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## Datascience for Finance

• Teacher(s):   F.Ielpo
• Course given in: English
• ECTS Credits: 6 credits
• Schedule: Autumn Semester 2019-2020, 4.0h. course + 1.0h exercices (weekly average)
•  sessions
•  course website
• Related programmes:
Master of Science (MSc) in Finance, Orientation Asset and Risk Management

Master of Science (MSc) in Finance, Orientation Corporate Finance

Master of Science (MSc) in Finance : Financial Entrepreneurship and Data Science

### Objectives

The objective of the class is to provide students with:

• an understanding the basic concepts of statistics and estimation
• an understanding of how to design an estimation strategy
• an understanding of how to efficiently implement it and then reach an interpretation of the results.

This class should be a "hands-on" class on dealing with data.

### Contents

1. From moment estimation to maximum likelihood estimation

• Moment estimation
• Generalized method of moments
• Maximum likelihood estimation
• Goodness of fit tests
• Numerical optimization

2. The linear model

• Ordinary Least Square for the univariate linear model
• Multivariate linear model
• Instrumental variables
• Introduction to time series analysis
• Forecasting

3. Big data and non-linear models

• Dealing with large datasets
• From non parametric estimation to machine learning.

### References

J. Hamilton (1994), “Time Series Analysis” (Princeton University Press).

F. Hayashi (2000), “Econometrics” (Princeton University Press).

W. Greene (2011), “Econometric Analysis” (7th edition, Prentice Hall).

### Evaluation

#### First attempt

Exam:
Without exam (cf. terms)
Evaluation:

Grade will be determined based on

• Assignments (A)
• Project (P)

according to the rule:

a group project will be accounting for 50% of the grade and 50% for the weekly assignments

#### Retake

Exam:
Oral 0h20 minutes
Documentation:
Not allowed
Calculator:
Not allowed
Evaluation:

Retake exam is an oral exam with a set of questions to prepare and answer. Closed book exam, no calculator permitted.

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