Hi Traders,
In this episode, our Trader Nathan shows you a system that is designed to trade between predetermined ranges. This allows us to use mean reversion strategies to capture moves in a ranging market.
We hope you enjoy the episode.
Hi Traders,
In this episode, our Trader Nathan shows you a system that is designed to trade between predetermined ranges. This allows us to use mean reversion strategies to capture moves in a ranging market.
We hope you enjoy the episode.
In this episode we analyse the trading model and find that when the strategy takes trades later in the day they are less successful, compared to when taking them earlier in the trading day.
With this information we create a Trading Session function that helps limit the time of the day that the strategy can trade, in doing this the model takes less trades and increases the win rate %.
In this episode, we check in on the results of the My First Algo mini-series from the past 30 days and explore key upgrades for running algos in X Manager.
We’ll cover modifying and saving running algos, adding hedging when exposure exceeds net 5, implementing a pyramiding function, and testing across 28 Forex symbols to optimize for low drawdown. Plus, we’ll set up a brand-new algo on a fresh demo account.
In this episode we continue upgrading the previous Breakout strategy and start creating a portfolio with multiple symbols and multiple timeframes.
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Risk Warning: Trading leveraged products carries significant risks and is not suitable for all investors. Please ensure that you fully understand the risks involved before entering into any trades. You could lose substantially more than your initial deposit. Any information on this website is general in nature and does not take into account your financial situation, objectives or your needs. Hypothetical or Simulated performance results have certain limitations, unlike an actual performance record. Simulated results DO NOT represent actual trading. Also, since trades have not been executed the results may have under-or-over compensated for impact, if any, of certain market factors, such as lack of liquidity. Simulated Trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profit or loss similar to those shown.