Markov chain theory is proving to be a powerful approach to bootstrap highly nonlinear time series. In this work we provide a method to estimate the memory of a Markov chain (i.e. its order) and to identify its relevant states. In particular the choice of memory lags and the aggregation of...

The concept of genetic action trees combines action trees with genetic algorithms. In this paper, we create a multi-agent simulation on the base of this concept and provide the interested reader with a software package to apply genetic action trees in a multi-agent simulation to simulate complex...

Backtesting stock market investment strategies is fraught with danger – for example, overfitting. The signal to noise ratio in stock markets is so low that overfitting is inevitable. Simulation offers a means of assessing and compensating for the dangers. It is not obvious at first how...

Local volatility model is a relatively simple way to capture volatility skew/smile. In spite of its drawbacks, it remains popular among practitioners for derivative pricing and hedging. For long-dated options or interest rate/equity hybrid products, in order to take into account the effect of...

We propose a general simulation-based procedure for estimating quality of approximate policies in heterogeneous-agent equilibrium models, which allows to verify that such approximate solutions describe a near-rational equilibrium. Our procedure endows agents with superior knowledge of the future...

Promoting social information reporting and disclosure can promote sustainable banking. The paper aims to measure banking social sustainability by constructing a new interval-based composite indicator using the Thomson Reuters database. In this work, we propose an approach to constructing...

Macroeconomic models with sticky information include an infinite number of lagged expectations. Several authors have developed specialized solutions algorithms to solve these models under rational expectations. We demonstrate that it is also possible to implement this class of models in Dynare...

I use simulated series of buys and sells to test nine different PIN estimation algorithms implemented in SAS, proc NLP. I conclude that the algorithms do a good job estimating PIN, on average, when applied to series generated from high-PIN data generating process (PIN0.2). However, when applied...