Automated Trading System(using NAR Neural Network) Implemented by matlab and metatrader
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Schlagwort: Matlab
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MatLab Neural Team Value Prediction

This video explains and demos a neural network that was created from scratch in Matlab that can be used to predict stock prices.
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In this webinar you will learn how MATLAB can be used to set up, analyze, and monitor a commodities trading workflow. This webinar is for financial professionals, quantitative analysts, traders, portfolio managers or energy traders whose focus is quantitative analysis, trading strategy development or commodity research.
Highlights include:
• Data gathering options, including daily historic and intraday data
• Trading strategy development in MATLAB
• Performing back-testing and walk-forward analysis
• Creating dynamic portfolio management strategies
• Interacting with real-time trading platforms
About the Presenter: Anshuman Mishra is a product marketing manager at The MathWorks. His prior experience includes the sell-side trading of FX derivatives as well as proprietary trading of equity index futures. Anshuman holds a B.Tech. and M.Tech. in Computer Science and Engineering from the Indian Institute of Technology, and an MBA from UNC Chapel Hill.
Immersed getting to know using LSTM organization to estimate/research forthcoming beliefs in MATLAB

From predicting sales to finding patterns in stock market’s data, Long short-term memory (LSTMs) networks are very effective to solve problems.
This video shows how to forecast time series data using a LSTM network.
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