Forecasting time series data using ARIMA models. Used covariance matrix to find dependencies between stocks.
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Updated
May 7, 2022 - R
Forecasting time series data using ARIMA models. Used covariance matrix to find dependencies between stocks.
R code for exchange rate prediction using Multilayer Perceptron (MLP) models with various architectures and evaluation metrics
Using MS Excel and R, accurately forecasted total core deposit data from a Richmond Bank. The Holt’s Linear Exponential Smoothing had the overall lowest “Quick and Dirty” MAPE (1.2%), the lowest overall Maximum MAPE (3.49%), and consistently more accurate projections for each of the forecast horizons. Overall, the Unaided, Holts Linear Exponenti…
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