High Frequency Trading & The Case For Emerging Markets


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The increasing competition in HFT among hedge funds and other market participants will inevitably reduce alpha opportunities in developed markets and cause hedge funds to focus more on emerging markets that are less efficient.

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High Frequency Trading & The Case For Emerging Markets

  1. 1. Mark J. Finn – mark@finsight.net 1/7The Effect of HFT on Markets:Introduction:The rise of computer technology and the internet has led to an explosion in “High Frequency Trading” (HFT).Traditionally, market participants would place orders individually, or through a broker. There was little automation inthe process and it was very much dependent on the time it took a human to place and execute an order. The increasingadoption of computer power to automate this process has resulted in a rapidly reduced order execution time. Althoughnot an exact application of Moore’s law (that transistor counts double every year), it is clear that reduction of executiontime is accelerating each year.1 A report by the SEC into the “Flash Crash” of May 6, 2010 found that the average speedof execution for small immediately executable orders had fallen from 10.1 seconds in January 2005 to 0.7 seconds inOctober 2009.2 This has ultimately led to HFT becoming a dominant influence on US capital markets, accounting for over70% of dollar volume trade.3This paper seeks to explore the impact of HFT on the market itself. There is a growing body of literature which hasanalysed the effect of HFT on price discovery and volatility. Although it is broadly accepted that HFT results in greaterliquidity and market quality overall, there is contradictory evidence regarding its effect on volatility. Naturally, theimpact of this form of trading also has an impact on market participants, traders and hedge funds. It is contended thatthe inevitable continuation and acceleration of HFT will reduce the opportunities for alpha generation in establishedmarkets and cause hedge funds and other alpha seekers to focus more on emerging markets.What is HFT?Despite the rapid growth of HFT there is no clear, all-encompassing definition. Distinctions have been made betweenalgorithmic trading and HFT,4 although for the purposes of this paper, they are used interchangeably as they are bothcomputer driven.Commonly agreed upon characteristics of HFT are that investments are “held for very short periods of time and typically(but not necessarily) positions are not carried overnight.” Below are a number of definitions provided in academic andregulatory literature:  High frequency traders are professionals acting in a proprietary capacity and able to generate a large number of trades per day - U.S. Securities and Exchange Commission (SEC)5  HFT is a form of trading that leverages high-speed computing, high-speed communications, tick-by-tick data, and technological advances to execute trades in as little as milliseconds. A typical objective of high frequency traders is to identify and capture (small) price discrepancies present in the market. They do so with no human intervention, using computers to automatically capture and read market data in real-time, transmit thousands of order messages per second to an exchange, and execute, cancel, or replace orders based on new information on prices or demand. High Frequency Trading – Methodologies and Market Impact6  High-frequency trading firms deploy fully automated trading strategies across one or more asset classes which identify and profit from short-term (e.g., intra-day) price regularities. HFT strategies try to earn small amounts of money on each trade—often just a few basis points, and the small profits from individual trades are amplified by high trading volume. The Effect of High-Frequency Trading on Stock Volatility and Price Discovery7Hedge Funds & HFTThe origin of classical economics is that an invisible hand determines market prices and those market prices follow arandom walk.8 The underlying premise of this school of thought is that everyone reacts in the same way to marketevents. As news events are typically random and unpredictable, it follows that market movements are also random andthus unpredictable.9
  2. 2. Mark J. Finn – mark@finsight.net 2/7HFT, however, assumes that market participants are not homogeneous and do not react to market events in thesame way. They have defined characteristics which influence their behaviour. Proponents of HFT claim that marketparticipants exhibit two key properties that ultimately results in heterogeneous pricing and trading activity. Firstly,market participants have differing degrees of risk aversion and secondly, they have different time horizons for holdinginvestments. The second point is arguably the cornerstone of high frequency trading (as opposed to other algorithmictrading that seeks to exploit fundamental pricing inefficiencies) which generates alpha by reacting to market events (i.e.news) faster than other market participants.Broadly, high frequency trading assumes that there are market participants that do not follow the market on anintraday basis. The consequence is that there is a time lag between market events and the ability, or willingness, of thelonger term traders to react to the new information. This phenomenon allows hedge funds to profit by reacting quickerto information, which essentially pre-empts trades from market participants that have a longer term trading horizon.Hedge funds employing HFT techniques are essentially trying to identify the ‘visible hand’ that operates as aconsequence of differing characteristics of market participants. One of the most successful hedge funds that harnessHFT is Renaissance Technologies. Renaissance have been able to generate compound returns in excess of 30 per annumfor over 20 years by exploiting mathematical relationships that can be deduced from trading activity in liquid markets.10As HFT techniques become more advanced, however, the lag times required for market participants to ‘digest’information will become shorter and lead to a more ‘efficient’ market. The corollary of this, however, is that the abilityto generate alpha from HFT will require greater and greater investment which will ultimately reach a point where theability to generate alpha does not offset the investment required. This will inevitably lead to hedge funds targetingemerging markets that are not as efficient.Impact on Markets:There is a growing body of academic literature on the effect of HFT on price discovery and volatility. Although there is ageneral consensus that HFT leads to greater liquidity and market quality overall, its effects are not always clear. Thissection of the paper canvasses the dominant views on the effects of HFT on price discovery and volatility. It alsoprovides a brief overview and analysis of the events surrounding the ‘Flash Crash’ of May 6, 2010.Price Discovery:Analyzing the effect of high frequency trading on price discovery in markets is inherently difficult because it requires thecomparison of an actual outcome with a hypothetical one. The general view however, is that HFT trading impoundsinformation faster than traditional trading, 11 which all else equal should lead to a more ‘efficient’ market. It also bringsliquidity to the market (evidenced through higher volumes and narrowed bid-ask spreads)12, which can allow othermarket participants to more easily adjust their portfolios to reflect their fundamental views on the company’sperformance. HFT should therefore, reduce transaction costs and drive market prices to converge to their intrinsicvalues.13This analysis is, however, somewhat paradoxical as HFT is not necessarily driven by fundamentals; it is driven bydiscrepancies in market participants and their reactions to news. Because of the indifference to fundamental value, HFTcan lead to a stock trading 400 million units at a price of $5 or $10. Trades occur irrespective of the fundamental valueof the stock, which obviously has a distorting effect on true price discovery. Terry Hendershott from the University ofCalifornia observed that “if you consider the actual price as having fundamental information plus noise, high frequencydata has no long-term fundamental information, but HFT can help get short-term information into prices faster.”14An interesting consequence of HFT is that its increasing application will ultimately eliminate opportunities for alphageneration. Naturally, this implies that it must have a positive effect on price discovery and improving market quality asmispricings are quickly eliminated. As trading speeds approach a natural or physical limit (as trading can never beinstantaneous in the absolute sense), high frequency traders will no longer be able to exploit the different investment
  3. 3. Mark J. Finn – mark@finsight.net 3/7(and reaction) profiles of market participants. This is why the application of HFT will inevitably shift toward emergingmarkets where trading speeds have not reached a natural / physical limit.Some commentators have argued that although HFT tends to reduce bid offer spreads, the interaction with largefundamental investors could also create price momentum or reversal.15 If a large fundamental investor placed a tradethat had an effect on the market price, high frequency momentum traders could follow the investors position (or evenfront-run) leading to a potential amplification of the initial trade and a deviation away from the theoretical long termvalue. Despite the potential for distorting effects on price discovery, it is however, generally accepted that pricediscovery is improved by competition and automation.16VolatilityPerhaps as a result of the conflicting forces affecting price discovery, there appears to be no clear relationship betweenHFT and volatility. Although there is a large body of academic research that suggests HFT does not increase volatility(but actually decreases it), there are a number of recent papers and empirical examples to the contrary. The mostprominent empirical example that suggests a positive correlation between HFT and volatility was the ‘Flash Crash’ ofMay 6, 2010. A survey conducted in the June 2010, showed that over 80 per cent of US retail advisors believed that thecrash was due to an “overreliance on computer systems and high-frequency trading”.17Jonathan Brogaard is one academic who contends that HFT does not have a statistically positive effect on volatility. Inhis paper “High Frequency Trading and Its Impact on Market Quality”18, Brogaard presents the results of a regression ofvolatility against volume for 120 US stocks over five days with 10 second price point intervals. The results actuallysuggested that there was a statistically significant negative relationship between the two when volatility is thedependent variable (implying the HFT does not, in and of itself, cause greater volatility). To validate the results, he alsoestimated what the price impact would have been if there were no HFT demanding or supplying liquidity. Based on hisestimates, only one stock’s volatility would not be reduced if HFT were not in the market (essentially meaning that theother 119 would exhibit increased volatility if HFT were absent). From these results, Brogaard concluded that HFT leadsto “lower volatility” and that it plays “a very important role in price efficiency and the price discovery process”.Interestingly, Brogaard also points out that high frequency traders make more money in volatile times, suggesting asignificantly positive correlation between volatility and volume when volume is the dependent variable. The problem ofendogeneity in the results, however, makes it difficult to accept the conclusion that HFT tends to reduce volatility.The contrary (and most prevalent view empirically) is, however, that HFT increases volatility. In the paper “The Effect ofHigh-Frequency Trading on Stock Volatility and Price Discovery”19, Frank Zhang argues that there are at least threereasons why the interaction between HFT and fundamental investors can lead to increased volatility.20 The threereasons are outlined below: 1. High trading volume generated by HFT is not necessarily a reliable indicator of market liquidity, especially in times of significant volatility. The automated execution of large orders by fundamental investors, which typically use trading volume as the proxy for liquidity, could trigger excessive price movement, especially if the automated program does not take prices into account. 2. HFT is often based on short-term statistical correlations among stock returns. A large number of unidirectional trades can create price momentum and attract other momentum traders to the stock, a practice that amplifies price swings and thus increases price volatility. Positive feedback investment strategies may therefore result in excess volatility even in the presence of rational speculators 3. High frequency traders detect and front-run large orders by institutional investors, a practice that pushes the stock price up (down) if institutional investors have large buy (sell) orders, thereby increasing stock price volatility.
  4. 4. Mark J. Finn – mark@finsight.net 4/7In a paper released on the 19th of August, 2011, Victor Marinez and Ioanid Rosu21 expressly acknowledged thatthere is disagreement between market participants and academics on the effect of HFT on volatility. In addressing theissue, they provided an alternative model of the phenomenon by assuming that high frequency traders are informedtraders and that they do not take directional bets. Rather, they act in response to a continuous stream of news that hasvarying degrees of precision. They show (through the application of a mathematical model) that in the presence of newsHFTs generate “most of the volatility and trading volume in the market”. Where the degree of precision in news ishigher, the contribution of the informed HFTs is greater to volatility, largely because they do not take directional bets. Ina news rich world where HFTs typically only hold short positions, it is therefore expected that the presence of HFT willtend to increase volatility. This effect is again a consequence of the co-existence of market participants who havediffering investment horizons.Flash CrashPerhaps the most apt case study of the potential effect HFT on volatility is the Flash Crash. On the 6th of May, 2010, USstock market and futures indices experienced a sudden drop of around 5% in 30 minutes. As there was no clearexplanation at the time, many market participants, analysts and commentators concluded that it was driven byautomated HFT. On the 11th of August 2010, a number of high profile asset management companies and marketintermediaries suggested that the nature of electronic market place was such that the event could easily occur.In the time that has passed since the crash, however, no conclusive answer has been provided for its cause, despitesignificant research and investigation. After studying the events of the day, along with the subsequent SECinvestigations, one group of academics released a paper addressing the causes and the involvement of HFT.22 Theirconclusion was that although there was a larger than normal amount of HFT on the day, it was caused primarily by alarge fundamental selling program that did not have sufficient corresponding demand for prices to remain stable. Theyargued that the HFTs most likely bought large portion of the initial stock from the fundamental sellers, but as they donot typically hold inventory for that long, and trade on the markets direction, they sold in line with the broader market.The reversal was also largely attributed to fundamental investors who formed the view that prices had fallen belowtheir intrinsic values. They concluded that “irrespective of technology, markets can become fragile when imbalancesarise as a result of large traders seeking to buy or sell quantities larger than intermediaries are willing to temporarilyhold.”23 Interestingly, their analysis of the actual events shows that it is not HFT that causes volatility in its own right,but its potential interaction with differing (i.e. fundamental) investors.Conclusion:HFT now represents a significant portion of trading in US markets, as well as other developed markets around theworld. The rise of HFT is driven by a belief that markets are not perfectly efficient and that differences in marketparticipants, particularly in risk appetite and investment horizon, create opportunities to generate alpha. Hedge fundshave invested heavily in computer technology to gain a trading edge in responding to news and compete aggressively toexploit. Despite their competitive short term edge, fundamental investors still make up a large portion of overall volumeand have a significant effect on the market. The co-existence of the two can lead to excessive volatility, as was evidencein the Flash Crash. Although many market participants and commentators consider HFT to be the cause of excessivevolatility, the academic and empirical evidence is inconclusive. There are varying views of the effects of HFT on pricediscovery and volatility, however, it is generally accepted that because markets are not purely efficient, circumstancescan arise that are conducive to extreme volatility. The increasing competition in HFT among hedge funds and othermarket participants will inevitably reduce alpha opportunities in developed markets and cause hedge funds to focusmore on emerging markets that are less efficient.
  5. 5. Mark J. Finn – mark@finsight.net 5/7Bibliography:* The paper referred directly to the following academic papers. Specific references are provided in the endnotes. 1. Álvaro Cartea and José Penalva, “Where is the value in High Frequency Trading?”, Banco De Espana, 2011 2. Kirilenko, Kyle, Samadi, Tuzun, “The Flash Crash: The Impact of High Frequency Trading on an Electronic Market”, 18 Jan 2011 3. X Zhang, “The Effect of High-Frequency Trading on Stock Volatility and Price Discovery”, Nov 2010 4. Olsen, “High frequency finance the hedge fund category of the future”, 2001. 5. Fabozzi, Focardi, Jonas, “High-Frequency Trading: Methodologies and Market Impact”, 2010 6. Jonathon Brogaard, “High Frequency Trading and its impact on market quality”, 16 Jul 2010 7. Victor Martinez and Ioanid Rosu, “High Frequency Traders, News and Volitlity”, 19 Aug 2011
  6. 6. Mark J. Finn – mark@finsight.net 6/7APPENDIX:* HFT Literature Review – June 2011 (provided for information purposes only)Paper Data Set Key FindingsAngel, Harris, Spatt U.S. equities, 1993 – Trading costs have declined, bid‐ask spreads have"Equity trading in the 21st 2009 narrowed and available liquidity has increasedcentury" - February 2010RGM Advisors “Market Efficiency U.S. equities, Bid-ask spreads have narrowed, available liquidity hasand Microstructure Evolution in US 2006-2010 Increased and price efficiency has improvedEquity Markets: A High FrequencyPerspective” -October 2010Credit Suisse “Sizing Up US U.S. equities, Bid-ask spreads have narrowed, available liquidity hasEquity Microstructure” - April 2003-2010 increased and short term volatility has declined2010Saar Hasbrouck: Full NASDAQ order Low latency automated trading was associated with‘Low-Latency Trading’ - book lower queated and effective spreads, lower volatilityMay 2011 June 2007 to Oct 2008 and greater liquidityRiordan Hendershott, Deutsche Automate trades made prices more efficient and did‘Algorithmic Trading and Börse equities, Jan not contribute to higher volatilityInformation’ – Aug 2009 2008Brogaard "High HFT vs. other trades. HFT helped to narrow bid-ask spreads, improved priceFrequency trading and its impact U.S. equities on Nasdaq discovery and may have reduced volatilityon market quality" - 2008 – 2010August 2009Chaboud, Hjalmarsson, Vega and EBS forex market Automated trades increased liquidity and may haveChiquoine, 2006-07 lowered volatility‘Rise of the Machines: AlgorithmicTrading in the Foreign ExchangeMarket’ -Oct 2009Hendershott, Riordan HFT vs. other trades. HFT trades were positively correlated with permanent“High Frequency Trading and U.S. equities on price changes and negatively correlated with transitoryPrice Discovery” (working paper) Nasdaq, various price changes, suggesting that HFT periods in Improves price discovery 2008 – 2010Jarnecic, Snape HFT vs. other trades. HFT improved liquidity and was unlikely to have"An analysis of trades by high LSE equities, April - increased volatilityfrequency participants on the June, 2009London Stock Exchange".June 2010
  7. 7. Mark J. Finn – mark@finsight.net 7/7CME Group "Algorithmic trading Automated vs. other Automated trading was associated with improvedand market dynamics", trades. CME futures, liquidity and reduced volatilityJuly 2010 May 2008 - May 2010Menkveld Dutch equities traded A single high frequency trader played an“High Frequency Trading and the On Chi-X and Euronext, Important role in the development of a competitiveNew-Market Makers”, 2007 market center, resulting in better liquidity and lowerApril 2011 trading costsHendershott, Jones, Menkveld Automated quoting Automated trading narrowed bid--‐ask spreads,“Does Algorithmic Trading Improve facility, NYSE equities, lowered trading costs, and improved price efficiencyLiquidity?”, February 20032011Riordan, Storkenmairm Xetra high--‐speed Higher system speeds led to increased liquidity and“Latency, Liquidity and Price trading system, improved price discoveryDiscovery”, 2009 Deutsche Börse, 2007Hendershott, Moulton NYSE TAQ database Introduction of automation via the NYSE hybrid system“Automation, Speed and Stock plus others, June 1, improved price discovery and made prices moreMarket Quality: The NYSE’s 2006 – May 31, 2007 efficientHybrid”, February 2010Gomber, Arndt, Lutat, Uhle Various Survey paper that highlights beneficial aspects of HFT,“High-Frequency Trading”, while noting that perceived problems are largely aMarch 2011 result of U.S. market structureREFERENCES:1 Álvaro Cartea and José Penalva, “Where is the value in High Frequency Trading?”, Banco De Espana, 20112 Kirilenko, Kyle, Samadi, Tuzun, “The Flash Crash: The Impact of High Frequency Trading on an Electronic Market”, 18 Jan 20113 X Zhang, “The Effect of High-Frequency Trading on Stock Volatility and Price Discovery”, Nov 20104 Ibid.5 Securities and Exchange Commision Papers, 17 CFR PARTS 240 and 249, 2011.6 Fabozzi, Focardi, Jonas, “High-Frequency Trading: Methodologies and Market Impact”, 20107 X Zhang, “The Effect of High-Frequency Trading on Stock Volatility and Price Discovery”, Nov 20108 Olsen, “High frequency finance the hedge fund category of the future”, 2001.9 Ibid.10 Ibid.11 Ibid.12 X Zhang, “The Effect of High-Frequency Trading on Stock Volatility and Price Discovery”, Nov 201013 Ibid.14 Fabozzi, Focardi, Jonas, “High-Frequency Trading: Methodologies and Market Impact”, 201015 X Zhang, “The Effect of High-Frequency Trading on Stock Volatility and Price Discovery”, Nov 201016 Literature Review (as provided in appendix).17 Kirilenko, Kyle, Samadi, Tuzun, “The Flash Crash: The Impact of High Frequency Trading on an Electronic Market”, 18 Jan 201118 Jonathon Brogaard, “High Frequency Trading and its impact on market quality”, 16 Jul 201019 X Zhang, “The Effect of High-Frequency Trading on Stock Volatility and Price Discovery”, Nov 201020 Ibid.21 Victor Martinez and Ioanid Rosu, “High Frequency Traders, News and Volitlity”, 19 Aug 201122 Kirilenko, Kyle, Samadi, Tuzun, “The Flash Crash: The Impact of High Frequency Trading on an Electronic Market”, 18 Jan 201123 Kirilenko, Kyle, Samadi, Tuzun, “The Flash Crash: The Impact of High Frequency Trading on an Electronic Market”, 18 Jan 2011