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MSc MORSE/Financial Engineering/Mathematical Finance

A Bayesian Framework for Sensor Placements
Prediction of atrial fibrillation incidents using ECGs during sinus rhythm
Alternating Direction Method of Multipliers for Big Data
The nearest correlation matrix: a problem from finance
Conic Optimization with Application to Integer Programming
Robust Linear Programming
Robust Portfolio Optimization
Conic Optimization with an Application in Finance
Travelling salesman problem
Aid distribution after disaster
Modelling delay propagation in railways with Max-Plus Algebra and cellular automata
Capacity Analysis for Railway Networks using Max-Plus Algebra
Public key cryptography based on Max-Plus Algebra
Portfolio Allocation using Mean-Variance Optimization
Credit Scoring Algorithms and Analysis
Sentiment Analysis of Social Media Posts
Predicting Results in a Football Match
Prediction of Heart Failure using Learning Methods
Modelling high-fidelity clinical data using statistical learning methods
Risk factor analysis using statistical learning methods
How weather influence England Acute Care Hospitals, Emergency Department admissions and ICU admissions
Understanding Uncertainties and market volatilities
Estimating the reproduction number of COVID-19 in the UK
Microgravity Data Postprocessing using Wavelets

## 英国论文代写|Birmingham University MSc Dissertation |The nearest correlation matrix: a problem from finance

A correlation matrix is characterized as being a real, square symmetric matrix with ones on the diagonal and with non-negative eigenvalues. There are numerous examples illustrating the use of correlation matrices but the one we have encountered the most arises in finance where the correlation between various stocks is used to construct sensible portfolios. Unfortunately, for a variety of reasons, an input matrix which is supposed to be a correlation matrix may fail to be semidefinite. For example the correlations may be between stocks measured over a period of time and some data may be missing, treated incorrectly the missing data problem can give rise to an indefinite matrix. The goal of the project is to examine various algorithm for finding a nearest correlation matrix, i.e., a correlation matrix that is as close as possible (for instance in the least square sense) to a given matrix. This problem can be formulated as an optimization problem with semidefinite constraints (constraints on the eigenvalues) and solved either by specialized algorithms or by general-purpose methods. The aim is to find which method is most suitable for some specific applications.

## 英国论文代写|The nearest correlation matrix: a problem from finance选题导师介绍

Professor Michal Kočvara is joint Head of Applied Mathematics. His research interests include nonlinear and semidefinite optimization, optimization of elastic structures, and optimization with equilibrium constraints. Before joining the academic sphere, he worked for several years in the industry. He is particularly skilled to create a bridge between academic research and practical needs of the industry.

Before joining the University of Birmingham in January 2007, he was with the Academy of Sciences of the Czech Republic and, simultaneously, working on research projects at the Universities in Bayreuth and Erlangen, Germany.

His recent work has been supported by Horizon 2020 (ITN) and EPSRC (Bridging-the-Gap), and involves several academic and industrial partners across Europe. Michal is a (co-)author of a monograph and over 50 journal articles on various aspects of mathematical optimization and optimization of mechanical structures. He developed or co-developed several computer programs for nonlinear optimization and optimization of elastic structures, some of them routinely used in academia and industry. He was a long-term visitor at the Institute of Mathematics and its Applications, University of Minnesota (2003), the Technical University of Denmark (2007) and the Institute for Pure and Applied Mathematics, UCLA (2010).

• nonlinear and semidefinite optimization
• optimization of elastic structures
• optimization with equilibrium constraints

## 英国论文代写|The nearest correlation matrix: a problem from finance选题参考文献

References:

J. Outrata, M. Kočvara and J. Zowe. Nonsmooth Approach to Optimization Problems with Equilibrium Constraints: Theory, Applications and Numerical Results. Kluwer Academic Publishers, Dordrecht, $1998 .$
J. Haslinger, M. Kočvara, G. Leugering, and M. Stingl. Multidisciplinary Free Material Optimization. SIAM J. Appl. Math. $70(7): 2709-2728,2010 .$
M. Stingl, M. Kočvara and G. Leugering. A Sequential Convex Semidefinite Programming Algorithm for MultipleLoad Free Material Optimization. SIAM J. Optimization, 20(1):130-155, $2009 .$
W. Achtziger and M. Kočvara. Structural Topology Optimization with Eigenvalues. SIAM J. Optimization 18(4): $1129-1164,2007 .$

M. Kočvara and M. Stingl. On the solution of large-scale SDP problems by the modified barrier method using iterative solvers. Mathematical Programming, Series B, 109(2-3):413-444, $2007 .$

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## 金融数学代写

• 随机微积分 Stochastic calculus
• 随机分析 Stochastic analysis
• 随机控制理论 Stochastic control theory
• 微观经济学 Microeconomics
• 数量经济学 Quantitative Economics
• 宏观经济学 Macroeconomics
• 经济统计学 Economic Statistics
• 经济学理论 Economic Theory
• 计量经济学 Econometrics

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