Quantitative Finance and Algorithmic Trading II-Time Series – Holczer Balazs

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Quantitative Finance and Algorithmic Trading II-Time Series – Holczer Balazs Download. This course is about time series analyses. You will use R as the pro…

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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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