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Covariance appears throughout investment management, e.g., in risk reporting and control, portfolio construction, risk parity, smart beta, algorithmic trading, and hedging. It is usually represented via multi-factor model. The form’s fewer parameters and structure—comovement through...
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a mixture stochastic volatility model providing a tractable method for capturing certain market characteristics. To … estimate the parameter of a mixture stochastic volatility model, we first use the Expectation-Maximisation (EM) algorithm. The …
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volatility for estimating conditional variances and covariances; (2) alternative currencies; and (3) alternative maturities of … Chang et al. [17], we estimate four multivariate volatility models (namely CCC, VARMA-AGARCH, DCC and BEKK), and calculate …
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This paper formulates dynamic density functions, based upon skewed-t and similar representations, to model and forecast electricity price spreads between different hours of the day. This supports an optimal day ahead storage and discharge schedule, and thereby facilitates a bidding strategy for...
Persistent link: https://www.econbiz.de/10014107616
Purpose This paper aims to present a literature review of the most recent optimisation methods applied to Credit Scoring Models (CSMs). Design/methodology/approach The research methodology employed technical procedures based on bibliographic and exploratory analyses. A traditional investigation...
Persistent link: https://www.econbiz.de/10014506795
An analogue can be made between: (a) the slow pace at which species adapt to an environment, which often results in the emergence of a new distinct species out of a once homogeneous genetic pool, and (b) the slow changes that take place over time within a fund, mutating its investment style. A...
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