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
Université de l'Illinois à Urbana-ChampaignÀ propos de ce cours
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Niveau intermédiaire
Approx. 23 heures pour terminer
Anglais
Sous-titres : Anglais
Ce que vous allez apprendre
Understand the forecasting process
Describe time series data
Develop an ARIMA Model
Understand a basic trading algorithm
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
Approx. 23 heures pour terminer
Anglais
Sous-titres : Anglais
Offert par
Université de l'Illinois à 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.
Commencez à travailler pour obtenir votre master
Ce cours fait partie du diplôme intégralement en ligne Master of Science in Accountancy (iMSA) de Université de l'Illinois à Urbana-Champaign.
Si vous êtes admis(e) au programme complet, vos cours sont pris en compte dans votre apprentissage diplômant.
Programme du cours : ce que vous apprendrez dans ce cours
1 heure pour terminer
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.
1 heure pour terminer
3 vidéos (Total 11 min), 4 lectures, 1 quiz
3 vidéos
Instructor Bio: Jose Rodriguez ***2 min
Interview with Jose Rodriguez6 min
4 lectures
Syllabus30 min
Glossary10 min
Resources for R10 min
About the Discussion Forums10 min
1 exercice pour s'entraîner
Orientation Quiz10 min
5 heures pour terminer
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 heures pour terminer
7 vidéos (Total 45 min), 2 lectures, 5 quiz
7 vidéos
Jose Rodriguez: Forecasting in Practice2 min
Lesson 1-1.1 Subjective Forecasting6 min
Lesson 1-1.2 Business Forecasting and Time Series Data7 min
Lesson 1-2.1 Introduction to Financial Analytics10 min
Lesson 1-3.1 Forecasting Performance Measurements: Distance6 min
Lesson 1-3.2 Forecasting Performance Measurements: Metrics10 min
2 lectures
Module 1 Overview20 min
Module 1 Readings1h 30min
5 exercices pour s'entraîner
Lesson 1-1 Practice Quiz10 min
Lesson 1-2 Practice Quiz10 min
Lesson 1-3 Practice Quiz10 min
Module 1 Quiz30 min
Module 1 Lab Exercise Quiz30 min
5 heures pour terminer
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 heures pour terminer
15 vidéos (Total 87 min), 2 lectures, 7 quiz
15 vidéos
Jose Rodriguez: Forecasting Models in Practice2 min
Lesson 2-1.1 Introduction to Forecasting: Average Method6 min
Lesson 2-1.2 Introduction to Forecasting: Naive Method3 min
Lesson 2-1.3 Introduction to Forecasting: Linear Regression ***13 min
Lesson 2-1.4 Introduction to Forecasting: R Example4 min
Lesson 2-2.1 Moving Averages7 min
Lesson 2-3.1 Introduction to Exponential Smoothing5 min
Lesson 2-3.2 Simple Exponential Smoothing8 min
Lesson 2-3.3 Simple Exponential Smoothing: R Example5 min
Lesson 2-4.1 Holt's Exponential Smoothing7 min
Lesson 2-4.2 Holt-Winter's Forecasting Model4 min
Lesson 2-4.3 Holt-Winter's Model: R Example7 min
Lesson 2-5.1 Autoregression6 min
Lesson 2-5.2 Autoregression: R Example2 min
2 lectures
Module 2 Overview20 min
Module 2 Readings7 min
7 exercices pour s'entraîner
Lesson 2-1 Practice Quiz10 min
Lesson 2-2 Practice Quiz10 min
Lesson 2-3 Practice Quiz30 min
Lesson 2-4 Practice Quiz30 min
Lesson 2-5 Practice Quiz10 min
Module 2 Quiz30 min
Module 2 Lab Exercise Quiz30 min
5 heures pour terminer
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 heures pour terminer
11 vidéos (Total 55 min), 2 lectures, 4 quiz
11 vidéos
Jose Rodriguez: ARIMA in Practice2 min
Lesson 3-1.1 Stationarity: Introduction5 min
Lesson 3-1.2 Stationarity: Differencing11 min
Lesson 3-2.1 ARIMA: Introduction6 min
Lesson 3-2.2 ARIMA: Components7 min
Lesson 3-2.3 ARIMA: Model and R Example Part 17 min
Lesson 3-2.4 ARIMA: Model and R Example Part 24 min
Lesson 3-2.5 ARIMA: Model and R Example Part 31 min
Lesson 3-2.6 ARIMA: Model and R Example Part 43 min
Lesson 3-2.7 ARIMA: Model and R Example Part 54 min
2 lectures
Module 3 Overview20 min
Module 3 Readings30 min
4 exercices pour s'entraîner
Lesson 3-1 Practice Quiz30 min
Lesson 3-2 Practice Quiz30 min
Module 3 Quiz30 min
Module 3 Lab Exercise Quiz30 min
6 heures pour terminer
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.
6 heures pour terminer
15 vidéos (Total 77 min), 2 lectures, 4 quiz
15 vidéos
Jose Rodriguez: Portfolios in Practice4 min
Lesson 4-1.1 Portfolio Theory: Introduction3 min
Lesson 4-1.2 Portfolio Theory: Expected Returns4 min
Lesson 4-1.3 Portfolio Theory: Risk of a Security6 min
Lesson 4-1.4 Portfolio Theory: Efficient Frontier6 min
Lesson 4-1.5 Portfolio Theory: Portfolio Weights7 min
Lesson 4-1.6 Portfolio Theory: Capital Allocation Line10 min
Lesson 4-1.7 Portfolio Theory: Diversification3 min
Lesson 4-2.1 Introduction to Algorithmic Trading7 min
Lesson 4-2.2 Introduction to Algorithmic Trading: Trend Following Strategy3 min
Lesson 4-2.3 Introduction to Algorithmic Trading: Backtesting6 min
Lesson 4-2.4 Introduction to Algorithmic Trading: R Example9 min
Lesson 4-2.5 Introduction to Algorithmic Trading: Conclusion1 min
Course Summary: Applying Data Analytics in Finance1 min
2 lectures
Module 4 Overview20 min
Module 4 Readings1 h
4 exercices pour s'entraîner
Lesson 4-1 Practice Quiz30 min
Lesson 4-2 Practice Quiz30 min
Module 4 Quiz1 h
Module 4 Lab Exercise Quiz30 min
Avis
Meilleurs avis pour APPLYING DATA ANALYTICS IN FINANCE
par R31 mai 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.
par MK16 avr. 2020
It is a very nice course. Very useful for learning basics of Financial Analytics. Prof. Kim's sessions were very nice.
par VG2 mai 2020
Covers basics of time series modeling techniques and applications in R. Doesn't go deep into statistics behind models
par K22 mai 2020
This is a good course for Financial professionals/students who look forward to take up a as Financial Analyst.
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