This course introduces an overview of financial analytics. You will learn why, when, and how to apply financial analytics in real-world situations. You will explore techniques to analyze time series data and how to evaluate the risk-reward trade off expounded in modern portfolio theory. While most of the focus will be on the prices, returns, and risk of corporate stocks, the analytical techniques can be leverages in other domains. Finally, a short introduction to algorithmic trading concludes the course.
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Applying Data Analytics in Finance
University of Illinois at Urbana-ChampaignAbout this Course
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Shareable Certificate
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100% online
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Intermediate Level
Approx. 23 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
What you will learn
Understand the forecasting process
Describe time series data
Develop an ARIMA Model
Understand a basic trading algorithm
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level
Approx. 23 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Offered by
University of Illinois at Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
Start working towards your degree
This Course is part of an online degree program offered by the University of Illinois at Urbana-Champaign. When you apply for a for-credit non-degree course through the university and complete it online, it counts as credit hours towards a degree at Illinois. All you have to do is apply through the university.
Syllabus - What you will learn from this course
2 hours to complete
Course Introduction
In this course, we will introduce a number of financial analytic techniques. You will learn why, when, and how to apply financial analytics in real-world situations. We will explore techniques to analyze time series data and how to evaluate the risk-reward trade off expounded in modern portfolio theory. While most of the focus will be on the prices, returns, and risks of corporate stocks, the analytical techniques can be leveraged in other domains. Finally, a short introduction to algorithmic trading concludes the course.
2 hours to complete
4 videos (Total 12 min), 5 readings, 1 quiz
5 hours to complete
Module 1: Introduction to Financial Analytics and Time Series Data
In this module, we will introduce an overview of financial analytics. Students will learn why, when, and how to apply financial analytics in real-world situations. We will explore techniques to analyze time series data and how to evaluate the risk-reward trade off expounded in modern portfolio theory. While most of our focus will be on the prices, returns, and risks of corporate stocks, the analytical techniques can be leveraged in other domains. Finally, a short introduction to algorithmic trading concludes the course.
5 hours to complete
7 videos (Total 45 min), 2 readings, 5 quizzes
5 hours to complete
Module 2: Performance Measures and Holt-Winters Model
We will introduce analytical methods to analyze time series data to build forecasting models and support decision-making. Students will learn how to analyze financial data that is usually presented as time series data. Topics include forecasting performance measures, moving average, exponential smoothing methods, and the Holt-Winters method.
5 hours to complete
15 videos (Total 87 min), 2 readings, 7 quizzes
5 hours to complete
Module 3: Stationarity and ARIMA Model
In this module, we will begin with stationarity, the first and necessary step in analyzing time series data. Students will learn how to identify if a time series is stationary or not and know how to make nonstationary data become stationary. Next, we will study a basic forecasting model: ARIMA. Students will learn how to build an ARIMA forecasting model using R.
5 hours to complete
11 videos (Total 55 min), 2 readings, 4 quizzes
7 hours to complete
Module 4: Modern Portfolio Theory and Intro to Algorithmic Trading
We will introduce some basic measurements of modern portfolio theory. Students will understand about risk and returns, how to balance them, and how to evaluate an investment portfolio.
7 hours to complete
16 videos (Total 81 min), 4 readings, 4 quizzes
Reviews
- 5 stars66.32%
- 4 stars24.35%
- 3 stars3.10%
- 2 stars3.10%
- 1 star3.10%
TOP REVIEWS FROM APPLYING DATA ANALYTICS IN FINANCE
by ATAug 12, 2020
A very brief and informing course. Learnt a lot in a short period of time
by RMay 31, 2020
Basics of R and other sub-topics need to be introduced before the topic is taken up in a video.
Despite several ID verifications, I have not received the Course certificate till date.
by VGMay 2, 2020
Covers basics of time series modeling techniques and applications in R. Doesn't go deep into statistics behind models
by JSJun 26, 2020
The study has detailed information of analytics in finance
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