Algorithmic Trading Price Prediction Based Trading - Management Assignment Help

Assignment Task:

Task:

The assignment for this topic is going to look at the problem of formulating and applying trading rules using one or more of the techniques covered in the course: Genetic Algorithms, Genetic Programming, Neural Networks, Particle Swarm Optimisation, or Differential Evolution (or others of your own choice but check with me first). The choice of technique is up to you, as is the exact form of the problem you choose - take some time to read the related work - but below are two possible options based on the approaches covered in the lecture:

•  Price prediction-based trading. Build a model to predicting the price for the coming day. This can be based upon any information you like but could include various key factors from previous days such as opening price, closing price, high price, low price, volume, Relative Strength Index (RSI), Exponential Moving Average (EMA) etc, or just values from the previous days trading. On top of this prediction you would then build a trading rule which would choose to buy/sell/hold based on the current and predicted values (for example).
•  Optimising the parameters for pre-existing trading rules. Various technical indicators such as RSI or MACD can be used to trigger buy/sell actions based (for example) on the value of RSI or the relative positions of the MACD and signal lines. However, these are based on standard fixed values (e.g. MACD is built on the 26, 12 and 9 day EMA values), so an option here is to use approaches such as GAs to find a better combination of parameter values.
• These are just suggestions and you can investigate either of these or some other aspect of algorithmic trading of your own choice (but feel free to check with me first), but whatever strategy you choose must involve some element of automated trading - buying and selling of stocks.

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