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.

Applying Data Analytics in Finance
イリノイ大学アーバナ・シャンペーン校(University of Illinois at Urbana-Champaign)このコースについて
学習内容
Understand the forecasting process
Describe time series data
Develop an ARIMA Model
Understand a basic trading algorithm
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イリノイ大学アーバナ・シャンペーン校(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.
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シラバス - 本コースの学習内容
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.
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.
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.
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.
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.
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- 5 stars66.14%
- 4 stars24.47%
- 3 stars3.12%
- 2 stars3.12%
- 1 star3.12%
APPLYING DATA ANALYTICS IN FINANCE からの人気レビュー
Great Course and excellent explanation by professor
The course was upto the mark and helped me to learn data analytics Application in finance.
This is a good course for Financial professionals/students who look forward to take up a as Financial Analyst.
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.
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