Does VIX or volume improve GARCH volatility forecasts?

References

• Abu Hassan Shaari Mohd, N., and C. Chin Wen. 2007. “An Empirical Study of Realized Volatility and Trading Volume Dynamics.” International Research Journal of Finance and Economics 9: 160–166.
   Google Scholar
• Ahoniemi, K. 2008. “Modelling and Forecasting the VIX Index.” Unpublished Working Paper, Helsinki School of Economics and HECER.
   Google Scholar
• Akgiray, V. 1989. “Conditional Heteroscedasticity in the Time Series of Stock Returns: Evidence and Forecasts.” Journal of Business 62: 55–80. doi:10.1086/296451.
   Web of Science ®Google Scholar
• Andersen, T. G. 1996. “Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility.” The Journal of Finance 51 (1): 169–204. doi:10.1111/j.1540-6261.1996.tb05206.x.
   Web of Science ®Google Scholar
• Andersen, T. G., and T. Bollerslev. 1998. “Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts.” International Economic Review 39: 885–905. doi:10.2307/2527343.
   Web of Science ®Google Scholar
• Andersen, T. G., T. Bollerslev, P. F. Christoffersen, and F. X. Diebold. 2005. “Volatility Forecasting.” In Handbook of Economic Forecasting, edited by G. Elliot, C. W. J. Granger, and A. Timmermann, 778–878. Amsterdam: Noth-Holland.
   Google Scholar
• Andersen, T. G., T. Bollerslev, P. F. Christoffersen, and F. X. Diebold. 2006. “Volatility and Correlation Forecasting.” In Handbook of Economic Forecasting, edited by G. Elliott, C. W. J. Granger, and A. Timmermann. Amsterdam: North Holland Press.
   Google Scholar
• Ap Gwilym, O., D. G. McMillan, and A. Speight. 1999. “The Intra-Day Relationship Between Volume and Volatility in LIFFE Futures Markets.” Applied Financial Economics 9: 593–604. doi:10.1080/096031099332041.
   Google Scholar
• Basel Committee on Banking Supervision. 1988. International Convergence of Capital Measurement and Capital Standards. Basel: Basel Committee on Banking Supervision, BIS.
   Google Scholar
• Basel Committee on Banking Supervision. 1995. An Internal Model-Based Approach to Market Risk Capital Requirements. Basel: Basel Committee on Banking Supervision, BIS.
   Google Scholar
• Basel Committee on Banking Supervision. 1996. Amendment to the Capital Accord to Incorporate Market Risks. Basel: Basel Committee on Banking Supervision, BIS.
   Google Scholar
• Basel Committee on Banking Supervision. 2006. International Convergence of Capital Measurement and Capital Standards – A revised Framework. Basel: Basel Committee on Banking Supervision, BIS.
   Google Scholar
• Basel Committee on Banking Supervision. 2009. Revisions to the Basel II Market Risk Framework. Basel: Basel Committee on Banking Supervision, BIS.
   Google Scholar
• Becker, R., A. E. Clements, and S. I. White. 2006. “On the Informational Efficiency of S&P500 Implied Volatility.” The North American Journal of Economics and Finance 17: 139–153. doi:10.1016/j.najef.2005.10.002.
   Google Scholar
• Bessembinder, H., and P. J. Seguin. 1993. “Price Volatility, Trading Volume, and Market Depth: Evidence from Futures Markets.” The Journal of Financial and Quantitative Analysis 28 (1): 21–39. doi:10.2307/2331149.
   Web of Science ®Google Scholar
• Blair, B., S.-H. Poon, and S. J. Taylor. 2001. “Forecasting S&P 100 Volatility: The Incremental Information Content of Implied Volatilities and High-Frequency Index Returns.” Journal of Econometrics 105: 5–26. doi:10.1016/S0304-4076(01)00068-9.
   Web of Science ®Google Scholar
• Bollerslev, T. 1986. “Generalized Autoregressive Conditional Heteroskedasticity.” Journal of Econometrics 31: 307–327. doi:10.1016/0304-4076(86)90063-1.
   Web of Science ®Google Scholar
• Bollerslev, T., and D. Jubinski. 1999. “Equity Trading Volume and Volatility: Latent Information Arrivals and Common Long-Run Dependencies.” Journal of Business and Economic Statistics 17 (1): 9–21.
   Web of Science ®Google Scholar
• Boudoukh, J., M. Richardson, and R. F. Whitelaw. 1997. “Investigation of a Class of Volatility Estimators.” The Journal of Derivatives 4: 63–71. doi:10.3905/jod.1997.407973.
   Google Scholar
• Brailsford, T. J., and R. W. Faff. 1996. “An Evaluation of Volatility Forecasting Techniques.” Journal of Banking & Finance 20: 419–438. doi:10.1016/0378-4266(95)00015-1.
   Web of Science ®Google Scholar
• Brock, W. A., and B. D. LeBaron. 1996. “A Dynamic Structural Model for Stock Return Volatility and Trading Volume.” The Review of Economics and Statistics 78 (1): 94–110. doi:10.2307/2109850.
   Web of Science ®Google Scholar
• Brooks, C. 1998. “Predicting Stock Index Volatility: Can Market Volume Help?.” Journal of Forecasting 17: 59–80. doi:10.1002/(ISSN)1099-131X.
   Web of Science ®Google Scholar
• Canina, L., and S. Figlewski. 1993. “The informational Content of Implied Volatility.” Review of Financial Studies 6: 659–681. doi:10.1093/rfs/5.3.659.
   Web of Science ®Google Scholar
• Carr, P., and L. Wu. 2006. “A Tale of Two Indices.” The Journal of Derivatives 13 (3): 13–29. doi:10.3905/jod.2006.616865.
   Google Scholar
• Chiras, D. P., and S. Manaster. 1978. “The Information Content of Option Prices and a Test of Market Efficiency.” Journal of Financial Economics 6: 213–234. doi:10.1016/0304-405X(78)90030-2.
   Web of Science ®Google Scholar
• Chong, Y. Y., and D. F. Hendry. 1986. “Econometric Evaluation of Linear Macroeconomic Models.” The Review of Economic Studies 53: 671–690. doi:10.2307/2297611.
   Web of Science ®Google Scholar
• Christensen, B. J., and N. R. Prabhala. 1998. “The Relation between Implied and Realised Volatility.” Journal of Financial Economics 50 (2): 125–150. doi:10.1016/S0304-405X(98)00034-8.
   Web of Science ®Google Scholar
• Clark, P. K. 1973. “A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices.” Econometrica 41: 135–155. doi:10.2307/1913889.
   Web of Science ®Google Scholar
• Clements, A. C., and J. Fuller. 2012. “Forecasting Increases in the VIX: A time-Varying Long Volatility Hedge for Equities.” NCER Working Paper Series 88.
   Google Scholar
• Copeland, T. E. 1976. “A Model of Asset Trading under the Assumption of Sequential Information Arrival.” The Journal of Finance 31: 1149–1168. doi:10.2307/2326280.
   Web of Science ®Google Scholar
• Corrado, C. J., and T. W. Miller, Jr. 2005. “The Forecast Quality of CBOE Implied Volatility Indexes.” The Journal of Futures Markets 25: 339–373. doi:10.1002/(ISSN)1096-9934.
   Web of Science ®Google Scholar
• Day, T., and C. M. Lewis. 1992. “Stock Market Volatility and the Information Content of Stock Index Options.” Journal of Econometrics 52: 267–287. doi:10.1016/0304-4076(92)90073-Z.
   Web of Science ®Google Scholar
• Dennis, P., S. Mayhew, and C. Stivers. 2006. “Stock Returns, Implied Volatility Innovations, and the Asymmetric Volatility Phenomenon.” Journal of Financial and Quantitative Analysis 41: 381–406. doi:10.1017/S0022109000002118.
   Web of Science ®Google Scholar
• Dimson, E., and P. Marsh. 1990. “Volatility Forecasting without Data Snooping.” Journal of Banking & Finance 14: 399–421. doi:10.1016/0378-4266(90)90056-8.
   Web of Science ®Google Scholar
• Ding, Z., C. W. J. Granger, and R. F. Engle. 1993. “A Long Memory Property of Stock Market Returns and A New Model.” Journal of Empirical Finance 1: 83–106. doi:10.1016/0927-5398(93)90006-D.
   Google Scholar
• Donaldson, G. R., and M. J. Kamstra. 2005. “Volatility Forecasts, Trading Volume and the ARCH versus Option-Implied Volatility Trade-Off.” The Journal of Financial Research 28 (4): 519–538. doi:10.1111/j.1475-6803.2005.00137.x.
   Google Scholar
• Dunis, C., N. M. Kellard, and S. Snaith. 2013. “Forecasting EUR-USD Implied Volatility: The Case of Intraday Data.” Journal of Banking & Finance 37: 4943–4957. doi:10.1016/j.jbankfin.2013.08.028.
   Web of Science ®Google Scholar
• Ederington, L. H., and W. Guan. 2002. “Is Implied Volatility an Informational Efficient and Effective Predictor of Future Volatility?.” Journal of Risk 4: 29–46.
   Google Scholar
• Engle, R. F. 1982. “Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of UK Inflation.” Econometrica 50: 987–1008. doi:10.2307/1912773.
   Web of Science ®Google Scholar
• Engle, R. F. 2003. “Risk and Volatility: Econometric Models and Financial Practice”. Nobel Lecture, December 8, 2003, New York University, USA.
   Google Scholar
• Engle, R. F., and T. Bollerslev. 1986. “Modelling the Persistence of Conditional Variances.” Econometric Reviews 5: 1–50. doi:10.1080/07474938608800095.
   Google Scholar
• Engle, R. F., and G. G. J. Lee. 1999. “A Permanent and Transitory Component Model of Stock Return Volatility.” In Cointegration, Causality and Forecasting: A Festschrift in Honour of Clive W J Granger, edited by R. F. Engle and H. White. Oxford: Oxford University Press.
   Google Scholar
• Epps, T. W., and M. L. Epps. 1976. “The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis.” Econometrica 44: 305–321. doi:10.2307/1912726.
   Web of Science ®Google Scholar
• Fernandes, M., M. Medeiros, and M. Scharth. 2014. “Modeling and Predicting the CBOE Market Volatility Index.” Journal of Banking & Finance 40: 1–10. doi:10.1016/j.jbankfin.2013.11.004.
   Web of Science ®Google Scholar
• Figlewski, S. 1997. “Forecasting Volatility.” Financial Markets, Institutions and Instruments 6 (1): 1–88.
   Google Scholar
• Fleming, J. 1998. “The Quality of Market Volatility Forecasts Implied by S&P 100 Index Option Prices.” Journal of Empirical Finance 5 (4): 317–345. doi:10.1016/S0927-5398(98)00002-4.
   Google Scholar
• Fleming, J., B. Ostdiek, and R. E. Whaley. 1995. “Predicting Stock Market Volatility: A New measure.” Journal of Futures Markets 15 (3): 265–302. doi:10.1002/(ISSN)1096-9934.
   Web of Science ®Google Scholar
• Frennberg, P., and B. Hansson. 1996. “An Evaluation of Alternative Models for Predicting Stock Volatility: Evidence from a Small Stock Market.” Journal of International Financial Markets Institutions and Money 5: 117–134.
   Google Scholar
• Fuertes, A., M. Izzeldin, and E. Kalotychou. 2009. “On Forecasting Daily Stock Volatility: The Role of Intraday Information and Market Conditions.” International Journal of Forecasting 25: 259–281. doi:10.1016/j.ijforecast.2009.01.006.
   Web of Science ®Google Scholar
• Fuertes, A., E. Kalotychou, and N. Todorovic. 2015. “Daily Volume, Intraday and Overnight Returns for Volatility Prediction: Probability or Accuracy?” Review of Quantitative Finance and Accounting 45: 251–278.
   Google Scholar
• Giot, P. 2005. “Relationships Between Implied Volatility Indexes and Stock Index Returns.” The Journal of Portfolio Management 31 (3): 92–100.
   Web of Science ®Google Scholar
• Giot, P., and S. Laurent. 2007. “The Information Content of Implied Volatility in Light of the Jump/Continuous Decomposition of Realized Volatility.” Journal of Futures Markets 27: 337–359. doi:10.1002/(ISSN)1096-9934.
   Web of Science ®Google Scholar
• Glosten, L., R. Jagannathan, and D. Runkle. 1993. “On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks.” The Journal of Finance 48: 1779–1801. doi:10.1111/j.1540-6261.1993.tb05128.x.
   Web of Science ®Google Scholar
• Hansen, P. R., and A. Lunde. 2005. “A Forecast Comparison of Volatility Models: Does Anything Beat A GARCH(1,1)?.” Journal of Applied Econometrics 20: 873–889. doi:10.1002/(ISSN)1099-1255.
   Web of Science ®Google Scholar
• Hao, J., and J. E. Zhang. 2013. “GARCH Option Pricing Models, the CBOE VIX, and Variance Risk Premium.” Journal of Financial Econometrics 11: 556–580. doi:10.1093/jjfinec/nbs026.
   Web of Science ®Google Scholar
• Harris, L. 1986. “Cross-Security Tests of the Mixture of Distributions Hypothesis.” The Journal of Financial and Quantitative Analysis 21: 39–46. doi:10.2307/2330989.
   Web of Science ®Google Scholar
• Harris, L. 1987. “Transaction Data Tests of the Mixture of Distributions Hypothesis.” The Journal of Financial and Quantitative Analysis 22: 127–141. doi:10.2307/2330708.
   Web of Science ®Google Scholar
• Harris, M., and A. Raviv. 1993. “Differences of Opinion Make a Horse Race.” The Review of Financial Studies 6 (3): 473–506. doi:10.1093/rfs/5.3.473.
   Web of Science ®Google Scholar
• Haugom, E., H. Langeland, P. Molnár, and S. Westgaard. 2014. “Forecasting Volatility of the U.S. Oil Market.” Journal of Banking & Finance 47: 1–14. doi:10.1016/j.jbankfin.2014.05.026.
   Web of Science ®Google Scholar
• Heynen, R. C., and H. M. Kat. 1994. “Volatility Prediction: A Comparison of the Stochastic Volatility GARCH(1,1) and EGARCH(1,1) Models.” The Journal of Derivatives 2: 50–65. doi:10.3905/jod.1994.407912.
   Google Scholar
• Hiemstra, C., and J. D. Jones. 1994. “Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation.” Journal of Finance 49 (5): 1639–1664.
   Web of Science ®Google Scholar
• Hol, E. M. J. H. 2003. “Forecasting the Variability of Stock Index Returns with Stochastic Models and Implied Volatility.” In Empirical Studies on Volatility in International Stock Markets, 71–98. Boston, MA: Kluwer Academic Publishers.
   Google Scholar
• Jenning, R., L. Starks, and J. C. Fellingham. 1981. “An Equilibrium Model of Asset Trading with Sequential Information Arrival.” Journal of Finance 36: 143–161. doi:10.1111/j.1540-6261.1981.tb03540.x.
   Web of Science ®Google Scholar
• Jorion, P. 1995. “Predicting Volatility in the Foreign Exchange Market.” The Journal of Finance 50: 507–528. doi:10.1111/j.1540-6261.1995.tb04793.x.
   Web of Science ®Google Scholar
• Kanniainen, J., B. Lin, and H. Yang. 2014. “Estimating and Using GARCH Models with VIX Data for Option Valuation.” Journal of Banking & Finance 43: 200–211. doi:10.1016/j.jbankfin.2014.03.035.
   Web of Science ®Google Scholar
• Karpoff, J. M. 1987. “The Relation Between Price Changes and Trading Volume: A Survey.” The Journal of Financial and Quantitative Analysis 22: 109–126. doi:10.2307/2330874.
   Web of Science ®Google Scholar
• Konstantinidi, E., G. Skiadopoulos, and E. Tzagkaraki. 2008. “Can the Evolution of Implied Volatility Be Forecasted? Evidence from European and US Implied Volatility Indices.” Journal of Banking & Finance 32: 2401–2411. doi:10.1016/j.jbankfin.2008.02.003.
   Web of Science ®Google Scholar
• Koopman, S. J., B. Jungbacker, and E. Hol. 2005. “Forecasting Daily Variability of the S&P 100 Stock Index Using Historical, Realised and Implied Volatility Measurements.” Journal of Empirical Finance 12: 445–475. doi:10.1016/j.jempfin.2004.04.009.
   Google Scholar
• Lamoureux, C. G., and W. D. Lastrapes. 1990. “Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects.” The Journal of Finance 45 (1): 221–229. doi:10.1111/j.1540-6261.1990.tb05088.x.
   Web of Science ®Google Scholar
• Lamoureux, C. G., and W. D. Lastrapes. 1994. “Endogenous Trading Volume and Momentum in Stock Return Volatility.” Journal of Business and Economic Statistics 12: 253–260.
   Web of Science ®Google Scholar
• Latane, H. A., and R. J. Rendleman. 1976. “Standard Deviations of Stock Price Ratios Implied in Option Prices.” Journal of Finance 31: 369–381. doi:10.1111/j.1540-6261.1976.tb01892.x.
   Web of Science ®Google Scholar
• Luu, J. C., and M. Martens. 2003. “Testing the Mixture-Of-Distributions Hypothesis Using “Realised” Volatility.” The Journal of Futures Markets 23 (7): 661–679. doi:10.1002/fut.10077.
   Web of Science ®Google Scholar
• Martens, M., and J. Zein. 2002. “Predicting Financial Volatility: High-frequency Time-series Forecasts vis-à-vis Implied Volatility.” Working Paper, Erasmus University, Rotterdam.
   Google Scholar
• Mencia, J., and E. Sentana. 2013. “Valuation of VIX Derivatives.” Journal of Financial Economics 108 (2): 367–391. doi:10.1016/j.jfineco.2012.12.003.
   Web of Science ®Google Scholar
• Mincer, J., and V. Zarnowitz. 1969. “The Evaluation of Economic Forecasts.” In Economic Forecasts and Expectations, edited by J. Mincer, 3–46. New York: Columbia University Press.
   Google Scholar
• Nelson, D. B. 1991. “Conditional Heteroskedasticity in Asset Returns: A New Approach.” Econometrica 59 (2): 347–370. doi:10.2307/2938260.
   Web of Science ®Google Scholar
• Pagan, A. R., and G. W. Schwert. 1990. “Alternative Models for Conditional Stock Volatility.” Journal of Econometrics 45: 267–290. doi:10.1016/0304-4076(90)90101-X.
   Web of Science ®Google Scholar
• Poon, S., and C. W. J. Granger. 2003. “Forecasting Volatility in Financial Markets: A Review.” Journal of Economic Literature 41 (2): 478–539. doi:10.1257/.41.2.478.
   Web of Science ®Google Scholar
• Richardson, M., and T. Smith. 1994. “A Direct test of the Mixture of Distributions Hypothesis: Measuring the Daily Flow of Information.” The Journal of Financial and Quantitative Analysis 29: 101–116. doi:10.2307/2331193.
   Web of Science ®Google Scholar
• Schwert, G. W., and P. J. Seguin. 1990. “Heteroskedasticity in Stock Returns.” The Journal of Finance 45: 1129–1155. doi:10.1111/j.1540-6261.1990.tb02430.x.
   Web of Science ®Google Scholar
• Simons, D. P. 2003. “The NASDAQ Volatility Index During and After the Bubble.” The Journal of Derivatives 11 (2): 9–24. doi:10.3905/jod.2003.319213.
   Google Scholar
• Smirlock, M., and L. Starks. 1984. A Transactions Approach to Testing Information Arrival Models.” Typescript, St. Louis: University of Washington.
   Google Scholar
• Szakmary, A., E. Ors, J. K. Kim, and W. Davidson. 2003. “The Predictive Power of Implied Volatility: Evidence from 35 Futures Markets.” Journal of Banking & Finance 27: 2151–2175. doi:10.1016/S0378-4266(02)00323-0.
   Web of Science ®Google Scholar
• Tauchen, G. E., and M. Pitts. 1983. “The Price Variability-Volume Relationship on Speculative Markets.” Econometrica 51: 485–505. doi:10.2307/1912002.
   Web of Science ®Google Scholar
• Taylor, N. 2008. “Can Idiosyncratic Volatility Help Forecast Stock Market Volatility?.” International Journal of Forecasting 24: 462–479. doi:10.1016/j.ijforecast.2008.06.001.
   Web of Science ®Google Scholar
• Wagner, N., and T. A. Marsh. 2005. “Surprise Volume and Heteroskedasticity in Equity Market Returns.” Quantitative Finance 5 (2): 153–168. doi:10.1080/14697680500147978.
   Web of Science ®Google Scholar
• Wang, J. 1994. “A Model of Competitive Stock Trading Volume.” Journal of Political Economy 10: 127–168. doi:10.1086/261924.
   Web of Science ®Google Scholar
• Whaley, R. E. 2009. “Understanding the VIX.” The Journal of Portfolio Management 35: 98–105. doi:10.3905/JPM.2009.35.3.098.
   Web of Science ®Google Scholar
• Yang, M. J., and M.-Y. Liu. 2012. “The Forecasting Power of the Volatility Index in Emerging Markets: Evidence from the Taiwan Stock Market.” International Journal of Economics and Finance 4 (2): 217–231. doi:10.5539/ijef.v4n2p217.
   Google Scholar
• Yu, W. W., E. C. Lui, and J. W. Wang. 2010. “The Predictive Power of the Implied Volatility of Options Traded OTC and on Exchanges.” Journal of Banking and Finance 34: 1–11. doi:10.1016/j.jbankfin.2009.06.017.
   Web of Science ®Google Scholar