Hi Traders,
In this episode, we add a small MA cross filter to reduce the amount of trades the model takes which increases the overall success of the algo.
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In Episode 411 of Trading Talk, we introduce our new internal Code Snippets library, designed to streamline the way traders build and modify algorithmic models.
In this week’s episode of Trading Talk, we combine two recent developments from previous sessions — the Z-Lock volatility function and the adaptive trade management system — to demonstrate how they can work together as a simple strategy framework.
In this week’s episode of Trading Talk, we build out the volatility function introduced in the previous episode and walk through the key formulas step by step. This session focuses on combining log returns, variance and standard deviation to construct a statistical framework that produces a Z-score volatility model.
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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.
