Estimation of Continuous-Time Models with an Application to Equity Volatility Dynamics
By Gurdip Bakshi, Nengjiu Ju, Ou-Yang Hui. 2006
135 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/bc62ff3fae62ed4741a25c3b2adc2104a1f01f41
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Mark Podolskij
- Kim Christensen
- Roel C. A. Oomen
- Raphael N. Markellos
- Jan Hannig
- Dimitris Psychoyios
- George Dotsis
- Gabriel G. Drimus
In Finance
- Kim Christensen
- Mark Podolskij
- Roel C. A. Oomen
- Andrew J. Patton
- Suzanne S. Lee
- Raphael N. Markellos
- Jan Hannig
- Martino Grasselli
Citations in the corpus
- Realised quantile-based estimation of the integrated variance (2010, methodology): “(20)–(22) are taken from the empirical study by Bakshi et al. (2006) whereas the parameters for the SV2F-LEVmodel in Eq.”
- Detecting Jumps from Levy Jump Diffusion Processes (2010, methodology): “…drift and diffusion coefficient model as in Merton (1976), the stochastic volatility model in Heston (1993), and its extended versions studied in Bakshi, Ju, and Ou-Yang (2005), which allow nonlinearities in the drift coefficients and more flexible diffusion specifications. any specific…”
- Consistent Modelling of VIX and Equity Derivatives Using a 3/2 plus Jumps Model (2012, result): “These observations support the findings of Bakshi et al. (2006), Carr and Sun (2007) and Drimus (2012) who suggest that the 3/2 model is a good candidate for the pricing of volatility derivatives.”
- Maximum-likelihood estimation for diffusion processes via closed-form density expansions (2013, background): “Along the line of Aı̈t-Sahalia [1–3], a number of substantial refinements and applications emerged in the literature of likelihood-based statistical inference (see surveys in Aı̈t-Sahalia [4]); see, for example, Bakshi and Ju [11], Bakshi, Ju and Ou-Yang [12], Aı̈t-Sahalia”
- Testing for Jumps When Asset Prices are Observed with Noise - A Swap Variance Approach (2008, unknown): “Using VIX data, Bakshi, Ju, and Ou-Yang (2006) estimate a mean reversion coefficient of 8 and volatility of volatility coefficient of 0.43.”
- Jump and volatility risk premiums implied by VIX (2010, unknown): “d ln St = [ r − q − Vt 2 + λ∗ ( μJ − e ∗ J+ σ2 J 2 )] dt + √ VtdW ∗ t + J ∗ t dN ∗ t − λμJdt (3) dVt = (κθ − κ∗Vt) dt + vV γ t dB∗ t (4)”
- Options on realized variance by transform methods: a non-affine stochastic volatility model (2009, methodology): “The estimation for 3 obtained by Bakshi et al. (2006) reinforces similar results from an earlier study by Jones (2003).”
- Estimating affine multifactor term structure models using closed-form likelihood expansions (2010, unknown): “When applied to term structure models, likelihoodmethods usually assume, as do Chen and Scott (1993) and Duffee (2002), that an arbitrary set of benchmark yields are observed without error, with all remaining yields observed with some error; Brandt and He (2002) perform simulated maximum likelihood ”
- Fact or friction: jumps at ultra high frequency (2014, unknown): “…to a return volatility of about 20% annualized, (2) a Heston (1993)-type stochastic volatility (SV) model, using parameter values as in Bakshi, Ju, and Ou-Yang (2006), (3) a two-factor stochastic volatility model with leverage (SV2F-LEV) proposed by Chernov, Gallant, Ghysels, and…”
- Adding and subtracting Black-Scholes: A new approach to approximating derivative prices in continuous-time models (2011, unknown): “Similar expansions are widely used in financial econometrics and empirical finance (see, e.g., Aït-Sahalia, 2002; Schaumburg, 2004; Aït-Sahalia and Yu, 2006; Bakshi, Ju, and Ou-Yang, 2006; Aït-Sahalia and Kimmel, 2007; Xiu, 2010).”
- A jump diffusion model for VIX volatility options and futures (2010, methodology): “Bakshi et al. (2006) estimated various general specifications of diffusion processes with a non-linear drift and diffusion component. The authors considered the squared implied volatility index VIX as a proxy to the unobserved instantaneous variance. Wagner and Szimayer (2004) investigated the prese”
- A closed-form pricing formula for European options under a new stochastic volatility model with a stochastic long-term mean (2020, background): “Moreover, it has been pointed out that the volatility process usually has a non-linear mean-reverting property [4].”
- Hermite Polynomial Based Expansion of European Option Prices (2014, unknown): “Related work also includes Aït-Sahalia and Kimmel (2010, 2007), Bakshi and Ju (2005), and Bakshi et al. (2006).”
- THE 4/2 STOCHASTIC VOLATILITY MODEL: A UNIFIED APPROACH FOR THE HESTON AND THE 3/2 MODEL (2017, methodology): “From a statistical/econometric perspective, Bakshi et al. (2006) tested the dynamics of a Constant Elasticity of Variance (CEV) volatility process with a general power in the diffusion term.”