Algorithmic Trading Strategies for Experienced Traders

Mix and match best algorithmic trading strategies for even more efficient trading.

By Marcel Deer

Edited by Dragan Stevanovic

Published May 21, 2024.

a hand touching a digital screen with a stock chart in the background

In 2024, algorithmic trading accounts for 60–75% of trading volume in the US, Europe, and major Asian markets. This type of trading soared because of faster and more efficient trades, automated data analysis, risk exposure control, and uninterrupted 24/7 trading.
Note: Fortrade offers the ability to trade the price changes of instruments with CFDs and NOT to buy/sell ownership of instruments themselves. All the information in this blog is purely educational and should not be considered advice.
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1. Momentum & Trend-Following StrategiesThese strategies utilize market momentum and trends by charting the direction of the prices and then executing trades in the same direction (under the assumption the momentum will continue).
Momentum strategies involve buying instruments on the rise and selling as they start to decline. 
Trend-following strategies rely on moving averages to check the price direction before making trades.
Note: Fortrade offers the ability to trade the price changes of instruments and NOT to buy/sell ownership of instruments themselves. 
2. Mean Reversion StrategiesMean reversion strategies operate on the idea that any movement of the stock price will eventually return to its average value.
Mean reversion traders sell instruments trading above their historical averages and buy those priced below the mean. The strategy hinges on recognizing overbought or oversold trades and then executing with precise timing to catch the price reversal.
With this approach, traders look for instruments that have deviated significantly from their historical averages. 
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3. Market Making Strategies﻿Market makers play a crucial role in the trading market because they ensure liquidity. In other words, they make sure there are both buyers and sellers for a security.
Traders use market making strategies to leverage the spread between buying and selling prices, known as the bid-ask spread. Advanced algorithms adjust bid and ask prices to create potential profit. To do this, algorithms take into account:
Market conditions
Risk evaluations
Order flows 
» Curious about the market makers strategy in forex? Find out how bid-ask spread works in forex trading﻿
4. High-Frequency TradingHigh-frequency trading (HFT) strategies involve high-speed trading in large volumes. Traders use algorithms to find minor price differences that might gain potential profit. Instruments are usually held for a short time.
HFT has been a revolutionary force across financial markets, accounting for a high proportion of trading volume in forex, futures, and equities. However, some critics argue that HFT strategies increase market volatility and trading risks.
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5. Machine Learning StrategiesIn machine learning strategies, artificial intelligence (AI) algorithms and advanced statistical models analyze massive datasets and find patterns and signals to inform trading. As more data is fed, machine-learning models adapt, refine predictions, and increase accuracy.
These strategies are sometimes best combined with other methods, like momentum trading and mean reversion.
» Want to uncover data patterns? Consider AI algorithmic trading﻿
6. Sentiment Analysis StrategiesSentiment analysis uses market sentiment indicators to gauge the overall market sentiment and make trading decisions accordingly. 
Indicators usually come from investor and trader surveys, social media, and news outlets.
Sentiment analysis is a strategy to remove emotion from trading on instruments. This strategy capitalizes on mispricing driven by emotive trader or market responses. 
Advanced Strategies for Savvy TradersMany strategies automate the trading process, so there is less need for human interference. At the same time, the automated parameters aim to secure optimal buying and selling prices.
However, that doesn't mean there should be no human oversight. Even with sophisticated trading technologies, proper research and due diligence are a must.
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