Short-Term Forecasting Weekly Natural Gas Spot Pricing

May 23, 2017

This presentation was given by Ave Sam Luxenberg, a Quantitative Analyst at I Know First. He graduated from the University of California with a Masters in Mathematics. 

Short-Term Forecasting

Samuel Luxenberg, Quantitative Analyst at I Know First, presents a short-term forecasting method of weekly natural gas spot prices. The method of analysis is based on the paper “Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks,” by Junghwan Jin and Jinsoo Kim. The stationary wavelet transform is employed to break down our price signal into simpler and easier-to-forecast components. The method of forecasting for each component varies between using artificial neural networks and traditional time series forecasting techniques like ARIMA and GARCH. The various one-step forecasts with the different models are then compared with several measures of error.

Press Release

I Know First, Ltd. is a financial technology company that provides daily investment forecasts based on an advanced, self-learning algorithm. The company’s algorithm predicts over 3,000 securities (and growing). It has capabilities to discover patterns in large sets of historical stock market data.

The underlying technology of the algorithm is based on artificial intelligence. It also based itself on machine learning and incorporating elements of artificial neural networks and genetic algorithms. Moreover, the algorithm generates daily market predictions for stocks, commodities, ETF’s, interest rates, currencies, and world indices for the short, medium and long-term time horizons.

For more information, visit I Know First.

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