Member Login
New York
London
Mumbai
Hong Kong
Related News
| Hedge fund ponder choices and challenges of pre-trade analytics |
 |
 |
 |
| Friday, 15 August 2008 | ||
| Hedge Fund Review | ||
|
Finding the right technology solution to give historical and current trade analysis is a challenge. Stephen Quigley talks to a variety of providers (including Neil Edelstein of GoldenSource) and discovers how hedge funds are coping with the variety of choices on offer for pre-trade analysis. Below is an excerpt from the longer article featured in Hedge Fund Review. (Subscription is required). Pre-trade analytics help traders decide where and when to send orders through the analysis of historical and current volume and price data. These analytics also allow traders to decide whether to use algorithms or manually trade an order. Some of the larger buy-side organisations employ research and trading teams to conduct their own analyses through real time data. Most buy-side clients get their analytics from brokers as part of an overall service package. Some fund managers have turned to computerised algorithms provided by brokers at cut rate commissions. Pre-trade analytics help traders decide where and when to send orders through the analysis of historical and current volume and price data. These analytics also allow traders to decide whether to use algorithms or manually trade an order. Some of the larger buy-side organisations employ research and trading teams to conduct their own analyses through real time data. Most buy-side clients get their analytics from brokers as part of an overall service package. Some fund managers have turned to computerised algorithms provided by brokers at cut rate commissions. However, as more algorithms are available, it is thought the buy side will be looking for more quantitative support rather than just post-trade transaction cost analysis. Hedge funds are faced with a duel challenge. They need to satisfy increasing investor demands for clear, reliable and well documented risk reports in troubled economic conditions. They also need detailed and timely information for their own use. Hedge funds are using pre-trade analytics, most often from vendors and brokers instead of driving analytics from their own data. This is because they do not have the historical data at their disposal to allow them to create effectively their own pre-trade analytics across the securities they trade. Some hedge funds are using broker-provided front-end systems which have pre-trade analytics built into the platform. However, hedge funds want a variety of opinions on the projected cost and market impact of a trade and not just a single broker's viewpoint so they can see how easy or hard it will be to trade. Houses should not have to struggle with building technology solutions because there are vendor solutions out there. "Small and mid-size firms are better suited by a hosted analytic environment where infrastructure would be hosted and stored, then the analytics can be customized at the user end to create a level playing field. In addition to high frequency automated trading models, there has been a big rise in companies using strategies predicated on quantitative research. "This requires sifting through many terabytes of data over long periods of time using statistical analysis tools and then working the findings into production trading. Because of the huge amounts of data as well as decisions moving from milliseconds to nano-seconds, software-only solutions cannot keep pace and we are seeing a shift to accelerated software/hardware hybrid solutions. GoldenSource, a company that accesses, stores, back tests and scrubs data before sending it on, publishes all data to internal master security, portfolio management, risk and order management systems. Its multi dimensional data model includes storage capabilities for fundamental and analytic data. Neil Edelstein, vice president of products at Goldensource says the depth of data necessary for hedge funds has increased. "Accurate analytics is essential for downstream applications to seamlessly feed into internal systems on an enterprise level," says Edelstein. "Hedge funds typically invest heavily in alternative investment and derivative securities. These and other over the counter securities require both depth and complexity of information," he adds. Many brokers provide pre-trade analytics for listed products. These look at liquidity in relation to the size of the intended trade. For unlisted products, such as interest rate swaps, swaptions and credit derivatives which are not constrained by liquidity, pre-trade analysis takes a different form. The skill of the fund manager lies in the decision-making process. The best fund managers know what they are good at and why. Pre trade models merely help implement the decision of the fund manager. Some hedge funds take concentrated positions and rely on pre-trade analytic tools or compliance engines to monitor position levels closely, according to Chuck Molinary, managing director of Citisoft. "In terms of pre-trade analytics, several firms use these tools in order to stay within limits and avoid regulatory filings. The tools can help prevent a trade from triggering a costly public filing," says Molinary. Subprime problems have not affected analytics hugely. "If anything, market volatility warrants greater focus on these tools as risk management aids. With recent technology advances such as algorithms, dark pools and execution management systems, traders now have a wider array of choices for execution," Molinary says. "When executing large orders, there is rarely a clear best choice among these avenues. The value a trader brings to the equation is knowing when and how to use each available avenue. Pre-trade analytic tool usage grows in relation to a firm's size. The larger a fund, the more likely they are to be using such tools," concludes Molinary.
|