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

Quantitative Finance & Algorithmic Trading II – Time SeriesRandom walk, autoregressive model, moving average model, arima model, arch and garch modelThis 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 noisemoving average modelautoregressive modelconditional heteroskedastic modelsIn 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 CurriculumIntroductionIntroduction (1:20)Intsalling RStudio (1:02)Time Series Analysis – BasicsTime 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 ModelWhite noise introduction (6:04)Random walk introduction (6:57)Modeling assets with random walk (3:51)Get Quantitative Finance & Algorithmic Trading II – Time Series – Holczer Balazs, Only Price $47Autoregressive 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 ModelGARCH model introduction (2:12)GARCH model example (5:14)Modeling assets with GARCH model (5:28)FOREX Trading StrategyFOREX 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 StrategyStock market trading strategy implementation I (1:28)Stock market trading strategy implementation II (3:09)Course MaterialSource code & slidesGet Quantitative Finance & Algorithmic Trading II – Time Series – Holczer Balazs, Only Price $47Tag: Quantitative Finance & Algorithmic Trading II – Time Series – Holczer Balazs Review. Quantitative Finance & Algorithmic Trading II – Time Series – Holczer Balazs download. Quantitative Finance & Algorithmic Trading II – Time Series – Holczer Balazs discount. quantitative finance masters. quantitative finance journal. quantitative finance internship. quantitative finance and risk management. quantitative finance and economics. quantitative finance analyst salary