Matlab for Finance Training Course

Nobleprog Limited

Course

In City Of London

Price on request

The best .Net and C# courses

See all

See all

Description

  • Type

    Course

  • Location

    City of london

7 week comprehensive Data Science course

The explosion of information and data in today’s world is un-paralleled, our ability to innovate and push the boundaries of the possible is growing faster than it ever has. The role of Data Scientist is one of the highest in-demand skills across industry today.

We offer much more than learning through theory; we deliver practical, marketable skills that bridge the gap between the world of academia and the demands of industry.

This 7 week curriculum can be tailored to your specific Industry requirements.

Course Outline

Week 1 - Big Data concepts:
VVVV (Velocity, Volume, Variety, Veracity) definition
Limits to traditional data processing capacity
Distributed Processing
Statistical Analysis
Machine Learning Analysis Types
Data Visualization
Distributed Processing
Introduction to used languages
R language crash-course
Python crash course

Weeks 2&3 - Performing Data Analysis:
Statistical Analysis
Descriptive Statistics in Big Data sets
Inferential Statistics
Forecasting with Correlation and Regression models
Time Series analysis
Basics of Machine Learning
Supervised vs unsupervised learning
Classification and clustering
Estimating cost of specific methods
Filter

Week 4 - Natural Language Processing:
Processing text
Understanding meaning of the text
Automatic text generation
Sentiment/Topic Analysis

Week 5&6 - Tooling concept:
Data storage solution
Choosing right solution to the problem
Distributed Processing
Spark
Machine Learning with Spark
Spark SQL
Scalability
Public cloud
Private cloud
Autoscalability

Week 7 - Soft Skills:
Advisory & Leadership Skills
Making an impact: data-driven story telling
Understanding your audience
Effective data presentation - getting your message across
Influence effectiveness and change leadership
Handling difficult situations

Exam
End of Programme graduation exam

Facilities

Location

Start date

City Of London (London)
See map
Token House, 11-12 Tokenhouse Yard, EC2R 7AS

Start date

On request

Questions & Answers

Add your question

Our advisors and other users will be able to reply to you

Who would you like to address this question to?

Fill in your details to get a reply

We will only publish your name and question

Reviews

Subjects

  • Financial Training
  • IT risk
  • Financial
  • Finance
  • Fixed Income
  • Risk
  • Leadership
  • Forecasting
  • Artificial Intelligence
  • Testing
  • Data Mining
  • Database
  • Database training
  • Data analysis
  • Statistics
  • Technology
  • Industry
  • Python
  • Machine Learning
  • Big Data
  • Data science

Teachers and trainers (1)

Kristian Rother

Kristian Rother

Trainer

Course programme

Overview of the MATLAB Financial Toolbox

Objective: Learn to apply the various features included in the MATLAB Financial Toolbox to perform quantitative analysis for the financial industry. Gain the knowledge and practice needed to efficiently develop real-world applications involving financial data.

  • Asset Allocation and Portfolio Optimization
  • Risk Analysis and Investment Performance
  • Fixed-Income Analysis and Option Pricing
  • Financial Time Series Analysis
  • Regression and Estimation with Missing Data
  • Technical Indicators and Financial Charts
  • Monte Carlo Simulation of SDE Models

Asset Allocation and Portfolio Optimization

Objective: perform capital allocation, asset allocation, and risk assessment.

  • Estimating asset return and total return moments from price or return data
  • Computing portfolio-level statistics, such as mean, variance, value at risk (VaR), and conditional value at risk (CVaR)
  • Performing constrained mean-variance portfolio optimization and analysis
  • Examining the time evolution of efficient portfolio allocations
  • Performing capital allocation
  • Accounting for turnover and transaction costs in portfolio optimization problems

Risk Analysis and Investment Performance

Objective: Define and solve portfolio optimization problems.

  • Specifying a portfolio name, the number of assets in an asset universe, and asset identifiers.
  • Defining an initial portfolio allocation.

Fixed-Income Analysis and Option Pricing

Objective: Perform fixed-income analysis and option pricing.

  • Analyzing cash flow
  • Performing SIA-Compliant fixed-income security analysis
  • Performing basic Black-Scholes, Black, and binomial option-pricing

Financial Time Series Analysis

Objective: analyze time series data in financial markets.

  • Performing data math
  • Transforming and analyzing data
  • Technical analysis
  • Charting and graphics

Regression and Estimation with Missing Data

Objective: Perform multivariate normal regression with or without missing data.

  • Performing common regressions
  • Estimating log-likelihood function and standard errors for hypothesis testing
  • Completing calculations when data is missing

Technical Indicators and Financial Charts

Objective: Practice using performance metrics and specialized plots.

  • Moving averages
  • Oscillators, stochastics, indexes, and indicators
  • Maximum drawdown and expected maximum drawdown
  • Charts, including Bollinger bands, candlestick plots, and moving averages

Monte Carlo Simulation of SDE Models

Objective: Create simulations and apply SDE models

  • Brownian Motion (BM)
  • Geometric Brownian Motion (GBM)
  • Constant Elasticity of Variance (CEV)
  • Cox-Ingersoll-Ross (CIR)
  • Hull-White/Vasicek (HWV)
  • Heston

Conclusion

See related categories

Matlab for Finance Training Course

Price on request

The best .Net and C# courses

See all

See all