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Common Mistakes when Applying Computational Intelligence and Machine Learning to Stock Market modelling
Computational intelligence machine learning stock market equities automated stock tradin mistakes.
2012/9/17
For a number of reasons, computational intelligence and machine learning methods have been largely dismissed by the professional community. The reasons for this are numerous and ...
Yield to maturity modelling and a Monte Carlo Technique for pricing Derivatives on Constant Maturity Treasury (CMT) and Derivatives on forward Bonds
interest rate bonds recovery rate survival probability hazard rate function yield to maturity CMS CMT
2012/4/28
This paper proposes a Monte Carlo technique for pricing the forward yield to maturity, when the volatility of the zero-coupon bond is known. We make the assumption of deterministic default intensity (...
Discrete-Time Interest Rate Modelling
Interest rates models pricing kernels financial time series Flesaker-Hughston models transversality condition
2010/11/2
This paper presents an axiomatic scheme for interest rate models in discrete time.
We take a pricing kernel approach, which builds in the arbitrage-free property and pro-
vides a link to equilibrium...
Optimisation of Stochastic Programming by Hidden Markov Modelling based Scenario Generation
Markov Processes Risk Analysis Stochastic Programming Scenarios
2010/10/29
This paper formed part of a preliminary research report for a risk consultancy and academic research. Stochastic Programming models provide a powerful paradigm for decision making under uncertainty. I...
Quantum Neural Computation for Option Price Modelling
Option price modelling Quantum neural computation nonlinear Schr¨odinger equations leverage effect bidirectional associative memory
2010/10/29
We propose a new cognitive framework for option price modelling, using quantum
neural computation formalism. Briefly, when we apply a classical nonlinear neuralnetwork
learning to a linear quantum S...