[PDF] Top 20 Semiparametric estimation of diffusion models with applications in finance

... of semiparametric two-step estimators: In the first step a function is (nonparam etrically) estim ated, while in the second step this is used to obtain an estim ator of a finite-dimensional param ...profiled ... See full document

... various diffusion models, the new strategy enables us to select underlying assets across different markets and taking different price patterns into ... See full document

... with a(.) and 6 (.) being finite order polynomials whose zeros are outside the unit circle in the complex plane. This case was indeed considered by Baillie, Bollerslev, and Mikkelsen (1996) but with 0 a free parameter ... See full document

... regression models under the α–mixing condition complement some existing results under the β–mixing ...nonparametric estimation and testing of time series with the α–mixing ...(1.2). Applications of ... See full document

... of models for which this is the case in a finance context are the AR (Autoregressive) model, the MA (Moving Average) model, and the NLMA (Non-Linear Moving Average) ... See full document

... The semiparametric AFT model assumes that the random errors are i ...existing estimation methods rely on this assumption. However, in many applications, the random errors tend to depend on the ... See full document

... For certain forms of diffusion with time delay, the analytical solutions are possible to find [49] [50]. But for general solutions of (3.2), little is known of the analytical solution, and numerical methods come ... See full document

... The first major shortcoming in the literature is the relative lack of effort made to de- velop methods for actually applying the unique properties of unifractal and multifractal processes to common financial problems, ... See full document

... linear semiparametric spatial models recently proposed in the literature (Su & Jin, 2010; Su, 2012; Zhang, 2013; Sun, Hongjia, Zhang & Lu, 2014), its distinct feature is that it permits the spatial ... See full document

... filtering applications is formed by constructing a matrix with a dimension of 181 × 3 over the period 30 April 1998 – 30 April 2013 with the TED, VIX and MktIll in the first, second and third columns, ... See full document

... Estimation in semiparametric spatial regression Gao, Jiti and Lu, Zudi and Tjostheim, Dag The University of Adelaide, London School of Economics, The University of Bergen... marginal add[r] ... See full document

... In p articu lar, th e approach of Robinson (1988e) does not require nonparam etric regression in forming instrum ent and makes fuller use of th e sam ple of data. It can be combined w ith th e use of nonparam etric ... See full document

... auction models are many. First, auction models lead to highly nonlinear econometric models through the equilibrium ...auction models may not lead to tractable solutions rendering even more ... See full document

... The purpose of this paper is then to develop estimators for a spatial semiparametric (par- tially linear) structure and to derive their asymptotic properties. In the companion paper by Lu, et al (2005), the ... See full document

... Economic exchange games represent a relevant quan- titative research paradigm to evaluate the social ex- change, in terms of the subject’s internal norms assess- ment for the fairness in an exchange, and they require ... See full document

... self-consistent estimation algorithm, and Groeneboom and Wellner (1992) introduced the iterative convex minorant (ICM) algorithm to compute the nonparametric maximum likelihood estimator (NPMLE) for the dis- ... See full document

... (zeppelin compartment). A fiber segment is defined as the local bundle of aligned sticks with the extra‐neurite space surrounding them. Voxels are composed of a large number of fiber segments. The SM consists of the ... See full document

... implement semiparametric methods for estimating binary response models with endogenous ...with semiparametric estimation in single index binary response models to the continuous ... See full document

... derivative matrix exists. If it does, then it may not be easily computable in models in which the estimator of the nuisance parameter is not explicit. To overcome these problems, discretized versions of the ... See full document

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