Volatility 102
This week, we continue our on-going series on volatility modeling and forecast. In this issue, we start by defining the various terms in an asset’s
July 6, 2012
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On this page, find free resources on using NumXL functions and wizards in Microsoft Excel for data analysis and forecasting.
This week, we continue our on-going series on volatility modeling and forecast. In this issue, we start by defining the various terms in an asset’s
This week, we will show how to make a backward forecast using only NumXL functions in Excel. We will also discuss the relationship between a regular time series model and an implied backward/reversed time series model.
We are pooling all the examples we have developed over the years and are making them available to our users via a cloud-based storage service (Box.net)!
This week, we go over time series smoothing functions, highlight its assumptions and parameters, and demonstrate its application through examples. Why should we care? Smoothing
We’ve featured ARIMA models in a few of our tutorials before, but this week we’ll explore them in rich detail, starting with a clear definition of the process and moving on from there.
In this week’s issue, the final entry in our series of data preparation tutorials, we discuss the influence of outliers on our time series analysis.
This week, we continue with the fourth issue in our ongoing data preparation series by addressing two important anomalies commonly found in sample data: (1)
This week, we unveil the third issue in our ongoing series of tutorials on data preparation. This time, our focus is another bedrock assumption in
We’ve heard a few questions from many of our users about the new 7-day grace period offered with our latest NumXL release. Simply put, you can now run a full version of NumXL immediately for seven days, no license key required.
Today we launch the second tutorial in our ongoing series about data preparation in time series analysis. Our focus this time around is one of
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