Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R

Specifications

Book Description

Demonstrates how R can be used effectively to find solutions to issues that arise in quantitative finance.

An Introduction to Applied Probabilistic Calculus with Applications in Financial Engineering R recipes are provided in the Using R document format (PDF) for solving asset allocation and portfolio optimization issues. Before moving on to topics related to asset allocation and portfolio optimization with R codes illustrated for various examples, it begins by introducing all of the necessary probabilistic and statistical foundations. This is followed by a discussion of how to construct optimal portfolios. This ebook provides a succinct and understandable overview of financial engineering, as well as the use of R in data analysis, as well as univariate, bivariate, and multivariate data analysis. In addition to discussing Ito Calculus, it investigates the use of probabilistic calculus for modeling financial engineering. Specifically, it guides the reader through the process of constructing an efficient financial model based on the Geometric Brownian Motion (GBM) Model by using probabilistic calculus. The Two Mutual Fund Theorem and the Sharpe Ratio are two of the classical mathematical models that are discussed, along with other topics related to financial engineering and modern portfolio theory. R is examined both as a calculator and as a tool for performing data analysis in financial engineering throughout this ebook. In addition, it discusses asset allocation by using R, as well as financial risk modeling and portfolio optimization by using R; global and local optimal values; locating functional maxima and minima; and portfolio optimization by using performance analytics in CRAN.

• Includes both the Generalized Boltzmann Machine Model and the Random Walk Model.
• This article provides the answer to the question, “What does a Financial Theory known as “Random Walk” look like?”
• Examines various optimization techniques utilizing probabilistic calculus for the purpose of financial engineering.
• Explores contemporary models of portfolio optimization, such as The Markowitz Model of Modern Portfolio Theory (also known as MPT), The Black-Litterman Model, and The Black-Scholes Option Pricing Model.

An Introduction to Applied Probabilistic Calculus with Applications in Financial Engineering The Use of R Is an Ideal Reference for Professionals and Students in Economics, Econometrics, and Finance, Along with Financial Investment Quants and Financial Engineers Using R Is an Ideal Reference for Professionals and Students in Economics, Econometrics, and Finance