Properties of Realized Variance Under Alternative Sampling Schemes

By Roel C. A. Oomen. 2006

175 citations recorded by the source corpus.

Subfields: Finance

View Paper: https://www.semanticscholar.org/paper/ebbb749d15838ccb42a62baf36b72d54397fa6b4

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Citations in the corpus

Optimal combinations of realised volatility estimators (2009, background): “…(2008, in press), Barndorff-Nielsen and Shephard (2002, 2004, 2006), Christensen and Podolskij (2007), Bandi and Russell (2006, 2008), Christensen, Oomen, and Podolskij (2008), Hansen and Lunde (2006a), Large (2005), Oomen (2006) and Zhang, Mykland, and Aı̈t-Sahalia (2005) amongst others. ters.”
Covariance measurement in the presence of non-synchronous trading and market microstructure noise (2011, unknown): “V (HYk) = σ 1σ 2 2 ( λ1 + λ2 λ1λ2 + ρ2 λ1 + λ2 ( λ2 λ1 + λ1 λ2 )) (k + 1) + 2σ 1ξ 2 2 + 2σ 2 2ξ 2 1 + 4ξ 2 1ξ 2 2 λ1λ2 λ1 + λ2 k−1 (9) From this the optimal – MSE minimizing – sampling frequency can be worked out explicitly as: k∗ = 2 √ λ1λ2γ1γ2 (λ1 + λ2) 2 + ρ2 ( λ2 + λ 2 1 ) (10) where γi = √ λiξi”
Realized Volatility: A Review (2008, methodology): “Compared with the standard literature, Oomen ( 2006 ) proposed a pure jump process for the high frequency-prices, which allows for the analysis of the following sampling schemes: calendar time, business time, and transaction time sampling.”
Market microstructure noise, integrated variance estimators, and the accuracy of asymptotic approximations (2011, background): “4 The estimator's …nite sample MSE properties in the context of a pure jump process of …nite variation for the equilibrium price are studied by Oomen (2006). an unrestricted q with w 0 = 1 and w s = m ms : The limiting features of b V as a " near-consistent " estimator of the integrated variance of…”
Financial econometric analysis at ultra-high frequency: Data handling concerns (2006, unknown): “Blume and Goldstein (1997) details how they eliminated NYSE quote data which appeared to be affected by errors; Oomen (2006) suggests a filter for detecting outliers for the IBM stock; Vergote (2005) raises concerns about the widespread use of the 5-s rule suggested by Lee and Ready (1991) to sync”
Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns (2010, methodology): “Most strikingly, Peters and de Vilder (2006) make no adjustments for jumps and rely on tests with much less power than is the case in the current paper.”
Realized volatility with stochastic sampling (2010, background): “Oomen [23] and Griffin and Oomen [9] found that tick time sampling, where prices are sampled with every price change, is superior to calendar time sampling, that is, the equidistant sampling scheme, in terms of the mean squared error.”
Data-based ranking of realised volatility estimators (2011, methodology): “…existing theory: estimators based on trade prices versus quote prices; estimators de ned using calendar-time sampling versus tick-time sampling (see Oomen, 2006, for a comparison of these estimators); or estimators based on very di¤erent assumptions, such as the multi-scale sub-sampled realised…”
Realized range-based estimation of integrated variance (2007, unknown): “Oomen (2005) gives a characterization of RV under alternative sampling schemes.”
Subsampling Realised Kernels (2007, background): “(2006). A particularly interesting sampling scheme is that known as business time sampling, see e.g. Oomen (2005, 2006) .”
Out of sample forecasts of quadratic variation (2008, methodology): “The behavior of this estimator has been studied by Zumbach et al. (2002). Efficient likelihood estimation of σ is studied by Aı̈t-Sahalia et al.”
Testing for Jumps When Asset Prices are Observed with Noise - A Swap Variance Approach (2008, unknown): “…for instance Aı̈t-Sahalia, Mykland, and Zhang, 2005a,b; Bandi and Russell, 2006; Barndorff-Nielsen, Hansen, Lunde, and Shephard, 2006; Hansen and Lunde, 2006; Christensen, Podolskij, and Vetter, 2006; Large, 2005; Oomen, 2005, 2006b; Zhang, 2006; Zhang, Mykland, and Aı̈t-Sahalia, 2005; Zhou, 1996).”
Fact or friction: jumps at ultra high frequency (2014, unknown): “It drops out when we compute RV ∗ − BV ∗ and so it is of limited importance. b Here, we use the estimator proposed by Oomen (2006), which is deﬁned as ω 2 is an estimator of the noise variance ω 2 .”
No-Arbitrage Semi-Martingale Restrictions for Continuous-Time Volatility Models subject to Leverage Effects, Jumps and i.i.d. Noise: Theory and Testable Distributional Implications (2007, background): “In a different context, Oomen (2006) has recently advocated the use of transaction time sampling in the construction of superior realized volatility estimates.”
Pre-Averaging Estimators of the Ex-Post Covariance Matrix in Noisy Diffusion Models with Non-Synchronous Data (2010, unknown): “This reaﬃrms previous empirical work (see, e.g., Barndorﬀ-Nielsen, Hansen, Lunde, and Shephard, 2008b; Griﬃn and Oomen, 2006; Voev and Lunde, 2007), so these results are not surprising or novel.”
Moving Average-Based Estimators of Integrated Variance (2008, methodology): “APPENDIX C: ALTERNATIVE ESTIMATORS In Figures 2–5 we benchmark the MA(1) and MA(20) estimators to two realized kernel estimator suggested in Zhou (1996) and Hansen and Lunde (2006) and the so-called Two-Scale measures of IV, from Zhang et al.”