Algorithmic Trading Strategies

December 19, 2014 Algorithmic Trading 3 min read
Microseconds are changing the fortunes of Traders

Concept and origin of algorithmic trading

Algorithmic trading is the use of advanced mathematical concepts along with advanced technological tools to program and automate online trading strategies which get initiated on some pre-defined parameters. This genre of online trading may have originated way back in late 1990s when the US financial markets became fully electronically executable. But this concept came to light and gained momentum when a team of IBM researchers showcased a research paper in 2001, highlighting the experimental evidence that some algorithmic strategies could consistently outperform human traders.

Algorithmic trading a share trader should know

This research paper sowed seeds for rampant growth of algorithmic trading especially High Frequency Trading (HFT). HFT is a type of algorithmic trading in which trades are carried out for very small time frames, from few seconds to fraction of seconds in some cases. HFT strategies assess and interpret large volumes of data in seconds or less than a second which is beyond the capabilities of human traders. It is estimated that by end of 2010, HFT accounted for almost 60-70 percent of total equity volumes in the US, followed by 30-40 percent in Europe and 5-10 percent in Asia. In terms of execution, HFTs have been reduced to as low as microseconds by the end of 2010.

1 Second – 1000 Milliseconds

1 Millisecond – 1000 Microseconds

Algorithmic Trading

This phenomenal growth of HFTs can be attributed to the low margins deployment since most of the HFT do not leverage or carry their positions overnight. Moreover, they have been able to manage incredible returns as compared to traditional strategies. Most of the HFTs compete with other HFTs rather than the positional long-term funds in the share market.

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How do High-frequency traders (HFTs) make money?

As we know that large fund houses hit usually big orders in share markets, causing some lumpiness in price movements. Normally, it takes a while for the prices to get back to normal levels. HFT stand to profit from price actions which result from large institutional trades.

Stock price

But HFTs need to read huge volumes of data to identify whether these price distortions are just a blip or long-term trend making. HFTs try to capture these blips to make profits. However, with the presence of so much of competition out there, it is not easy to make these profits. In fact, the competition among the HFTs has reduced the execution time to milliseconds and even microseconds in some cases. HFTs rely ona number of strategies to earn profits with the pre-dominant ones being market making, statistical arbitrage, event/news based arbitrage, filter-trading and low-latency strategies. Share Market making and capturing arbitrage opportunities remain at the forefront of HFTs.Arbitrage opportunities refer to differential pricing of the same asset on different platforms or in the form of cash-future arbitrage (when the futures trade below or above the risk-free cost of funds). Likewise, statistical arbitrage arises when a statistical relationship (for instance pair ratio of two stocks) witnesses temporary deviations. Low-latency strategies are designed to take advantage in terms of execution time to capture any price discrepancies. Filter trading is revolved around observing and identifying any unusual behavior in price and volume patterns.


Also Read : How Psychology affects Trading

HFT Strategies

HFT – a boon or a bane

HFTs are credited with providing liquidity to the markets through their market making strategies and thereby reducing the bid-ask spreads, resulting in lower impact cost for investors (impact cost is the average of bid-ask spread which happens to be high in case of wide bid-ask spreads). Furthermore, large funds have been able to execute big orders at a lesser cost backed by some high-frequency execution strategies.

On the other side, it is believed that the rising dominance of HFTs has led to enhanced volatility in the share markets. In fact, some of the strategies run by large fund houses in the US were held liable for flash crash 2010 (an event when the US Dow Jones had dropped by about 1000 points and then recovered few minutes later). A lot of research has been done to quantify the rise in volatility as a function of increase in high-frequency trading but none of the reports could furnish any concrete evidence on this.

Growth of HFT in Indian Markets

India is not much behind as far as high-frequency trading is concerned. Though there is no official number on HFT volumes on Indian stock market exchanges, it is believed that 30-40 percent of volumes in Indian equities are routed through HFT. With more and more proprietary firms entering into this segment and India still to catch up with the global markets in terms of HFT volumes, there is no looking back for algorithmic trading in India. As a result, the competition among the HFTs to earn profits in microseconds will only intensify.

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