A nonparametric model that includes non-Gaussian characteristics of skewness and kurtosis is proposed based on the cubic market capital asset pricing model. It is an equilibrium pricing model but risk-neutral valuation can be introduced through return data transformation. The model complies with...

A nonparametric model that includes non-Gaussian characteristics of skewness and kurtosis is proposed based on the cubic market capital asset pricing model. It is an equilibrium pricing model but risk-neutral valuation can be introduced through return data transformation. The model complies with...

This paper investigates the estimation of the Value-at-Risk (VaR) across various probability levels for the log-returns of a comprehensive dataset comprising four thousand crypto-assets. Employing four recently introduced Adaptive Conformal Inference (ACI) algorithms, we aim to provide robust...

This paper introduces a novel Bayesian time series model that combines the nonparametric features of an infinite hidden Markov model with the volatility persistence captured by the GARCH framework, to effectively model and forecast short-term interest rates. When applied to US 3-month Treasury...

This paper deals with estimating data from experiments determining lottery certainty equivalents. The paper presents the parametric and nonparametric results of the least squares (mean), quantile (including median) and mode estimations. The examined data are found to be positively skewed for low...

Model risk in the estimation of value-at-risk is a challenging threat for the success of any financial investments. The degree of the model risk increases when the estimation process is constructed with a portfolio in the emerging markets. The proper model should both provide flexible joint...

In this paper authors analyzed the importance of investments in human resources. This has been done through an empirical study conducted in Serbian financial sector, in which we measure the impact of human resources index level (HR index) on company business results. Research was implemented in...

This paper proves a nonparametric identification result for a stochastic dynamic discrete choice game of incomplete information. The joint distribution of the private information and the stage game payoffs of the players are both assumed unknown for the econometrician and the private...

This paper proposes a new nonparametric identification strategy for static multiple choice models with random heterogeneity in unobservables. The strategy relies on functional properties of the sub-utilities and the distribution of the unobservables, a known payoff function for the “outside...

Estimation of the parameters of Garch models for financial data is typically based on daily close-to-close returns. This paper shows that the efficiency of the parameter estimators may be greatly improved by using volatility proxies based on intraday data. The paper develops a Garch quasi...