Financial Modeling Excellence
By Azhar ul Haque Sario
Length3h 41m
About this audiobook
Financial Modeling Excellence: Innovative Approaches to Stock Predictions (Third Edition) provides a comprehensive and advanced exploration of various probabilistic models used in stock price predictions. The book begins with an in-depth analysis of time series data, covering essential topics such as stationarity, trend and seasonality analysis, and time series decomposition. It then delves into autoregressive (AR) models, moving average (MA) models, and their combinations, including ARMA and ARIMA models. Each chapter provides detailed explanations of model selection, parameter estimation, diagnostics, and validation, along with practical applications in financial forecasting.
The book further explores state space models and the Kalman filter, offering insights into their implementation and applications in stock price predictions. Hidden Markov models (HMM), Bayesian models, and stochastic processes are also thoroughly examined, with a focus on their mathematical formulations, parameter estimation techniques, and real-world applications. Case studies and practical examples are provided throughout the book to illustrate the effectiveness of these models in financial analysis. This edition also introduces advanced techniques and future directions for each model, ensuring that readers are equipped with the latest tools and knowledge in the field.
This is the third edition of the series, following the first edition titled Stock Price Predictions: An Introduction to Probabilistic Models and the second edition titled Forecasting Stock Prices: Mathematics of Probabilistic Models. This third edition continues to build on the foundation laid by its predecessors, offering new insights and innovations in financial modeling. As the first series of this edition, readers can look forward to the next series, which will be released soon, providing even more advanced techniques and applications in stock price predictions.
Audiobook details
GenreOther
Length3 hrs 41 mins
Narrated byListen with 1,000+ voices
FormateBook with Audio
Publish dateNov 27, 2024
LanguageEnglish
Table of contents
1Abstract
2Time Series Analysis
3Introduction to Time Series Data
4Stationarity and non-stationarity
5Trend and Seasonality Analysis
Show all chaptersShow less
6Time Series Decomposition
7Time Series Smoothing Techniques
8Autoregressive (AR) Models
9Introduction to Autoregressive Models
10Order Selection in AR Models
11Parameter Estimation in AR Models
12Model Diagnostics and Validation
13Applications of AR Models in Finance
14Moving Average (MA) Models
15Introduction to Moving Average Models
16Order Selection in MA Models
17Parameter Estimation in MA Models
18Model Diagnostics and Validation
19Applications of MA Models in Finance
20Autoregressive Moving Average (ARMA) Models
21Introduction to ARMA Models
22Order Selection in ARMA Models
23Parameter Estimation in ARMA Models
24Model Diagnostics and Validation
25Applications of ARMA Models in Finance
26Autoregressive Integrated Moving Average (ARIMA) Models
27Introduction to ARIMA Models
28Order Selection in ARIMA Models
29Parameter Estimation in ARIMA Models
30Model Diagnostics and Validation
31Applications of ARIMA Models in Finance
32State Space Models
33Introduction to State Space Models
34Kalman Filter for State Space Models
35Parameter Estimation in State Space Models
36Model Diagnostics and Validation
37Applications of State Space Models in Finance
38Kalman Filter
39Introduction to the Kalman Filter
40Implementation of the Kalman Filter
41Extended Kalman Filter
42Unscented Kalman Filter
43Applications of the Kalman Filter in Finance
44Hidden Markov Models (HMM)
45Introduction to Hidden Markov Models
46Parameter Estimation in HMM
47Model Diagnostics and Validation
48Applications of HMM in Finance
49Advanced HMM Techniques
50Bayesian Models
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