An online course is a form of education taught via the Internet. Most online courses involve distance learning, meaning you do not have to take the course on a physical campus. Interaction between the student and instructor is completed via chat rooms, email, and discussion forums. Online courses can be taken on their own or as part of a larger program.
What is an online course in financial mathematics? This course is focused on developing managerial and quantitative finance skills. Students study subjects such as risk management, financial derivatives, portfolio theories, and data analysis. Some courses provide instruction on specific areas of focus, such as programming skills, numerical techniques, and probabilistic concepts.
Financial mathematics students often gain several invaluable skills, including understanding financial market models, solving linear complementarity problems, and interpreting the global economy. Students learn how financial markets fluctuate through time and conduct research of financial processes.
Online courses in financial mathematics have a global appeal and are accessible through distance learning modules. The costs of enrolling in this course are different among each institution. The best way to determine fees is contacting the university of your interest.
An online course in financial mathematics can provide students with diverse employment opportunities that include professions in government, marketing, and finance. Students may work for banks, insurance companies, or brokerage firms to compile forecasts, analyze data, and research trends. A profession in market research is possible, which involves conducting focus groups, carrying out surveys, and collecting data from test markets. Students may find employment in local and federal governments for budgeting purposes.
Educational institutions across the world provide students with more opportunities than ever. Enrolling in classes is easy, and that’s especially true when it comes to online courses. Search for your program below and contact directly the admission office of the school of your choice by filling in the lead form.
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. [+]