NKD-GROUP e-BOOKS
E-books are well suited to an educational environment shaped by AI, rapidly changing information, and digital learning. They can be updated efficiently with new market developments, AI applications, data, and examples, while offering portable access, searchable text, multimedia, interactive exercises, and links to analytical tools. By connecting theory with current datasets, simulations, and experiential assignments, well-designed e-books promote active analysis, verification, and problem solving—preparing students to work thoughtfully and responsibly in technology-rich professional settings.
The ARMDAT e-Book
Applied Risk Management: Valuation of Derivatives Under AI and Data Science Technologies
Financial Theory, Derivatives, and Experiential Market Applications Updated in 2026, ARMDAT is a 21-chapter textbook available exclusively in e-book format. Designed for advanced undergraduate, graduate, MBA, and professional-development courses. | Understand Derivatives in an Investment Context ARMDAT examines options, futures, and swaps, explaining how these instruments are structured, priced, traded, and applied to hedging, speculation, arbitrage, and portfolio-risk management. | Integrate Portfolio Construction and Risk Control A central theme is the connection between portfolio diversification and effective hedging. Students explore portfolio construction using shrinkage-based covariance estimates designed to improve estimation stability and practical usefulness. |
Learn Through Simulation and Application Simulation-based exercises for equity and fixed-income instruments turn theoretical concepts into opportunities for investigation. | Automated & Algorithmic Option Trades Automated trading of individual option contracts and multi-leg spreads enables timely hedging and the pursuit of profit opportunities across complex market scenarios. | Visit ARMDAT for Compelling Information Visiting the ARMDAT website helps students and instructors assess how the textbook fits their learning goals and course requirements. |
Seniors to MS & MBA AISIM is a comprehensive 19-chapter textbook that has been designed for an experiential approach for today's contemporary AI driven course in investments, portfolio management, and financial analytics. | Understand Investment Theory & Foundations The volume combines the theoretical foundations of investment analysis with experiential, application-oriented learning activities that help students connect core principles to the practical decisions faced by analysts, portfolio managers, institutional investors, and individual market participants. | Portfolio Efficiency and Risk Management A central theme links portfolio diversification with effective hedging. Students learn to construct portfolios using shrinkage-based covariance estimates that enhance stability and support practical investment decisions. |
Learn Through Simulation and Application Compare simulation-based exercises for equity and fixed-income portfolios, and examine how AI-derived hedge ratios for options and futures affect both the managed portfolio and an enhanced Markowitz-efficient portfolio. | Automating Behavioral Portfolio Management Automated trading with integrated simulation capabilities provides a structured pedagogical framework in which behaviorally inspired AI agents manage a portfolio subject to investor-defined constraints and a hierarchical set of investment objectives. | Visit AISIM for Compelling Information We invite students and instructors to visit the AISIM website to assess how the textbook aligns with their understanding of the contemporary investment landscape. |