Calculates the KPSS statistics for I(0) processes against long-memory alternatives. We consider two tests, denoted by KPSS_mu and KPSS_t, based on a regression on a constant mu, and on a constant and a time trend t, respectively. The quantlet returns the value of the estimated statistic for two the
Uses the Breeden and Litzenberger (1978) method and a semiparametric specification of the Black-Scholes option pricing function to calculate the empirical State Price Density. The analytic formula uses an estimate of the volatility smile and its first and second derivative to calculate the State-pr
using the given data stockestsim estimates the parameters for the following models: model 1, a Wiener Process, and model 2, a Wiener Process with jumps which are following a compounded Poisson Jump Process; after that both models are compared with the real dataset by a simulation.
simulates random processes for a stock price by three different ways: 1. using a Wiener Process, 2. using a compounded Poisson Jump Process with a log normal distribution of jump height and 3. using a mixture of both.
volsurf computes the implied volatility surface using a Kernel smoothing procedure. Either a Nadaraya-Watson estimator or a local polynomial regression is employed. Both are computed with a quartic Kernel. The metric is either moneyness, i.e. strike devided by the (implied) forward price of the und
computes the implied volatility surface using a local polynomial estimation with an automatic bandwidth selection algorithm. The metric is either moneyness, i.e. strike devided by the (implied) forward price of the underlying, or the original strikes.