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The techniques used by fund managers when dealing in equities will be the focus of greater attention as three new developments come together. The first is the implementation, from November 1, of Mifid, with its new pre- and post-trade transparency requirements for equity markets.
Second, traditional models of fund manager access to the market - for example, via a broker's sales trader - are being supplemented by direct market access systems. A typical DMA system involves the fund manager's broker providing the required electronic trading tools to route trades directly to the market.
Third, with this facility in place, enhanced DMA strategies and algorithmic trading techniques are becoming more commonplace. Perhaps the most notable feature of these techniques is their diversity, meaning they appeal to a wide range of fund managers with different requirements.
Perhaps the most straightforward form of enhanced DMA strategy is to slice orders into smaller sizes. This can be with the intention of hiding, or partially hiding, a large order from other market participants, a technique sometimes called "iceberging". The maximum number of shares to be bought at any one time and during a certain sub-period can be specified by the fund manager. Clearly, for a fund manager aiming to build a stake in a particular company and wanting to disguise the extent of accumulation, such a technique can be useful.
Slicing orders into smaller sizes can also be done with the intention of minimising its market impact. "Guerrilla", an algorithm developed by Credit Suisse, for example, attempts to determine in real time which publicly displayed bids or offers (that is, those on an exchange or trading platform) can be hit or taken without a high likelihood of causing jumps or displacements in the stock's trading patterns. The technique is useful for fund managerswanting to avoid moving prices against themselves.
"Participating" strategies can be used to ensure that a certain proportion of the trading volume in a particular stock is captured. A fixed percentage - or a range - of the trading volume in a stock can be specified by the fund manager. The algorithm then assures the required share of trading volume is achieved. Such strategies may appeal to "momentum-based" investors and fund managers who place an emphasis on trends in volume as an indicator that often corroborates price trends.
Fund managers following indexed or enhanced index strategies will also find a use for algorithmic trading. "Benchmark" algorithms, for example, can be used to achieve a specific benchmark, such as the volume weighted average price over a certain time period. For such investors, the shorter latency (that is, the lag between placing an order and it being implemented) of algorithmic trades compared with those using moretraditional methods willhelp avoid slippage between the price movements of an index and its constituent components.
One step on from these algorithms is those that use "smart order routing". With such algorithms, liquidity from many different sources is aggregated and orders are sent out to the destination offering the best price or liquidity.
These pools of liquidity will typically not be shown on conventional trading platforms - those provided by the stock exchanges or crossing networks - and are therefore commonly referred to as "dark pools of liquidity". Indeed, algorithms have been developed (for example Credit Suisse's "Sniper") to detect such hidden sources of liquidity.
Many algorithms have been developed by investment banks and are supplied to their fund manager clients. This raises the risk of users of algorithms "gaming" the system.
For example, an algorithm may trigger a buy order on a certain percentage upward movement in a share price. But if such systems become widely used, then triggering such an algorithm can be a way of generating a better market price into which to sell.
Not surprisingly, "sniffers" - another form of algorithm - can be used to detect the presence of algorithmic trading and the algorithms they are using. Bespoke algorithms are being developed to overcome thatproblem.
Bespoke algorithms would be more difficult to "sniff out" and though they would add to the current diverse range of algorithmic trading tools, expected gains would have to be weighed alongside significant development costs.
Paul Temperton is director of the FT Portfolio Management Academy which runs in London from July 16 to July 24 2007. See 301 Moved Permanently
Second, traditional models of fund manager access to the market - for example, via a broker's sales trader - are being supplemented by direct market access systems. A typical DMA system involves the fund manager's broker providing the required electronic trading tools to route trades directly to the market.
Third, with this facility in place, enhanced DMA strategies and algorithmic trading techniques are becoming more commonplace. Perhaps the most notable feature of these techniques is their diversity, meaning they appeal to a wide range of fund managers with different requirements.
Perhaps the most straightforward form of enhanced DMA strategy is to slice orders into smaller sizes. This can be with the intention of hiding, or partially hiding, a large order from other market participants, a technique sometimes called "iceberging". The maximum number of shares to be bought at any one time and during a certain sub-period can be specified by the fund manager. Clearly, for a fund manager aiming to build a stake in a particular company and wanting to disguise the extent of accumulation, such a technique can be useful.
Slicing orders into smaller sizes can also be done with the intention of minimising its market impact. "Guerrilla", an algorithm developed by Credit Suisse, for example, attempts to determine in real time which publicly displayed bids or offers (that is, those on an exchange or trading platform) can be hit or taken without a high likelihood of causing jumps or displacements in the stock's trading patterns. The technique is useful for fund managerswanting to avoid moving prices against themselves.
"Participating" strategies can be used to ensure that a certain proportion of the trading volume in a particular stock is captured. A fixed percentage - or a range - of the trading volume in a stock can be specified by the fund manager. The algorithm then assures the required share of trading volume is achieved. Such strategies may appeal to "momentum-based" investors and fund managers who place an emphasis on trends in volume as an indicator that often corroborates price trends.
Fund managers following indexed or enhanced index strategies will also find a use for algorithmic trading. "Benchmark" algorithms, for example, can be used to achieve a specific benchmark, such as the volume weighted average price over a certain time period. For such investors, the shorter latency (that is, the lag between placing an order and it being implemented) of algorithmic trades compared with those using moretraditional methods willhelp avoid slippage between the price movements of an index and its constituent components.
One step on from these algorithms is those that use "smart order routing". With such algorithms, liquidity from many different sources is aggregated and orders are sent out to the destination offering the best price or liquidity.
These pools of liquidity will typically not be shown on conventional trading platforms - those provided by the stock exchanges or crossing networks - and are therefore commonly referred to as "dark pools of liquidity". Indeed, algorithms have been developed (for example Credit Suisse's "Sniper") to detect such hidden sources of liquidity.
Many algorithms have been developed by investment banks and are supplied to their fund manager clients. This raises the risk of users of algorithms "gaming" the system.
For example, an algorithm may trigger a buy order on a certain percentage upward movement in a share price. But if such systems become widely used, then triggering such an algorithm can be a way of generating a better market price into which to sell.
Not surprisingly, "sniffers" - another form of algorithm - can be used to detect the presence of algorithmic trading and the algorithms they are using. Bespoke algorithms are being developed to overcome thatproblem.
Bespoke algorithms would be more difficult to "sniff out" and though they would add to the current diverse range of algorithmic trading tools, expected gains would have to be weighed alongside significant development costs.
Paul Temperton is director of the FT Portfolio Management Academy which runs in London from July 16 to July 24 2007. See 301 Moved Permanently