Quantitative strategy, or quant strategy for short, is a type of investment strategy that uses mathematical and statistical models to identify and exploit trading opportunities in financial markets. The goal of a quant strategy is to use quantitative analysis to generate alpha, or excess returns, while managing risk and minimizing trading costs.
Quant strategies can take many different forms, depending on the specific trading approach and the data being used. Some common types of quant strategies include statistical arbitrage, trend following, mean reversion, and machine learning-based approaches.
This type of strategies are designed to be systematic and objective, using data and algorithms to drive trading decisions rather than relying on human intuition or subjective judgments. While they can be complex and require significant resources to implement, quant strategies can be highly effective in generating returns and managing risk in today’s increasingly complex financial markets.
Once a trade is opened, the details of the transaction will be published in the dedicated telegram channel.
Consequently when the position is closed, you will see the exit message published.
Here is an example:
The messages are pretty much self-explanatory. If you still have questions, please contact our support team at email@example.com
The recommended risk strategy is Fixed Lot due to the nature of the signals, which is no Fixed Stop and no Fixed Target levels.
You can join via the “Quant Signals” link in “Live Trades” section of the website.
The Quant project is currently in forward test phase.
It runs on 10k account (virtual/demo/paper), Leverage 1:100. It trades CFDs on indices (swap applies).
The actual deviation from live account conditions shouldn’t be a problem since there is no scalping involved.
The real problem here would be if the portfolio stops working rather than the deviations between paper/live execution.