Low-Rank Tensor Approximation for Chebyshev Interpolation in Parametric Option Pricing.
Kathrin GlauDaniel KressnerFrancesco StattiPublished in: SIAM J. Financial Math. (2020)
Keyphrases
- low rank
- option pricing
- frobenius norm
- trace norm
- high order
- tensor decomposition
- missing data
- matrix factorization
- convex optimization
- stock price
- low rank approximation
- matrix completion
- linear combination
- low rank matrix
- decision analysis
- singular value decomposition
- rank minimization
- high dimensional data
- semi supervised
- black scholes model
- higher order
- singular values
- real option
- dimensionality reduction
- pairwise
- learning algorithm
- neural network
- historical data
- approximation methods
- non stationary
- active learning
- high dimensional
- bayesian networks