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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.

공유 가능한 수료증

완료 시 수료증 획득

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 23시간 필요

영어

자막: 영어

배울 내용

Understand the forecasting process

Describe time series data

Develop an ARIMA Model

Understand a basic trading algorithm

공유 가능한 수료증

완료 시 수료증 획득

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 23시간 필요

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

주

1

주 1

완료하는 데 2시간 필요

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.

완료하는 데 2시간 필요

10개 동영상 (총 48분), 5 개의 읽기 자료, 1 개의 테스트

10개의 동영상

Course Overview: Applying Data Analytics in Finance1m

Interview with Jose Rodriguez6m

Tour of R and RStudio5m

Projects3m

Math Function4m

Scalar Variables6m

Column Vectors9m

Data Frame6m

Data Frame Import2m

Help and Cheat Sheets2m

5개의 읽기 자료

Syllabus30m

Glossary10m

Update Your Profile10m

About the Discussion Forums10m

Data Download Tutorial10m

1개 연습문제

Orientation Quiz10m

완료하는 데 4시간 필요

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.

완료하는 데 4시간 필요

6개 동영상 (총 44분), 2 개의 읽기 자료, 4 개의 테스트

6개의 동영상

Jose Rodriguez: Forecasting in Practice2m

Lesson 1-1.1 Subjective Forecasting6m

Lesson 1-1.2 Business Forecasting and Time Series Data7m

Lesson 1-2.1 Introduction to Financial Analytics10m

Lesson 1-3.1 Forecasting Performance Measurements: Distance6m

Lesson 1-3.2 Forecasting Performance Measurements: Metrics10m

2개의 읽기 자료

Module 1 Overview20m

Module 1 Readings1시간 30분

4개 연습문제

Lesson 1-1 Practice Quiz10m

Lesson 1-2 Practice Quiz10m

Lesson 1-3 Practice Quiz10m

Module 1 Quiz30m

주

2

주 2

완료하는 데 5시간 필요

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.

완료하는 데 5시간 필요

15개 동영상 (총 92분), 2 개의 읽기 자료, 7 개의 테스트

15개의 동영상

Jose Rodriguez: Forecasting Models in Practice2m

Lesson 2-1.1 Introduction to Forecasting: Average Method6m

Lesson 2-1.2 Introduction to Forecasting: Naive Method3m

Lesson 2-1.3 Introduction to Forecasting: Linear Regression13m

Lesson 2-1.4 Introduction to Forecasting: R Example4m

Lesson 2-2.1 Moving Averages6m

Lesson 2-2.2 Moving Averages: R Example6m

Lesson 2-3.1 Introduction to Exponential Smoothing5m

Lesson 2-3.2 Simple Exponential Smoothing8m

Lesson 2-3.3 Simple Exponential Smoothing: R Example5m

Lesson 2-4.1 Holt's Exponential Smoothing7m

Lesson 2-4.2 Holt-Winter's Forecasting Model4m

Lesson 2-4.3 Holt-Winter's Model: R Example7m

Lesson 2-5.1 Autoregression6m

Lesson 2-5.2 Autoregression: R Example2m

2개의 읽기 자료

Module 2 Overview20m

Module 2 Readings7m

6개 연습문제

Lesson 2-1 Practice Quiz10m

Lesson 2-2 Practice Quiz10m

Lesson 2-3 Practice Quiz30m

Lesson 2-4 Practice Quiz30m

Lesson 2-5 Practice Quiz10m

Module 2 Quiz30m

주

3

주 3

완료하는 데 5시간 필요

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.

완료하는 데 5시간 필요

10개 동영상 (총 54분), 2 개의 읽기 자료, 4 개의 테스트

10개의 동영상

Jose Rodriguez: ARIMA in Practice2m

Lesson 3-1.1 Stationarity: Introduction5m

Lesson 3-1.2 Stationarity: Differencing11m

Lesson 3-2.1 ARIMA: Introduction6m

Lesson 3-2.2 ARIMA: Components7m

Lesson 3-2.3 ARIMA: Model and R Example Part 17m

Lesson 3-2.4 ARIMA: Model and R Example Part 24m

Lesson 3-2.5 ARIMA: Model and R Example Part 31m

Lesson 3-2.6 ARIMA: Model and R Example Part 43m

Lesson 3-2.7 ARIMA: Model and R Example Part 54m

2개의 읽기 자료

Module 3 Overview20m

Module 3 Readings30m

3개 연습문제

Lesson 3-1 Practice Quiz30m

Lesson 3-2 Practice Quiz30m

Module 3 Quiz30m

주

4

주 4

완료하는 데 7시간 필요

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.

완료하는 데 7시간 필요

14개 동영상 (총 76분), 2 개의 읽기 자료, 4 개의 테스트

14개의 동영상

Jose Rodriguez: Portfolios in Practice4m

Lesson 4-1.1 Portfolio Theory: Introduction3m

Lesson 4-1.2 Portfolio Theory: Expected Returns4m

Lesson 4-1.3 Portfolio Theory: Risk of a Security6m

Lesson 4-1.4 Portfolio Theory: Efficient Frontier6m

Lesson 4-1.5 Portfolio Theory: Portfolio Weights7m

Lesson 4-1.6 Portfolio Theory: Capital Allocation Line10m

Lesson 4-1.7 Portfolio Theory: Diversification3m

Lesson 4-2.1 Introduction to Algorithmic Trading7m

Lesson 4-2.2 Introduction to Algorithmic Trading: Trend Following Strategy3m

Lesson 4-2.3 Introduction to Algorithmic Trading: Backtesting6m

Lesson 4-2.4 Introduction to Algorithmic Trading: R Example9m

Lesson 4-2.5 Introduction to Algorithmic Trading: Conclusion1m

Course Summary: Applying Data Analytics in Finance1m

2개의 읽기 자료

Module 4 Overview20m

Module 4 Readings1시간

3개 연습문제

Lesson 4-1 Practice Quiz30m

Lesson 4-2 Practice Quiz30m

Module 4 Quiz1시간

자주 묻는 질문

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?

You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.
Is financial aid available?

Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.

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Applying Data Analytics in Finance