A probabilistic neural network is applied as a tool to approximate the statistical evaluation function for a simple version of the game Tic-Tac-Toe. We solve the problem by a sequential estimation of the underlying di...
详细信息
A probabilistic neural network is applied as a tool to approximate the statistical evaluation function for a simple version of the game Tic-Tac-Toe. We solve the problem by a sequential estimation of the underlying discrete distribution mixture of product components. (c) 2005 Elsevier B.V. All rights reserved.
A probabilistic neural network is applied as a tool to approximate the statistical evaluation function for a simple version of the game Tic-Tac-Toe. We solve the problem by a sequential estimation of the underlying di...
详细信息
A probabilistic neural network is applied as a tool to approximate the statistical evaluation function for a simple version of the game Tic-Tac-Toe. We solve the problem by a sequential estimation of the underlying discrete distribution mixture of product components. (c) 2005 Elsevier B.V. All rights reserved.
A technique for online estimation of spot volatility for high-frequency data is developed. The algorithm works directly on the transaction data and updates the volatility estimate immediately after the occurrence of a...
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A technique for online estimation of spot volatility for high-frequency data is developed. The algorithm works directly on the transaction data and updates the volatility estimate immediately after the occurrence of a new transaction. Furthermore, a nonlinear market microstructure noise model is proposed that reproduces several stylized facts of high-frequency data. A computationally efficient particle filter is used that allows for the approximation of the unknown efficient prices and, in combination with a recursive emalgorithm, for the estimation of the volatility curve. We neither assume that the transaction times are equidistant nor do we use interpolated prices. We also make a distinction between volatility per time unit and volatility per transaction and provide estimators for both. More precisely we use a model with random time change where spot volatility is decomposed into spot volatility per transaction times the trading intensity-thus highlighting the influence of trading intensity on volatility.
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