Algorithmic Stock Trading

Algorithmic Stock Trading

An algorithm is a specific set of clearly defined instructions aimed to carry out a task or process.

Algorithmic stock trading, also referred to as algo trading or black box trading, is a trading system that utilizes advanced and complex mathematical models and formulas to make high-speed decisions and transactions in the financial markets. Algorithmic trading involves the use of fast computer programs and complex algorithms to create and determine trading strategies for optimal returns.

Algorithmic stock trading is a method of executing a large order (too large to fill all at once) using automated pre-programmed trading instructions accounting for variables such as time, price, and volume to send small slices of the order (child orders) out to the market over time.

They were developed so that traders do not need to constantly watch a stock and repeatedly send those slices out manually. Popular “algos” include Percentage of Volume, Pegged, VWAP, TWAP, Implementation Shortfall, Target Close. In the past several years algorithmic stock trading has been gaining traction with both retail and institutional traders. Popular platforms for algorithmic trading include MetaTrader, NinjaTrader, IQBroker, and Quantopian.

Algorithmic trading is not an attempt to make a trading profit. It is simply a way to minimize the cost, market impact and risk in execution of an order. It is widely used by investment banks, pension funds, mutual funds, and hedge funds because these institutional traders need to execute large orders in markets that cannot support all of the size at once.

Suppose a trader follows these simple trade criteria:

Buy 50 shares of a stock when its 50-day moving average goes above the 200-day moving average, then sell shares of the stock when its 50-day moving average goes below the 200-day moving average.

Using this set of two simple instructions, it is easy to write a computer program which will automatically monitor the stock price (and the moving average indicators) and place the buy and sell orders when the defined conditions are met. The trader no longer needs to keep a watch for live prices and graphs, or put in the orders manually. The algorithmic trading system automatically does it for him, by correctly identifying the trading opportunity.

Benefits of Algorithmic Stock Trading

  • Trades executed at the best possible prices
  • Instant and accurate trade order placement (thereby high chances of execution at desired levels)
  • Trades timed correctly and instantly, to avoid significant price changes
  • Reduced transaction costs
  • Simultaneous automated checks on multiple market conditions
  • Reduced risk of manual errors in placing the trades
  • Backtest the algorithm, based on available historical and real time data
  • Reduced possibility of mistakes by human traders based on emotional and psychological factors

The greatest portion of present day algorithmic stock trading is high frequency trading (HFT), which attempts to capitalize on placing a large number of orders at very fast speeds across multiple markets and multiple decision parameters, based on pre-programmed instructions. Algorithmic stock trading is used in many forms of trading and investment activities, including:

Mid to long term investors or buy side firms (pension funds, mutual funds, insurance companies) who purchase in stocks in large quantities but do not want to influence stocks prices with discrete, large-volume investments.

Short term traders and sell side participants (market makers, speculators, and arbitrageurs) benefit from automated trade execution; in addition, algo-trading aids in creating sufficient liquidity for sellers in the market.

Systematic traders (trend followers, pairs traders, hedge funds, etc.) find it much more efficient to program their trading rules and let the program trade automatically.


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