What is a layman’s definition of algorithmic trading and why is it so different?
As opposed to traditional trading where an analyst will analyse the stock market before executing a trade manually, algorithmic trading harnesses the power of technology and allows the system to trade on behalf, through a set of pre-determined conditions. Thus, algorithmic trading is deemed to empower the trader with the ability to spot market opportunities faster. It can be employed for a wide range of financial instruments such as derivatives, commodities, stocks and exchange rates.
What are the benefits of algorithmic trading?
As the volume of real-time market data increases, algorithmic trading has enabled the financial industry to respond to market data with near zero latency. It allows banks and financial institutions to trade effectively in competitive markets and execute on rapid, opportunistic responses to changing market conditions, before the competition can seize those opportunities.
In the world of algorithmic trading, a reaction that’s even milliseconds faster than the competition can mean access to prices and liquidity that determine profitability. This is because trading volumes are constantly increasing and competition is as fierce as ever, for both sell-side and buy-side traders. Algorithmic trading was first adopted by brokerage houses to offer value added services to their clients. Today, we see the use spreading to proprietary desk and buy-side.
How would you describe the impact that algorithmic trading has had on the financial services industry across the world?
Stock markets are becoming more liquid as traders are able to get in and out of a trading position even more quickly with algorithmic trading. National and Regional Exchanges rides on the trend and improve infrastructure, financial institutions are gearing up to offer innovative products to their clients, and more asset classes are traded using algorithmic trading.
As banks and financial institutions are able to gain access to and analyse real-time data in huge volumes, market surveillance is another aspect which this technology is being implemented in financial markets and also in the middle offices of financial institutions. This means that patterns that point towards financial abnormalities can be more easily detected using real-time data instead of historical data.
What research figures can you provide about the current use of algorithmic trading in Asia, compared to its use in other regions? What has been the rate of take up?
Global banks and financial institutions have started to roll out algorithmic trading in their Asia offices after the success in their European and US offices. However, regional and local players are slower to adopt it. The general trend points to an increase in both interest and adoption of algorithmic trading.
Why is Singapore lagging behind financial markets in Hong Kong, Japan and Korea in the adoption of algorithmic trading technology?
This is due to the history of the financial centres and the nature of the financial business in these cities. Next we have the challenge of available resources to undertake the complex development modeling.
What is the current environment in Asia and why are algorithmic and high-velocity traders, beginning to establish a strong presence here?
Global banks and financial institutions (Tier 1) have started to roll out algorithmic trading in their Asia offices after reaping the success in Europe and the US. We have recently seen some regional and local players gradually getting into the game.
Banks and institutions in Japan and Hong Kong have already begun to develop their own localised algorithms, often bringing in foreign talent to enable them to trade in sub-millisecond timeframes and to deploy new trading scenarios to better meet the increasingly sophisticated client demands.
Korea has also begun to invest in development. Progress Apama and Koscom (the IT provider for the Korea Stock Exchange) have a strategic partnership. Its selection of the Progress® Apama® Algorithmic Trading Platform has enabled algorithmic trading on the Korea Exchange (KRX).
Local banks and financial institutions are beginning to jump on the bandwagon.
What impact is algorithmic trading having on regional and local banks in Singapore?
Local and regional banks have just started to adopt algorithmic trading, with SGX setting to change the competitive landscape and introduction of incentives designed to attract algorithmic traders to Singapore.
Also as more local banks diversify their business from the main base of retail banking to investment banking, these banks will be placing a larger focus on acquiring the right technologies such as algorithmic trading technology to compete with the international banks based in Singapore.
What is the future for algorithmic trading in Singapore and in Asia generally?
Algorithmic trading is in its infancy here, with the maturity of the concept varying among financial institutions. Local domestic players are less advanced than regional and international players.
However, this is set to change with the changing competitive landscape and the introduction of incentives by the SGX, designed to attract algorithmic traders to
Singapore. As the SGX strengthens its position as an Asian gateway, the local trading exchange landscape is changing. In July 2008, the exchange moved its securities market to a new, enhanced trading system to attract algorithmic and high-velocity traders.
Currently, according to SGX data, algorithms account for about 12 per cent of value traded in equities on SGX and 18 per cent in derivatives. We expect these values to rise significantly in the near term.
What sort of platforms are be being used for algorithmic trading?
Progress® Apama®is the market-leading platform for algorithmic trading, allows traders to rapidly design, deploy and refine automated strategies that leverage a trader's unique trading techniques.
Unlike ‘black box’ trading solutions that offer commoditised, pre-defined strategies, Apama's ‘white box’ solution allows traders to quickly develop unique trading strategies that build on their own intellectual property.
Upon deployment, Apama's execution engine—the Apama Correlator—easily manages a virtually unlimited number of algorithmic trading scenarios that operate on financial data feeds. Apama applications can execute a wide array of unique strategies that monitor and analyse events from real-time market feeds, taking action in milliseconds. Apama delivers fast, responsive action even when incoming rates exceed thousands of events per second and concurrent strategies number in the thousands.
