1. [1] Ackerberg, D. A. 2000. “Importance Sampling and the Method of Simulated Moments.” Department of Economics, Boston University and NBER.
  2. [2] Aihara, S., Bagchi, A. 2000. “Estimation of Stochastic Volatility in the Hull-White Model.” Applied Mathematical Finance 7.
  3. [3] Aihara, S., Bagchi,2006. Filtering and identification of Heston's stochastic volatility model and its market risk. Journal of Economic Dynamics and Control, 30 (12).
  4. [4] Aït-Sahalia, Y. 2001. “Telling from Discrete Data whether the Underlying Continuous-Time Model Is a Diffusion.” Journal of Finance 57 (5).
  5. [5] Aït-Sahalia, Y. 2002. “Maximum Likelihood Estimation of Discretely Sampled Diffusions: A Closed-Form Approximation Approach.” Econometrica 70 (1).
  6. [6] Aït-Sahalia, Y. 2003. “Disentangling Volatility from Jumps.” NBER Working Paper No. 9915, Princeton University.
  7. [7] Aït-Sahalia, Y., Wang, Y., Yared, F. 2001. “Do Option Markets Correctly Price the Probabilities of Movement of the Underlying Asset?.” Journal of Econometrics 101.
  8. [8] Alexander, C. 1999. “A Primer on the Orthogonal GARCH Model.” ISMA Center, University of Reading.
  9. [9] Alexander, C. 2000. “Principles of Skew.” RISK.
  10. [10] Alexander, C. 2001. Market Models: A Guide to Financial Data Analysis. New York: John Wiley & Sons.
  11. [11] Alizadeh, S., Brandt, W.M., Diebold, X.F. 2002. “Range-Based Estimation of Stochastic Volatility Models.” Journal of Finance, 57 (3).
  12. [12] Amin, K. I., Ng, V. 1993. “Option Valuation with Systematic Stochastic ...

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