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processors employed. The performance of the algorithms is illustrated using a well-known macroeconomic model. Bayesian estimation …
Persistent link: https://www.econbiz.de/10003779724
We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model is calibrated at a quarterly frequency for ten European countries. We also use maximum-likelihood estimates and Bayesian estimates to account for parameter uncertainty. We find...
Persistent link: https://www.econbiz.de/10008797745
One of the most important factors to control for the achievements of investment portfolio returns is risk. If we only think that a 100% positive return is needed to recover a portfolio loss of 50%, we can understand why. With the advent of the exponential growth of technology usage in markets,...
Persistent link: https://www.econbiz.de/10014254526
In this paper we explore the use of Genetic Algorithms (GA) to calibrate seasonal BVAR models. In this way, the mechanistic use of seasonal adjustment procedures is avoided, since seasonality becomes a structural, basic and explicit part of the BVAR model. At the same time, the use of GA allows...
Persistent link: https://www.econbiz.de/10014132203
Persistent link: https://www.econbiz.de/10012297507
This paper considers an alternative way of structuring stochastic variables in a dynamic programming framework where the model structure dictates that numerical methods of solution are necessary. Rather than estimating integrals within a Bellman equation using quadrature nodes, we use nodes...
Persistent link: https://www.econbiz.de/10012968342
Persistent link: https://www.econbiz.de/10011499989
An analogue can be made between: (a) the slow pace at which species adapt to an environment, which often results in the emergence of a new distinct species out of a once homogeneous genetic pool, and (b) the slow changes that take place over time within a fund, mutating its investment style. A...
Persistent link: https://www.econbiz.de/10013092381
estimation errors. We apply our strategy to several datasets and show that it consistently outperforms various existing downside …
Persistent link: https://www.econbiz.de/10012840952
We consider the basic problem of refi tting a time series over a finite period of time and formulate it as a stochastic dynamic program. By changing the underlying Markov decision process we are able to obtain a model that at optimality considers historical data as well as forecasts of future...
Persistent link: https://www.econbiz.de/10012894079