4.5
stars
197 ratings

Sung Won Kim +1 more instructor

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Make progress toward the Master of Business Administration (iMBA) degree

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Applying Data Analytics in Finance

University of Illinois at Urbana-Champaign

About this Course

15,780 recent views

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.
After completing this course, you should be able to understand time series data, create forecasts, and determine the efficacy of the estimates. Also, you will be able to create a portfolio of assets using actual stock price data while optimizing risk and reward. Understanding financial data is an important skill as an analyst, manager, or consultant.

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.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Intermediate Level

Approx. 23 hours to complete

English

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.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Intermediate Level

Approx. 23 hours to complete

English

Instructors

Instructor rating

4.59/5 (48 Ratings)

Sung Won Kim

Associate Professor

Business Administration

20,233 Learners

1 Course

Jose Luis Rodriguez

Director of Margolis Market Information Lab

Department of Finance - Gies College of Business

20,669 Learners

2 Courses

Offered by

University of Illinois at Urbana-Champaign

Get a head start on your degree

This course is part of the Master of Business Administration (iMBA) from University of Illinois at Urbana-Champaign. If you are admitted to the full program, your coursework will count towards your degree learning and all of your progress will transfer with you.

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Syllabus - What you will learn from this course

Content Rating93%(1,065 ratings)

Week1

Week 1

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

7 videos

Module 1 Overview ***54sJose Rodriguez: Forecasting in Practice2mLesson 1-1.1 Subjective Forecasting6mLesson 1-1.2 Business Forecasting and Time Series Data7mLesson 1-2.1 Introduction to Financial Analytics10mLesson 1-3.1 Forecasting Performance Measurements: Distance6mLesson 1-3.2 Forecasting Performance Measurements: Metrics10m

2 readings

Module 1 Overview20mModule 1 Readings1h 30m

5 practice exercises

Lesson 1-1 Practice Quiz10mLesson 1-2 Practice Quiz10mLesson 1-3 Practice Quiz10mModule 1 Quiz30mModule 1 Lab Exercise Quiz30m

Week2

Week 2

5 hours to complete

Module 2: Performance Measures and Holt-Winters Model

5 hours to complete

15 videos (Total 87 min), 2 readings, 7 quizzes

15 videos

Module 2 Overview ***37sJose Rodriguez: Forecasting Models in Practice2mLesson 2-1.1 Introduction to Forecasting: Average Method6mLesson 2-1.2 Introduction to Forecasting: Naive Method3mLesson 2-1.3 Introduction to Forecasting: Linear Regression ***13mLesson 2-1.4 Introduction to Forecasting: R Example4mLesson 2-2.1 Moving Averages7mLesson 2-3.1 Introduction to Exponential Smoothing5mLesson 2-3.2 Simple Exponential Smoothing8mLesson 2-3.3 Simple Exponential Smoothing: R Example5mLesson 2-4.1 Holt's Exponential Smoothing7mLesson 2-4.2 Holt-Winter's Forecasting Model4mLesson 2-4.3 Holt-Winter's Model: R Example7mLesson 2-5.1 Autoregression6mLesson 2-5.2 Autoregression: R Example2m

2 readings

Module 2 Overview20mModule 2 Readings7m

7 practice exercises

Lesson 2-1 Practice Quiz10mLesson 2-2 Practice Quiz10mLesson 2-3 Practice Quiz30mLesson 2-4 Practice Quiz30mLesson 2-5 Practice Quiz10mModule 2 Quiz30mModule 2 Lab Exercise Quiz30m

Week3

Week 3

5 hours to complete

Module 3: Stationarity and ARIMA Model

5 hours to complete

11 videos (Total 55 min), 2 readings, 4 quizzes

11 videos

Module 3 Overview ***43sJose Rodriguez: ARIMA in Practice2mLesson 3-1.1 Stationarity: Introduction5mLesson 3-1.2 Stationarity: Differencing11mLesson 3-2.1 ARIMA: Introduction6mLesson 3-2.2 ARIMA: Components7mLesson 3-2.3 ARIMA: Model and R Example Part 17mLesson 3-2.4 ARIMA: Model and R Example Part 24mLesson 3-2.5 ARIMA: Model and R Example Part 31mLesson 3-2.6 ARIMA: Model and R Example Part 43mLesson 3-2.7 ARIMA: Model and R Example Part 54m

2 readings

Module 3 Overview20mModule 3 Readings30m

4 practice exercises

Lesson 3-1 Practice Quiz30mLesson 3-2 Practice Quiz30mModule 3 Quiz30mModule 3 Lab Exercise Quiz30m

Week4

Week 4

7 hours to complete

Module 4: Modern Portfolio Theory and Intro to Algorithmic Trading

7 hours to complete

16 videos (Total 81 min), 4 readings, 4 quizzes

16 videos

Module 4 Overview ***49sJose Rodriguez: Portfolios in Practice4mLesson 4-1.1 Portfolio Theory: Introduction3mLesson 4-1.2 Portfolio Theory: Expected Returns4mLesson 4-1.3 Portfolio Theory: Risk of a Security6mLesson 4-1.4 Portfolio Theory: Efficient Frontier6mLesson 4-1.5 Portfolio Theory: Portfolio Weights7mLesson 4-1.6 Portfolio Theory: Capital Allocation Line10mLesson 4-1.7 Portfolio Theory: Diversification3mLesson 4-2.1 Introduction to Algorithmic Trading7mLesson 4-2.2 Introduction to Algorithmic Trading: Trend Following Strategy3mLesson 4-2.3 Introduction to Algorithmic Trading: Backtesting6mLesson 4-2.4 Introduction to Algorithmic Trading: R Example9mLesson 4-2.5 Introduction to Algorithmic Trading: Conclusion1mCourse Summary: Applying Data Analytics in Finance1mGies Online Programs3m

4 readings

Module 4 Overview20mModule 4 Readings1hCongratulations!10mGet Your Course Certificate10m

4 practice exercises

Lesson 4-1 Practice Quiz30mLesson 4-2 Practice Quiz30mModule 4 Quiz1hModule 4 Lab Exercise Quiz30m

Reviews

4.5

37 reviews

5 stars
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4 stars
24.87%
3 stars
3.55%
2 stars
3.04%
1 star
3.04%

TOP REVIEWS FROM APPLYING DATA ANALYTICS IN FINANCE

by EDec 23, 2020

Very nice course. Loved the way of teaching. Thank you so much. Best regards,

Enjo

by SGMay 14, 2020

Very nice combination of R programming, financial concepts and statistical concepts.

by KMay 23, 2020

This is a good course for Financial professionals/students who look forward to take up a as Financial Analyst.

by VGMay 3, 2020

Covers basics of time series modeling techniques and applications in R. Doesn't go deep into statistics behind models

View all reviews

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Applying Data Analytics in Finance

Applying Data Analytics in Finance

About this Course

What you will learn