In this paper, a Chover-type law of the iterated logarithm is established for the weighted sums of independent and identically distributed random variables with a distribution in the domain of attraction of a stable law.

This paper builds a venture capital index from 1987 to 1999 that consists of 12,946 rounds of venture financing with 5,643 venture-backed firms. The paper uses two innovative techniques, a re-weighting procedure and a method of moment repeat sales regression, to mitigates three problems -...

This paper investigates whether individual investors adjust their stock trading according to their stock selection abilities, which can be inferred from their trading history. Fixed-effect panel regressions provide strong evidence that the ability to forecast future stock returns significantly...

For estimating a rare event via the multivariate extreme value theory, the so-called tail dependence function has to be investigated (see [L. de Haan, J. de Ronde, Sea and wind: Multivariate extremes at work, Extremes 1 (1998) 7-45]). A simple, but effective estimator for the tail dependence...

This paper studies improvements of multivariate local linear regression. Two intuitively appealing variance reduction techniques are proposed. They both yield estimators that retain the same asymptotic conditional bias as the multivariate local linear estimator and have smaller asymptotic...

Parametric models for tail copulas are being used for modeling tail dependence and maximum likelihood estimation is employed to estimate unknown parameters. However, two important questions seem unanswered in the literature: (1) What is the asymptotic distribution of the MLE and (2) how does one...

In general, the risk of joint extreme outcomes in financial markets can be expressed as a function of the tail dependence function of a high-dimensional vector after standardizing marginals. Hence, it is of importance to model and estimate tail dependence functions. Even for moderate dimension,...

In certain cases partial sums of i.i.d. random variables with finite variance are better approximated by a sequence of stable distributions with indices \alpha_n \to 2 than by a normal distribution. We discuss when this happens and how much the convergence rate can be improved by using...