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$129.99 $34 – Quantitative Finance and Algorithmic Trading II-Time Series – Holczer Balazs
Quantitative Finance & Algorithmic Trading II – Time Series
Random walk, autoregressive model, moving average model, arima model, arch and garch model
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 !!!
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 noise
- moving average model
- autoregressive model
- 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!
Course Curriculum
Introduction
- Introduction (1:20)
- Intsalling RStudio (1:02)
Time Series Analysis – Basics
- Time series features (5:55)
- Basic statistics I – mean and variance (7:19)
- Basic statistics II – covariance (6:03)
- Stationarity (6:55)
- Correlogram (8:26)
Random Walk Model
- White noise introduction (6:04)
- Random walk introduction (6:57)
- Modeling assets with random walk (3:51)
Autoregressive Model (AR)
- Autoregressive model introduction (7:02)
- How to select the best model? (2:25)
- Autoregressive model example (3:59)
- Modeling assets with autoregressive model (6:27)
Moving Average Model (MA)
- Moving average model introduction (4:18)
- Moving average model example (6:40)
- Modeling assets with moving average model (4:12)
Autoregressive Moving Average Model (ARMA)
- Autoregressive moving average model introduction (2:21)
- Ljung-Box test (2:50)
- Autoregressive moving average model example (3:42)
- Autoregressive moving average model example II (5:41)
- Modeling assets with ARMA model (6:34)
Autoregressive Integrated Moving Average Model (ARIMA)
- ARIMA model introduction (3:33)
- ARIMA model example (2:59)
- Modeling assets with ARIMA model (5:09)
Autoregressive Conditional Heteroskedatic Model (ARCH)
- Heteroskedasticity in finance (3:44)
- ARCH model introduction (7:26)
Generalised Autoregressive Heteroskedastic Model
- GARCH model introduction (2:12)
- GARCH model example (5:14)
- Modeling assets with GARCH model (5:28)
FOREX Trading Strategy
- FOREX trading strategy implementation I (2:29)
- FOREX trading strategy implementation II (4:48)
- FOREX trading strategy implementation III (5:46)
- FOREX trading strategy implementation IV (6:23)
- FOREX trading strategy implementation V (3:54)
- FOREX trading strategy implementation VI (2:53)
Stock Market Trading Strategy
- Stock market trading strategy implementation I (1:28)
- Stock market trading strategy implementation II (3:09)
Course Material
- Source code & slides
$129.99 $34 – Quantitative Finance and Algorithmic Trading II-Time Series – Holczer Balazs
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