From the September 01, 2011 issue of Futures Magazine • Subscribe!

HFT: How fast can you really trade?

Over the past two years, public debate has increased on whether to regulate the maximum frequency of trading. The idea of regulation stems from a perception that the so-called high-frequency traders can move in and out of positions in milliseconds, “flipping” capital from one stock to another using market orders before the wider population of traders barely can blink. This perceived high speed of trading has been thought by some to disadvantage traders without access to high-speed technology, and regulators have been called in to level such inequalities.

The “frequency” in high-frequency trading (HFT) refers to the number of times a trader or a computer program places a trading order within a certain period of time. The higher the trading frequency, the shorter the time duration between orders. In the popular press, high-frequency trading often is described as moving money in and out of positions within milli- and micro-seconds. Traders who are registered market makers are allowed to place simultaneous buy and sell orders on both sides of the market price, and may get “hit” within a tiny fraction of a second, regardless of whether the traders are human or automated. As this article shows, however, market participants that are not registered market makers generally are prevented from profitably trading at frequencies faster than 1 second by structure of the markets.

A trader who is not a registered market maker is generally disallowed from placing simultaneous bids and offers on the same security at the same time. Instead, this trader is typically limited to a sequential trading pattern: A buy followed by a sell, followed by a buy, etc. Independent of trading frequency, the key to profitability in such sequential trading is to buy at a low price, on average, and to sell at a higher average price, whether using limit or market orders.

While there has been quite a bit of talk about high-frequency traders trying to detect underlying trading algorithms, such as iceberg orders and stops, and then front-run those orders, the main activity of HFT is speed. While some such algorithms exist, the majority of high-frequency traders are making a bet like everyone else and attempting to gain an edge through speed. These players are closest to the old floor local scalpers who constantly would attempt to buy on the bid and sell on the offer. Doing this, however, is not an easy proposition. If you manage to get an edge on one end, you are not guaranteed a profit. The main challenge at high frequencies is to overcome the bid-ask spread and the transaction costs that can be large relative to market moves. For a trader to profit within a specific time interval in the presence of transaction costs and the absence of liquidity rebates, the maximum best bid achieved during the time interval has to rise above the minimum best offer registered during the same interval, generating a profit potential. If the trader is acting on perceived order flow, it is more likely that he is attempting to buy the offer before or as it goes bid and then take his chances on the ability to sell on the offer. So he is acting on the same information as everyone else — rather than having an information advantage — and trying to beat everyone else with speed.

The case of the best bid exceeding the best offer during a trading interval does not guarantee profitability, but is just a minimum condition for a possible success. Discerning whether the markets are about to move up or down is the key to profitability and a true test of the trader’s analytical abilities. However, regardless of how well the trader can predict future price movements, if the markets do not move within a certain time interval, the non-market-making trader cannot profit.

The times when the best bid rises above the best ask in a very short interval are few and far between, as Table 1 illustrates. As Table 1 shows profitably “flipping” in and out of a trading position at ultra-high frequencies is much more difficult than it is at lower frequencies on an example of three commonly traded near-term currency futures on a randomly picked trading day, May 25, 2011. Table 1 shows one of the most liquid futures, euro FX, had moved either up or down by more than the spread in only 10.8% of 15-second intervals throughout the day. That is, in nearly 90% of the time from 9 a.m. to 4 p.m. no high-frequency trader facing positive transaction costs had a chance of profiting at 15-second intervals. At higher-frequency intervals, the situation looked even worse: The price of euro FX futures cleared the spread less than 0.1% of all 1-second time slots, with 99.9% of time leaving no chance to any high-frequency trader.

Table 1: For each frequency, the table presents the percentage of time during the 9AM-4PM EST trading session that the best-bid exceeded the best-ask during a period of the specified frequency, recorded on May 25. 2011.

Frequency

Proportion of time intervals where max best bid exceeds min best offer

CAD futures, Sept 2011

JPY futures, June 2011

EURO futures, Sept 2011

10 minutes

100.0%

100.0%

100.0%

5 minutes

80.7%

91.5%

100.0%

45 seconds

13.2%

35.6%

48.6%

15 seconds

0.8%

9.8%

10.8%

1 second

0.0%

0.2%

0.08%

200 milli-seconds

0.0%

0.0%

0.01%

The observed lack of profitable opportunities at narrow time intervals is not an arbitrary happenstance, but rather a function of the speed with which markets move. Table 2 and Table 3 document the average number of times bid and ask quotes change in the given time period. Most/ask quotes of shown currency futures did not change even once during time periods of 1 second and under, rendering profitable non-market-making trading at such frequencies nothing but impossible.

Table 2: Average number of times best-bid of selected currency futures changed during a given time interval from 9 a.m. ET to 4 p.m. ET on May 25. 2011.

Frequency

Average number of times best bid moved within the time interval.

CAD futures, Sept 2011

JPY futures, June 2011

EUR futures, Sept 2011

10 minutes

100.0

25.9

170.5

5 minutes

51.7

34.7

87.7

45 seconds

8.2

5.3

13.7

15 seconds

3.1

1.9

5.0

1 second

0.5

0.2

0.6

200 mille-seconds

0.3

0.1

0.4

Table 3: Average number of times best-ask of selected currency futures changed during a given time interval from 9 a.m. ET to 4 p.m. ET on May 25, 2011.

Frequency

Average number of times best offer moved within the time interval

CAD futures, Sept 2011

JPY futures, June 2011

EUROFX futures, Sept 2011

10 minutes

105.1

70.2

163.4

5 minutes

54.3

36.1

84.2

45 seconds

8.6

5.5

13.1

15 seconds

3.2

2.0

4.7

1 second

0.5

0.2

0.6

200 mille-seconds

0.3

0.1

0.4

The frequency of trading is dependent on the size of the minimum bid-ask spread, as that is often the biggest cost in non-market-making strategies. The maximum frequency of portfolio allocation also is linked tightly with the volatility of the market and the security: Wilder market oscillations increase the number of short-term periods where the best-bid may overcome the best-offer. Days with higher market volatility are naturally more conducive to higher trading frequencies.

Irene Aldridge is a quantitative portfolio manager, investment consultant and managing partner at ABLE Alpha Trading, LTD. She is also the author of “High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems.” Irene’s research on properties of high-frequency data applicable to portfolio management of HFT strategies is forthcoming in “Equity Valuation and Portfolio Management” (F. Fabozzi and H. Markowitz, eds.). She also teaches a course in high-frequency trading. To learn more, you can reach her at ialdridge@ablealpha.com.

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