Trading to Win through Transaction Cost Analysis

Transaction Cost Analysis is the idea of monitoring and reporting on trade performance. Certainly not a new concept in the trading industry. Brokers, EMS and OMS vendors have been providing this capability for a quite a while.  Yet, it is just as common for the buy side, sell-side and quantitative trading firms to build their own analysis platforms. They are creating complex TCA platforms leveraging modern technology such as OneTick’s CEP, high performance tick database and Panopticon’s state of the art visualization dashboards. Recently OneMarketData and Panopticon, conducted a live webinar on TCA highlighting our fit-for-purpose technologies for cost analysis. You can view the recording of that here.

A more competitive trading environment, thinner margins and that enduring desire to win have pushed traders to explore more cross asset trading models. Strategies leveraging a multiplicity of markets across Equities, Futures, and Options and of course currencies are becoming more common. Firms are managing big data over longer time periods for both strategy research and cost analysis. The result is increasing complexity of costing models, incorporation of order books for market impact analysis and not-just-VWAP (NJV) for benchmarks. But a vital aspect in today’s competitive trading landscape is how quickly and accurately can transaction costs be delivered and what do traders do with the information once they have it?

Typically TCA is as post-trade exercise, comparing an actual execution against a benchmark such as VWAP. The buy-side can measure the performance of individual brokers and various venues for best execution. TCA can accurately measure the costs incurred by trading strategies to show a different side of their profitability. This transaction cost decision analysis leveraged by buy side trading desks can improve their ability to capture alpha.

An example of this is Implementation Shortfall, a measure of slippage that looks to identify costs at multiple levels. One is implicit costs, trades that represent lost opportunity. The disparity between decision time… that time an order enters the market and the final price obtained, plus any outstanding quantities that failed to execute. Implicit costs are imposed by market forces – the impact of your own trades and others. Pre-trade benchmark analytics provide the best measure to forecast implicit costs for determining strategy decisions. The second measurable costs are more quantifiable. The explicit costs of taxes, fees and commissions. Measures such as these provide an end of trading day analysis to help evaluate strategy effectiveness.

But there is another angle, specifically intra-day or real-time cost analysis. That of measuring trade cost performance as it happens not just at the end of day. What is driving this need?  The desire to compete more effectively and win. Faster trading technology, low latency infrastructure, fire-hose market data volumes and high frequency traders have made best execution and alpha capture ever more elusive for institutional investors and buy-side firms alike.

Real-time TCA is an effective competitive weapon to outpace the market, with it you can continuously monitor execution price against arrival price and recalibrate benchmarks.  The continuous analysis of executing orders showing realized and unrealized P&L can indicate in real-time those implicit opportunity costs, the impact of market forces however volatile they may be on any given day.

The insight of real-time costing analytics for order execution provides traders the decision-making tools to be more profitable. Trading strategies can be adjusted intelligently, either aggressively or passively to respond to market conditions.

But these aspects of TCA, historical and real-time are not mutually exclusive. Practically speaking they are closely tied together. The ideal case is to view historical activity and real-time as a single time continuum. What happened yesterday, last week or last month is simply as extension of what is occurring today and what may occur in the future. For example, comparing current market volumes to historic volumes, prices and volatility for participation strategies. Or the need to monitor market prices may involve benchmarks that include sector and index movements, both intra-day and historic market trends to gauge volatility and smooth outliers. And this has to occur at a very granular level to keep pace with complex order routing strategies that result in smaller orders and fills. 

Accurate transaction cost analysis is reflected in pre-trade, post-trade and real-time analytics for optimum trade performance. And it’s a well-known fact that 80% of information processing is attained visually.  So having visual representations such as heat-maps and trend-lines to plot those executions, analytics and benchmarks to spot performance outliers can vastly improve an order’s final quality.

Once again thanks for reading.
Louis Lovas

For an occasional opinion or commentary on technology in Capital Markets you can follow me on  twitter, here.

About Louis Lovas

Director of Solutions, OneMarketData, with over 20 years of experience in developing cutting edge solutions and a leading voice in technology and trends in the Capital Markets industry.
This entry was posted in Algorithmic Trading, Analytics, Big Data, Complex Event Processing, Equities, Foreign Exchange, Futures and Options, HFT, High Frequency Trading, OneMarketData, OneTick, Tick database. Bookmark the permalink.

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