Published On: Wed, Dec 9th, 2009

Credit Suisse AES Launches Algorithmic Trading in Indonesia

Credit Suisse’s Advanced Execution Services (AES®) announced December 8th the launch of algorithmic trading for Indonesian equities. A range of AES® algorithmic trading strategies are now available, enabling Credit Suisse clients to trade Indonesian equities more efficiently and achieve best execution.

This development is further evidence of Credit Suisse’s leadership in electronic trading and of its strong position in Indonesia – the Bank was also the first foreign broker to offer Direct Market Access in the Indonesian market in August 2008.

“This offering gives Credit Suisse clients trading in Indonesia an edge,” said Hani Shalabi, Head of AES Sales for Asia. “The technology is tuned specifically for Indonesia’s market structure to maximize liquidity and minimize the impact of clients’ trades. It’s another step forward in our ongoing drive to deliver best execution to clients wherever they are trading.”

Credit Suisse’s launch of algorithmic trading in Indonesia confirms the Bank’s standing as a leading provider of algorithmic execution in the region. Credit Suisse clients can now use algorithms to trade equities listed in Australia, Hong Kong, India, Indonesia, Japan, Korea, Malaysia, Singapore, Taiwan and Thailand.

Credit Suisse is one of the leading foreign financial institutions in Indonesia, offering Investment Banking and Investment Management services. The Bank is currently ranked #1 among bookrunners of Indonesian equity capital markets issuance and has managed a series of landmark equity, debt and mergers and acquisitions transactions in 2009.*

Algorithms have become increasingly popular globally, enabling investors to trade more efficiently, reduce transaction costs and minimize the market impact of their trades. The AES® suite of algorithms offers the widest range of strategies in Asia Pacific with 12 headline strategies and over 100 custom strategies currently available in the region.

These include traditional algorithms that seek to divide trading volumes up over time, strategies that seek to trade at the Volume Weighted Average Price of a stock, strategies that seek to minimize implementation shortfall – or the difference between the price at which a client decides to trade and the actual execution cost – and strategies that seek to trade a certain percentage of a stock’s daily volume.

*According to Dealogic, for the year until 7 December 2009

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