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
39Introduction to the Kalman Filter
2Time Series Analysis
40Implementation of the Kalman Filter
3Introduction to Time Series Data
41Extended Kalman Filter
4Stationarity and non-stationarity
42Unscented Kalman Filter
5Trend and Seasonality Analysis
43Applications of the Kalman Filter in Finance
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6Time Series Decomposition
44Hidden Markov Models (HMM)
7Time Series Smoothing Techniques
45Introduction to Hidden Markov Models
8Autoregressive (AR) Models
46Parameter Estimation in HMM
9Introduction to Autoregressive Models
47Model Diagnostics and Validation
10Order Selection in AR Models
48Applications of HMM in Finance
11Parameter Estimation in AR Models
49Advanced HMM Techniques
12Model Diagnostics and Validation
50Bayesian Models
13Applications of AR Models in Finance
51Introduction to Bayesian Models
14Moving Average (MA) Models
52Bayesian Inference
15Introduction to Moving Average Models
53Bayesian Networks
16Order Selection in MA Models
54Hierarchical Bayesian Models
17Parameter Estimation in MA Models
55Applications of Bayesian Models in Finance
18Model Diagnostics and Validation
56Bayesian Inference
19Applications of MA Models in Finance
57Introduction to Bayesian Inference
20Autoregressive Moving Average (ARMA) Models
58Prior and Posterior Distributions
21Introduction to ARMA Models
59Markov Chain Monte Carlo (MCMC) Methods
22Order Selection in ARMA Models
60Gibbs Sampling and Metropolis-Hastings Algorithm
23Parameter Estimation in ARMA Models
61Applications of Bayesian Inference in Finance
24Model Diagnostics and Validation
62Bayesian Networks
25Applications of ARMA Models in Finance
63Introduction to Bayesian Networks
26Autoregressive Integrated Moving Average (ARIMA) Models
64Structure Learning in Bayesian Networks
27Introduction to ARIMA Models
65Parameter Learning in Bayesian Networks
28Order Selection in ARIMA Models
66Inference in Bayesian Networks
29Parameter Estimation in ARIMA Models
67Applications of Bayesian Networks in Finance
30Model Diagnostics and Validation
68Stochastic Processes
31Applications of ARIMA Models in Finance
69Introduction to Stochastic Processes
32State Space Models
70Types of Stochastic Processes
33Introduction to State Space Models
71Brownian Motion and Its Properties
34Kalman Filter for State Space Models
72Geometric Brownian Motion
35Parameter Estimation in State Space Models
73Applications of Stochastic Processes in Finance
36Model Diagnostics and Validation
74Supplementary Data
37Applications of State Space Models in Finance
75About Author
38Kalman Filter
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