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Persistent link: https://www.econbiz.de/10003926961
We consider Taylor’s stochastic volatility model (SVM) when the innovations of the hidden log-volatility process have a Laplace distribution (ℓ <Subscript>1</Subscript> exponential density), rather than the standard Gaussian distribution (ℓ <Subscript>2</Subscript>) usually employed. Recently many investigations have employed ℓ <Subscript>1</Subscript>...</subscript></subscript></subscript>
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Persistent link: https://www.econbiz.de/10011656711
This article considers estimation of regression function <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$f$$</EquationSource> </InlineEquation> in the fixed design model <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$Y(x_i)=f(x_i)+ \epsilon (x_i), i=1,\ldots ,n$$</EquationSource> </InlineEquation>, by use of the Gasser and Müller kernel estimator. The point set <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$$\{ x_i\}_{i=1}^{n}\subset [0,1]$$</EquationSource> </InlineEquation> constitutes the sampling design points, and <InlineEquation ID="IEq4"> <EquationSource...</equationsource></inlineequation></equationsource></inlineequation></equationsource></inlineequation></equationsource></inlineequation>
Persistent link: https://www.econbiz.de/10010994970
An asymptotic expansion is given for the autocovariance matrix of a vector of stationary long-memory processes with memory parameters d satisfying 0 < d < 1/2. The theory is then applied to deliver formulae for the long run covariance matrices of multivariate time series with long memory.
Persistent link: https://www.econbiz.de/10005463993
May 2008 A commonly used defining property of long memory time series is the power law decay of the autocovariance function. Some alternative methods of deriving this property are considered working from the alternate definition in terms of a fractional pole in the spectrum at the origin. The...
Persistent link: https://www.econbiz.de/10005593519
In this paper, we extend SiZer (SIgnificant ZERo crossing of the derivatives) to dependent data for the purpose of goodness-of-fit tests for time series models. Dependent SiZer compares the observed data with a specific null model being tested by adjusting the statistical inference using an...
Persistent link: https://www.econbiz.de/10005639670
In this paper, we study the robust estimation for the covariance matrix of stationary multivariate time series. As a robust estimator, we propose to use a minimum density power divergence estimator (MDPDE) designed by Basu et al. (1998). To supplement the result of Kim and Lee (2011), we employ...
Persistent link: https://www.econbiz.de/10011056612
<Para ID="Par1">In the paper the consistency of the circular block bootstrap for the coefficients of the autocovariance function of almost periodically correlated time series is proved. The pointwise and the simultaneous bootstrap equal-tailed confidence intervals for these coefficients are constructed....</para>
Persistent link: https://www.econbiz.de/10011240995
An argument for adjusting Black Scholes implied call deltas downwards for a gamma exposure in a left skewed market is presented. It is shown that when the objective for the hedge is the conservation of capital ignoring the gamma for the delta position is expensive. The gamma adjustment factor in...
Persistent link: https://www.econbiz.de/10011843221