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Introduction
Maria Grith currently works at the Erasmus School of Economics, Erasmus University Rotterdam. Maria does research in Statistics, Econometrics and Financial Economics. Her most recent publication is 'Functional Principal Component Analysis for Derivatives of Multivariate Curves.'
Publications
Publications (16)
Based on options and realized returns, we analyze risk premia in the Bitcoin market through the lens of the Pricing Kernel (PK). We identify that: 1) The projected PK into Bitcoin returns is W-shaped and steep in the negative returns region; 2) Negative Bitcoin returns account for 33% of the total Bitcoin index premium (BP) in contrast to 70% of S&...
We propose two methods based on the functional principal component analysis (FPCA) to estimate smooth derivatives for a sample of observed curves with a multidimensional domain. We apply the eigendecomposition to a) the dual covariance matrix of the derivatives; b) the dual covariance matrix of the observed curves, and take derivatives of their eig...
We present two methods based on functional principal component analysis (FPCA) for the estimation of smooth derivatives of a sample of random functions, which are observed in a more than one-dimensional domain. We apply eigenvalue decomposition to a) the dual covariance matrix of the derivatives, and b) the dual covariance matrix of the observed cu...
Supported by several recent investigations, the empirical pricing kernel (PK) puzzle might be considered as a stylized fact. Based on an economic model with referencedependent preferences for the financial investors, we emphasize a microeconomic view that explains the puzzle via state-dependent aggregate preferences. We also investigate how the sha...
Supported by several recent investigations, the empirical pricing kernel (EPK) puzzle might be considered a stylized fact. Based on an economic model with state dependent preferences for the financial investors, we want to emphasize a microeconomic view that succeeds in explaining the puzzle. We retain the expected utility framework in a one period...
Several empirical studies reported that pricing kernels exhibit a common pattern across different markets. The main interest
in pricing kernels lies in validating the presence of the peaks and their variability in location among curves. Motivated
by this observation we investigate the problem of estimating pricing kernels based on the shape invaria...
This chapter deals with the estimation of risk neutral distributions for pricing index options resulting from the hypothesis of the risk neutral valuation principle. After justifying this hypothesis, we shall focus on parametric estimation methods for the risk neutral density functions determining the risk neutral distributions. We we shall differe...
This chapter deals with nonparametric estimation of the risk neutral density. We present three different approaches which do not require parametric functional assumptions on the underlying asset price dynamics nor on the distributional form of the risk neutral density. The first estimator is a kernel smoother of the second derivative of call prices...
Pricing kernels play a major role in quantifying risk aversion and investors' preferences. Several empirical studies reported that pricing kernels exhibit a common pattern across different markets. Mostly visual inspection and occasionally numerically summarise are used to make comparison. With increasing amount of information updated every day, th...