Holczer Balazs – Quantitative Finance & Algorithmic Trading II – Time Series

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Holczer Balazs – Quantitative Finance & Algorithmic Trading II – Time Series

This course is about time series analyses. You will use R as the programming language and RStudio as the integrated developement environment.This course is about time series analyses. You will use R as the programming language and RStudio as the integrated developement environment.

IMPORTANT: only take this course, if you are interested in statistics and mathematics !!!IMPORTANT: only take this course, if you are interested in statistics and mathematics !!!

The aim of the course is to construct a model capable of forecasting future stock prices. You will learn about the most important time series related concepts:The aim of the course is to construct a model capable of forecasting future stock prices. You will learn about the most important time series related concepts:

white noisewhite noise
moving average model moving average model
autoregressive model autoregressive model
conditional heteroskedastic models conditional heteroskedastic models

In the last chapter you will implement a model (combining ARIMA and GARCH models) from scratch that is able to outperform the buy&hold (so long term investing) strategy!In the last chapter you will implement a model (combining ARIMA and GARCH models) from scratch that is able to outperform the buy&hold (so long term investing) strategy!

Your InstructorYour Instructor

Holczer BalazsHolczer Balazs
Holczer Balazs Holczer Balazs

My name is Balazs Holczer. I am from Budapest, Hungary. I am qualified as a physicist and later on I decided to get a master degree in applied mathematics. At the moment I am working as a simulation engineer at a multinational company. I have been interested in algorithms and data structures and its implementations especially in Java since university. Later on I got acquainted with machine learning techniques, artificial intelligence, numerical methods and recipes such as solving differential equations, linear algebra, interpolation and extrapolation. These things may prove to be very very important in several fields: software engineering, research and development or investment banking. I have a special addiction to quantitative models such as the Black-Scholes model, or the Merton-model. Quantitative analysts use these algorithms and numerical techniques on daily basis so in my opinion these topics are definitely worth learning.My name is Balazs Holczer. I am from Budapest, Hungary. I am qualified as a physicist and later on I decided to get a master degree in applied mathematics. At the moment I am working as a simulation engineer at a multinational company. I have been interested in algorithms and data structures and its implementations especially in Java since university. Later on I got acquainted with machine learning techniques, artificial intelligence, numerical methods and recipes such as solving differential equations, linear algebra, interpolation and extrapolation. These things may prove to be very very important in several fields: software engineering, research and development or investment banking. I have a special addiction to quantitative models such as the Black-Scholes model, or the Merton-model. Quantitative analysts use these algorithms and numerical techniques on daily basis so in my opinion these topics are definitely worth learning.

Course CurriculumCourse Curriculum

IntroductionIntroduction

Introduction (1:20)Introduction (1:20)

Intsalling RStudio (1:02)Intsalling RStudio (1:02)

Time Series Analysis – BasicsTime Series Analysis – Basics

Time series features (5:55)Time series features (5:55)

Basic statistics I – mean and variance (7:19)Basic statistics I – mean and variance (7:19)

Basic statistics II – covariance (6:03)Basic statistics II – covariance (6:03)
Stationarity (6:55) Stationarity (6:55)

Correlogram (8:26)Correlogram (8:26)

Random Walk ModelRandom Walk Model

White noise introduction (6:04)White noise introduction (6:04)

Random walk introduction (6:57)Random walk introduction (6:57)

Modeling assets with random walk (3:51)Modeling assets with random walk (3:51)

Autoregressive Model (AR)Autoregressive Model (AR)

Autoregressive model introduction (7:02)Autoregressive model introduction (7:02)

How to select the best model? (2:25)How to select the best model? (2:25)

Autoregressive model example (3:59)Autoregressive model example (3:59)

Modeling assets with autoregressive model (6:27)Modeling assets with autoregressive model (6:27)

Moving Average Model (MA)Moving Average Model (MA)

Moving average model introduction (4:18)Moving average model introduction (4:18)

Moving average model example (6:40)Moving average model example (6:40)

Modeling assets with moving average model (4:12)Modeling assets with moving average model (4:12)

Autoregressive Moving Average Model (ARMA)Autoregressive Moving Average Model (ARMA)

Autoregressive moving average model introduction (2:21)Autoregressive moving average model introduction (2:21)

Ljung-Box test (2:50)Ljung-Box test (2:50)

Autoregressive moving average model example (3:42)Autoregressive moving average model example (3:42)

Autoregressive moving average model example II (5:41)Autoregressive moving average model example II (5:41)

Modeling assets with ARMA model (6:34)Modeling assets with ARMA model (6:34)

Autoregressive Integrated Moving Average Model (ARIMA)Autoregressive Integrated Moving Average Model (ARIMA)

ARIMA model introduction (3:33)ARIMA model introduction (3:33)

ARIMA model example (2:59)ARIMA model example (2:59)

Modeling assets with ARIMA model (5:09)Modeling assets with ARIMA model (5:09)

Autoregressive Conditional Heteroskedatic Model (ARCH)Autoregressive Conditional Heteroskedatic Model (ARCH)

Heteroskedasticity in finance (3:44)Heteroskedasticity in finance (3:44)

ARCH model introduction (7:26)ARCH model introduction (7:26)

Generalised Autoregressive Heteroskedastic ModelGeneralised Autoregressive Heteroskedastic Model

GARCH model introduction (2:12)GARCH model introduction (2:12)

GARCH model example (5:14)GARCH model example (5:14)

Modeling assets with GARCH model (5:28)Modeling assets with GARCH model (5:28)

FOREX Trading StrategyFOREX Trading Strategy

FOREX trading strategy implementation I (2:29)FOREX trading strategy implementation I (2:29)

FOREX trading strategy implementation II (4:48)FOREX trading strategy implementation II (4:48)

FOREX trading strategy implementation III (5:46)FOREX trading strategy implementation III (5:46)

FOREX trading strategy implementation IV (6:23)FOREX trading strategy implementation IV (6:23)

FOREX trading strategy implementation V (3:54)FOREX trading strategy implementation V (3:54)

FOREX trading strategy implementation VI (2:53)FOREX trading strategy implementation VI (2:53)

Stock Market Trading StrategyStock Market Trading Strategy

Stock market trading strategy implementation I (1:28)Stock market trading strategy implementation I (1:28)

Stock market trading strategy implementation II (3:09)Stock market trading strategy implementation II (3:09)

Course MaterialCourse Material

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Frequently Asked QuestionsFrequently Asked Questions

When does the course and finish?When does the course and finish?
The course s now and never ends! It is a completely self-paced online course – you decide when you and when you finish. The course s now and never ends! It is a completely self-paced online course – you decide when you and when you finish.
How long do I have access to the course? How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like – across any and all devices you own. How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like – across any and all devices you own.
What if I am unhappy with the course? What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund. We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.

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