Acerca de este Curso
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Aprox. 27 horas para completar

Sugerido: 4 weeks - 4 hours per week...

Inglés (English)

Subtítulos: Inglés (English)
User
Los estudiantes que toman este Course son
  • Traders
  • Financial Analysts
  • Financial Advisors
  • Risk Managers
  • Data Scientists

Qué aprenderás

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    Gain an intuitive understanding for the underlying theory behind Modern Portfolio Construction Techniques

  • Check

    Write custom Python code to estimate risk and return parameters

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    Utilize powerful Python optimization libraries to build scientifically and systematically diversified portfolios

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    Build custom utilities in Python to test and compare portfolio strategies

User
Los estudiantes que toman este Course son
  • Traders
  • Financial Analysts
  • Financial Advisors
  • Risk Managers
  • Data Scientists

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Aprox. 27 horas para completar

Sugerido: 4 weeks - 4 hours per week...

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
5 horas para completar

Analysing returns

14 videos (Total 225 minutos), 2 lecturas, 1 cuestionario
14 videos
Installing Anaconda3m
Fundamentals of Returns10m
Lab Session-Basics of returns29m
Measures of Risk and Reward9m
Lab Session-Risk Adjusted returns28m
Measuring Max Drawdown10m
Lab Session-Drawdown30m
Deviations from Normality9m
Lab Session-Building your own modules12m
Downside risk measures8m
Lab Session-Deviations from Normality30m
Estimating VaR10m
Lab Session-Semi Deviation, VAR andCVAR27m
2 lecturas
Material at your disposal5m
Module 1- Key points2m
1 ejercicio de práctica
Module 1 Graded Quiz1h
Semana
2
4 horas para completar

An Introduction to Portfolio Optimization

10 videos (Total 172 minutos), 1 lectura, 1 cuestionario
10 videos
Lab Session-Efficient frontier-Part 123m
Markowitz Optimization and the Efficient Frontier9m
Applying quadprog to draw the efficient Frontier11m
Lab Session-Asset Efficient Frontier-Part 220m
Lab Session-Applying Quadprog to Draw the Efficient Frontier38m
Fund Separation Theorem and the Capital Market Line7m
Lab Session-Locating the Max Sharpe Ratio Portfolio25m
Lack of robustness of Markowitz analysis5m
Lab Session-Plotting EW and GMV on the Efficient Frontier20m
1 lectura
Module 2 - Key points2m
1 ejercicio de práctica
Module 2 Graded Quiz1h
Semana
3
5 horas para completar

Beyond Diversification

15 videos (Total 236 minutos), 2 lecturas, 1 cuestionario
15 videos
Lab session- Limits of Diversification-Part119m
Lab session-Limits of diversification-Part 222m
An introduction to CPPI - Part 17m
An introduction to CPPI - Part 210m
Lab session-CPPI and Drawdown Constraints-Part129m
Lab session-CPPI and Drawdown Constraints-Part228m
Simulating asset returns with random walks10m
Monte Carlo Simulation6m
Lab Session-Random Walks and Monte Carlo22m
Analyzing CPPI strategies11m
Lab Session-Installing IPYWIDGETS5m
Designing and calibrating CPPI strategies12m
Lab session - interactive plots of monte Carlo Simulations of CPPI and GBM-Part119m
Lab session - interactive plots of monte Carlo Simulations of CPPI and GBM-Part221m
2 lecturas
Module 3 - Key points2m
Instruction prior to begin the module 3 graded quizz10m
1 ejercicio de práctica
Module 3 Graded Quiz45m
Semana
4
9 horas para completar

Introduction to Asset-Liability Management

12 videos (Total 327 minutos), 4 lecturas, 1 cuestionario
12 videos
Lab Session-Present Values,liabilities and funding ratio22m
Liability hedging portfolios12m
Lab Session-CIR Model and cash vs ZC bonds1h 8m
Liability-driven investing (LDI)10m
Lab Session-Liability driven investing51m
Choosing the policy portfolio14m
Lab Session-Monte Carlo simulation of coupon-bearing bonds using CIR33m
Beyond LDI11m
Lab Session-Naive risk budgeting between the PSP & GHP44m
Liability-friendly equity portfolios10m
Lab Session-Dynamic risk budgeting between PSP & LHP40m
4 lecturas
Module 4 - Key points2m
Dynamic Liability-Driven Investing Strategies: The Emergence Of A New Investment Paradigm For Pension Funds?1h 30m
Liability-Driven-Investing1h
Instruction prior to begin module 4 graded quizz2m
1 ejercicio de práctica
Module 4 Graded Quiz1h
4.9
6 revisionesChevron Right

Principales revisiones sobre Introduction to Portfolio Construction and Analysis with Python

por MLOct 20th 2019

VERY DIDACTIC AND THOROUGH TEACHERS : every classes were extremely well-driven, it was a pleasure. I learned a lot!!!

por KWNov 7th 2019

Good theory and great lab sessions. An interesting mix of asset management theory and Python.

Instructores

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Vijay Vaidyanathan, PhD

Optimal Asset Management Inc.
CEO
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Lionel Martellini, PhD

EDHEC-Risk Institute, Director
Finance

Acerca de EDHEC Business School

Founded in 1906, EDHEC is now one of Europe’s top 15 business schools . Based in Lille, Nice, Paris, London and Singapore, and counting over 90 nationalities on its campuses, EDHEC is a fully international school directly connected to the business world. With over 40,000 graduates in 120 countries, it trains committed managers capable of dealing with the challenges of a fast-evolving world. Harnessing its core values of excellence, innovation and entrepreneurial spirit, EDHEC has developed a strategic model founded on research of true practical use to society, businesses and students, and which is particularly evident in the work of EDHEC-Risk Institute and Scientific Beta. The School functions as a genuine laboratory of ideas and plays a pioneering role in the field of digital education via EDHEC Online, the first fully online degree-level training platform. These various components make EDHEC a centre of knowledge, experience and diversity, geared to preparing new generations of managers to excel in a world subject to transformational change. EDHEC in figures: 8,600 students in academic education, 19 degree programmes ranging from bachelor to PhD level, 184 professors and researchers, 11 specialist research centres. ...

Acerca de Programa especializado Investment Management with Python and Machine Learning

The Data Science and Machine Learning for Asset Management Specialization has been designed to deliver a broad and comprehensive introduction to modern methods in Investment Management, with a particular emphasis on the use of data science and machine learning techniques to improve investment decisions.By the end of this specialization, you will have acquired the tools required for making sound investment decisions, with an emphasis not only on the foundational theory and underlying concepts, but also on practical applications and implementation. Instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language through a series of dedicated lab sessions....
Investment Management with Python and Machine Learning

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

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