Bibliography
Andersen, T. G., 1996, Return volatility and trading volume: an information flow interpretation
of stochastic volatility, Journal of Finance 51, 169–204.
Anderson, B. D. O., and J. B. Moore, 1979, Optimal Filtering (Englewood Cliffs: Prentice-
Hall).
Avellaneda, M., P. Levy, and A. Par´as, 1995, Pricing and hedging derivative securities in
markets with uncertain volatilities, Applied Mathematical Finance 2, 73–88.
Bhar, R., C. Chiarella, and W. Runggaldier, 2004, Inferring the forward looking equity
risk premium from derivative prices, Studies in Nonlinear Dynamics and Econometrics
8, 1, Berkeley Economic Press, March 2004.
Bielecki, B., and M. Rutkowski, 2001, Credit Risk: Modeling, Valuation and Hedging
(Springer-Verlag: Berlin).
Bittlingmayer, G., 1998, Output, stock volatility and political uncertainty in a natural
experiment: Germany, 1880-1940, Journal of Finance 53, 2243–2257.
Black, F., and M. Scholes, 1973, The pricing of options and corporate liabilities, Journal
of Political Economy 81, 637–654.
Blattberg, R., and N. Gonedes, 1974, A comparison of stable and student distributions as
statistical models for stock prices, Journal of Business 47, 244–280.
Bollerslev, T., 1986, Generalized autoregressive conditional heteroskedasticity, Journal of
Econometrics 31, 307–327.
, 1987, A conditionally heteroskedastic time series model for speculative prices and
rates of return, Review of Economics and Statistics 69, 542–547.
141
142 BIBLIOGRAPHY
Bucklew, J. A., 1990, Large Deviation Techniques in Decision, Simulation, and Estimation
(Wiley: New York).
Chan, K. S., and J. Ledolter, 1995, Monte carlo em estimation for time series models
involving counts, Journal of the American Statistical Association 90, 242–252.
Chib, S., F. Nardari, and N. Shephard, 2002, Markov chains monte carlo methods for
stochastic volatility models, Journal of Econometrics 108, 281–316.
Choudhury, G. L., D. M. Lucantoni, and W. Whitt, 1994, Multidimensional transform
inversion with applications to the transient m/g/1 queue, Annals of Applied Probability4, 719–740.
Cont, R., 2001, Empirical properties of asset returns: Stylized facts and statistical issues,
Quantitative Finance 1, 223–236.Cox, J., S. Ross, and M. Rubinstein, 1979, Option pricing, a simplified approach, Journal
of Financial Economics 7, 229–263.
David, A., 1997, Fluctuating confidence in stock markets: Implications for returns and
volatility, Journal of Financial and Quantitative Analysis 32, 427–462.
Doucet, A., N. de Freitas, and N. Grodon, 2001, Sequential Monte Carlo Methods in Prac-
tice (Springer-Verlag).
Duan, J. C., 1995, The garch option pricing model, Mathematical Finance 5, 13–32.
, I. Popova, and P. Ritchken, 2002, Option pricing under regime switching, Qunati-
tative Finance 2, 116–132.
Duffie, D., and J. Pan, 1997, An overview of value-at-risk, The Journal of Derivatives pp.
7–49.
Durrett, R., 1996, Probability: Theory and Examples (Duxbury Press: Second Edition).
Efron, B., 1979, Bootstrap methods: Another look at the jackknife, The Annals of Statistics
7, 1–26.
, and R. Tibshirani, 1993, An Introduction to the Bootstrap (Chapman & Hall:
New York).
Embrechts, P., A. McNeil, and D. Straumann, 2002, Correlation and dependence in risk
management: Properties and pitfalls. dempsker m., Risk Management:Value at Risk and
Beyond Cambridge: Cambridge University Press, 176–223.
BIBLIOGRAPHY 143
Engle, R., 1982, Autoregressive conditional heteroscedasticity with estimates of the variance
of united kingdom inflation, Econometrics 50, 987–1007.
Eraker, B., 1998, Mcmc analysis of diffusion models with applications to finance, Working
paper Norwegian School of Economics and Business Administration, 281–316.
Fama, E. F., 1965, The behavior of stock market prices, Journal of Business 38, 34–105.
Findley, D. F., 2005, Asymptotic second-moment properties of out-of-sample forecast errors
of misspecified regarima models and the optimality of gls, Statistica Sinica 15, 447–476.
Fleming, J., and C. Kirby, 2003, A closer look at the relation between garch and stochastic
autoregressive volatility, Journal of Financial Econometrics 1, 3, 365–419., and B. Ostdieka, 1998, Information and volatility linkages in the stock, bond, and
money markets, Journal of Financial Economics 49, 111–137.
F¨ollmer, H., and D. Sondermann, 1986, Hedging of nonredundant contingent claims. in:
Hildenbrand and mas-colell, eds., contributions to mathematical economics, pp. 205–223.
Fuh, C. D., and I. Hu, 2004, Efficient importance sampling for events of moderate deviations
with applications, Biometrika 91, 471–490.
Glasserman, P., 2003, Monte Carlo Methods in Financial Engineering (Springer-Verlag:
New York).
, P. Heidelberger, and P. Shahabuddin, 1999a, Asymptotically optimal importance
sampling and stratification for pricing path-dependent options, Mathematical Finance
9, 117–152.
, 1999b, Importance sampling in the heath-jarrow-morton framework, Journal of
Derivatives 7, 32–50.
, 2000, Variance reduction techniques for estimating value-at-risk, Management
Science 46, 1349–1364.
, 2002, Portfolio value-at-risk with heavy-tailed risk factors, Mathematical Finance
12, 3, 239–269.
Goffinet, B., and D. Wallach, 1996, Optimized importance sampling quantile estimation,
Biometrika 83, 4, 791–800.
Gordon, N. J., D. J. Salmond, and A. F. M. Smith, 1993, Novel approach to nonlinear/nongaussian
bayesian state estimation, IEE Proceedings-F 140(2), 107–113.
144 BIBLIOGRAPHY
Guo, X., 2001, Information and option pricing, Journal of Quantitative Finance 1, 38–44.Hall, P., 1990, Asymptotic properties of the bootstrap for heavy-tail distributions, Annals
of Probability 18, 1342–1360.
, 1991, Bahadur representations for uniform resampling and importance resampling
with applications to asymptotic relative efficiency, The Annals of Statistics 19, 1062–
1072.
, 1992, The Bootstrap and Edgeworth Expansion (Springer-Verlag: New York).
Hamilton, J. D., 1988, Rational-expectations econometric analysis of changes in regime:
an investigation of term structure of interest rates, Journal of Economic Dynamics and
Control 12, 385–423.
, 1989, A new approach to the economic analysis of nonstationary time series and
the business cycle, Econometrica 57, 357–384.
, and R. Susmel, 1994, Autoregressive conditional heteroscedasticity and changes
in regime, Journal of Econometrics 64, 307–333.
Hansen, L. P., and J. A. Scheinkman, 1995, Back to the future: Generating moment
implications for continuous-time markov processes, Econometrica 63, 767–804.
Harrison, J. M., and D. Kreps, 1979, Martingales and multiperiod securities markets,
Journal of Economic Tbeory 20, 381–408.
Harrison, J. M., and S. R. Pliska, 1981, Martingales and stochastic integrals in the theory
of continuous trading, Stochastic Processes and Their Applications 11, 215–260.
Harvey, A. C., 1989, Forecasting Structural Time Series Models and the Kalman Filter
(Cambridge University Press).
Heston, S. L., 1993, A closed-form solution for options with stochastic volatility with
applications to bond and currency options, Review of Financial Studies 6, 327–343.
Horowitz, J. L., 2001, The bootstrap, Handbook of Econometrics 5, 3161–3228.
Hull, J., 2000, Options, Futures, and other derivatives (Prentice-Hall International: Inc.
Fourth Edition).
, and A. White, 1987, The pricing of options on assets with stochastic volatility,
Journal of Finance 2, 281–300.
BIBLIOGRAPHY 145
Jacquier, E., N. G. Poison, and P. E. Rossi, 1994, Bayesian analysis of stochastic volatility
models, Journal of Business and Economic Statistics 12, 371–389.
Johns, M. V., 1988, Importance sampling for bootstrap conference intervals, Journal of the
American Statistical Association 83, 403, 709–714.
Jones, C., 1998, Bayesian estimation of continuous-time finance models, Working paper
Simon School of Business, University of Rochester.
Jorion, P., 2000, Value-at-Risk (McGraw-Hill: New York).
Kim, S., N. Shephard, and S. Chib, 1998, Stochastic volatility: Likelihood inference and
comparison with arch models, Review of Economic Studies 65, 361–393.
Kitagawa, G., 1998, Self-organising state space model, Journal of the American Statistical
Association 93, 1203–1215.
, and Sato, 2000, Nonlinear State Space Model Approach to Financial Time Series
with Time-varying Variance (Proceedings of the Hong Kong International Workshop on
Statistics in Finance: Imperial College Press, London).
Koopman, S. J., A. C. Harvey, J. A. Doornik, and N. Shephard, 1995, Stemp 5.0: Structural
Time Series Analyser (Modeller and Predior: London: Chapman and Hall).
Lin, S. K., C. D. Fuh, and T. J. Ko, 2004, A bootstrap method with importance resampling
to evaluate value-at-risk, Journal of Financial Studies 12, 1, 81–117.Lin, S. K., R. H. Wang, and C. D. Fuh, 2006, Risk management for linear and non-linear
assets – a bootstrap method with importance resampling to evaluate value-at-risk, Asia-
Pacific Financial Markets 13, 261–295.
Mandelbrot, B., 1963, The variation of certain speculative pricings, Journal of Business
36, 394–419.
Masi, G. B. Di, Y. M. Kabanov, and W. J. Runggaldier, 1994, Mean-variance hedging of
options on stocks with markov volatility, Theory of Probability and Its Applications 39,
173–181.
McKean, H. P., 1969, Stochastic Integrals (Acadmemic Press: New York).
Merton, R. C., 1969, Lifetime portfolio selection under uncertainty: The continuous-time
case, Review of Economics and Statistics 51, 247–257.
146 BIBLIOGRAPHY
, 1973, Theory of rational option pricing, Bell Journal of Economics and Manage-
ment Science 4, 141–183.
, 1976, Option pricing when underlying stock returns are discontinuous, Journal of
Financial Economics 3, 125–144.
Morgan, J. P., 1995, Riskmetrics Technical Manual (J. P. Margan: New York).
Nelsen, R. B., 1999, An Introduction to Copulas (Springer-Verlag: New York).
Oh, S., and S. J. Moon, 2006, Comparative analysis of portfolio risk measures based on
evt-copula approach during financial crises, Asia-Pacific Journal of Financial Studies
35, 175–205.
Pan, J., 2002, The jump-risk premia implicit in options: Evidence from an integrated
time-series study, Journal of Financial Economics 63, 3–50.
Rachev, S., and S. Mittnik, 2000, Stable Paretian Models in Finance (John Wiley and
Sons).
Ross, S. A., 1989, Information and volatility, the no-arbitrage martingale approach to
timing and resolution irrelevancy, Journal of Finance 44, 1–8.
Runggaldier, W., 2004, Estimation via stochastic filtering in financial market models, in
: Mathematics of finance (G.Yin and Q.Zhang eds.), Contemporary Mathematics 351,
309–318.
Schweizer, M., 1991, Option hedging for semimartingales, Stochastic Processes and their
Applications 37, 339–363.
So, M. K. P., K. Lam, and W. K. Li, 1998, A stochastic volatility model with markov
switching, Journal of Business & Economic Statistics 16, 244–253.
Stein, E. M., and C. J. Stein, 1991, Stock prices distribution with stochastic volatility, an
analytic approach, Review of Financial Studies 4, 727–752.
Turner, C., R. Startz, and C. Nelson, 1989, A markov model of heteroscedasticity, risk,
and learning in the stock market, Journal of Financial Economics 25, 3–22.
Veronesi, P., 1999, Stock market overreaction to bad news in good times: a rational expectations
equilibrium model, Review of Financial Studies 12, 5, 975–1007.
BIBLIOGRAPHY 147
Wei, G. C. G., and M. A. Tanner, 1990, A monte carlo implementation of the em algorithm
and the poor man’s data augmentation algorithms, Journal of the American Statistical
Association 85, 699–704.
Wells, C., 1996, The Kalman Filter in Finance (Kluwer Academic Publishers: Boston).
Wiggins, J. B., 1987, Option values under stochastic volatility. theory and empirical evidence,
Journal of Financial Economics 19, 351–372.