## Fundamentals of Mathematics and Statistics

### Lehrinhalte

mathematics: calculation rules for exponentials and roots; functions and their properties; special functions: exponential and logarithmic functions; basics of differential and integral calculus; properties of and calculation rules for vectors and matrices (basics); linear system of equations. financial mathematics: discrete (both arithmetic and geometric) and continuously compounded computation of interest and returns and their conversion; compounding and discounting with different types of interest. descriptive statistics: understanding and computation of absolute, relative, joint and conditional frequencies from data samples; depiction of data samples using histograms and frequency plots; computation of arithmetic mean, median, mode, quantiles, variance and standard deviation, skewness, kurtosis, covariance and (linear) correlation from data samples. probability calculus: random variables; computation using probabilities; probability mass function - probability density function pdf - cumulative distribution function cdf; parameters of univariate distributions: expected value, variance and standard deviation; specific distributions: binomial, Poisson, normal and log-normal distribution

### Art der Vermittlung

Präsenzveranstaltung

Pflichtfach

### Empfohlene Fachliteratur

Anton, H., Bivens, I., Davis, S., 2009, Calculus Early Transcendentals Combined, 9th edition, Wiley

### Lern- und Lehrmethode

Interactive teaching (lecture, examples for students and discussion of the examples afterwards)

### Prüfungsmethode

This course is based on continuous assessment (30%, 30 home-assignment questions) and a written final exam (70%).

### Voraussetzungen laut Lehrplan

Meet the admission requirements for this master’s programme

### Schnellinfos

#### Studiengang

Quantitative Asset and Risk Management (Master)

Master

4.00

Englisch

Berufsbegleitend

2024

1 WS

Ja

#### Lernergebnisse der Lehrveranstaltung

After the successful completion of the course students are able to understand and apply basic models and concepts in asset management and risk management and have a wide range of skills including, for example: the computation and modelling of asset returns and other relevant variables in asset and risk management as well as the computation and interpretation of their important statistical measures. Further, they are prepared to understand more advanced mathematical concepts employed in financial models that are taught at a later stage of the curriculum (courses "Multivariate Methods" and "Time Series Analysis").

#### Kennzahl der Lehrveranstaltung

0613-09-03-BB-EN-01