Algo Trading 101: Intro to Guerillas, Snipers and Sniffers
Line BreakAuthor: tester (10 Articles)
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Before we start I would like to specially thank Jessica Vrazelik for bringing everything together with her special touch.
Algorithmic trading uses coded programs for entering trading orders with the algorithm deciding on various aspects of the order such as the timing, price, or quantity, thereby booking the order without a human trader intervening. While companies who utilize this technology make up a mere 2% of the financial institutions trading on the US market, HFT companies are estimated as being responsible for over 70% of all orders being carried out, and 60% of total volume traded. These are especially impressive statistics given the fact that the average investor is largely unaware of the scope of algo trading technologies and strategies.
A Brief History of Algo Trading
In the era before automatic trading systems, trading desks included four to eight screens and traders monitored the market while executing trades simultaneously. Since judgment, risk and oversight were handled manually, properties were typed into the system, and only then could the orders be carried out. However, today’s algo systems no longer require a trader’s physical presence at any stage of the trade with the exception of programming and monitoring the platform.
Computerized trading of stocks first appeared on the Wall Street landscape in the 1980s, and it was blamed for exacerbating the market plunges in October 1987. Since then, computers have only grown more powerful and the algorithms that guide their trading more sophisticated. The daily flows in the financial market bring with them a slew of beneficial strategic arbitrage opportunities to exploit. The ability to instantly adapt to the continuously changing market gives algo trading market players a competitive advantage, where even slight improvements in the algorithm or technological platform can result in a significant divergence between profit and loss.
A Brief Overview of Commonly Used Algo Trading Strategies
Algo traders apply multiple techniques when executing automatic trades and the following examples represent popular algorithmic strategies.
“Double hedging” describes a strategy that supervises pairs of assets with identical statistical correlations. Changes in market price of the given pair of assets are tracked, and once the change occurs the algorithm counts the difference in standard deviation between the two assets, and then executes the hedging procedure. For example, “Shell” and “Exxon” shares are both in the energy sector and therefore are correlated. Following this pair of stocks allows the algo system to determine if future profits can be made, and the possibility of profit increases as the correlation between the two assets gets smaller. Thus, “double hedging” occurs as the correlation value goes down, presenting the opportunity to simultaneously buy one share and sell the other thereby locking in a profit.
Slicing orders into smaller sizes is one strategy that can be executed in order to minimize the market impact of a trade. “Guerrilla”, an algorithm developed by Credit Suisse, attempts to determine in real time which publicly displayed (exchange traded) bids or offers can be hit or lifted without the likelihood of causing a rise or a displacement in the stock’s trading patterns. This technique is useful for fund managers wanting to avoid moving prices against themselves while executing their trading strategy.
With “smart order routing” algorithms, liquidity from many different sources is aggregated and orders are sent out to the destination offering the best price or liquidity. Some of these sources may include thinly traded “dark pools” of liquidity that are not traded on an exchange. The Sniper strategy, also invented by Credit Suisse, works via executing trades primarily in dark pools, without signaling the presence of the buyer or seller to the market place.
My personal favorite is “Sniffer.” Sniffers attempt to detect the presence of other algorithms operating in the market, mimicking their strategies by identifying and exploiting the unseen opportunity or spread.
As they say – “it takes one to know one.”
Line BreakAuthor: tester (10 Articles)
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high frequency trading
