Lines of products Buying and selling MATLAB

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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.

Electric bill Burden Predicting through Artificial Neural System in matlab

One day ahead electricity load forecasting in Matlab with the help of the Artificial neural network.

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Stock exchange prophecy technique | MATLAB | System Discovering | Instantaneous Statistics Breakdown

Hello friends today I’m going to show you how the stock market prediction system works and how machine learning helps you to get the exact estimation of the stock market.

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Working on Time Number Numbers in MATLAB

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A key challenge with the growing volume of measured data in the energy sector is the preparation of the data for analysis. This challenge comes from data being stored in multiple locations, in multiple formats, and with multiple sampling rates. This presentation considers the collection of time-series data sets from multiple sources including Excel files, SQL databases, and data historians. Techniques for preprocessing the data sets are shown, including synchronizing the data sets to a common time reference, assessing data quality, and dealing with bad data. We then show how subsets of the data can be extracted to simplify further analysis.

About the Presenter: Abhaya is an Application Engineer at MathWorks Australia where he applies methods from the fields of mathematical and physical modelling, optimisation, signal processing, statistics and data analysis across a range of industries. Abhaya holds a Ph.D. and a B.E. (Software Engineering) both from the University of Sydney, Australia. In his research he focused on array signal processing for audio and acoustics and he designed, developed and built a dual concentric spherical microphone array for broadband sound field recording and beam forming.
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Currency rate prediction by Neural Networks in Matlab

See how Time Series Neural Network Regression model can be trained to accurately predict the fluctuations in currency rate trends.

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