Acerca de este Curso
5,822 vistas recientes

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. 11 horas para completar

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

Inglés (English)

Subtítulos: Inglés (English)

Qué aprenderás

  • Check

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

  • Check

    Write custom Python code to estimate risk and return parameters

  • Check

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

  • Check

    Build custom utilities in Python to test and compare portfolio strategies

Los estudiantes que toman este Course son
  • 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. 11 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
    7 horas para completar

    Introduction to Asset-Liability Management

    12 videos (Total 327 minutos), 2 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
    2 lecturas
    Module 4 - Key points2m
    Instruction prior to begin module 4 graded quizz2m
    1 ejercicio de práctica
    Module 4 Graded Quiz1h

    Instructores

    Avatar

    Vijay Vaidyanathan, PhD

    Optimal Asset Management Inc.
    CEO
    Avatar

    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.

    ¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.