Jones industrial average plummeted almost 700 points in just minutes, wiping out $1 trillion in market value in a move that industry players blamed on HFT.3 As in the

3 We will come back to the flash crash later on to consider the proposition that it was caused primarily by HFT.

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Figure 8.1 Time taken by exchanges to execute trades (in milliseconds).


US this issue has been controversial because the proponents of HFT argue that a flash crash la Wall Street could not happen in Asia because the markets are not as intercon-nected as in the US and Europe and because many exchanges have limits on how far stock prices can fall in one session. In any case we will argue that what happened in May 2010 cannot be blamed on high-frequency traders.

Indicative of regulatory apprehension about HFT is that Australian regulators intro-duced new market trading rules in December 2010. Among the devices are the so-called kill switches that can be used to stop computer-generated trading in the event of sudden or adverse market movements.4 The Hong Kong Exchanges and Clearing has announced that while rapid-fire electronic trading strategies will eventually make their way to the city-state, regulators in Hong Kong are still studying markets in the US and Europe before they push for changes to the local market structure to attract com-puter traders (Ho, 2013). In July 2012, Hong Kongs Securities and Futures Commission (SFC) released a consultation paper to enhance the regulatory framework for electronic trading, which includes internet trading, direct market access, and algorithmic trading. Japan, Hong Kong, and Singapore have all explored new regulations intended to reduce the potential for sudden and unexpected market changesfor example, circuit break-ers that act to stop or slow the condition that leads to market crash.

While Asia has a lot of potential, it is far behind the US and Europe with respect to the volume of trading accounted for by HFT. Figure 8.2 shows that Asia without Japan lags even behind Brazil in terms of the percentage of turnover attributed to HFT. Apart from regulatory skepticism, the infrastructure required for HFT is not yet developed adequately across Asian markets. In some of these markets, it can take seconds to execute an order, which is a lifetime for a trader who uses sophisticated algorithms to trade thousands of shares in a millisecond with the aim of earning profit from market making and price imbalances. The importance of the infrastructure for the expansion of HFT and the proliferation of high-speed traders is evident in the case of Australia. Hutchens (2012) quotes Carole Comerton-Forde, of ANUs College of Business and Economics as saying that Australia has become more attractive for HFT in recent years because of improvements in the trading infrastructure. The Australian Stock Exchange upgraded its trading technology in November 2010, allowing trading capacity to exceed 5 million trades and 500 million order book changes per day. It also launched its high-speed dis-tribution network (ASX Net) and improved its co-location facilities (ASX Liquidity Centre). A new exchange, Chi-X, opened its doors in 2011.

In 2012 Trading Architecture Asia and WBR (2012) conducted a survey of the views on HFT in Asia Pacific (APAC) and received feedback from over 150 participants. Six questions were asked:

4 A computer-driven adverse market movement can be caused by long-term traders as what happened in October 1987 when the Dow plunged by 25%. It does not make sense that kill switches are aimed at high-frequency traders only.


1. Do you consider that HFT firms in APAC should form a lobby group to help man-age their mutual interests?

2. Some people claim that this means that HFT firms are not real market makers because they are not operating when the market most needs them. What do you think?

3. How do you rate the regional percentages of HFT volumes as a percentage across asset classes?

4. Which categories of HFT activity do you expect to increase or decrease over the next 5 years?

5. To what extent do you consider various categories of low latency trading to change over the coming years?

6. What do you see as the longer term implications of exchanges adopting the HFT-based market making technology-driven model and the impact of increased competition?

The survey revealed some interesting results, including the following: (i) 65% of respon-dents thought that HFT firms should form a lobby group to protect their interests; (ii) most respondents predicted that in 5 years time, HFT would be more common across all the main asset classes but particularly equities, futures, and FX; (iii) 35% thought that HFT could bring about a big market system failure but this was countered by 50% who thought that technology would help mitigate the risks so that any future problems

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Figure 8.2 High-frequency trading as a percentage of total trading.


caused by HFT would be small and easily managed; (iv) not everyone believed the statements of some HFT firms claiming to be market makers with 38% of respondents arguing that they are not real market markers; (v) 35% of the respondents declared that high-frequency traders provide valuable liquidity under most conditions; and (vi) the adoption of the low latency technology service sector was considered by most respon-dents to be more common in the years ahead with these services spreading across nearly all key trading areas.

It will most likely take a long time for Asian markets to catch up with markets in the US and Europe in terms of the percentage of trading accounted for by HFT. The Trading Architecture Asia-WBR (2012) report suggests that the overall adoption of high-frequency trading in APAC is expected to lag behind Europe and the US by a sig-nificant margin due to the lack of IT infrastructure, complexity in regulation, and lack of attractive market microstructure. Hence the trend is underway but progress is mov-ing with some sort of a dragging anchor. In the remainder of this chapter we explore the reasons why HFT is viewed with suspicion and explain why it is a benign activity that causes no damage over and above the damage that can be caused by long-term investors.

8.3 SOME MISCONCEPTIONS

The HFT debate is littered with misconceptions about what the activity is all about. The three important misconceptions are: (i) confusion with other kinds of activities, (ii) that HFT caused the flash crash of May 2010, and (iii) that it is a license to print money.

8.3.1 Confusion with Other ActivitiesConfusion with other kinds of activities arises because HFT has no precise definition. At its most basic, HFT implies speed: using supercomputers, firms make trades in a matter of microseconds. The techniques used to generate profit vary. Some trading firms try to catch fleeting moves in everything from stocks to currencies to commodities. They hunt for signals such as the movement of interest rates that indicate which way parts of the market may move in short periods. Some try to find ways to take advantage of subtle quirks in the infrastructure of trading. Other firms are market makers, providing securities on each side of a buy and sell order.

HFT may take one of three primary forms: market making, ticker tape trading, and arbitrage. Market making as an HFT strategy involves the placement of limit orders to sell or buy to earn the bid-ask spread. Ticker tape trading involves the gathering of embedded market data, such as stock prices and the number of shares traded. By observing a flow of quotes, high-frequency trading machines are capable of extracting information that has not yet become news. They then use this information to place orders at a rapid pace. The objective of arbitrage is to make profit from the differ-ence in prices on a security traded in different markets. Certain events surrounding a


security (such as a judicial ruling, a merger, or announcement of a new product) can set off the securitys price up or down. While all investors aspire to generate profit out of these events, high-frequency traders jump on these opportunities more quickly than others.

HFT is frequently equated to algorithmic trading, alternatively known as automated quantitative trading and automated program trading. However, while HFT is a type of algorithmic trading, not all forms of algorithmic trading can be described as HFT. Algorithmic trading predates HFT and has been used extensively as a tool to determine some or all aspects of trading like timing, price, quantity, and venue. For example, the algorithm may be a simple filter or a moving average rule, which may generate buy and sell signals frequently or infrequently. While arbitrage is classified as an HFT strategy, the underlying algorithm may or may not generate buy and sell signals frequently. While the term high-frequency trading is typically associated with computer technology, which is a valid characterization, this does not mean that technology-driven trading is necessarily HFT. Furthermore, HFT is typically confused with the use of technology to execute orders, which gives rise to the concepts of electronic trading, electronic markets, and automated trading, but HFT and electronic trading are two different creatures. For example, Clark (2012) investigates the losses resulting from high-speed trading, but she actually talks about the operational risk and losses resulting from the failure of technology. In a nutshell, HFT may be blamed for things that have nothing to do with it.

8.3.2 HFT as the Cause of the Flash CrashThe flash crash was a brief but dramatic stock market crash when the market (measured by the Dow Jones Industrial Average) experienced its largest ever intra-day point loss in history, only to recover much of the loss within minutes (for a few minutes, $1 tril-lion in market value vanished). Figure 8.3 shows what happened on 6 May 2010 using 10-minute intervals over the time span 10 am4 pm. The market dropped sharply but recovered quickly.

The crash was initiated by Waddell & Reed Financial, a little-known mutual fund. Portfolio managers at Waddell instructed their computers to start an automated program of selling financial contracts that were linked to the DJIA (which is algorithmic trading, not HFT). After almost 5 months of investigation, the Commodity Futures Trading Commission (CFTC) and the US Securities and Exchange Commission (SEC) issued a joint report iden-tifying the causes that set off the sequence of events leading to the flash crash and concluding that the actions of high-frequency traders contributed to volatility during the crash (CFTC and SEC, 2010). The report found that high-frequency traders quickly magnified the impact of the selling by Waddell. This characterization of what happened on 6 May 2010 exhibits several flaws and misinterpretation of HFT. It sounds as if the report was written in such a way as to confirm the preconceived idea that HFT is bad for the market.


The International Organization of Securities Commissions (IOSCO) concludes that while algorithms and HFT technology have been used by market participants to man-age their trading and risk, their usage was another contributing factor in the flash crash (IOSCO, 2011; Jones, 2011). However, there is the opposing view that HFT was not the cause of the flash crash and that it may even have been a major factor in minimizing and partially reversing the flash crash (for example, Corkery, 2010). The CME Group, a large futures exchange, stated that its investigation had not revealed any support for the proposition that HFT was related to the crash of stock index futuresrather it had a market stabilizing effect (CME Group, 2010).

By examining the sequence of events that took place on 6 May 2010, we find that the role of HFT has been grossly overstated. To start with, the crash was initiated by Waddell & Reed Financial, not because they indulged in HFT but because they took a long-term outlook. Their losses were incurred as a result of a computer glitch, so it was an operational loss not a trading-related market loss. A headline of the 2 October 2010 issue of USA Today said massive computer driven sell order triggered May 6 plunge, and that what it was: a computer glitch.

In the CFTCSEC joint report it is concluded without evidence that high-frequency traders quickly magnified the impact of the selling by Waddell. Incidentally,

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Figure 8.3 The DJIA: 10 am4 pm on 6 May 2010.


the joint report puts the blame on automatic computerized traders in one place and on computerized high-frequency traders in another place. Irrespective, the underlying argument is flawed because high-frequency traders sell and then buy, which means that their action could not have exacerbated the effect of the Waddell sales. It would have been caused by the actions of long-term traders who would have sold and stayed out of the market. On the contrary, the market would not have recovered so quickly if it were not for the action of high-frequency traders. It is also unlikely that the actions of diverse high-frequency traders drive stock prices in the same direction, given that they use different algorithms.

The behavior of traders described in the joint report is the exact opposite to that of high-frequency traders. For example, the report says that computerized high-frequency traders exited the stock market, but this is not what high-frequency traders do, it is what long-term traders do. The report also says that high-frequency firms that remained in the market exacerbated price declines because they escalated their aggres-sive selling during the downdraft. Again this is inconsistent with the nature of HFT.

8.3.3 The Alleged Profitability of HFTOne argument against HFT is that it is a license to print money that is owned by a minority of market participants who make certain profit while other traders watch with envy high-frequency traders fill buckets with dollars at a high speed. But we know that there is no free lunch. High-frequency traders work on algorithms to generate buy and sell signals, but there is no guarantee that these algorithms generate profit. Forecasting financial prices and determining the timing of highs and lows are not easy, even for the brightest quantitative brains. The proposition that high-frequency traders are certain winners sounds like suggesting that a gambler who plays on four boxes of a Blackjack table always wins, while a more conservative gambler who plays on one box and skips rounds always loses. This cannot be true because both of these gamblers are subject to the same set of probabilities and the fact that the Blackjack rules favor the casino. Likewise, a high-frequency trader and a long-term trader are subject to the same stochastic behavior of financial prices.5

Kearns et al. (2010) demonstrate that the maximum amount of profit that HFT can make based on TAQ data is $2.13 billion a year. This is a magical figure that is obtained only by the imposition of the implausible assumption that high-frequency traders enter every profitable transaction and nothing else. Likewise, HFT has been shown to have a potential Sharpe ratio (a measure of reward per unit of risk, hence risk-adjusted return) thousands of times higher than the traditional buy-and-hold strategies. Aldridge (2010) reports what she describes as colloquial evidence that HFT is indeed profitable. This

5 Skill is a crucial factor in gambling and financial trading. However, there is no reason why high-frequency traders are more skillful than long-term traders (tell that to George Soros).


evidence, however, is not based on actual data on the profitability of HFT relative to long-term trading because Aldridge admits that hard data on performance of high- frequency strategies is indeed hard to find. Moosa (forthcoming) argues that the measure of profitability used by Aldridge is faulty while the underlying arguments are flawed. We should expect nothing other than the standard deviation associated with a 10-s holding period to be lower than that of a 1-minute horizon.

There is simply no logical reason to suggest that trading more frequently is a recipe for guaranteed profit. On the contrary the practice involves transaction costs, which would reduce profitability. HFT can be more profitable if the trader has a magical for-mula that picks the highs and lows but such a formula is as fictitious as the fountain of youth or the process of converting iron into gold.

8.4 THE HFT DEBATE: AN ASIAN PERSPECTIVE

In evaluating the impact of HFT we find both pros and cons. Pros come in the form of increased liquidity provisioning, narrow spreads, faster and more reliable execution of transactions, and enhanced volumes, suggesting a healthy environment for price formation. Cons come in the form of increased intra-day volatility in some stocks, adverse selection for some market participants, and higher implementation shortfall costs. Conventional institutional trading firms are complaining about the unfair playing field afforded to high-frequency, advanced-technology players. But the reality of the new, evolved electronic trading environment is that the trading rules are now based on technology more than ever. The contrasting views on these points expressed in various Asian forums are examined in this section.

Lee Porter, a Hong Kong-based professional in the financial services industry, is quoted by Ho (2013) as saying that while some high-frequency traders do inject liquidity into the market by acting as market makers, others are almost toxic, because they go in and try to take advantage of any indication in the market that theres a buysell imbalance so that they can trade ahead of it. He describes high-frequency traders as being not fun-damental investors and that they typically dont care that much about the management [of the company] or, for example, its long-term profitability. He adds: as long as they can buy and sell it very, very quickly and make a quick profit, thats all they care about.

Two observations can be made of Porters characterization of high-frequency trad-ers: (i) there is absolutely nothing (ethically or legally) wrong with this trading strategy as described by Porter, and (ii) this characterization does not describe high-frequency traders. George Soros, who is a long-term investor, acts on imbalances, and technical traders are not fundamental investors. Then why is it that only high-frequency traders care about nothing but making profit, irrespective of the fundamentals? Making profit is in the spirit of free-market capitalism, and it is what technical traders (irrespective of frequency) aim for while ignoring fundamentals. During a bubble, all types of investors


(including fundamentalists) keep on buying although the fundamentals indicate that the market is overvalued, as long as they believe that they can sell at profit subsequently. If the implication here is that the good guys act on fundamentals and the bad guys do not, why is it that there is always an outcry against short sellers, who take action only after a thorough investigation of the fundamentals of the underlying company?

Concerns about HFT were raised in a trading and technology conference in Singapore in December 2012 (Ho, 2013). Jonathan Evans, managing director at JP Morgan Asset Management ( Japan), said that trading using super-fast computers does not boost liquidity in the market, adding that it provides no real opportunity to get real liquidity. He also said that its a net taker of liquidity from the market and that high-frequency firms dont hold inventory they dont bring anything to the market and everything is closed out at the end of the day. Another speaker at the conference, Kent Rossiter (head of Asia-Pacific trading at RCM Capital Management), noted that high-frequency trading can paint a false picture of the level of liquidity in the market. According to Lee Porter, high-frequency traders who are in the game solely to make a quick buck and have no intention for market making offer no real value to anyone. He goes on the offensive by arguing that you have to question the value of high-frequency trading when many of these traders are opportunistic, predator-type, trading 10 shares at a time, buying and selling, and buying and selling. He then wonders what value are they providing in the marketplace by buying and selling 10 shares at the click of a finger?

One can respond to these arguments against HFT with another question: what value, if any, is provided by the parasitic financial activity involving $700 trillion worth of over-the-counter derivatives (and this is not the only parasitic financial activity)? Yet another question that can be raised in response is: in what sense are high-frequency traders opportunistic and predatory while long-term investors are not? It was one long-term investor who in the 1990s brought the Central Bank of Thailand and the Bank of England to their knees by taking predatory action. Was what George Soros did wrong? No, because he made huge profit by following the rules, and the rules do not say that you can trade once a month, a week, a day, or a second. Stock markets (and financial markets in general) serve two main purposes: price discovery and the provision of liquidity. We will argue later that HFT does not hinder price discovery and contributes to market liquidity by standing ready to buy and sell.

Some of Porters peers maintain that there is room for HFT. Chris Jenkins, Asia-Pacific managing director at TORA (a registered broker-dealer in Hong Kong and a dark-pool operator), argues that to tar all high-frequency trading as bad is probably inaccurate, even if investors such as buy-side institutions are naturally concerned about the risk of being beaten by super-fast computerized trades. 6 He adds that some high-frequency trading is very relevant, certainly on the lit exchanges, which can benefit

6 The term dark pool refers to the trading volume created by institutional orders that are unavailable to the public. The major part of dark pool liquidity is block trades facilitated away from central exchanges.


from it because it puts liquidity out there. Jenkins argues that liquidity, or the lack of it, has always been an issue in Asia, pointing out that high-frequency traders count for a non-negligible proportion of trading in various markets, which means that they pro-vide a lot of liquidity to not have. Jenkins further argues that regulators sometimes are looking to solve problems that are not necessarily there because the market should be able to cope with a variety of trading stances and parties, whether its slow or fast, mums and dads, hedge funds and so on. Like any other class of traders, he argues, high-frequency traders should be able to engage in the market according to how they want to trade.

Recent findings from an independent research outfit in Australia appear to back Jenkins (see, for example, McCartney, 2012). The Sydney-based Capital Markets Cooperative Research Centre (CMCRC) carried out an empirical study to detect the presence or otherwise of any relationship between HFT and market abuse. Using data from the London Stock Exchange and Euronext Paris over 5 years from 2006 to 2011, CMCRC concluded that HFT does not correlate with an increase in market manipu-lation. Ho (2013) quotes Alex Frino, the CEO of CMCRC, as saying that the debate on high-frequency trading has become almost hysterical in some regions and that its characterized by an excess of opinion and deficit of proof because orders arent tagged as such, you cant look at any one order and say, Thats high-frequency trading. Hence, Frino argues that HFT does not deserve the bad press it has received. In an environment of low returns, everyone is going to be looking for a scapegoat. HFT and its relationship to market fabric is very complex and needs to be analyzed as such before any conclu-sions can be drawn.

Hutchens (2012) quotes Zachary May of the Australian Securities and Investments Commission (ASIC) as saying that market fairness involves the dissemination of infor-mation by market operators that results in a level playing field and that this is different from the provision of non-discriminatory access to special information services which necessarily results in information asymmetry and a two-tiered market. Comerton-Forde (also quoted by Hutchens) responds by saying that theres nothing wrong with the advance of technology, as long as people who wish to pay for it can use it, and that each individual investor has to make a decision on whether its worth investing in that tech-nology to get that advantage. We will come back to this point in the following section.

Ross Smyth-Kirk, the chairman of gold producer Kingsgate Consolidated, is also quoted by Hutchens (2012) as attributing disorderly stock markets to HFT, which exacerbates share price movements, whether up or down. He argues that HFT distorts the market completely, and that the market is no longer about supply and demandrather its about what some machine does in a flick of a second. He goes on to attack academic apologists for saying that HFT boosts liquidity. How does a machine impede the working of supply and demand in a free market? Putting an order to buy a stock represents an increase in demand whether a human being does it once


a week or a machine does it 1000 times a day. It is less obvious how a machine-driven action affects the supply side. As far as liquidity is concerned, it is more intuitive and plausible to suggest that high-frequency traders provide liquidity. Unlike Mr. Smyth-Kirk, academics who claim the HFT boots liquidity back up their claims with reasoning and empirical evidence. But it is not only academics who make such claims. Haigh and Himaras (2012) quote Greg Medcraft, Chairman of ASIC, as saying that I know that some high-frequency trading provides liquidity. Whether or not high-frequency traders provide liquidity is a point that will be discussed in the following section.

8.5 THE HFT DEBATE: A GENERAL PERSPECTIVE

In this section we present the arguments for and against HFT from a general perspective. The arguments are evaluated critically and undermined. We came across some of the points raised in this section when we discussed the Asian views of HFT.

8.5.1 HFT Discourages Market ParticipationThe first argument against HFT came out in an IOCSO survey (IOSCO, 2011). The survey shows that some market participants believe that the presence of high-frequency traders discourages them from participating in the market as they have been put at a disadvantage by the superior technology used to conduct HFT. It is not clear why high-frequency traders have a monopoly over the use of superior technology, while long-term traders still use stone-age technology. This argument is like an airline using propeller planes from the 1950s complaining about competition from an airline with a fleet of modern jets. It sounds like condemning the use of modern technology.

A related but bizarre argument has been put forward by an academic participating in the IOSCO panel sessions, who suggested that HFT participation in the market may lead to an arms race, as market participants compete against one another to possess the fastest and most sophisticated technology, which is very costly. Foucault et al. (2011) provide a rationale for this argument based on the intuitive and logical proposition that HFT requires fixed investment ( hardware, programming, co-location) but generates profit from it. However, they go on to argue that low-frequency traders have to invest in algorithmic trading capacities, which may lead to a situation where investment in HFT might be collectively too high compared to what would be socially optimal. But do low-frequency traders have to follow high-frequency traders and adopt their trading style? This would be the case if HFT is a license to print money, which is a myth as argued earlier. If the proposition put forward by Foucault et al. (2011) is valid then it is equally valid that the use by everyone of PCs as opposed to typewriters and calcula-tors as opposed to slide rules may be too high compared to what would be socially optimal. The regulatory consequence of this line of thinking is that a limit must be imposed on the use of PCs in universities, companies, and government offices, a limit


that guarantees a socially optimal use of PCs. Those expressing views that boil down to condemning the use of technology seem to be unaware of the history of the use of technology in financial trading. Leinweber (2009) discusses a number of episodes in which technological breakthroughs gave special advantage to certain traders.

Some anti-HFT observers argue that since HFT disadvantages long-term investors it may discourage capital market participation and deprive companies from funds or increases the cost of capital. If anything, all market participants have benefited from the dramatic reductions in trading costs and spreads over the past 10 years, mainly attributed to HFT (Smith, 2010). Furthermore, this argument seems to confuse the primary and secondary market functions of the stock market.

8.5.2 Transmission of ShocksAnother argument against HFT, as identified by the IOSCO (2011), is that the grow-ing involvement of automated quantitative trading strategies may also contribute to the transmission of shocks across trading venues for the same product or across markets trading different assets or asset classes. It is not obvious whether this argument makes a distinction between HFT and automated quantitative trading, but the first impression is that it does not. Irrespective, this kind of effect has nothing to do with the frequency of tradingit has something to do with technology. But technology is a catalyst while the main cause for such an effect is market integration, multiple listing and financial liberalization in general. These developments are typically hailed as reform. It follows that in order to condemn HFT we have to condemn technology and financial reform.

8.5.3 Impairing the Price Discovery Function and Enhancing VolatilityThe third argument against HFT is that the very short-term nature of many HFT strategies might move market prices away from fundamental values in the short run and impair the price discovery process that takes place on public and transparent markets. The argument is that HFT distorts price discovery and enhances volatility.

Various studies have reported that HFT reduces volatility and does not pose systemic risk (Smith, 2010; Lambert, 2010; CME Group, 2010). Some empirical studies suggest that HFT has a positive impact on the efficiency of the price discovery mechanism. An important role identified as being performed by HFT firms is that they contribute to price discovery across different trading venues, a function that is particularly important in a fragmented market environment. High-frequency traders process new market information rapidly and embed it into their quotes and orders, changing market prices to reflect this new information as quickly as possible (see, for example, Brogaard, 2010; Hendershott and Riordan, 2011). As for volatility, Brogaard (2010) constructs a hypo-thetical alternative price path that removes high-frequency traders from the market, demonstrating that the volatility of stocks is roughly unchanged when HFT initiated trades are eliminated and significantly higher when all types of HFT trades are removed.


8.5.4 HFT has Adverse Effects on LiquidityThe proposition that HFT has an adverse effect on liquidity is counterintuitive because anyone wishing to sell is bound to find a high-frequency trader wanting to buy, and anyone wishing to buy is bound to find a high-frequency trader wanting to sell. The available evidence fails to find a consistent and significant negative effect of HFT on liquidity (for example, Brogaard, 2010).

8.5.5 The Effect on Market Fairness and IntegrityYet another argument against HFT is that the superior trading capabilities of high-frequency traders may produce an unfair advantage over other market participants, such that the overall fairness and integrity of the market are put at risk. This is a strange argu-mentsince when are markets about fairness? Are not markets about the survival of the fittest? Markets do not operate on altruism, but rather on predatory action and cut-throat competition. This is capitalism at its best (or at worst, depending on the underly-ing view of the world). As long as the rules and regulations are followed and there is a level playing field, there is nothing wrong with adopting one style of trading or another.

8.5.6 HFT May Lead to Abusive PracticesHFT-phobia is partly attributed to the possibility that technological advantage offers HFT firms the possibility of engaging in abusive practices on a larger scale than would have been possible previously. These practices include momentum ignition, spoofing, and layering.7 Again it is not obvious why these malpractices are uniquely associated with HFT. And again if these malpractices are enabled by technology, that does not mean that we should condemn technology.

8.5.7 The Risk of Rogue AlgorithmsYet another source of fear is that heavy reliance on algorithms for trading decisions and execution may pose serious risk when one or more algorithms behave in an unexpected way. This proposition has given rise to the concept of rogue algorithmsthat is, algo-rithms that malfunction and operate in an unintended way. Malfunctioning algorithms, the argument goes, may trigger a chain reaction and, in turbulent market conditions, withdraw liquidity from the market or impair orderly trading. Such risk, it is claimed, is magnified when trading takes place at fractions of a second.

We must distinguish between the algorithms used for trading (that is, generating buy and sell signals) and those used for executing transactions. If a trading algorithm malfunctions,

7 With momentum ignition, a high-frequency trader initiates a series of orders and trades (perhaps while spreading false rumours) in an attempt to ignite a rapid price move either up or down. Spoofing is an abusive practice whereby the use of displayed limit orders are used to manipulate prices. Layering entails stuffing the book with multiple bids and offers at different prices and sizes, generating an enormous volume of orders and high cancelation rates of 90% or more.


the trader will incur lossesthis is not to say that properly functioning algorithms always produce profit. Then why is it always assumed that a malfunctioning algorithm deprives the market of liquidity when it could be the other way round? For a sizeable adverse effect on liquidity and market order, a large number of high-frequency traders must experience mal-functioning algorithms simultaneously and they all initiate liquidity withdrawal. Brogaard (2010) found no evidence indicating that high-frequency traders withdraw from the mar-ket in bad times (if they do, they will not be high-frequency traders). If what we are talking about here is an execution algorithm, then this is pure exposure to operational risk that produces operational losses. Specifically this is the technology risk kind of operational risk.

8.5.8 Divorce from FundamentalsHFT is also portrayed to be the cause of price moves that are unrelated to fundamentals, particularly intra-day moves. The Economist (2012) argues that high-frequency traders are not making decisions based on a companys future prospects. This is not a descrip-tion of high-frequency traders but rather of noise traders. Intra-day moves, even daily moves, are rarely related to fundamentals, if at all. These moves are determined by tech-nical factorsthey happened before the invention of the computer. In general, price moves that are not related to fundamentals are bubbles, and bubbles have been with us since the early history of financial markets, hundreds of years before the computer became a realityeven before the industrial revolution.

8.5.9 The Risk of Short-TermismSmith (2010) describes as the final bogeyman raised by critics [of HFT] the claim that high-frequency traders are simply the latest speculators on Wall Street and that we have to deal with the short-termism of the high-frequency traders before they cause another bubble and subsequent crash. Smith responds by saying that while some kinds of risky speculation are real concerns and should be taken seriously, speculation has nothing to do with high-frequency trading. The global financial crisis was not caused by high-frequency traders but by financial institutions indulging in large bets by taking massive risky and illiq-uid positions. That was long-term speculation. The bubbles and crashes caused by high-frequency traders are temporary and short-lived, unlikely to affect long-term investors.

8.5.10 The Case for Regulating HFTImposing position and profitloss limits on high-frequency traders is problematical and difficult to implement, at least because there is no acceptable definition of HFT, in which case it becomes difficult to identify the subject of regulation. Measures like approvals of algorithms boil down to regulatory capture and perhaps big brotherhood. Regulators do not seem to have learned the lesson that financial institutions cannot be regulated the same way as they are managed. Then who says that regulators have the expertise to evaluate and stress-test algorithms? The bright minds that develop the


algorithms work for high-frequency traders or for themselves, not for regulators. This is the same point made against Pillar 2 of the Basel II accord, which requires regulatory approval of internal models.8

If we examine various HFT strategies we find nothing wrong with them as far as rules and regulations are concerned. There is nothing wrong with the development and utilization of algorithms that make it possible to engage in event and statistical arbitrage. If high-frequency traders wish to utilize these strategies more frequently than down-to-earth traders, then this is a matter dictated by their risk appetites and riskreturn trade-offs. Trying to regulate risk appetites does not sound right and hurts the diversity (hence the liquidity) of the market.

8.6 CONCLUSION

The spread of HFT in Asian markets is underway but progress is slow. One reason is the inadequacy of the financial infrastructure in Asian markets. High-frequency trad-ers execute thousands of trades a second, which means that exchanges are required to process trades in microseconds. They also need to boost the speed with which traders receive market data to feed into their algorithms; however, these upgrades are expensive.

The most important impeding factor is perhaps regulatory concern about the potential adverse consequences of HFT. But the fear of HFT is unfounded. It was only recently that any market crash would have been blamed on short selling. The fashion these days, as popularized by the media, is to blame crashes on high-frequency traders. However, high-frequency traders are informed traders, not cheetah traders. If they are smart enough to utilize modern technology to make money out of frequent trading, there is absolutely nothing wrong with that. They take big risk, so if they make big profit, this is the basic principle of finance of the risk-return trade off. It does not make any sense to argue that HFT should be a specific target for regulators because down-to-earth traders do not make as much money since they are not smart enough to develop profitable algorithms or because they cannot use, or afford, modern technology. Then it is a myth that HFT is always profitableit may be and it may be not. And, contrary to common belief, HFT did not cause the flash crashon the contrary it was high-frequency traders who saved the day as the market recovered very quickly.

Asian regulators should embrace HFT as an activity that has been enabled by supe-rior computer technology. It is a different trading style that is as legitimate as any other. On the contrary, this activity provides liquidity and strengthens the price discovery function. If Asian regulators impede the adoption of this activity by those who wish to do so, Asian markets will be left behind. This is unlikely to happen because the Trading Architecture Asia-WBR survey shows that most participants believe that HFT is an unstoppable force for change influencing all the key players in the trading value chain.

8 On this point see, for example, Moosa (2010, 2011) and Moosa and Burns (2012).


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8 The Regulation of High-Frequency Trading: An Asian Perspective8.1 Introduction8.2 The Growth of HFT in Asia8.3 Some Misconceptions8.3.1 Confusion with Other Activities8.3.2 HFT as the Cause of the Flash Crash8.3.3 The Alleged Profitability of HFT

8.4 The HFT Debate: An Asian Perspective8.5 The HFT Debate: A General Perspective8.5.1 HFT Discourages Market Participation8.5.2 Transmission of Shocks8.5.3 Impairing the Price Discovery Function and Enhancing Volatility8.5.4 HFT has Adverse Effects on Liquidity8.5.5 The Effect on Market Fairness and Integrity8.5.6 HFT May Lead to Abusive Practices8.5.7 The Risk of Rogue Algorithms8.5.8 Divorce from Fundamentals8.5.9 The Risk of Short-Termism8.5.10 The Case for Regulating HFT

8.6 ConclusionReferences

Documents

Handbook of Asian Finance || The Regulation of High-Frequency Trading: An Asian Perspective