IDEAS home Printed from https://ideas.repec.org/f/pli447.html
   My authors  Follow this author

Jeffrey Todd Lins

(We have lost contact with this author. Please ask them to update the entry or send us the correct address or status for this person. Thank you.)

Personal Details

First Name:Jeffrey
Middle Name:Todd
Last Name:Lins
Suffix:
RePEc Short-ID:pli447
[This author has chosen not to make the email address public]
The above email address does not seem to be valid anymore. Please ask Jeffrey Todd Lins to update the entry or send us the correct address or status for this person. Thank you.

Affiliation

Saxo Bank

http://www.saxobank.com
Denmark, Copenhagen

Research output

as
Jump to: Working papers Articles

Working papers

  1. Johannes Vitalis Siven & Jeffrey Todd Lins, 2009. "Gain/loss asymmetry in time series of individual stock prices and its relationship to the leverage effect," Papers 0911.4679, arXiv.org, revised Nov 2009.
  2. Johannes Vitalis Siven & Jeffrey Todd Lins, 2009. "Temporal structure and gain/loss asymmetry for real and artificial stock indices," Papers 0907.0554, arXiv.org.
  3. Johannes Vitalis Siven & Jeffrey Todd Lins & Jonas Lundbek Hansen, 2008. "A multiscale view on inverse statistics and gain/loss asymmetry in financial time series," Papers 0811.3122, arXiv.org.

Articles

  1. Siven, Johannes Vitalis & Lins, Jeffrey Todd & Szymkowiak-Have, Anna, 2009. "Value-at-Risk computation by Fourier inversion with explicit error bounds," Finance Research Letters, Elsevier, vol. 6(2), pages 95-105, June.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Johannes Vitalis Siven & Jeffrey Todd Lins, 2009. "Gain/loss asymmetry in time series of individual stock prices and its relationship to the leverage effect," Papers 0911.4679, arXiv.org, revised Nov 2009.

    Cited by:

    1. Aaron Wheeler & Jeffrey D. Varner, 2023. "Scalable Agent-Based Modeling for Complex Financial Market Simulations," Papers 2312.14903, arXiv.org, revised Jan 2024.

  2. Johannes Vitalis Siven & Jeffrey Todd Lins, 2009. "Temporal structure and gain/loss asymmetry for real and artificial stock indices," Papers 0907.0554, arXiv.org.

    Cited by:

    1. Kantar, Ersin & Keskin, Mustafa, 2013. "The relationships between electricity consumption and GDP in Asian countries, using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5678-5684.
    2. C. M. Rodr'iguez-Mart'inez & H. F. Coronel-Brizio & A. R. Hern'andez-Montoya, 2019. "A multi-scale symmetry analysis of uninterrupted trends returns of daily financial indices," Papers 1908.11204, arXiv.org.
    3. Niu, Hongli & Wang, Jun & Lu, Yunfan, 2016. "Fluctuation behaviors of financial return volatility duration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 30-40.
    4. Rodríguez-Martínez, C.M. & Coronel-Brizio, H.F. & Hernández-Montoya, A.R., 2021. "A multi-scale symmetry analysis of uninterrupted trends returns in daily financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).

  3. Johannes Vitalis Siven & Jeffrey Todd Lins & Jonas Lundbek Hansen, 2008. "A multiscale view on inverse statistics and gain/loss asymmetry in financial time series," Papers 0811.3122, arXiv.org.

    Cited by:

    1. Johannes Vitalis Siven & Jeffrey Todd Lins, 2009. "Temporal structure and gain/loss asymmetry for real and artificial stock indices," Papers 0907.0554, arXiv.org.
    2. Andrea Giuseppe Di Iura & Giulia Terenzi, 2021. "A Bayesian analysis of gain-loss asymmetry," Papers 2104.06044, arXiv.org.

Articles

  1. Siven, Johannes Vitalis & Lins, Jeffrey Todd & Szymkowiak-Have, Anna, 2009. "Value-at-Risk computation by Fourier inversion with explicit error bounds," Finance Research Letters, Elsevier, vol. 6(2), pages 95-105, June.

    Cited by:

    1. Mitra, Sovan, 2017. "Efficient option risk measurement with reduced model risk," Insurance: Mathematics and Economics, Elsevier, vol. 72(C), pages 163-174.
    2. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    3. Huang, Alex YiHou, 2010. "An optimization process in Value-at-Risk estimation," Review of Financial Economics, Elsevier, vol. 19(3), pages 109-116, August.
    4. Leitao, Álvaro & Oosterlee, Cornelis W. & Ortiz-Gracia, Luis & Bohte, Sander M., 2018. "On the data-driven COS method," Applied Mathematics and Computation, Elsevier, vol. 317(C), pages 68-84.
    5. Alex YiHou Huang, 2010. "An optimization process in Value‐at‐Risk estimation," Review of Financial Economics, John Wiley & Sons, vol. 19(3), pages 109-116, August.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Jeffrey Todd Lins should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can 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.