HIGH FREQUENCY TRADING
discrepancies in some particular security trading simultaneously on disparate markets. As human trade execution skill will be insufficient, computers with very high speed are used for trading. Directional Strategies: Some ‘directional’ strategies may be looking for transitory pricing errors i.e. price of the underlying that may have temporarily moved away from its ‘fundamental value’. In such a situation, HFT traders establish a position in anticipation that the price relationship will correct itself. Hence, these types of strategies may often contribute to the quality of price discovery.
A variety of market participants employ these types of trading
behaviours and strategies, ranging from firms that execute customer orders to those engaged solely in proprietary trading (whether as a proprietary trading firm that may or may not be a registered broker-dealer, a proprietary trading desk of a multiservice broker-dealer, or a hedge fund). Importantly, many market participants employ HFT-type trading strategies to enhance other market activities – such as market making, customer facilitation and arbitrage ... said to be critical to the functioning of financial markets.
HFT in Commodities Around the middle of October 2011, the CME
size of their quotes. This may result in larger orders having to transact with many small orders and may affect overall transaction costs.
Another interesting issue that gets
a mention in the report is whether HFT contributes to the price formation process on equities markets. In this context, Brogaard (2010) examines a large data set of HFT firms trading on NASDAQ and finds that HFT adds substantially to the price formation process as they tend to follow a price reversal strategy. Hendershott and Riordan (2009) find that algorithmic traders’ quotes play a larger role in the price formation process than human quotes. In terms of market volatility, neither Hendershott and
HFT is a natural evolution of the trading
Group unveiled a range of new services to allow its member firms to trade faster than ever. Last December, the London Metal Exchange launched proximity hosting services for high frequency trading firms. These and other examples underline the increasing desire to cater to the growing HFT requirements and techniques of commodity market participants and to those seeking to diversify their portfolios into a range of new asset classes including commodities. Numerically, according to Aite Group consultancy estimates, high frequency trading in energy futures already accounts for around 15% of all volume at CME. The estimate clearly indicates the inroads that HFT has already made in commodities trading. Moreover, Paul Rowady at the TABB Group expects that HFT volumes will double in energy markets in the next two to three years. This clearly suggests that HFT in commodities is not only here to stay but will rise significantly.4
HFT’s Impact – Empirical Findings Evidence related to the impact of HFT on market quality and
efficiency indicators remains highly inconclusive. A Deutsche Bank research report5
on HFT mentions some studies (e.g.
Hendershott and Riordan, 2009; Jovanovic and Menkveld, 2010; Fabozzi, 2011) suggesting that HFT using market making and arbitrage strategies has added liquidity to the market, reduced spreads and helped align prices across markets. While the report finds no evidence of a negative liquidity impact of HFT in the academic literature, it does highlight the following:
• HFTs are under no affirmative market-making obligation, i.e. they are not obliged to provide liquidity by consistently
displaying high-quality, two-sided quotes. This may translate into a lack of available liquidity, in particular during volatile market conditions.
• HFTs contribute little to market depth due to the marginal
process, enabled by advances in computer and communications technology
Riordan nor Brogaard find any evidence for a detrimental impact of either algorithmic trading or HFT. In another study on HFT, Fabozzi et argue that HFT is a natural
al (2011)6
evolution of the trading process, enabled by advances in computer and communications technology. The authors further conclude that given the short-term nature of HFT and the fact that positions are typically not carried overnight, the potential for market manipulation and creation of bubbles and other nefarious market effects seems to be modest. The authors further state that the problems posed by HFT are more of the domain of model or system breakdown or cascading (typically downward) price movements as high frequency traders withdraw liquidity from the markets. Cartea and Penalva (2010)7
attempt to measure socially valuable liquidity generated by HFT as against that mandated by market makers. They contend that HFTs generate additional microstructure noise at smaller intervals and accelerates market transactions. This brings about several questions on how the
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