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Maximum entropy distribution of stock price fluctuations
Maximum entropy distribution stock price fluctuations
2011/7/4
The principle of absence of arbitrage opportunities allows obtaining the distribution of
stock price fluctuations by maximizing its information entropy. This leads to a physical
description of the u...
Optimal Portfolio Diversification Using Maximum Entropy Principle
Diversification Entropy measure Portfolio selection Shrinkage rule Simulation methods
2011/4/2
Markowitz’s mean-variance (MV) efficient portfolio selection is one of the most widely used approaches in solving portfolio diversification problem. However, contrary to the notion of diversification,...
A Family of Maximum Entropy Densities Matching Call Option Prices
Entropy Information Theory I-Divergence Asset Distribution Option Pricing
2011/3/23
We investigate the position of the Buchen-Kelly density in a family of entropy maximising densities which all match European call option prices for a given maturity observed in the market. Using the L...
Maximum Entropy Distributions Inferred from Option Portfolios on an Asset
Entropy Information Theory I-Divergence Asset Distribution Option Pricing Volatility Smile
2010/10/29
We obtain the Maximum Entropy distribution for an asset from call and digital option prices. A
rigorous mathematical proof of its existence and exponential form is given, which can also be applied to...
Maximum entropy autoregressive conditional heteroskedasticity model
Maximum entropy density ARCH models Excess kurtosis Asymmetry Peakedness of distribution Stock returns data
2011/4/2
In many applications, it has been found that the autoregressive conditional heteroskedasticity (ARCH) model under the conditional normal or Student’s t distributions are not general enough to account ...
Spatial data modelling and maximum entropy theory
spatial data classification distribution function error distribution and maximum entropy approach
2014/3/20
Spatial data modelling and consequential error estimation of the distribution function are key points of spatial analysis. For many practical problems, it is impossible to hypothesize distribution fun...
