IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v24y2008i3p480-489.html
   My bibliography  Save this article

Quarterly beta forecasting: An evaluation

Author

Listed:
  • Hooper, Vincent J.
  • Ng, Kevin
  • Reeves, Jonathan J.

Abstract

No abstract is available for this item.

Suggested Citation

  • Hooper, Vincent J. & Ng, Kevin & Reeves, Jonathan J., 2008. "Quarterly beta forecasting: An evaluation," International Journal of Forecasting, Elsevier, vol. 24(3), pages 480-489.
  • Handle: RePEc:eee:intfor:v:24:y:2008:i:3:p:480-489
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169-2070(08)00037-X
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
    2. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.
    3. John M. Maheu & Thomas H. McCurdy, 2002. "Nonlinear Features of Realized FX Volatility," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 668-681, November.
    4. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics," Econometrica, Econometric Society, vol. 72(3), pages 885-925, May.
    5. Eric Ghysels, 1998. "On Stable Factor Structures in the Pricing of Risk: Do Time-Varying Betas Help or Hurt?," Journal of Finance, American Finance Association, vol. 53(2), pages 549-573, April.
    6. Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
    7. Ferson, Wayne E & Harvey, Campbell R, 1991. "The Variation of Economic Risk Premiums," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 385-415, April.
    8. Breen, William & Glosten, Lawrence R & Jagannathan, Ravi, 1989. " Economic Significance of Predictable Variations in Stock Index Returns," Journal of Finance, American Finance Association, vol. 44(5), pages 1177-1189, December.
    9. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    10. Martin Martens & Dick van Dijk & Michiel de Pooter, 2004. "Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity," Tinbergen Institute Discussion Papers 04-067/4, Tinbergen Institute.
    11. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    12. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    13. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2000. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," Multinational Finance Journal, Multinational Finance Journal, vol. 4(3-4), pages 159-179, September.
    14. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-1153, December.
    15. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    16. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    17. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    18. Ferson, Wayne E & Korajczyk, Robert A, 1995. "Do Arbitrage Pricing Models Explain the Predictability of Stock Returns?," The Journal of Business, University of Chicago Press, vol. 68(3), pages 309-349, July.
    19. Keim, Donald B. & Stambaugh, Robert F., 1986. "Predicting returns in the stock and bond markets," Journal of Financial Economics, Elsevier, vol. 17(2), pages 357-390, December.
    20. Ferson, Wayne E, 1989. " Changes in Expected Security Returns, Risk, and the Level of Interest Rates," Journal of Finance, American Finance Association, vol. 44(5), pages 1191-1217, December.
    21. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
    22. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    23. Kevin Q. Wang, 2003. "Asset Pricing with Conditioning Information: A New Test," Journal of Finance, American Finance Association, vol. 58(1), pages 161-196, February.
    24. Mandelker, Gershon, 1974. "Risk and return: The case of merging firms," Journal of Financial Economics, Elsevier, vol. 1(4), pages 303-335, December.
    25. Ole E. Barndorff‐Nielsen & Neil Shephard, 2001. "Non‐Gaussian Ornstein–Uhlenbeck‐based models and some of their uses in financial economics," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 167-241.
    26. Ferson, Wayne E & Harvey, Campbell R, 1993. "The Risk and Predictability of International Equity Returns," Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 527-566.
    27. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiong, Tao & Bao, Yukun & Hu, Zhongyi, 2013. "Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices," Energy Economics, Elsevier, vol. 40(C), pages 405-415.
    2. Tolga Cenesizoglu & Denada Ibrushi, 2020. "Predicting Systematic Risk With Macroeconomic And Financial Variables," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 649-673, August.
    3. Taiyong Li & Min Zhou & Chaoqi Guo & Min Luo & Jiang Wu & Fan Pan & Quanyi Tao & Ting He, 2016. "Forecasting Crude Oil Price Using EEMD and RVM with Adaptive PSO-Based Kernels," Energies, MDPI, vol. 9(12), pages 1-21, December.
    4. Ortas, E. & Salvador, M. & Moneva, J.M., 2015. "Improved beta modeling and forecasting: An unobserved component approach with conditional heteroscedastic disturbances," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 27-51.
    5. Guglielmo Maria Caporale & Luis A. Gil-Alana & Miguel Martin-Valmayor, 2020. "Persistence in the Realized Betas: Some Evidence for the Spanish Stock Market," CESifo Working Paper Series 8171, CESifo.
    6. Andrew Phin & Todd Prono & Jonathan J. Reeves & Konark Saxena, 2018. "Level Shifts in Beta, Spurious Abnormal Returns and the TARP Announcement," Finance and Economics Discussion Series 2018-081, Board of Governors of the Federal Reserve System (U.S.).
    7. Doan, Bao & Lee, John B. & Liu, Qianqiu & Reeves, Jonathan J., 2022. "Beta measurement with high frequency returns," Finance Research Letters, Elsevier, vol. 47(PA).
    8. Tolga Cenesizoglu & Jonathan J. Reeves, 2013. "CAPM, Components of Beta and the Cross Section of Expected Returns," CIRANO Working Papers 2013s-09, CIRANO.
    9. Cenesizoglu, Tolga & de Oliveira Ferrazoli Ribeiro, Fabio & Reeves, Jonathan J., 2017. "Beta forecasting at long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 936-957.
    10. Juan Carlos Gutierrez Betancur, 2017. "Robust Estimation of beta and the hedging ratio in Stock Index Futures In the Integrated Latin American Market," Revista Ecos de Economía, Universidad EAFIT, vol. 21(44), pages 37-71, June.
    11. Taiyong Li & Zhenda Hu & Yanchi Jia & Jiang Wu & Yingrui Zhou, 2018. "Forecasting Crude Oil Prices Using Ensemble Empirical Mode Decomposition and Sparse Bayesian Learning," Energies, MDPI, vol. 11(7), pages 1-23, July.
    12. Dimitrios Dadakas & Christos Karpetis & Athanasios Fassas & Erotokritos Varelas, 2016. "Sectoral Differences in the Choice of the Time Horizon during Estimation of the Unconditional Stock Beta," IJFS, MDPI, vol. 4(4), pages 1-13, December.
    13. Nolan, Sheila & O’Malley, Mark, 2015. "Challenges and barriers to demand response deployment and evaluation," Applied Energy, Elsevier, vol. 152(C), pages 1-10.
    14. Phin, Andrew & Prono, Todd & Reeves, Jonathan J. & Saxena, Konark, 2022. "Shifts in beta and the TARP announcement," Finance Research Letters, Elsevier, vol. 47(PB).
    15. Papageorgiou, Nicolas & Reeves, Jonathan J. & Xie, Xuan, 2016. "Betas and the myth of market neutrality," International Journal of Forecasting, Elsevier, vol. 32(2), pages 548-558.

    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. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    2. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    3. Chun Liu & John M. Maheu, 2009. "Forecasting realized volatility: a Bayesian model-averaging approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 709-733.
    4. Michael McAleer & Marcelo Medeiros, 2008. "Realized Volatility: A Review," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 10-45.
    5. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    6. Nielsen, Morten Ørregaard & Frederiksen, Per, 2008. "Finite sample accuracy and choice of sampling frequency in integrated volatility estimation," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 265-286, March.
    7. Maheu, John M. & McCurdy, Thomas H., 2011. "Do high-frequency measures of volatility improve forecasts of return distributions?," Journal of Econometrics, Elsevier, vol. 160(1), pages 69-76, January.
    8. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2008. "Quantile forecasts of daily exchange rate returns from forecasts of realized volatility," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 729-750, September.
    9. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    10. Ortas, E. & Salvador, M. & Moneva, J.M., 2015. "Improved beta modeling and forecasting: An unobserved component approach with conditional heteroscedastic disturbances," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 27-51.
    11. Grané, Aurea & Veiga, Helena, 2007. "The effect of realised volatility on stock returns risk estimates," DES - Working Papers. Statistics and Econometrics. WS ws076316, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    13. Bollerslev, Tim & Kretschmer, Uta & Pigorsch, Christian & Tauchen, George, 2009. "A discrete-time model for daily S & P500 returns and realized variations: Jumps and leverage effects," Journal of Econometrics, Elsevier, vol. 150(2), pages 151-166, June.
    14. Vortelinos, Dimitrios I. & Thomakos, Dimitrios D., 2013. "Nonparametric realized volatility estimation in the international equity markets," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 34-45.
    15. Torben G. Andersen & Luca Benzoni, 2008. "Realized volatility," Working Paper Series WP-08-14, Federal Reserve Bank of Chicago.
    16. repec:wyi:journl:002108 is not listed on IDEAS
    17. Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
    18. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    19. Chun Liu & John M. Maheu, 2008. "Are There Structural Breaks in Realized Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 326-360, Summer.
    20. Nour Meddahi, 2003. "ARMA representation of integrated and realized variances," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 335-356, December.
    21. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.

    More about this item

    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:eee:intfor:v:24:y:2008:i:3:p:480-489. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    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.