Wide Gaps in Algo Performance Across Asian Markets, Finds Tora Analysis

A study analysing algorithm performance in Asia during the first half of 2010 found wide variations in performance across markets, with Hong Kong and Singapore faring weaker than Japan.

The transaction performance analysis compiled by Tora, an Asian provider of trading technology and financial services, reviewed approximately 120,000 algorithm orders from the first six months of 2010 and found slippage for VWAP algorithms varied across markets and brokers. Average slippage was 15.1 basis points (bps) in Singapore, 9.5 bps in Hong Kong and 4.5 bps in Japan. In percentage terms, slippage was 111% higher for Hong Kong than Japan, and 236% higher in Singapore than Japan.

The study showed performance varied by as much as 8.0 bps across brokers in Asia and that algorithms, despite variations in performance, can offer cost savings compared to a traditional execution.

“Algorithms are an important tool increasingly used by traders in Asia, yet the study results clearly show there are differences in performance,” said Robert Dykes, Tora’s chief executive officer (CEO). “The overall advantages are clear as long as traders are diligent about which brokers’ algo they use given their trading objectives.”

Slippage is the difference between the intended price of a trade and the price where the trade is actually executed. The study focused on VWAP as this benchmark remains the predominant trading objective used in Asia.

Dykes said that the difference between the three markets can partly be attributed to the concentration of liquidity in those markets in individual names (equities). Another factor is volatility, which is substantially higher in Hong Kong and Singapore when compared to Japan.

“Our analysis looked at a wide range of factors that affect performance including liquidity, volatility, spreads and user-defined parameters,” Dykes said. “The key to maximising algorithm performance is to use the one that best reacts to prevailing market condition.”


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