Fractional stochastic volatility models have been widely used to capture the non-Markovian structure revealed from financial time series of realized volatility. On the other hand, empirical studies have identified sca...
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In this paper, we consider what may be done when researchers anticipate that in the implementation of field experiments, random assignment to experimental and control groups is likely to be flawed. We then reanalyze d...
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The obvious way to present information is in a graph. But not all graphs are created equal. A well-designed graph can make clear what an ill-thought-out one conceals. Jarad Niemi and Andrew Gelman present visualisatio...
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A generic control variate method is proposed to price options under stochastic volatility models by Monte Carlo simulations. This method provides a constructive way to select control variates which are martingales in ...
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This paper extends the generalized variable elimination algorithm [1]. The generalized variable elimination algorithm is a query-oriented algorithm. The improved algorithm is a 'global' algorithm, which comput...
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ISBN:
(纸本)193241567X
This paper extends the generalized variable elimination algorithm [1]. The generalized variable elimination algorithm is a query-oriented algorithm. The improved algorithm is a 'global' algorithm, which computes marginal probability for all variables in a network given any set of observed variables. It builds a bucket tree of data structures buckets and then updates the bucket tree to produce the marginal probability density for every variable in the network. The algorithm relies solely on independence relations and probability manipulation, without any requirement for complex graphical theory, is easy to understand and implement [1].
The Black-Scholes option pricing methodology requires that the model for the price of the underlying asset be completely specified. Often the underlying price is taken to be a geometric Brownian motion with a constant...
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We price European-style options written on forward contracts in a commodity market, which we model with an infinite-dimensional Heath–Jarrow–Morton (HJM) approach. For this purpose, we introduce a new class of state...
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We investigate a machine learning approach to option Greeks approximation based on Gaussian Process (GP) surrogates. Our motivation is to implement Delta hedging in cases where direct computation is expensive, such as...
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We suggest that certain open driven systems self-organize to a critical point because their continuum diffusion limits have singularities in the diffusion constants at the critical point. We rigorously establish a con...
We suggest that certain open driven systems self-organize to a critical point because their continuum diffusion limits have singularities in the diffusion constants at the critical point. We rigorously establish a continuum limit for a one-dimensional automaton that has this property, and show that certain exponents and the distribution of events are simply related to the order of the diffusion singularity. Numerically, we show that some of these results can be generalized to include a class of sandpile models that are described by a similar, but higher-order, singularity.
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