Courses can be taken to achieve a variety of purposes: They can serve as remedial or foundational classes, they might be taken to gain valuable skills, or they could be chosen simply to pursue an interest.
Students of financial mathematics might expect to encounter subjects such as probability and linear algebra. These analytical tools are often used by professionals who need to understand the behavior of markets, such as consultants, accountants and bankers.
The United Kingdom of Great Britain and Northern Ireland, commonly known as the United Kingdom and Britain, is a sovereign state located off the north-western coast of continental Europe.The two most famous (and oldest) universities are Oxford and Cambridge (often referred to as Oxbridge by many Britons) England also has several other world-class institutions, including several in London (notably Imperial College, the London School of Economics, University College London and King's College London, all are part of London University)
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. [+]