"cointegration" R

Financial Econometrics with R  eBooks & eLearning

Posted by Free butterfly at July 2, 2024
Financial Econometrics with R

Financial Econometrics with R: A Comprehensive Guide: Mastering Financial Data Analysis and Modeling with Real-World Applications by Hayden Van Der Post, Reactive Publishing, Alice Schwartz
English | June 19, 2024 | ISBN: N/A | ASIN: B0D3XYMC55 | 369 pages | EPUB | 0.44 Mb

Financial Econometrics with R  eBooks & eLearning

Posted by Free butterfly at July 2, 2024
Financial Econometrics with R

Financial Econometrics with R: A Comprehensive Guide: Mastering Financial Data Analysis and Modeling with Real-World Applications by Hayden Van Der Post, Reactive Publishing, Alice Schwartz
English | June 19, 2024 | ISBN: N/A | ASIN: B0D3XYMC55 | 369 pages | EPUB | 0.44 Mb

Financial Econometrics with R  eBooks & eLearning

Posted by Free butterfly at July 2, 2024
Financial Econometrics with R

Financial Econometrics with R: A Comprehensive Guide: Mastering Financial Data Analysis and Modeling with Real-World Applications by Hayden Van Der Post, Reactive Publishing, Alice Schwartz
English | June 19, 2024 | ISBN: N/A | ASIN: B0D3XYMC55 | 369 pages | EPUB | 0.44 Mb

Algorithmic Trading & Time Series Analysis in Python and R  eBooks & eLearning

Posted by lucky_aut at Feb. 1, 2024
Algorithmic Trading & Time Series Analysis in Python and R

Algorithmic Trading & Time Series Analysis in Python and R
Last updated 1/2023
Duration: 18h45m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 4.89 GB
Genre: eLearning | Language: English

Technical Analysis (SMA and RSI), Time Series Analysis (ARIMA and GARCH), Machine Learning and Mean-Reversion Strategies

Time Series: Applications to Finance with R and S-Plus (repost)  eBooks & eLearning

Posted by libr at June 10, 2017
Time Series: Applications to Finance with R and S-Plus (repost)

Time Series: Applications to Finance with R and S-Plus by Ngai Hang Chan
English | ISBN: 0470583622 | 2010 | PDF | 296 pages | 11 MB

Introduction to R for Quantitative Finance [Repost]  eBooks & eLearning

Posted by AlexGolova at Oct. 2, 2018
Introduction to R for Quantitative Finance [Repost]

Introduction to R for Quantitative Finance by Gergely Daróczi
English | November 22, 2013 | ISBN: 178328093X | 164 pages | EPUB | 4.09 MB

Introduction to R for Quantitative Finance [Repost]  eBooks & eLearning

Posted by Free butterfly at May 7, 2019
Introduction to R for Quantitative Finance [Repost]

Introduction to R for Quantitative Finance by Gergely Daroczi
English | November 22, 2013 | ISBN: 178328093X | 164 pages | PDF | 4.06 Mb

Mastering R for Quantitative Finance  eBooks & eLearning

Posted by readerXXI at Oct. 7, 2017
Mastering R for Quantitative Finance

Mastering R for Quantitative Finance
by Ferenc Illes and Edina Berlinger
English | 2015 | ISBN: 1783552077 | 346 Pages | Mobi/Code Files | 15/8.5 MB
Statistics and Data Analysis for Financial Engineering: with R examples, Second Edition (Repost)

Statistics and Data Analysis for Financial Engineering: with R examples, Second Edition by David Ruppert
English | EPUB | 2015 | 736 Pages | ISBN : 1493926136 | 9.37 MB

The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data.
Statistics and Data Analysis for Financial Engineering: with R examples, Second Edition (Repost)

Statistics and Data Analysis for Financial Engineering: with R examples, Second Edition by David Ruppert
English | EPUB | 2015 | 736 Pages | ISBN : 1493926136 | 9.37 MB

The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data.