Classification of High-Frequency Strategies - Singapore Forex Trading, Singapore Forex Academy, Singapore Forex Association

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Classification of High-Frequency Strategies

1. Automated liquidity provision
Quantitative algorithms for optimal pricing and execution of market-making positions
Typical holding period: <1 minute

2. Market microstructure trading

Identifying trading party order flow through reverse engineering of observed quotes
Typical holding period: <10 minutes

3. Event trading
Short-term trading on macro events
Typical holding period: <1 hour

4. Deviations arbitrage
Statistical arbitrage of deviations from equilibrium: triangle trades, basis trades, and the like
Typical holding period: <1 day

Many successful high-frequency strategies run on foreign exchange, equities, futures, and derivatives. By its nature, high-frequency trading can be applied to any sufficiently liquid financial instrument.

A “liquid instrument” can be a financial security that has enough buyers and sellers to trade at any time of the trading day.

High-frequency trading strategies can be executed around the clock. Electronic foreign exchange markets are open 24 hours, 5 days a week. U.S. equities can now be traded “outside regular trading hours,” from 4 A.M. EST to midnight EST every business day. Twenty-four-hour trading is also being developed for selected futures and options.

Many high-frequency firms are based in New York, Connecticut, London, Singapore, and Chicago. 

Many Chicago firms use their proximity to the Chicago Mercantile Exchange to develop fast trading strategies for futures, options, and commodities. 

New York and Connecticut firms tend to be generalist, with a preference toward U.S. equities. 

European time zones give Londoners an advantage in trading currencies, and Singapore firms tend to specialize in Asian markets. 

While high-frequency strategies can be run from any corner of the world at any time of day, natural affiliations and talent clusters emerge at places most conducive to specific types of financial securities.

The largest high-frequency names worldwide include Millennium, DE Shaw, Worldquant, and Renaissance Technologies. 

Most of the highfrequency firms are hedge funds or other proprietary investment vehicles that fly under the radar of many market participants. 

Proprietary trading desks of major banks, too, dabble in high-frequency products, but often get spun out into hedge fund structures once they are successful.

Developing high-frequency trading presents a set of challenges previously unknown to most money managers. 

The first is dealing with large volumes of intra-day data. Unlike the daily data used in many traditional investment analyses, intra-day data is much more voluminous and can be irregularly spaced, requiring new tools and methodologies. 

As always, most prudent money managers require any trading system to have at least two years worth of back testing before they put money behind it. Working with two or more years of intra-day data can already be a great challenge for many. Credible systems usually require four or more years of data to allow for full examination of potential pitfalls.

The second challenge is the precision of signals. Since gains may quickly turn to losses if signals are misaligned, a signal must be precise enough to trigger trades in a fraction of a second.

Speed of execution is the third challenge. Traditional phone-in orders are not sustainable within the high-frequency framework. The only reliable way to achieve the required speed and precision is computer automation of order generation and execution. 

Programming high-frequency computer systems requires advanced skills in software development. 

Run-time mistakes can be very costly; therefore, human supervision of trading in production remains essential to ensure that the system is running within prespecified risk boundaries. Such discretion is embedded in human supervision. 

However, the intervention of the trader is limited to one decision only: whether the system is performing within prespecified bounds, and if it is not, whether it is the right time to pull the plug.

From the operational perspective, the high speed and low transparency of computer-driven decisions requires a particular comfort level with computer-driven execution. 

This comfort level may be further tested by threats from Internet viruses and other computer security challenges that could leave a system paralyzed.

Finally, just staying in the high-frequency game requires ongoing maintenance and upgrades to keep up with the “arms race” of information technology (IT) expenditures by banks and other financial institutions that are allotted for developing the fastest computer hardware and execution engines in the world.

Overall, high-frequency trading is a difficult but profitable endeavor that can generate stable profits under various market conditions. 

Solid footing in both theory and practice of finance and computer science are the normal prerequisites for successful implementation of high-frequency environments. 

Although past performance is never a guarantee of future returns, solid investment management metrics delivered on auditable returns net of transaction costs are likely to give investors a good indication of a high-frequency manager’s abilities.