Acerca de este Curso
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Nivel principiante

You will get the most out of the course if you have basic knowledge in probability.

Aprox. 10 horas para completar

Sugerido: 4 weeks of study, 3-4 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel principiante

You will get the most out of the course if you have basic knowledge in probability.

Aprox. 10 horas para completar

Sugerido: 4 weeks of study, 3-4 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
3 horas para completar

Visualizing and Munging Stock Data

Why do investment banks and consumer banks use Python to build quantitative models to predict returns and evaluate risks? What makes Python one of the most popular tools for financial analysis? You are going to learn basic python to import, manipulate and visualize stock data in this module. As Python is highly readable and simple enough, you can build one of the most popular trading models - Trend following strategy by the end of this module!...
7 videos (Total 30 minutos), 2 readings, 1 quiz
7 videos
1.0 Module Introduction3m
1.1 Packages for Data Analysis1m
1.2 Importing data2m
1.3 Basics of Dataframe5m
1.4 Generate new variables in Dataframe8m
1.5 Trading Strategy5m
2 lecturas
Grading Criteria5m
Getting started with Jupyter Notebook10m
1 ejercicio de práctica
Quiz 130m
Semana
2
2 horas para completar

Random variables and distribution

In the previous module, we built a simple trading strategy base on Moving Average 10 and 50, which are "random variables" in statistics. In this module, we are going to explore basic concepts of random variables. By understanding the frequency and distribution of random variables, we extend further to the discussion of probability. In the later part of the module, we apply the probability concept in measuring the risk of investing a stock by looking at the distribution of log daily return using python. Learners are expected to have basic knowledge of probability before taking this module....
4 videos (Total 19 minutos), 1 quiz
4 videos
2.1 Outcomes and Random Variables2m
2.2 Frequency and Distributions5m
2.3 Models of Distribution7m
1 ejercicio de práctica
Quiz 230m
Semana
3
3 horas para completar

Sampling and Inference

In financial analysis, we always infer the real mean return of stocks, or equity funds, based on the historical data of a couple years. This situation is in line with a core part of statistics - Statistical Inference - which we also base on sample data to infer the population of a target variable.In this module, you are going to understand the basic concept of statistical inference such as population, samples and random sampling. In the second part of the module, we shall estimate the range of mean return of a stock using a concept called confidence interval, after we understand the distribution of sample mean.We will also testify the claim of investment return using another statistical concept - hypothesis testing....
5 videos (Total 32 minutos), 1 quiz
5 videos
3.1 Population and Sample8m
3.2 Variation of Sample5m
3.3 Confidence Interval4m
3.4 Hypothesis Testing11m
1 ejercicio de práctica
Quiz 330m
Semana
4
4 horas para completar

Linear Regression Models for Financial Analysis

In this module, we will explore the most often used prediction method - linear regression. From learning the association of random variables to simple and multiple linear regression model, we finally come to the most interesting part of this course: we will build a model using multiple indices from the global markets and predict the price change of an ETF of S&P500. In addition to building a stock trading model, it is also great fun to test the performance of your own models, which I will also show you how to evaluate them!...
6 videos (Total 46 minutos), 1 reading, 2 quizzes
6 videos
4.1 Association of random variables5m
4.2 Simple linear regression model13m
4.3 Diagnostic of linear regression model4m
4.4 Multiple linear regression model14m
4.5 Evaluate the strategy5m
1 lectura
Please rate this course!2m
2 ejercicios de práctica
Quiz 430m
Post-course survey5m
4.6
38 revisionesChevron Right

Principales revisiones

por DAJan 21st 2019

Perfect for the beginning to intermediate python programmer who wants to utilize finance data to make decisions (i.e. trading).

por SDMay 1st 2019

I learned a lot about how to implement financial statistics in Python and some added knowledge on statistics. Great Course.

Instructor

Avatar

Xuhu Wan

Associate Professor
Department of Information Systems, Business Statistics and Operations Management

Acerca de Universidad Científica y Tecnológica de Hong Kong

HKUST - A dynamic, international research university, in relentless pursuit of excellence, leading the advance of science and technology, and educating the new generation of front-runners for Asia and the world....

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 compras un Certificado, obtienes acceso a todos los materiales del curso, incluidas las tareas calificadas. Una vez que completes el curso, 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 participar del curso como oyente sin costo.

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