One of the best ways to further career goals is investing in higher education. By taking courses in their field, students demonstrate commitment to their careers. Individual classes can provide valuable skills and advanced training.
Certain mathematical subjects, such as statistics and linear algebra, are effective in the analysis of the behavior of markets. Economists, bankers and business consultants would all benefit from applying themselves to a detailed study of these concepts in a financial mathematics program.
Education in the United Kingdom is a devolved matter with each of the countries of the United Kingdom having separate systems under different governments: the UK Government is responsible for England, and the Scottish Government, the Welsh Government and the Northern Ireland Executive are responsible for Scotland, Wales and Northern Ireland, respectively.
Online Course in Financial Mathematics in United Kingdom
Stochastic Interest Rates covers practical topics such as calibration, numerical implementation and model limitations in detail. The authors provide numerous exercises and carefully chosen examples to help students acquire the necessary skills to deal with interest rate modelling in a real-world setting. [+]
Driven by concrete computational problems in quantitative finance, this book provides aspiring quant developers with the numerical techniques and programming skills they need. The authors start from scratch, so the reader does not need any previous experience of C++. [+]
The Black–Scholes option pricing model is the first and by far the best-known continuous-time mathematical model used in mathematical finance. Here, it provides a sufficiently complex, yet tractable, testbed for exploring the basic methodology of option pricing. [+]
The authors study the Wiener process and Itô integrals in some detail, with a focus on results needed for the Black–Scholes option pricing model. After developing the required martingale properties of this process, the construction of the integral and the Itô formula (proved in detail) become the centrepiece, both for theory and applications, and to provide concrete examples of stochastic differential equations used in finance. [+]
It provides a clear treatment of the scope and limitations of mean-variance portfolio theory and introduces popular modern risk measures. Proofs are given in detail, assuming only modest mathematical background, but with attention to clarity and rigour. [+]
Relatively elementary mathematics leads to powerful notions and techniques - such as viability, completeness, self-financing and replicating strategies, arbitrage and equivalent martingale measures - which are directly applicable in practice. The general methods are applied in detail to pricing and hedging European and American options within the Cox–Ross–Rubinstein (CRR) binomial tree model. [+]
Students and instructors alike will benefit from this rigorous, unfussy text, which keeps a clear focus on the basic probabilistic concepts required for an understanding of financial market models, including independence and conditioning. Assuming only some calculus and linear algebra, the text develops key results of measure and integration, which are applied to probability spaces and random variables, culminating in central limit theory. [+]