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Implements cointegration/cotrending rank selection algorithm in Guo and Shintani(2011). Paper: "Consistant Cotrending rank selection when both stochastic and nonlinear deterministic trends are present", Preprint, Feb 2011.


Functions, examples and data from the book 'Numerical Methods and Optimization in Finance' by M. Gilli, D. Maringer and E. Schumann. The package contains, in particular, implementations of several optimisation heuristics (such as Differential Evolution, Genetic Algorithms and Threshold Accepting).


This package gives classical trading strategy called "Pair trading" to you. you can easily specify pairs for trading and do back-test by this package. It's based on cointegration. Cointegration is a statistical feature of time series proposed by Engle and Granger.


Simulation, estimation and forecasting of first-order Beta-Skew-t-EGARCH models with leverage (one-component, two-component, skewed versions).


ARFIMA, in-mean, external regressors and various GARCH flavours, with methods for fit, forecast, simulation, inference and plotting.


Financial and actuarial functions to evaluate life contingencies.


maRketSim is a market simulator for R. It was initially designed around the bond market, with plans to expand to stocks. maRketSim is built around the idea of portfolios of fundamental objects. Therefore it is slow in its current incarnation, but allows you the flexibility of seeing exactly what is in your final results, since the objects are retained.


Companion package to the book Option Pricing and Estimation of Financial Models in R, Wiley, Chichester. ISBN: 978-0-470-74584-7


The Trades and Quotes data of the New York Stock Exchange is a popular input for the implementation of intraday trading strategies, the measurement of liquidity and volatility and investigation of the market microstructure, among others. This package contains a collection of R functions to carefully clean and match the trades and quotes data, calculate ex post liquidity and volatility measures and detect price jumps in the data.


This package provides detailed functionality for working with the Schwartz 1997 two-factor commodity model. Essentially, it contains pricing formulas for futures and European options and the standard d/p/q/r functions for the distribution of the state variables and futures prices. In addition, a parameter estimation procedure is contained together with many utilities as filtering and plotting functionality. This package is accompanied by futures data of ten commodities.