Implications of parameter uncertainty on option prices.
Incompleteness of the bond market with Lévy noise under the physical measure
The problem of completeness of the forward rate based bond market model driven by a Lévy process under the physical measure is examined. The incompleteness of market in the case when the Lévy measure has a density function is shown. The required elements of the theory of stochastic integration over the compensated jump measure under a martingale measure are presented and the corresponding integral representation of local martingales is proven.
Indifference valuation in incomplete binomial models
The indifference valuation problem in incomplete binomial models is analyzed. The model is more general than the ones studied so far, because the stochastic factor, which generates the market incompleteness, may affect the transition propabilities and/or the values of the traded asset as well as the claim’s payoff. Two pricing algorithms are constructed which use, respectively, the minimal martingale and the minimal entropy measures. We study in detail the interplay among the different kinds of...
Information pricing for portfolio optimization
Instantaneous self-fulfilling of long-term prophecies on the probabilistic distribution of financial asset values
Integral price formulas for lookback options.
Integral representations of risk functions for basket derivatives
The risk minimizing problem in the multidimensional Black-Scholes framework is studied. Specific formulas for the minimal risk function and the cost reduction function for basket derivatives are shown. Explicit integral representations for the risk functions for l(x) = x and , with p > 1 for digital, quantos, outperformance and spread options are derived.
Intelligent computational methods for financial engineering.
Intelligent financial time series forecasting: A complex neuro-fuzzy approach with multi-swarm intelligence
Financial investors often face an urgent need to predict the future. Accurate forecasting may allow investors to be aware of changes in financial markets in the future, so that they can reduce the risk of investment. In this paper, we present an intelligent computing paradigm, called the Complex Neuro-Fuzzy System (CNFS), applied to the problem of financial time series forecasting. The CNFS is an adaptive system, which is designed using Complex Fuzzy Sets (CFSs) whose membership functions are complex-valued...