If you work in finance, accounting, or a related field, chances are you’ve had to put together a forecast... and then explain why you built it the way you did. Excel makes that process feel …
Copilot in Excel: How to build ARIMA forecasts with Python
ARIMA (short for AutoRegressive Integrated Moving Average) is a classic statistical model for time series forecasting. It works by combining three elements: autoregression (using past values to …
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Copilot in Excel: How to build exponential smoothing forecasts with Python
Forecasting is a constant challenge for Excel users. Business data doesn’t just grow in straight lines... it shifts with trends, cycles, and noise. Exponential smoothing is a family of methods that …
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Python in Excel: How to do rolling correlations
As a financial analyst, you often want to trace how relationships between asset returns evolve over time. Maybe you're looking to understand diversification benefits, detect changing market dynamics, …
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Advanced analysis with Python in Copilot: How to work with time series data
Time series analysis lets analysts identify patterns, trends, and cyclic fluctuations over time. These insights are essential for accurate forecasting, strategic planning, and informed …
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Python in Excel: How to upsample and interpolate time series data
Upsampling time series data involves increasing the frequency of your data points by filling in gaps to transform a lower-frequency dataset into a higher-frequency one. This process is often necessary …
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