In this episode, we build a hedging strategy that is very easy to describe and write down, but very complex to create. This is a style of trading that only algo traders can deploy. If you are not automating, you are missing out.
In this model we take a look at a client suggestion who is trying to build a complex hedging model.
In this episode, we are looking at Bitcoin above $100k and creating a simple breakout model can take advantage of this.
In this episode, we create multiple functions to help build more advanced strategies, this includes a spread checking function that helps reduce trading when spreads are increased like during news time and when the markets open.
In this episode, we look at the daily CCI to determine the direction of the markets. This indicator can be a great tool to determine momentum in the markets.
In this episode, we take a model from 2 years ago and test this with a tighter take profit target allowing the model to trade faster.
In this episode, we look at the current market structure of USD leading up to the US elections in 17 days.
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.
In this episode, we build a calculation for the standard deviation z-score and create a strategy to trade the extreme levels.
In this episode, we build an inside bar detection algo that will trigger a trade when the market breaks outside these levels.
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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.
