Applied Risk Management:
Valuation of Derivatives under AI and Data Science Technologies

Gordon H Dash and Nina Kajiji



Table of Contents
 

 

Preface

 

Part I:  Financial Assets and Risk Management

Chapter 1

Introduction to Risk Management and Derivatives
In addition to providing a framework by which to classify the concept of risk, the purpose of this chapter is to introduce the study of risk management for individual securities and portfolios using derivative instruments, neuroeconomic models and automated trading.

Chapter 2

Equity Valuation and the Investment Portfolio
This chapter begins with analyzing the firm's financial statement. AI method is used to predict the quarterly price from the financial statements. Next, the chapter introduces basic equity portfolio building skills needed to use the WinORS portfolio management system and generate a basic mean-variance efficient set for user entered portfolio.

Chapter 3

Price, Returns, and Volatility Modeling
This chapter develops a uniform approach for measuring the statistical characteristics of traded instruments. The discussion begins with the development of simple averages and concludes with the development of volatility. Both historical and implied volatility are covered in detail

Chapter 4

Financial Econometrics and Explainable AI
The chapter introduces AI, more specifically machine learning techniques for financial econometrics. The application of regression and artificial intelligence through neural networks to predict end-of-day and high-frequency stock prices is developed in detail. Focus is on optimizing trading profitability with minimization of wrong-direction trade errors.

 

Part II:  Option Contracts and Valuation Models

Chapter 5

Option Contract Basics
This chapter provides a structured overview of global derivatives markets.  The chapter presents the terminology of traded options including coverage of the put-call-parity theorem.

Chapter 6

The Binomial Option Pricing Model
This chapter presents the single- and multi-period Binomial Option Pricing Model.  Detailed examples with calculator solutions are provided.

Chapter 7

The Black and Scholes Option Pricing Model
This chapter presents Black and Scholes Option Pricing Model. Computational differences between the Binomial approach and the Black-and-Scholes pricing model are provided. Development of option Greeks and a detailed calculation-based approach to estimate implied volatility are presented. The discussion is enhanced to support preparation for all qualifying examinations: Actuarial Society examination, FRM and PRM.

 

Part III:  Option Strategies for Directional Volatility

Chapter 8

Fundamental Option Strategies
A description and definition of the basic option strategies for both call and put contracts.  Includes coverage of covered calls and puts for portfolio insurance.  Focus is on both micro-hedges (individual securities) and macro hedges (portfolios using index-based contracts).

Chapter 9

Advanced Option Spread Strategies
This chapter describes and develops many of the well-known option spread strategies. Close linkage to real-time applications using WinORS.  Spreads include various versions of butterflies, guts, condors, straddles and more.  Applicable for both individual securities and portfolios.

 

Part IV:  Futures Instruments

Chapter 10

The Foundation of Modern Futures Markets
The chapter presents and discusses the contemporary futures markets. References and comparisons are provided for both the global and domestic futures markets. The discussion continues with the development of futures pricing theories. 

Chapter 11

Fundamental Applications of Equity Futures
This is an applications-based chapter linked to simulation and back-testing algorithms within WinORS.  There is a strong focus on the calculation of real-time hedge ratios for equity portfolios.  State-of-the-art non-Gaussian risk-adjusted performance measures are introduced with calculation based examples.

Chapter 12

The Single Stock Futures Market
The chapter focuses on the robust Single Stock Futures Exchange. Linkages to both single stock futures, exchange for physicals, and exchange traded futures for equity and fixed income instruments is provided.

Chapter 13

Fundamental Applications of Fixed Income Futures
The WinORS bond valuation system focus on the portfolio valuation of risk-mitigating trading bonds across a number of different markets.  Markets covered include Treasuries, munis, corporate and zero-coupon.  Full coverage across a wide-number of analytical measures with supporting graphical output. Fixed income hedge methods provide a robust approach to the theory and approach of risk mitigating fixed income portfolios

Chapter 14

Crypto-Currency Futures
The chapter discusses the origins of cryto-currency and their rise in today’s investment portfolios. 

 

Part V:  Swaps, Automation, and Neuroeconomics

Chapter 15

Swaps, Interest Rate, and Credit Derivatives
The chapter presents a detailed discussion on the valuation and use of swap agreements. In addition to providing an overview of the swaps market, interest rate swaps and associated option derivatives, or swaptions, are exemplified by practical applications. The chapter closes with a look at credit default swap contracts.

Chapter 16

Neuroeconomics and Applied Automated Trading
This chapter presents an introduction of how operational artificial intelligence in the form of artificial neural networks are used to predict near high-frequency and end-of-day stock prices for the purpose of optimizing risk-adjusted trading profitability. Special emphasis is place on how to minimize wrong directional trade rules. 

Chapter 17

Automated Trading: Policies and Performance
An examination of the external and internal policies that guide the operation of the fully accessible WINKS automated trading system.  The chapter includes a detailed examination of real-time and historical risk-adjusted performance for both individual securities and all managed portfolios.  ESG and sector  performance reports are also provided.

Chapter 18

Neuroeconomics and Big Data in the Capital Markets
This chapter addresses  the question: What is a Big Data CAPM? The chapter begins by differentiating among the terms data analytics, data visualization and predictive analytics.  The chapter includes a “Big Data” exploration and critical evaluation of the equilibrium based CAPM valuation model.

Copyright

ISBN: 978-0-9908843-0-9, The NKD Group, Inc., 2010-2024, All Rights Reserved

Updated: 31-Aug-2024

[Home] [Table of Contents] [Resources] [Purchase] [Registration] [About Us] [Contact Us]

Copyright © 2010 - 2024 by The NKD-Group, Inc.. All rights reserved.

View My Stats