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  2. Makridakis Competitions - Wikipedia

    en.wikipedia.org/wiki/Makridakis_Competitions

    The time series included yearly, quarterly, monthly, daily, and other time series. In order to ensure that enough data was available to develop an accurate forecasting model, minimum thresholds were set for the number of observations: 14 for yearly series, 16 for quarterly series, 48 for monthly series, and 60 for other series. [1]

  3. Time series - Wikipedia

    en.wikipedia.org/wiki/Time_series

    Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values.

  4. Mean absolute scaled error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_scaled_error

    This metric is well suited to intermittent-demand series (a data set containing a large amount of zeros) because it never gives infinite or undefined values [1] except in the irrelevant case where all historical data are equal. [3] When comparing forecasting methods, the method with the lowest MASE is the preferred method.

  5. Box–Jenkins method - Wikipedia

    en.wikipedia.org/wiki/Box–Jenkins_method

    In time series analysis, the Box–Jenkins method, [1] named after the statisticians George Box and Gwilym Jenkins, applies autoregressive moving average (ARMA) or autoregressive integrated moving average (ARIMA) models to find the best fit of a time-series model to past values of a time series.

  6. Mean directional accuracy - Wikipedia

    en.wikipedia.org/wiki/Mean_Directional_Accuracy

    In simple words, MDA provides the probability that the under study forecasting method can detect the correct direction of the time series. MDA is a popular metric for forecasting performance in economics and finance. [1] [2] MDA is used in economics applications where the economist is often interested only in directional movement of variable of ...

  7. Forecasting - Wikipedia

    en.wikipedia.org/wiki/Forecasting

    This forecasting method is only suitable for time series data. [17] Using the naïve approach, forecasts are produced that are equal to the last observed value. This method works quite well for economic and financial time series, which often have patterns that are difficult to reliably and accurately predict. [17]

  8. Mortgage and refinance rates for Dec. 17, 2024: Average ... - AOL

    www.aol.com/finance/mortgage-and-refinance-rates...

    The average rate for shorter 15-year terms is 6.11% for purchase and 6.13% for refinance, down 3 basis points from 6.14% for purchase and 2 basis points from 6.15% for refinance this time last week.

  9. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Time series models are a subset of machine learning that utilize time series in order to understand and forecast data using past values. A time series is the sequence of a variable's value over equally spaced periods, such as years or quarters in business applications. [11]