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The proposed model was tested by performing numerical experiments using finance-related datasets including credit assignment, bank telemarketing, bankruptcy, and banknote authentication.
Quasi-Monte Carlo (QMC) methods are important numerical tools in computational finance.
The fractional Black-Scholes (B-S) equation is an important mathematical model in finance engineering, and the study of its numerical methods has very significant practical applications.
Numerical computation and other applications in finance will also be investigated in future work.
We discuss an implementation of the MRHSD method for a type of variational inequality problem in Section 4. Section 5 presents numerical experiments and results applicable to finance and statistics.
We show that the new methods can be applied in locally adaptive and dimension-adaptive ways and demonstrate their efficiency by numerical experiments with high-dimensional integrals from finance.
Quasi-Monte Carlo simulation is a popular numerical method in applications, in particular, economics and finance.
Compared with several state-of-the-art methods, preliminary numerical experiments on solving the Q-weighted low-rank correlation matrix problem from finance validate the efficiency of the proposed method.
To highlight the potential deviation caused using the two simplified financing policies instead of a maturity structure matching, we provide a numerical example in Sect. 5. A conclusion and outlook for future research are given in Sect.
Numerical calculations indicate that optimal social security systems should be at least partly paygo financed in many economies.
Through numerical studies, we show that the optimal network will be more consolidated with higher financing costs and significant cost reduction can be achieved by considering financial decisions at the strategic supply chain design stage.
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