References
- Andersen, T., Bollerslev, T. (1998). Answering the skeptics: Yes, standard volatility models do provide accurate forecasts. International Economic Review 39:885–906.
- Andersen, T. G., Bollerslev, T., Diebold, F. X. (2007). Roughing it up: Including jump components in the measurement, modeling and forecasting of return volatility. Review of Economics and Statistics 89:701–720.
- Andersen, T. G., Bollerslev, T., Diebold, F. X., Ebens, H. (2001a). The distribution of stock return volatility. Journal of Financial Economics 61:43–76.
- Andersen, T. G., Bollerslev, T., Diebold, F. X., Labys, P. (2000). Great realizations. Risk Magazine 13:105–108.
- Andersen, T. G., Bollerslev, T., Diebold, F. X., Labys, P. (2001b). The distribution of realized exchange rate volatility. Journal of American Statistical Association 96(453):42–55.
- Andersen, T. G., Bollerslev, T., Diebold, F. X., Labys, P. (2003). Modeling and forecasting realized volatility. Econometrica 71:529–626.
- Andersen, T. G., Dobrev, D., Schaumburg, E. (2009). Jump-Robust Volatility Estimation using Nearest Neighbor Truncation. Journal of Econometrics 169(1):75–93.
- Bandi, F., Russell, J. (2008). Microstructure Noise, Realized Variance, and Optimal Sampling. The Review of Economic Studies 75(2):339–369.
- Barndorff-Nielsen, O. E., Graversen, S. E., Jacod, J., Podolskij, M., Shephard, N. (2006). A central limit theorem for realised power and bipower variations of continuous semi-martingales. Journal of Financial Econometrics 2(1):1–37.
- Barndorff-Nielsen, O. E., Shephard, N. (2002). Estimating quadratic variation using realised volatility. Journal of Applied Econometrics 17:457–477.
- Barndorff-Nielsen, O. E., Shephard, N. (2004). Power and bipower variation with stochastic volatility and jumps. Journal of Financial Econometrics 2(1):1–37.
- Barndorff-Nielsen, O. E., Shephard, N., Winkel, M. (2006). Limit theorems for multipower variation in the presence of jumps. Stochastic Processes and their Applications 116:796–806.
- Blair, J. B., Poon, S. H., Taylor, S. J. (2001). Forecasting S&P100 volatility: The incremental information content of implied volatilities and high frequency index returns. Journal of Econometrics 105:5–26.
- Bollerslev, T., Kretschmer, U., Pigorsch, C., Tauchen, G. (2009). A discrete-time model for daily S&P 500 returns and realized variations: Jumps and leverage effects. Journal of Econometrics 150:5–26.
- Bolt, W., Demertzis, M., Diks, C., Hommes, C., van der Leij, M. (2014). Identifying Booms and Busts in House Prices under Heterogeneous Expectations. CeNDEF Working Paper 14-13, University of Amsterdam.
- Cheong, C. W. (2013). The computational of stock market volatility from the perspective of heterogeneous market hypothesis. Economic Computation and Economic Cybernetics Studies and Research 47(2):247–260.
- Cheong, C. W., Isa, Z., Abu Hassan, S. M. N. (2007). Modelling financial observable-volatility using long memory models. Applied Financial Economics Letters 3:201–208.
- Chiarella, C. (1992). The dynamics of speculative behavior. Annals Operation Research 37:101–123.
- Christoffersen, P. (1998). Evaluating Interval Forecasts. International Economic Review 39(4):841–862.
- Corsi, F. (2009). A simple approximate long memory model of realized volatility. Journal of Financial Econometrics 7:174–196.
- Corsi, R., Mittnik, S., Pigorsch, C., Pigorsch, U. (2008). The volatility of realized volatility. Econometric Reviews 27:46–78.
- Dacorogna, M., MÄuller, U., Dav, R., Olsen, R., Pictet, O. (1998). Modelling short-term volatility with GARCH and HARCH models. In: C. Dunis, B. Zhou, eds. Nonlinear Modelling of High Frequency Financial Time Series. John Wiley: Chichester, pp. 161–176.
- Dacorogna, M., Ulrich, M., Richard, O., Oliveier, P. (2001). Defining efficiency in heterogeneous markets. Quantitative Finance 1:198–201.
- Day, R. H., Huang, W. (1990). Bulls, bears and market sheep. Journal of Economic Behavior Organization l14(3):299–329.
- Dieckmann, S., Gallmeyer, M. (2013). Rare event risk and emerging market debt with heterogeneous beliefs. Journal of International Money and Finance 33:163–187.
- Dufour, J. M., Kurz-Kim, J. R. (2014). Heavy tails and stable Paretian distributions in econometrics. Journal of Econometrics 181(1):1–2.
- Engle, R., Manganelli, S. (2004). CAViaR: Conditional autoregressive value at risk by regression quantiles. Journal of Business & Economic Statistics 22(4):367–381.
- Engle, R., Gallo, G. M. (2006). A multiple indicators model for volatility using intradaily data. Journal of Econometrics 127:3–27.
- Fama, E. (1998). Market efficiency, long-term returns, and behavioral finance. Journal of Financial Economics 49:283–306.
- Hansen, P. R., Lunde, A. (2006). Realized variance and market microstructure noise. Journal of Business and Economic Statistics 24:127–218.
- Jorion, P. (2006). Value-at-Risk: The New Benchmark for Controlling Market Risk. 3rd ed. Chicago: McGraw-Hill.
- Koutmos, D. (2012). An intertemporal capital asset pricing model with heterogeneous expectations. Journal of International Financial Markets Institutions and Money 22(5):1176–1187.
- Kouwenberg, R., Zwinkels, R. C. J. (2011). Chasing Trends in the U.S. Housing Market. Erasmus University Rotterdam Working Paper.
- Kupiec, P. (1995). Techniques for Verifying the Accuracy of Risk Measurement Models. The Journal of Derivative 3(2):73–84.
- Lux, T., Marchesi, M. (1999). Scaling and criticality in a stochastic multi-agent model of financial market. Nature 397:498–500.
- Maheu, J. M., McCurdy, T. H. (2004). News arrival, jump dynamics and volatility components for individual stock returns. Journal of Finance 59:755–793.
- Malkiel, B. G. (2003). The efficient market hypothesis and its critics. The Journal of Economic Perspectives 17(1):59–82.
- Martens, M., Van Dijk, D. (2007). Measuring volatility with the realized range. Journal of Econometrics 138(1):181–207.
- Muller, U., Dacorogna, M., Dav, R., Olsen, R., Pictet, O., von Weizsacker, J. (1997). Volatilities of different time resolutions - analysing the dynamics of market components. Journal of Empirical Finance 4:213–239.
- Muller, U., Dacorogna, M., Dav, R., Pictet, O., Olsen, R., Ward, J. (1993). Fractals and intrinsic time - a challenge to econometricians. XXXIXth International AEA Conference on Real Time Econometrics, 14-15 Oct 1993, Luxembourg.
- Nelson, D. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica 59:347–370.