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Time Series Analysis in Python

In this course you'll learn the basics of analyzing time series data.

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4 Hours17 Videos59 Exercises48,107 Learners4850 XPTime Series Track

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Course Description

From stock prices to climate data, time series data are found in a wide variety of domains, and being able to effectively work with such data is an increasingly important skill for data scientists. This course will introduce you to time series analysis in Python. After learning about what a time series is, you'll learn about several time series models ranging from autoregressive and moving average models to cointegration models. Along the way, you'll learn how to estimate, forecast, and simulate these models using statistical libraries in Python. You'll see numerous examples of how these models are used, with a particular emphasis on applications in finance.

  1. 1

    Correlation and Autocorrelation

    Free

    In this chapter you'll be introduced to the ideas of correlation and autocorrelation for time series. Correlation describes the relationship between two time series and autocorrelation describes the relationship of a time series with its past values.

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    Introduction to Course
    50 xp
    A "Thin" Application of Time Series
    100 xp
    Merging Time Series With Different Dates
    100 xp
    Correlation of Two Time Series
    50 xp
    Correlation of Stocks and Bonds
    100 xp
    Flying Saucers Aren't Correlated to Flying Markets
    100 xp
    Simple Linear Regression
    50 xp
    Looking at a Regression's R-Squared
    100 xp
    Match Correlation with Regression Output
    50 xp
    Autocorrelation
    50 xp
    A Popular Strategy Using Autocorrelation
    100 xp
    Are Interest Rates Autocorrelated?
    100 xp

In the following tracks

Time Series

Collaborators

lore
Lore Dirick
nicksolomon
Nick Solomon
Rob Reider Headshot

Rob Reider

Consultant at Quantopian and Adjunct Professor at NYU

Rob is an Adjunct Professor at NYU's Courant Institute where he co-teaches a course on Times Series Analysis and Statistical Arbitrage. He is also currently a Consultant to Quantopian. He has been a Portfolio Manager for over 15 years at Millennium Partners, JPMorgan, and Visium Asset Management. Rob received his Ph.D. in Finance from Wharton.
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