calculates the price for path dependent options in the Black Scholes model by applying Quasi-Monte Carlo simulation in connection with a Brownian Bridge construction.
calculates the option price and its standard deviation for path independent options in the multi-dimensional Black Scholes model by Monte Carlo simulation.
calculates the option price and its standard deviation for path independent options in the multi-dimensional Black Scholes model by Monte Carlo simulation.
computes price of the CAT bond paying only coupons for the given claim amount distribution and the non-homogeneous Poisson process governing the flow of losses
computes price of the zero-coupon CAT bond for the given claim amount distribution and the non-homogeneous Poisson process governing the flow of losses.
starting program to calculate the stock price on the nodes in the implied binomial tree, the tree of transition probabilities and the tree of Arrow-Debreu prices using Barle and Cakici's method.
starting program to calculate the stock price on the nodes in the implied tree, the transition probability tree and the Arrow-Debreu tree using Derman and Kani's method.
determines the implied volatilities assuming the Black Scholes model for a vector of European style options; uses either the method of bisections or the default Newton-Raphson method.
main function for the Derman/Kani/Chriss method of implied trinomial trees (ITT). It computes the nodes of the ITT, the probability matrices, the Arrow-Debreu prices and the local volatility matrix.
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 assumptions of the Black-Scholes call-option pricing formula this quantlet calculates the Black- Scholes State-Price Density, Delta and Gamma from call-options data
estimates for a given dataset of a random process the parameters of the following two models: a Wiener Process (model 1) and a compounded Poisson Jump Process mixed with a Wiener Process (model 2)
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.