Algorithmic trading software
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Basics Of Algorithmic Trading And How It Works!

Algorithmic trading software also called automated trading, or algo-trading deploys a computer program that is fed with a defined set of instructions/algorithm to wage a trade. Algorithmic trade can generate profits at a higher frequency and speed than any human trader.

The defined programs or the sets of instructions are based on quantity, timing, price or any mathematical model. While registering profits for the traders, algorithmic trading strategies makes trading more systematic and markets more liquid by excluding the impact of human emotions on trading.

Algorithmic Trading in Practice

Suppose a trader follows these simple trade criteria.

Buy 1000 shares of a stock when its 100-day moving average goes above the 300-day moving average. (A moving average is an average of past data points that smooths out day-to-day price fluctuations and thereby identifies trends.)

Sell shares of the stock when its 100-day moving average goes below the 300-day moving average.

With these two simple instructions, a computer program will self-monitor the stock price and place the purchase and sell orders when it meets the set parameters/conditions. The trader can sit back and enjoy his time as he no longer needs to monitor live pricing and graphs and push manual orders. The algorithmic trading software does it all automatically by correctly identifying the trading opportunity.

Uses of Algo-Trading:

Algo-trading provides a systematic approach to active trading than other methods based on intuition, instinct or emotions. It is used in many forms of trading and investment activities, including:

1.) Mid- to long-term investors: 

Insurance companies, pension funds, mutual funds, put algo-trading in use to buy stocks in large quantities when influencing stock prices with discrete, large-volume investments is not required.

2.) Short-term traders and sell-side participants:

Speculators, Brokerage houses, and arbitrageurs derive benefits from automated trade. Besides, algo-trading helps in creating liquidity for the sellers in the market.

3.) Systematic traders:

Pairs traders (a market-neutral strategy used for trading that matches a long position with a short one in a pair of highly correlated instruments such as two stocks, exchange-traded funds (ETFs) or currencies), Trend followers, and hedge funds use algorithmic trading as they find it to be much more efficient to program the trading instructions and rules and let the program trade automatically.

Technical Requirements for Algo-Trading

Executing the algorithm with the help of a computer program is the final element of algorithmic trading, accompanied by back-testing, i.e., trying out the algorithm on previous periods of stock-market performance to analyse if using it would have been profitable. The real aim and challenge are to transform the identified strategy into a cohesive computerized process that can access trading accounts to place orders. Here are some basic requirements needed for algorithmic trading:

  • Good knowledge about computer-programming so that you can program the needed trading strategy, pre-made trading software or hired programmers.
  • Excellent network connectivity and access to trading platforms to place orders.
  • Access to market data feeds that the algorithm will monitor to look for opportunities to buy or sale the instruments.
  • The infrastructure and ability to backtest the system before going live and start trading in the real markets.
  • Availability of historical data for backtesting based on the complexity of a set of instructions implemented in the algorithm quantitative trading.

Algo-trading provides the following benefits:

  • Algorithmic software executes the trade at the best possible price.
  • Trade order placement is accurate and quick. Algo-trading software has high chances of execution at the desired levels.
  • Trade can be correctly and instantly measured to avoid any price changes.
  • Reduction in transaction costs.
  • Automated checks on multiple market conditions are done simultaneously.
  • Reduced risk of manual errors while trading.
  • Algo-trading can be backtested by using historical and real-time data to check the viability of the trading strategy.
  • Reduced possibility of mistakes by human traders due to psychological or any other factor.
  • Algo-trading is high-frequency automated trading, which attempts to capitalize on placing a large number of orders at an increased pace across multiple markets and multiple decision parameters based on pre-programmed rules.
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