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Time series analysis of daily stock data and building predictive models are complicated. This paper presents a comparative study for stock price prediction using three different methods, namely autoregressive integrated moving average, artificial neural network, and stochastic process-geometric...
Persistent link: https://www.econbiz.de/10012321966
Multifractal processes reproduce some of the stylised features observed in financial time series, namely heavy tails found in asset returns distributions, and long-memory found in volatility. Multifractal scaling cannot be assumed, it should be established; however, this is not a straightforward...
Persistent link: https://www.econbiz.de/10012304977
We show by Monte Carlo simulations that the jackknife estimation of QUENOUILLE (1956) provides substantial bias reduction for the estimation of short-term interest rate models applied in CHAN ET AL. (1992) - hereafter CKLS (1992). We find that an alternative estimation based on NOWMAN (1997)...
Persistent link: https://www.econbiz.de/10011422171
Maximum likelihood estimation of discretely observed diffusion processes is mostly hampered by the lack of a closed form solution of the transient density. It has recently been argued that a most generic remedy to this problem is the numerical solution of the pertinent Fokker-Planck (FP) or...
Persistent link: https://www.econbiz.de/10010287012
Using a two-account model with event risk, we model life insurance contracts taking into account both guaranteed and non-guaranteed payments in participating life insurance as well as in unit-linked insurance. Here, event risk is used as a generic term for life insurance events, such as death,...
Persistent link: https://www.econbiz.de/10011300329
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In light of the recent financial and real economic crisis, it seems clear that macroeconomists need to better account for the influence of financial markets. This paper explores the consequences of treating the interaction between different financial markets, monetary policy, and the real...
Persistent link: https://www.econbiz.de/10010126892