Statistical arbitrage strategies aim to profit

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From mean-reverting price movements by exploiting temporary deviations from historical correlations. Trend following strategies, on the other hand, seek to take advantage of ongoing price trends by establishing long or short positions depending on the direction of the trend. These strategies use technical indicators, moving averages, and trend following rules to identify and ride price trends with the goal of making profits as long as


The trend continues. Mean reversion strategies aim to profit from temporary deviations from an asset's mean or equilibrium price. These strategies identify oversold or overbought Guatemala Phone Number conditions based on statistical indicators such as standard deviation or scores and trade in the expectation that prices will return to.


The mean over time. Machine learning-based models are popular in quantitative trading due to their ability to analyze large amounts of data and identify complex patterns and relationships in market behavior. These models use algorithms such as neural networks, support vector machines, and decision trees to learn from historical data and predict future price movements.