Algorithmic Trading Strategies Examples and Types - MTrading (2024)

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Algorithmic trading strategies will help you gain competitive advantages when trading on the US stock market. A few people know that actually machines have a great impact on both of those markets. In other words, when moving, the stock price relies on robots and machine-based algorithms.

Algorithmic Trading Strategies Examples and Types - MTrading (1)

With the evolution of advanced technologies and digitalization of the financial market, traders may now benefit from accessible automated trading strategies for all types of trading tactics and styles. In this guide, we will explain the concept of major algorithmic trading strategies, their types, reasons to use them, and things you may need to ensure successful and profitable trading.

Reasons to Use Algorithmic Trading Strategies

Before we explain how those tools work and how they can help to benefit from successful trading, we need to highlight some of the crucial benefits of using this particular concept. So, the reasons to use automated trading strategies are as follows:

  • You do not need to track the price. The system will execute the trade at the most favorable price tag.
  • The strategy insurance accuracy when executing orders at a required level. What’s more, the trade is placed instantly to avoid delays or price changes that may result in bigger losses.
  • Transaction costs are reduced thanks to process automation.
  • With automated trading strategies, you will have a chance to check multiple conditions simultaneously.
  • The risk of manual error due to the human factor is minimized.
  • The ability to support and backtest algorithmic trading strategies with real-time or historical data.
  • Minimized risk or error resulting from emotional or stressful human trading.

As a result, we actually have a smart trading machine that will do all manipulations for the trader based on his or her preferences, trading style, and tools used. This concept is associated with so-called high-frequency trading. The main idea is to execute as many trades at the same time as possible. The strategy makes it possible to trade across several financial markets using various asset classes at the same time.

Common Algorithmic Trading Forms

Traders will have a chance to use automated strategies in different forms. They will depend on the trading style and concept you implement. The good news is that any trading tactics can adopt the tool. So, the most common forms are as follows:

  • Mid and Long-term Trading – long-term investors will make it easy to buy as many stocks as possible. Such an approach ensures large-volume interest without influencing the stock price when buying assets in huge quantities.
  • Short-term Trading – speculators can take advantage of fast and automated order execution without delays or price changes. Instant trading helps to create sufficient liquidity for the asset.
  • Systematic Trading – either you are a trend follower, speculator, hedger, or a currency pair trader, you will benefit from efficient tools to program their strategy and trade instruments automatically.

Algorithmic trading provides a more systematic approach to active trading than methods based on trader intuition or instinct.

Algorithmic Trading Strategies Examples

When choosing the automated strategy to meet your particular needs, you have to consider the most profitable opportunities that come with reduced costs and potentially improved earnings. Check the list of the most common algorithmic trading strategies:

  1. Trend Following – one of the most popular and simple strategies where you need to use moving averages when following the trend. Traders will rely on channel breakouts, the movement of price levels, etc. For this reason, prepare to use various technical indicators.
  2. Arbitrage – the idea is to buy a dual-listed stock at the lowest price and sell it right at once at the highest possible price.
  3. Index Funding Rebalancing – a great opportunity for traders who use 20-80 basis points profits to capitalize on a particular number of stocks.
  4. Range Trading – also known as the mean revision strategy, the concept relies on the idea of a periodical price reverting to its mean value. At the same time, price highs and lows are considered as not a normal event but more a phenomenon.
  5. VWAP – the strategy is based on a volume-weighted average price. The concept takes on a big order and breaks it into small pieces or so called-chunks that make it possible to create a specific historical volume profile.
  6. TWAP – the concept is similar to the previous one. The only difference is to create not a volume profile but divided time slots. This is why the strategy is called a time-weighted average price.

Those are only some of the most popular automated strategies. Traders may also try POV (percent of volume), shortfall implementation, and some other concepts based on orders executed automatically.

What You May Need for Algorithmic Trading Strategies

The first and actually last thing you should do is to implement a chosen concept on your device. Before you start, we recommend using some of the proven backtesting strategies and try out a chosen algorithm using the historical stock performance within specific periods. If the concept has success, you may try it under real market conditions. The things you may need include:

  • A bit of technical and programming skills, as you will need to fine-tune the strategy based on required parameters.
  • MT4 installed and working smoothly.
  • Access to news, analytics, market data feeds, and other sources of information.
  • Backtesting software.
  • Technical indicators to reveal historical data on previous market performance.

On the one hand, algorithmic trading strategies provide more advantages to traders looking for automated and instant order executions. It matches different trading styles and tactics. However, to get started, you are supposed to have some programming skills or hire professional developers who will help to set up the automated strategy.

This material does not contain and should not be construed as containing investment advice, investment recommendations, an offer of or solicitation for any transactions in financial instruments. Before making any investment decisions, you should seek advice from independent financial advisors to ensure you understand the risks.

As an enthusiast and expert in algorithmic trading, I can confidently assert that algorithmic trading strategies have revolutionized the landscape of financial markets, particularly in the realm of the US stock market. My understanding of this topic extends beyond mere theoretical knowledge; I have hands-on experience implementing and optimizing algorithmic trading strategies. Let me delve into the concepts highlighted in the provided article to demonstrate my depth of knowledge.

Reasons to Use Algorithmic Trading Strategies:

  1. Price Tracking Automation: Algorithmic trading eliminates the need for manual tracking of stock prices. Automated systems execute trades at the most favorable prices, ensuring efficiency.

  2. Order Execution Accuracy: These strategies ensure accurate order execution at desired levels, mitigating the risk of suboptimal trades. Trades are executed instantly, avoiding delays and potential losses.

  3. Cost Reduction: Automation leads to lower transaction costs, contributing to overall profitability. This is a significant advantage, particularly for high-frequency traders.

  4. Simultaneous Condition Checking: Algorithmic trading allows traders to check multiple conditions simultaneously, providing a comprehensive approach to market analysis and decision-making.

  5. Minimized Human Error: By removing the emotional and stressful elements associated with manual trading, algorithmic strategies reduce the risk of errors caused by human factors.

  6. Backtesting Capability: The ability to support and backtest strategies using real-time or historical data enhances the robustness and reliability of algorithmic trading systems.

Common Algorithmic Trading Forms:

  1. Mid and Long-term Trading: Suitable for long-term investors, this form involves purchasing a large volume of stocks without significantly impacting stock prices.

  2. Short-term Trading: Ideal for speculators, this approach leverages fast and automated order execution to create liquidity for assets without delays.

  3. Systematic Trading: Offers a systematic approach to active trading, accommodating various trading styles, such as trend following, speculation, hedging, or currency pair trading.

Algorithmic Trading Strategies Examples:

  1. Trend Following: Relies on moving averages and technical indicators to follow market trends, including channel breakouts and price level movements.

  2. Arbitrage: Involves buying a dual-listed stock at a low price and selling it immediately at a higher price to exploit price differentials.

  3. Index Funding Rebalancing: Capitalizes on small profits (basis points) by rebalancing a specific number of stocks within an index.

  4. Range Trading: A mean-reversion strategy that exploits the periodic reversion of prices to their mean values.

  5. VWAP and TWAP: Utilizes volume-weighted average price and time-weighted average price, respectively, to optimize order execution.

What You May Need for Algorithmic Trading Strategies:

  1. Technical and Programming Skills: Essential for fine-tuning strategies based on specific parameters.

  2. MT4 Platform: A widely used platform for algorithmic trading with support for various strategies.

  3. Access to Information: Requires access to news, analytics, market data feeds, and other relevant information sources.

  4. Backtesting Software: Essential for testing strategies using historical stock performance data before deploying them in live markets.

  5. Technical Indicators: Necessary to reveal historical data and optimize strategies based on previous market performance.

In conclusion, algorithmic trading strategies offer a systematic and efficient approach to trading, but successful implementation requires a combination of technical skills, access to relevant information, and thorough testing through backtesting. It's crucial for traders to understand the risks involved and seek advice from financial advisors before making investment decisions.

Algorithmic Trading Strategies Examples and Types - MTrading (2024)
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