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use the Lie algebra methodology of Björk et al. to investigate under what conditions on the volatility structure of the …
Persistent link: https://www.econbiz.de/10002450616
volatility/diffusion term is stochastic in the sense of being driven by a separate hidden Markov process. Within this framework … conditions for the existence of a finite dimensional Markovian realizations for the stochastic volatility models. We illustrate … the theory by analyzing a number of concrete examples. -- HJM models ; stochastic volatility ; factor models ; forward …
Persistent link: https://www.econbiz.de/10001664233
Persistent link: https://www.econbiz.de/10002993690
In this paper we introduce the Smooth Permanent Surge [SPS] model. The model is an integrated non lineal moving average process with possibly unit roots in the moving average coefficients. The process nests the Stochastic Permanent Break [STOPBREAK] process by Engle and Smith (1999) and in a...
Persistent link: https://www.econbiz.de/10002465176
since a volatility constraint on the stochastic discount factor is a particular case of a restriction on this distance. We …
Persistent link: https://www.econbiz.de/10001600073
correct and that the true theoretical price of the swap is in fact equal to zero. This result is shown to hold regardless of …
Persistent link: https://www.econbiz.de/10001645586
In this paper we derive a unit root test against a Panel Logistic Smooth Transition Autoregressive (PLSTAR). The analysis is concentrated on the case where the time dimension is fixed and the cross section dimension tends to infinity. Under the null hypothesis of a unit root, we show that the...
Persistent link: https://www.econbiz.de/10002577852
In this paper I define an evolutionary stability criterion for learning rules. Using Monte Carlo simulations, I then apply this criterion to a class of learning rules that can be represented by Camerer and Ho's (1999) model of learning. This class contains perturbed versions of reinforcement and...
Persistent link: https://www.econbiz.de/10001622441
We show how it is possible to generate multivariate data which have moments arbitrary close to the desired ones. They are generated as linear combinations of variables with known theoretical moments. It is shown how to derive the weights of the linear combinations in both the univariate and the...
Persistent link: https://www.econbiz.de/10001629177
Persistent link: https://www.econbiz.de/10000991637