This paper deals with efficient estimation in exchangeable nonlinear dynamic panel models with common unobservable factor. The specification accounts for both micro- and macro-dynamics, induced by the lagged individual observation and the common stochastic factor, respectively. For large...

Our paper introduces a new estimation method for arbitrary temporal heterogeneityin panel data models. The paper provides a semiparametric method for estimatinggeneral patterns of cross-sectional specific time trends. The methods proposed in thepaper are related to principal component analysis...

This paper considers a paradigm financial markets trades booking and valuation, data subscription and portfolio revaluation system. Traded instruments covered include: spot and forward exchange rates (FX); credit default swaps (CDS); total return swaps (TRS); commodity and bond futures; traded...

In this paper, we present a continuous time Capital Asset Pricing Model where the volatilities of the market index and the stock are both stochastic. Using a singular perturbation technique, we provide approximations for the prices of European options on both the stock and the index. We derive...

The paper attempts to measure the relationship between risk and return, and the effect of diversification on non-market risk in Indian stock market by applying Market Index Model. For the analysis monthly adjusted opening and closing prices of composite portfolio of BSE 100 companies, for the...

In parametric models a sufficient condition for local identification is that the vector of moment conditions is differentiable at the true parameter with full rank derivative matrix. We show that additional conditions are often needed in nonlinear, nonparametric models to avoid nonlinearities...

In parametric models a sufficient condition for local identification is that the vector of moment conditions is differentiable at the true parameter with full rank derivative matrix. We show that there are corresponding sufficient conditions for nonparametric models. A nonparametric rank...

In parametric models a sufficient condition for local identification is that the vector of moment conditions is differentiable at the true parameter with full rank derivative matrix. We show that there are corresponding sufficient conditions for nonparametric models. A nonparametric rank...

In parametric models a sufficient condition for local identification is that the vector of moment conditions is differentiable at the true parameter with full rank derivative matrix. We show that additional conditions are often needed in nonlinear, nonparametric models to avoid nonlinearities...

We consider time series models in which the conditional mean of the response variable given the past depends on latent covariates. We assume that the covariates can be estimated consistently and use an iterative nonparametric kernel smoothing procedure for estimating the conditional mean...