A trading system that utilizes very advanced mathematical models for making transaction decisions in the financial markets. The strict rules built into the model attempt to determine the optimal time for an order to be placed that will cause the least amount of impact on a stock's price. Large blocks of shares are usually purchased by dividing the large share block into smaller lots and allowing the complex algorithms to decide when the smaller blocks are to be purchased.
Algorithmic trading represents a significant portion of trades in many major markets, including more than a third of EU and US
How Algorithmic Trading works
In very simple words, Algorithmic Trading is about the automation of the “Sense-Analyze-Decide-Execute” process for maximizing the profitability.
Sensing refers to sensing the market data f
Sensing refers to sensing the market data f
rom multiple destinations. Analyzing includes statistical analysis for arbitrage and other opportunities based on different market patterns. A market pattern represents a set of historical data points and the behavior of the market at that time. Deciding refers to the use of an appropriate trading strategy for finalizing the order type, price, quantity and the marketplace for placing order. Executing refers to implementing the decision.
An algorithm simply refers to a sequence of steps to recognize patterns in real-time market data to detect trading opportunities. Historically, investment firms would employ a large number of individual traders to manually carry out the process of building trading algorithms. However, with the advanced technologies available now, it is a much faster process to build trading algorithms and put them to use, and many fewer personnel are necessary. Algorithmic trading has effectively replaced many of the personnel formerly needed by investment firms.
Application:- 1. In electronic financial markets, algorithmic trading or automated trading, also known as algo trading, black-box trading or robo trading, is the use of computer programs for entering trading orders with the computer algorithm deciding on aspects of the order such as the timing, price, or quantity of the order, or in many cases initiating the order without human intervention.
2. Algorithmic Trading is widely used by pension funds, mutual funds, and other buy side (investor driven) institutional traders, to divide large trades into several smaller trades in order to manage market impact, and risk.[1][2] Sell side traders, such as market makers and some hedge funds, provide liquidity to the market, generating and executing orders automatically.
3. A special class of algorithmic trading is "high-frequency trading" (HFT), in which computers make elaborate decisions to initiate orders based on information that is received electronically, before human traders are capable of processing the information they observe. This has resulted in a dramatic change of the market microstructure, particularly in the way liquidity is provided.[3]
4. Algorithmic trading may be used in any investment strategy, including market making, inter-market spreading, arbitrage, or pure speculation (including trend following). The investment decision and implementation may be augmented at any stage with algorithmic support or may operate completely automatically ("on auto-pilot").
ALGORITHMIC TRADING COMPONENTS
- Real time and historical market data.
- Algorithms to:
- Perform correlation analysis
- Identify trading opportunities
- Determine optimal timing to launch
- Measure trade execution against benchmarks (VWAP
- TWAP, etc.)
- Order management/order processing.
- Connectivity to liquidity pools:
- Exchanges, ECNs’, inter inter-dealer brokers, etc.
- Integration with internal systems:
- Trading
- Order Management
- Risk Management
- Compliance
16. Back Office
Features
- Leveraging artificial intelligence techniques like neural networks, fuzzy logic, neuro-fuzzy modeling for robustness
- Customizability for implementing client specified logic
- Optimization of huge search spaces for increased throughput
- Continuous monitoring of profit and loss, risk and compliance
- User console for the complete control
- High volume trading with a minimal or no market impact
- Easy integration with other applications like order management systems, execution management systems, market data distribution platform, real-time database management systems, analysis tools etc.
- Scalability for growing business and analysis needs
Key benefits:
- Overcoming the velocity and volume trading barriers: When market indicators refresh at millisecond intervals, only the trading algorithms implemented through appropriate software can execute bulk orders in steps, with speed and with a minimum effect on the market mood.
- Overcoming incorrect human decisions: Despite the support of elaborate analysis and charting tools, decisions of human traders can differ according to their moods and emotions and can result into a failure. Algorithmic Trading systems are programmed to apply situation dependent trading strategies based on a set of well defined rules and market parameters. These rules originate from the human experience and knowledge only, but Algorithmic Trading can implement them without errors.
- Higher profits levels with lower risks: Algorithmic Trading systems help in automating the trading for better profit margins at any given point of time. They reduce financial risks and transition costs through the correct formulation and routing of orders.
- Relaxed trading: The current trading process binds traders continuously to multiple trading and market data screens. Algorithmic Trading allow traders to work in a relaxed environment. The trading algorithms continuously monitor and analyze the market data and decide about the buy and sell actions in a systematic and well defined manner. They also generate the trade and market analysis reports. Traders can get sufficient time to have a look at the generated reports and decide their strategies.
Conclusion:-
The success of Algorithmic Trading systems depends on their speed, intelligence in recognition of dynamic market pattern, correctness of the set of rules for applying trading strategies and the supporting execution management mechanism.