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The Effects of Random and Discrete Sampling When Estimating Continuous-Time Diffusions

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Author Info
Yacine Ait-Sahalia
Per A. Mykland

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Abstract

High-frequency financial data are not only discretely sampled in time but the time separating successive observations is often random. We analyze the consequences of this dual feature of the data when estimating a continuous-time model. In particular, we measure the additional effects of the randomness of the sampling intervals over and beyond those due to the discreteness of the data. We also examine the effect of simply ignoring the sampling randomness. We find that in many situations the randomness of the sampling has a larger impact than the discreteness of the data.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0276.

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Date of creation: Apr 2002
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Handle: RePEc:nbr:nberte:0276

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Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing

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  1. Cysne, Rubens Penha, 2004. "On the Statistical Estimation of Diffusion Processes - A Partial Survey (Revised Version, Forthcoming Brazilian Review of Econometrics)," Economics Working Papers (Ensaios Economicos da EPGE) 570, Graduate School of Economics, Getulio Vargas Foundation (Brazil). [Downloadable!]
  2. Michael Sørensen, 2008. "Efficient estimation for ergodic diffusions sampled at high frequency," CREATES Research Papers 2007-46, School of Economics and Management, University of Aarhus. [Downloadable!]
  3. Alvaro Cartea & Thilo Meyer-Brandis, 2007. "How Does Duration Between Trades of Underlying Securities Affect Option Prices," Birkbeck Working Papers in Economics and Finance 0721, Birkbeck, Department of Economics, Mathematics & Statistics. [Downloadable!]
  4. Yacine Ait-Sahalia & Per A. Mykland & Lan Zhang, 2005. "Ultra High Frequency Volatility Estimation with Dependent Microstructure Noise," NBER Working Papers 11380, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  5. Yacine Ait-Sahalia & Per A. Mykland, 2003. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," NBER Working Papers 9611, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  6. Yacine Ait-Sahalia, 2002. "Closed-Form Likelihood Expansions for Multivariate Diffusions," NBER Working Papers 8956, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  7. Carrasco, Marine & Chernov, Mikhaël & Florens, Jean-Pierre & Ghysels, Eric, 2000. "Efficient Estimation of Jump Diffusions and General Dynamic Models with a Continuum of Moment Conditions," IDEI Working Papers 116, Institut d'Économie Industrielle (IDEI), Toulouse, revised 2002. [Downloadable!]
    Other versions:
  8. George Hall & John Rust, 2002. "Econometric Methods for Endogenously Sampled Time Series: The Case of Commodity Price Speculation in the Steel Market," NBER Technical Working Papers 0278, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  9. Yacine Ait-Sahalia & Robert Kimmel, 2004. "Maximum Likelihood Estimation of Stochastic Volatility Models," NBER Working Papers 10579, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  10. Yacine Ait-Sahalia, 2003. "Disentangling Volatility from Jumps," NBER Working Papers 9915, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  11. Wayne E. Ferson & Andrea Heuson & Tie Su, 2005. "Weak and Semi-Strong Form Stock Return Predictability Revisited," NBER Working Papers 11021, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  12. Michael Sørensen, 2008. "Parametric inference for discretely sampled stochastic differential equations," CREATES Research Papers 2008-18, School of Economics and Management, University of Aarhus. [Downloadable!]
  13. Yacine Ait-Sahalia & Robert Kimmel, 2002. "Estimating Affine Multifactor Term Structure Models Using Closed-Form Likelihood Expansions," NBER Technical Working Papers 0286, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
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