What Is Algorithmic Trading ?

A computer program that executes a predetermined set of instructions (an algorithm) is used in algorithmic trading, also known as automated trading, black-box trading, or algo-trading, to execute trades. Theoretically, the deal can produce profits more quickly and frequently than a human trader could.

The specified sets of instructions can be based on any mathematical model, timing, cost, or quantity. In addition to providing traders with opportunities for profit, algo-trading makes markets more liquid and trading more methodical by removing the influence of human emotions on trading behavior.

How Algorithmic Trading Works ?

Assume a trader adheres to these basic standards:

◼️When a stock’s 50-day moving average surpasses its 200-day moving average, purchase 50 shares. (A moving average is an average of  historical data points that helps identify trends by mitigating daily price swings.)
◼️When the stock’s 50-day moving average falls below the 200-day moving average, sell shares.

These two straightforward commands will cause a computer software to automatically track the stock price (as well as the moving average indicators) and, when the predetermined criteria are satisfied, place buy and sell orders. The trader no longer has to manually enter orders or keep an eye on real-time prices and graphs. By accurately detecting the trading opportunity, the algorithmic trading system accomplishes this automatically.

Advantages and Disadvantages of Algorithmic Trading :

◼️Best Execution: Trades are often executed at the best possible prices.

◼️Low Latency: Trade order placement is instant and accurate (there is a high chance of execution at the desired levels). Trades are timed correctly and instantly to avoid significant price changes.

◼️Reduced transaction costs.

◼️Simultaneous automated checks on multiple market conditions.

◼️No Human Error: Lowers the possibility of blunders or manual errors occurring during trade placement. Additionally, it disproves human traders’ propensity to be influenced by psychological and emotional elements.

◼️Backtesting: To determine whether algorithm trading is a profitable trading technique, it can be backtested utilizing historical and real-time data that is currently available.

Mathematical Model-Based Strategies :

Trading on both options and the underlying security is possible with well-established mathematical models, such as the delta-neutral trading technique. (A portfolio strategy known as “delta neutral” consists of several positions with opposing positive and negative deltas; this is a ratio that compares the price change of an asset, typically a marketable security, to the price change of its derivative, so that the total delta of the assets in question is zero.)

Trading Range (Mean Reversion)

The foundation of the mean reversion strategy is the idea that an asset’s high and low values are transient phenomena that eventually return to their mean value, or average value. By establishing a price range and putting an algorithm in place based on it, transactions can be made automatically whenever an asset’s price fluctuates inside or outside of that range.

Volume-Weighted Average Price (VWAP)

Using historical volume profiles specific to a company, the volume-weighted average price method divides a large order into smaller, dynamically calculated pieces and delivers them to the market. Executing the order near the volume-weighted average price (VWAP) is the goal.

Time-Weighted Average Price (TWAP)

Using regularly spaced time periods between a start and finish time, the time-weighted average pricing technique divides a large order into smaller, dynamically determined pieces and releases them to the market. The goal is to minimize the impact on the market by executing the order near the average price between the start and end times.

What Programming Language Do Algorithmic Traders Use ?

Algorithmic traders frequently choose C+ as their programming language due to its exceptional efficiency in handling large amounts of data. But since C and C++ are both more complicated and challenging, finance professionals who want to start programming might be better off switching to a more approachable language like Python.

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