Fund Managers Switching to Algorithmic Trading

by Gord Collins

Fund Managers Switching to Algorithmic Trading

Electronic trading (and algorithmic trading) continue to gain acceptance with investors. There are some differing views as to whether computerization is generating these changes, or whether it is the use of complex mathematics-driven programming that is creating the valued edge in performance for algorithmic trading.

Statistics do show that program trading and algorithmic trading are being used more by institutional investors. It is very apparent that the market is undergoing an evolution. Those who adopt the new technology may achieve a mastery of it that will give them a decided edge in performance. Human expertise hasn’t been taken out of the equation, it’s just moved to a different level.

New Algorithms Creating an Advantage

As the price point of algorithmic trading falls below that of program trading (and traditional human managed order desks), many buy-side customers such as institutional fund managers are drawn to algorithmic trades to cut costs and improve transaction privacy. Institutional brokers are seeing less activity at their cash desks as powerful proprietary, broker-developed algorithms provide better responsiveness to market trends, and an ability to make trades that can’t be conducted effectively via traditional systems.

With the high volume of electronic trading today, institutional trading systems are overwhelmed with the volume of the data. Traditional trading programs can’t respond fast enough to analyze market transactions and seize opportunities. The demand for algorithmic trading comes from institutional brokers who are seeking to lower trading costs and to minimize manually worked orders and the commissions on those transactions.

Algorithmic Trading

Algorithmic trading is revolutionizing the equity trading industry drawing from diverse fields of statistics, mathematics, risk management, econometrics, finance, market microstructure, economics, computer science, and artificial intelligence. The system serves buy-side traders in their transaction timing and price setting. Algorithmic trading manages uses real time information from large stock market databases. This database is overwhelming for traditional trading systems to deal with. By using fine tuned mathematical algorithms, modern systems can see essential information that better represents key market factors. Many large institutional traders are realizing the advantages and are switching to algorithmic trading. A shortage of qualified mathematicians will thwart many companies from using creating effective algorthmic trading systems effectively.

Mathematical algorithms are a major technical innovation today. Complex algorithms are used by companies such as Google and Yahoo. They help to analyze and filter a changing database of billions of documents and links between Web pages to find the exact documents people seek. Similarly, security traders need to see transactional patterns in prices, volume and money flow in trades, and find those patterns that best represent the optimal volume and price points where a buy should be made.

The key to effective algorithmic trading is in executing large trades while moving the market as little as possible. All algorithmic trading technology should deliver the highest trade execution quality while simultaneously reducing information leakage. Often, this is accomplished by cutting down huge blocks of securities into small chunks and feeding them piece-by-piece into the market. The algorithm's job is to make the transaction as close to or better than the volume weighted average price during a given period of time.

Weighted Average Pricing: Guaranteed VWAP

Guaranteed VWAP (guaranteed volume weighted average pricing) guarantees execution of a trade at the volume averaged price. To offer greater security to investors, some brokers will guarantee execution the optimal price point. Guaranteed VWAP is usually offered to large cap investors.

 VWAP (Volume Weighted Average Price)

Traditional securities trading systems are unable to recognize or respond effectively to market changes. To improve the ability to execute trades at better prices, traders such as SMEX use VWAP strategies.

VWAP makes trade EXECUTION QUALITY quantifiable, which is a big change from former trading systems which did not have hard and fast standards for verification and benchmarking. The financial industry is hungry for accountability and measurable standards and VWAP is suited to its needs. With an emphasis on fast trade execution, these benchmarks also drive buy-side brokers to utilize VWAP to maintain closeness to a performance benchmark.

TWAP
TWAP is (time weighted average price) the average price of contracts or shares over a specified time.

TWAP is used as an alternate way to buy and sell. Executing a single large order may impact the market. High-volume traders use TWAP to execute their orders over a specific time so they trade at a price that reflects the true market price. TWAP orders are a strategy of executing trades evenly over a specified time period. TWAP balances execution with volume. Often, a VWAP trade will buy or sell 40% of a trade in the first half of the day and then the other 60% in the second half of the day. A TWAP trade would most likely execute an even 50/50 volume in the first and second half of the day.