IDEAS home Printed from https://ideas.repec.org/r/aah/create/2011-46.html
   My bibliography  Save this item

Forecasting with Option Implied Information

Citations

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


Cited by:

  1. Costas Lambrinoudakis & Michael Neumann & George Skiadopoulos, 2014. "Capital Structure and Financial Flexibility: Expectations of Future Shocks," Working Papers 731, Queen Mary University of London, School of Economics and Finance.
  2. Ricardo Crisóstomo & Lorena Couso, 2018. "Financial density forecasts: A comprehensive comparison of risk‐neutral and historical schemes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 589-603, August.
  3. Pablo Neudorfer, 2022. "Tail risk in the fossil fuel industry: an option implied analysis around the unburnable carbon news," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(1), pages 493-511, March.
  4. Cao, Charles & Simin, Timothy & Xiao, Han, 2019. "Predicting the equity premium with the implied volatility spread," MPRA Paper 103651, University Library of Munich, Germany.
  5. Julien Chevallier & Benoît Sévi, 2013. "A Fear Index to Predict Oil Futures Returns," Working Papers 2013.62, Fondazione Eni Enrico Mattei.
  6. Bruno Feunou & Jean-Sébastien Fontaine & Abderrahim Taamouti & Roméo Tédongap, 2014. "Risk Premium, Variance Premium, and the Maturity Structure of Uncertainty," Review of Finance, European Finance Association, vol. 18(1), pages 219-269.
  7. Renato Faccini & Eirini Konstantinidi & George Skiadopoulos & Sylvia Sarantopoulou-Chiourea, 2019. "A New Predictor of U.S. Real Economic Activity: The S&P 500 Option Implied Risk Aversion," Management Science, INFORMS, vol. 65(10), pages 4927-4949, October.
  8. Herrera, Rodrigo & Piña, Marco, 2024. "Market risk modeling with option-implied covariances and score-driven dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
  9. Baule, Rainer & Korn, Olaf & Saßning, Sven, 2013. "Which beta is best? On the information content of option-implied betas," CFR Working Papers 13-11, University of Cologne, Centre for Financial Research (CFR).
  10. Vilkovz, Grigory & Xiaox, Yan, 2013. "Option-implied information and predictability of extreme returns," SAFE Working Paper Series 5, Leibniz Institute for Financial Research SAFE.
  11. Greenwood-Nimmo, Matthew & Nguyen, Viet Hoang & Rafferty, Barry, 2016. "Risk and return spillovers among the G10 currencies," Journal of Financial Markets, Elsevier, vol. 31(C), pages 43-62.
  12. Yaw‐Huei Wang & Kuang‐Chieh Yen, 2018. "The information content of option‐implied tail risk on the future returns of the underlying asset," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(4), pages 493-510, April.
  13. Annalisa Molino & Carlo Sala, 2021. "Forecasting value at risk and conditional value at risk using option market data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1190-1213, November.
  14. repec:ipg:wpaper:2014-053 is not listed on IDEAS
  15. Lambrinoudakis, Costas & Skiadopoulos, George & Gkionis, Konstantinos, 2019. "Capital structure and financial flexibility: Expectations of future shocks," Journal of Banking & Finance, Elsevier, vol. 104(C), pages 1-18.
  16. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
  17. Brinkmann, Felix & Kempf, Alexander & Korn, Olaf, 2014. "Forward-looking measures of higher-order dependencies with an application to portfolio selection," CFR Working Papers 13-08 [rev.], University of Cologne, Centre for Financial Research (CFR).
  18. Brinkmann, Felix & Korn, Olaf, 2014. "Risk-adjusted option-implied moments," CFR Working Papers 14-07, University of Cologne, Centre for Financial Research (CFR).
  19. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2023. "The sum of all fears: Forecasting international returns using option-implied risk measures," Journal of Banking & Finance, Elsevier, vol. 146(C).
  20. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
  21. Florian Ielpo & Benoît Sévi, 2014. "Forecasting the density of oil futures," Working Papers 2014-601, Department of Research, Ipag Business School.
  22. Ricardo Crisóstomo, 2021. "Estimating real‐world probabilities: A forward‐looking behavioral framework," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1797-1823, November.
  23. Peter Christoffersen & Xuhui (Nick) Pan, 2014. "Equity Portfolio Management Using Option Price Information," CREATES Research Papers 2015-05, Department of Economics and Business Economics, Aarhus University.
  24. Guidolin, Massimo & Wang, Kai, 2023. "The empirical performance of option implied volatility surface-driven optimal portfolios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
  25. Matthew Greenwood-Nimmo & Daan Steenkamp & Rossouw van Jaarsveld, 2022. "CaninformationonthedistributionofZARreturnsbeusedtoimproveSARBsZARforecasts," Working Papers 11035, South African Reserve Bank.
  26. repec:dau:papers:123456789/11714 is not listed on IDEAS
  27. Li, Yifan & Nolte, Ingmar & Pham, Manh Cuong, 2024. "Parametric risk-neutral density estimation via finite lognormal-Weibull mixtures," Journal of Econometrics, Elsevier, vol. 241(2).
  28. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
  29. Kazuhiro Hiraki & George Skiadopoulos, 2018. "The Contribution of Frictions to Expected Returns," Working Papers 874, Queen Mary University of London, School of Economics and Finance.
  30. Marco Piña & Rodrigo Herrera, 2021. "Risk modeling with option-implied correlations and score-driven dynamics," Working Papers Central Bank of Chile 932, Central Bank of Chile.
  31. Wei-han Liu, 2019. "National culture effects on stock market volatility level," Empirical Economics, Springer, vol. 57(4), pages 1229-1253, October.
  32. Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
  33. Kempf, Alexander & Korn, Olaf & Saßning, Sven, 2014. "Portfolio optimization using forward-looking information," CFR Working Papers 11-10 [rev.], University of Cologne, Centre for Financial Research (CFR).
  34. Sévi, Benoît, 2014. "Forecasting the volatility of crude oil futures using intraday data," European Journal of Operational Research, Elsevier, vol. 235(3), pages 643-659.
  35. Ricardo Crisóstomo, 2021. "Estimación de probabilidades representativas del mundo real: importancia de los sesgos conductuales," CNMV Documentos de Trabajo CNMV Documentos de Trabaj, CNMV- Comisión Nacional del Mercado de Valores - Departamento de Estudios y Estadísticas.
  36. Marie-Hélène Gagnon & Gabriel Power & Dominique Toupin, 2018. "Forecasting International Index Returns using Option-implied Variables," Cahiers de recherche 1807, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
  37. Buss, Adrian & Vilkov, Grigory & ,, 2018. "Expected Correlation and Future Market Returns," CEPR Discussion Papers 12760, C.E.P.R. Discussion Papers.
  38. Bo Young Chang & Bruno Feunou, 2013. "Measuring Uncertainty in Monetary Policy Using Implied Volatility and Realized Volatility," Staff Working Papers 13-37, Bank of Canada.
  39. Cao, Charles & Simin, Timothy & Xiao, Han, 2020. "Predicting the equity premium with the implied volatility spread," Journal of Financial Markets, Elsevier, vol. 51(C).
  40. Brinkmann, Felix & Kempf, Alexander & Korn, Olaf, 2013. "Forward-looking measures of higher-order dependencies with an application to portfolio selection," CFR Working Papers 13-08, University of Cologne, Centre for Financial Research (CFR).
  41. Shuaiqiang Liu & 'Alvaro Leitao & Anastasia Borovykh & Cornelis W. Oosterlee, 2020. "On Calibration Neural Networks for extracting implied information from American options," Papers 2001.11786, arXiv.org.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.