High-Frequency Trading

Once upon a time trading in stocks, securities, commodities, etc. was done on the ‘exchange floor’. Back then, ‘trading’ was a fairly straight-forward affair. Buyers and sellers gathered on exchange floors and heckled with each other until they struck a deal. Those were the heady days of power, pressure and sentiments. However, trading on the exchange floor had its own limitations and the trading practices were plagued with malpractice.

In case you have never had the chance to see how trading took place in the olden days or experience it, check these movies — English movies — Trading Places, Wall Street, Hindi movie — Guru.

By mid-nineties, computers and technology started gaining prominence. The ability of a computerised system, to flawlessly execute transactions, match buy and sell orders, etc., was growing exponentially. Then, in 1998, the Securities and Exchange Commission authorised electronic exchanges to compete with marketplaces like the New York Stock Exchange. The basic intent was to open markets to anyone with a desktop computer and a fresh idea. This objective was achieved largely.

Apparently, (as per data published by NYSE and other public sources) between 2005 and 2009 the trading volume (on the NYSE) grew about 164%. News reports have credited HFT for a large part of this meteoric rise. As a matter of fact, there are some who say that in the United States (US), while high-frequency trading firms represent 2% of the approximately 20,000 firms operating, they account for 73% of all equity orders volume. Currently, it is estimated that HFT trades account for 56% of all equity order volumes in the US, 38% of trades in Europe and 5-10% of trades executed in Asia.

Making money out of thin air

HFT became most popular when exchanges began to offer incentives for companies to add liquidity to the market. For instance, some exchanges have a group of liquidity providers called supplemental liquidly providers (SLPs), which attempt to add competition and liquidity for existing quotes on the exchange. As an incentive to the firm, the exchange pays a fee1 or rebate for providing the said liquidity. Rumour has it that the SLP was introduced following the collapse of Lehman Brothers in 2008, when liquidity was a major concern for investors.

High-frequency traders also benefit from competition among the various exchanges, which pay small fees that are often collected by the biggest and most active traders — typically a quarter of a cent per share to whoever arrives first. Those small payments, spread over millions of shares, help high-speed investors profit simply by trading enormous numbers of shares, even if they buy or sell at a modest loss.

HFT made simple

HFT is a program trading platform that uses powerful computers to transact a large number of orders at very fast speeds. HFT uses complex algorithms2 to analyse multiple markets and execute orders based on market conditions. Typically, the traders with the fastest execution speeds will be more profitable than traders with slower execution speeds.

Powerful algorithms — ‘algos,’ in industry parlance — execute millions of orders a second and scan dozens of public and private market-places simultaneously. They can spot trends before other investors can blink, changing orders and strategies within milliseconds.

Basic mechanics

The mechanics of such systems coupled with complex algorithms are not standardised. Conceptually, the design may be broken down as follows:

•     The data stream unit i.e., the part of the systems that receives data e.g., quotes, news, etc., from external sources.

•     The decision or strategy unit

•     The execution unit.

These systems are very intelligent and make use of social networks, scanning or screening technologies to read posts of users and extract human sentiment which may influence the trading strategies.

Characteristics of a HFT system

HFT can be characterised as under:

•     It uses computerised algorithms to analyse incoming market data and implement trading strategies;

•     HFT trading strategies are for investment horizons of less than one day. The primary game plan is to unwind all positions before the end of each trading day. An investment position is held only for very brief periods of time i.e., from seconds to hours. The system rapidly trades into and out of those positions, sometimes thousands or tens of thousands of times a day;

•     At the end of a trading day there is no net investment position. Since they must finish the day flat, HFTs exhibit balanced bi-directional (i.e., ‘two-way’) flow. It is argued that due to this feature HFTs can’t accumulate large positions.

•     HFTs can’t deploy large amounts of capital, infact, HFTs have little need for outside capital or leverage, and tend to be proprietary traders. In theory, HFTs can’t ‘blow up’ (they don’t use much leverage, and don’t have much capital, so they can’t lose much capital!);

•     Generally employed by proprietary firms or on proprietary trading desks in larger, diversified firms;

•     It is very sensitive to the processing speed of markets and of the traders own access to the market;

•     Positions are taken in equities, options, futures, ETFs, currencies, and other financial instruments that can be traded electronically;

•     High-frequency traders compete on a basis of speed with other high-frequency traders, not (supposedly) the long-term investors (who typically look for opportunities over a period of weeks, months, or years), and compete for very small, consistent profits;

•     HFT is a very low-margin (low-risk, low-reward) activity;

•     Theoretically speaking, HFTs follow a Gaussian (Normal) distribution. Their logic is simple i.e., large expected returns are rare and tiny expected returns are abundant;

•     For the HFTs, opportunities are short-lived because they are very small and they are heavily competed for;

•     Economics of HFT requires identification of large quantities of trading signals, which is highly technology-intensive. Success or failure in this case is determined by the HFTs speed i.e., speed in capturing opportunities before they are accessed by competitors.

Standard HFT strategies

Most high-frequency trading strategies fall within one of the following trading strategies:

•     Market making: involves placing a limit order to sell (or offer) or a buy limit order (or bid) in order to earn the bid-ask spread. By doing so, market makers provide counterpart to incoming market orders;

•     Ticker tape trading: much information happens to be unwittingly embedded in market data, such as quotes and volumes. By observing a flow of quotes, high-frequency trading machines are capable of extracting information that has not yet crossed the news screens;

•     Event arbitrage: certain recurring events generate predictable short-term response in a selected set of securities, HFTs take advantage of such predictability to generate short-term profits;

•     High-frequency statistical arbitrage: this strategy requires the HFT to exploit predictable temporary deviations from stable statistical relationships among securities.

HFT the dark side

High-frequency traders often confound other investors by issuing and then cancelling orders almost simultaneously. Loopholes in market rules give high-speed investors an early glance at how others are trading. And their computers can essentially bully slower investors into giving up profits — and then disappear before anyone even knows they were there.

HFT came into spotlight about two years ago when a very large Wall Street firm sued one of their former employees for stealing code that was used in one of their programs used to execute this type of trade. When the former employee (programmer) was accused of stealing secret computer codes/software — that a Government prosecutors said could ‘manipulate markets in unfair ways’ — it only added to the mystery be-cause the Wall Street firm acknowledges that it profits from high-frequency trading, but disputes that it has an unfair advantage.

It is rumored that in May 2010 — a flash crash took place in the Dow in which several companies and blue chips lost a lot of their value in a matter of minutes, and the New York Times reported that shares of big companies like P&G and Accenture saw ridiculous prices like a penny or a $100,000. The prices were later restored to more usual levels.

Even in India — BSE cancelled all the futures traded on in one of the trading last year, and at least an initial report blamed an algo trader from Delhi for causing havoc because of their trades.

In spite of the fact that HFT has been around for more than a decade, even today, very little is known about HFT and Algorithmic trading. Only recently regulators like the SEC and SEBI has started asking some questions. In fact, if the readers are interested they may look up the recent guidelines issued by SEBI on this issue. SEBI’s endeavour is to contain possibilities of systematic risk caused by the use of sophisticated automated software by brokers.

There are several questions like how do these programs work, what are the triggers, is there a risk and do these programs provide an undue/ unfair advantage to the user. Only time will tell.

Disclaimer:

This article is only intended to create awareness about HFT. The contents of this article are based on various stories, articles, research papers, etc. currently available in the public domain. The purpose of this article is neither to promote, nor malign any person or a company mentioned in the article.