IDEAS home Printed from https://ideas.repec.org/a/prg/jnlcfu/v2013y2013i4id363p145-163.html
   My bibliography  Save this article

Using R in Finance
[Využití R v oblasti financí]

Author

Listed:
  • Jiří Sedláček

Abstract

R is open source software environment (and language) for statistical computing and graphics. Different surveys are showing R's popularity has increased substantially in recent years, especially in academic environment. Therefore, at the beginning main advantages and comparison to commercial statistical software are presented. Second, selection of the best interface for given tasks is important. In each category (GUI or editors/IDEs) several product are compared. Data structure for time series in base installation is suitable for regular time series only. Therefore, several other data structures in different packages are compared: almost all support irregular time series, but differ in other attributes (often important for financial data). In following section, analysis of some well-known packages for financial data (quantmod, RQuantLib, Rmetrics collection and others) are performed. At the beginning of the last section, different ways of downloading data from Internet are shortly presented. Then the relevant sources of financial data are more deeply investigated (in particular web Quandl and corresponding Quandl package for R). Czech projects for open data (still in initial phase) are also shortly described.

Suggested Citation

  • Jiří Sedláček, 2013. "Using R in Finance [Využití R v oblasti financí]," Český finanční a účetní časopis, Prague University of Economics and Business, vol. 2013(4), pages 145-163.
    • Handle: RePEc:prg:jnlcfu:v:2013:y:2013:i:4:id:363:p:145-163
    DOI: 10.18267/j.cfuc.363
    as

    Download full text from publisher

    File URL: http://cfuc.vse.cz/doi/10.18267/j.cfuc.363.html
    Download Restriction: free of charge
    File URL: http://cfuc.vse.cz/doi/10.18267/j.cfuc.363.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.18267/j.cfuc.363?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zeileis, Achim & Grothendieck, Gabor, 2005. "zoo: S3 Infrastructure for Regular and Irregular Time Series," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i06).
    2. Fox, John, 2005. "The R Commander: A Basic-Statistics Graphical User Interface to R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i09).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Malte Willmes & Katherine M Ransom & Levi S Lewis & Christian T Denney & Justin J G Glessner & James A Hobbs, 2018. "IsoFishR: An application for reproducible data reduction and analysis of strontium isotope ratios (87Sr/86Sr) obtained via laser-ablation MC-ICP-MS," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-15, September.
    2. Bouras V. David & Wesseh Wollo, 2020. "Oligopoly Power, Cross-Market Effects and Demand Relatedness: An Empirical Analysis," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 6, September.
    3. Rödiger, Stefan & Friedrichsmeier, Thomas & Kapat, Prasenjit & Michalke, Meik, 2012. "RKWard: A Comprehensive Graphical User Interface and Integrated Development Environment for Statistical Analysis with R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 49(i09).
    4. Nicholas John Tierney & Dianne Cook & Tania Prvan, 2020. "brolgar: An R package to BRowse Over Longitudinal Data Graphically and Analytically in R," Monash Econometrics and Business Statistics Working Papers 43/20, Monash University, Department of Econometrics and Business Statistics.
    5. Michael Berlemann & Julia Freese & Sven Knoth, 2020. "Dating the start of the US house price bubble: an application of statistical process control," Empirical Economics, Springer, vol. 58(5), pages 2287-2307, May.
    6. Stübinger, Johannes & Endres, Sylvia, 2017. "Pairs trading with a mean-reverting jump-diffusion model on high-frequency data," FAU Discussion Papers in Economics 10/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    7. Judith M. Ament & Robin Freeman & Chris Carbone & Anna Vassall & Charlotte Watts, 2020. "An Empirical Analysis of Synergies and Tradeoffs between Sustainable Development Goals," Sustainability, MDPI, vol. 12(20), pages 1-12, October.
    8. Anota, Amélie & Savina, Marion & Bascoul-Mollevi, Caroline & Bonnetain, Franck, 2017. "QoLR: An R Package for the Longitudinal Analysis of Health-Related Quality of Life in Oncology," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i12).
    9. Ohana-Levi, Noa & Munitz, Sarel & Ben-Gal, Alon & Netzer, Yishai, 2020. "Evaluation of within-season grapevine evapotranspiration patterns and drivers using generalized additive models," Agricultural Water Management, Elsevier, vol. 228(C).
    10. Percebois, Jacques & Pommeret, Stanislas, 2019. "Storage cost induced by a large substitution of nuclear by intermittent renewable energies: The French case," Energy Policy, Elsevier, vol. 135(C).
    11. Ferstl, Robert & Hayden, Josef, 2010. "Zero-Coupon Yield Curve Estimation with the Package termstrc," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i01).
    12. Golyandina, Nina & Korobeynikov, Anton & Shlemov, Alex & Usevich, Konstantin, 2015. "Multivariate and 2D Extensions of Singular Spectrum Analysis with the Rssa Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i02).
    13. Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020. "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, vol. 58(1), pages 139-167, January.
    14. Thelma Dede Baddoo & Zhijia Li & Yiqing Guan & Kenneth Rodolphe Chabi Boni & Isaac Kwesi Nooni, 2020. "Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions," IJERPH, MDPI, vol. 17(11), pages 1-26, June.
    15. Hansin Bilgili & Chwen Sheu, 2022. "A Bibliometric Review of the Mathematics Journal," Mathematics, MDPI, vol. 10(15), pages 1-17, July.
    16. Perpiñán Lamigueiro, Oscar, 2012. "solaR: Solar Radiation and Photovoltaic Systems with R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 50(i09).
    17. Georgia Papacharalampous & Hristos Tyralis & Demetris Koutsoyiannis, 2018. "Univariate Time Series Forecasting of Temperature and Precipitation with a Focus on Machine Learning Algorithms: a Multiple-Case Study from Greece," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 5207-5239, December.
    18. Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022. "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers 964, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    19. Golyandina, Nina & Korobeynikov, Anton, 2014. "Basic Singular Spectrum Analysis and forecasting with R," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 934-954.
    20. Nikolaus Umlauf & Georg Mayr & Jakob Messner & Achim Zeileis, 2011. "Why Does It Always Rain on Me? A Spatio-Temporal Analysis of Precipitation in Austria," Working Papers 2011-25, Faculty of Economics and Statistics, Universität Innsbruck.

    More about this item

    Keywords

    Statistics; Finance; R; Program; Data structures; Packages; Data import; Statistika; Datové struktury; Balíčky; Import dat;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:prg:jnlcfu:v:2013:y:2013:i:4:id:363:p:145-163. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Stanislav Vojir (email available below). General contact details of provider: https://edirc.repec.org/data/uevsecz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.