Maths Refresher for Finance

London Financial Studies
En London (Inglaterra) yHong Kong (Hong Kong), New York (Estados Unidos)


Información importante


Mathematics is at the heart of financial techniques, but many finance texts and courses assume a lot of prior knowledge. This programme bridges the gap between mathematical theory and financial practice by providing a practical and visual approach to the most useful theories and methods. Calculations will be fully explained, and Excel spreadsheets will be used as a supporting resource to provide further examples.

Información importante
¿Qué objetivos tiene esta formación?

¿Esta formación es para mí?

Anyone who needs to develop their understanding and use of mathematics in a financial context.

Requisitos: The maths that you knew at school and some basic familiarity with Excel.


Dónde se imparte y en qué fechas

Inicio Ubicación
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Hong Kong
Hong Kong, Hong Kong
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30 mayo 2017
34 Curlew Street, se12nd, London, Inglaterra
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New York
New York, Estados Unidos
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¿Qué aprendes en este curso?

Financial Training
MS Excel
Numerical Methods
Maths Refresher
Polynomial functions
Financial techniques

Programa académico

Day One

Numbers, Algebra and Functions
  • Linear, quadratic and other polynomial functions
  • Numerical methods and the Taylor series
  • Role of the exponential function in Finance
  • Bonds and Bond Yields
  • Modelling Yield Curves with polynomials and splines
  • Price optimisation using quadratics
Differentials and Calculus
  • Gradients, rates of change and differential calculus
  • Partial Differentials and PDEs
  • Definite and indefinite integrals
  • Techniques in calculus
  • Bond Prices, Interest Rates and Duration
  • Role of the Diffusion Equation PDE in Finance
Matrix Algebra
  • Matrix rules and operations
  • Cofactors and Determinants
  • The Portfolio Matrix
  • Simultaneous equations and solutions
  • Payoff Matrices
  • Portfolio risk & return and the Variance Covariance matrix
Day Two

Probability and Sets
  • Sets, diagrams, notation and probability laws
  • Probability Trees and Discrete Probability Distributions
  • Hypothesis or Significance Testing
  • Probability Calculations
  • Expected Monetary Value
  • Significance Testing with Trading Data
Distributions and Stochastic Processes
  • Real world Distributions and Descriptive Statistics
  • Theoretical probability distributions – Binomial, Normal and others
  • Stochastic approaches to Financial Data
  • Random walks and the Wiener Process
  • Descriptive Statistics and the FTSE
  • Random variables and Random walks
  • Stochastic Equity Returns Modelling
Forecasting and Regression
  • Time series Approaches
  • Correlation, Variance and Covariance
  • Linear and multiple regression
  • Real data and cautions in forecasting
  • Simple linear regression
  • Multiple regression forecasting models
Further Advanced Workshop Excel examples combine mathematical techniques from across the course and cover:
  • Simple and Log returns, Volatility and VaR
  • Log returns, Alpha, Beta and the Security Characteristic Line
  • Modern Portfolio Theory and CAPM
  • Modelling Bond Default with Probability Transition Matrices