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
University of Illinois at Urbana-ChampaignÜber diesen Kurs
19,059 kürzliche Aufrufe
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Mittel“
Ca. 23 Stunden zum Abschließen
Englisch
Untertitel: Arabischer Raum, Französisch, Portugiesisch (europäisch), Chinesisch (vereinfacht), Italienisch, Vietnamesisch, Koreanisch, Deutsch, Russisch, Türkisch, Englisch, Spanisch
Was Sie lernen werden
Understand the forecasting process
Describe time series data
Develop an ARIMA Model
Understand a basic trading algorithm
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Mittel“
Ca. 23 Stunden zum Abschließen
Englisch
Untertitel: Arabischer Raum, Französisch, Portugiesisch (europäisch), Chinesisch (vereinfacht), Italienisch, Vietnamesisch, Koreanisch, Deutsch, Russisch, Türkisch, Englisch, Spanisch
von
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.
Beginnen Sie damit, auf Ihren Master-Abschluss hinzuarbeiten.
Dieses Kurs ist Teil des reinen Onlineabschlusses Master of Science in Accountancy (iMSA) von University of Illinois at Urbana-Champaign.
Wenn Sie in das komplette Programm aufgenommen werden, werden Ihre Kurse auf Ihren Abschluss angerechnet.
Lehrplan - Was Sie in diesem Kurs lernen werden
1 Stunde zum Abschließen
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 Stunde zum Abschließen
3 Videos (Gesamt 11 min), 4 Lektüren, 1 Quiz
3 Videos
Instructor Bio: Jose Rodriguez ***2m
Interview with Jose Rodriguez6m
4 Lektüren
Syllabus30m
Glossary10m
Resources for R10m
About the Discussion Forums10m
1 praktische Übung
Orientation Quiz10m
5 Stunden zum Abschließen
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 Stunden zum Abschließen
7 Videos (Gesamt 45 min), 2 Lektüren, 5 Quiz
7 Videos
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
2 Lektüren
Module 1 Overview20m
Module 1 Readings1h 30m
5 praktische Übungen
Lesson 1-1 Practice Quiz10m
Lesson 1-2 Practice Quiz10m
Lesson 1-3 Practice Quiz10m
Module 1 Quiz30m
Module 1 Lab Exercise Quiz30m
5 Stunden zum Abschließen
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 Stunden zum Abschließen
15 Videos (Gesamt 87 min), 2 Lektüren, 7 Quiz
15 Videos
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 Regression ***13m
Lesson 2-1.4 Introduction to Forecasting: R Example4m
Lesson 2-2.1 Moving Averages7m
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
2 Lektüren
Module 2 Overview20m
Module 2 Readings7m
7 praktische Übungen
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
Module 2 Lab Exercise Quiz30m
5 Stunden zum Abschließen
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 Stunden zum Abschließen
11 Videos (Gesamt 55 min), 2 Lektüren, 4 Quiz
11 Videos
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
2 Lektüren
Module 3 Overview20m
Module 3 Readings30m
4 praktische Übungen
Lesson 3-1 Practice Quiz30m
Lesson 3-2 Practice Quiz30m
Module 3 Quiz30m
Module 3 Lab Exercise Quiz30m
6 Stunden zum Abschließen
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 Stunden zum Abschließen
15 Videos (Gesamt 77 min), 2 Lektüren, 4 Quiz
15 Videos
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
2 Lektüren
Module 4 Overview20m
Module 4 Readings1h
4 praktische Übungen
Lesson 4-1 Practice Quiz30m
Lesson 4-2 Practice Quiz30m
Module 4 Quiz1h
Module 4 Lab Exercise Quiz30m
Bewertungen
Top-Bewertungen von APPLYING DATA ANALYTICS IN FINANCE
von 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.
von MK16. Apr. 2020
It is a very nice course. Very useful for learning basics of Financial Analytics. Prof. Kim's sessions were very nice.
von VG2. Mai 2020
Covers basics of time series modeling techniques and applications in R. Doesn't go deep into statistics behind models
von K22. Mai 2020
This is a good course for Financial professionals/students who look forward to take up a as Financial Analyst.
Häufig gestellte Fragen
Wann erhalte ich Zugang zu den Vorträgen und Aufgaben?
Was bekomme ich, wenn ich das Zertifikat erwerbe?
Is financial aid available?
Erhalte ich akademische Leistungspunkte für den Abschluss des Kurses?
Haben Sie weitere Fragen? Besuchen Sie das Hilfe-Center für Teiln..
