Modern Portfolio Management: From Markowitz to Probabilistic Scenario Optimisation - Goal-based and Long-Term Portfolio Choice - Risk Books
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Modern Portfolio Management: From Markowitz to Probabilistic Scenario Optimisation

By Paolo Sironi


Goal-based and Long-Term Portfolio Choice

Modern Portfolio Management
provides a methodology for portfolio choice based upon modern risk management techniques and a clearer definition of the investment risk/return profile to feature goal-based investing and probabilistic scenario optimisation.

The financial markets have undergone a period of distress that has strained the trusted relationship between investors and financial advisors; new regulation has been forged to push for higher levels of transparency and risk-based communication as part of investment decision-making. This has ignited the quest for better portfolio optimisation techniques that can combine the added-value asymmetry of real products (as they strongly contributed to pre-crisis budgets) with the life-cycle requirements of investors, supported by intuitive graphical representation of seemingly complex mathematical relationships between real portfolios and products as required by regulation.

Upon reading Modern Portfolio Management, readers will understand the importance of simulating real securities (especially fixed income and structured products) during the making of optimal portfolios, as well as the importance of simulating financial investments over time to match in a transparent way actual goals and constraints instead of relying solely upon past performance or personal judgement.

Take a look at the Intro and Chapter One here

Publish date: 16 Feb 2015

Availability: In stock

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Book - Modern Portfolio Management: From Markowitz to Probabilistic Scenario Optimisation

Book description

Traditional portfolio management approaches have proven to be ineffective. Probabilistic scenario optimisation is emerging as an appealing alternative framework to facilitate the realignment of investors’ risk/return preferences with the risk/return characteristics of actual investments.

Chapters include:

•    A Modern Risk Management Perspective and The Probability Measure
•    Dealing with Real Securities and Reinvestment Strategies: Fixed Income, Structured Products and Inflation
•    Elicitation and Modeling of Risk/Return Time Profiles
•    Review of Markowitz and Black-Litterman approaches
•    Probabilistic Scenario Optimisation and Goal-based Investing
•    Optimisation Case Studies

This book is a must-read for portfolio managers as well as financial advisors – in particular, all investment managers engaging in (or thinking of engaging in) long-term and goal-based asset allocations.

Book details

Book 9781782722045 / eBook 9781782722250
Publish date
16 Feb 2015
155mm x 235mm

Author biography

Paolo Sironi

Paolo Sironi is practice leader of wealth management solutions and risk content services at IBM Risk Analytics, where he is responsible for quantitative methods and asset allocation advisory for financial institutions (retail banking, private banking, ultra-high-net-worth and institutional advisory clients). Combining risk analytics and technology, Paolo’s expertise spans wealth management, asset management, investment banking, market and credit risk management, regulatory reporting, cognitive computing, on-cloud and banking digitalisation. Before joining IBM, Paolo worked as managing director of Capitects, the company (a provider of risk management solutions) which he founded in 2008 as a joint venture between Sal. Oppenheim Private Bank and Algorithmics and which became a part of IBM following the Algorithmics acquisition. Prior to Capitects, Paolo worked as head of market and counterparty risk modelling at Banca Commerciale Italiana and Banca Intesa Sanpaolo.

Table of contents


1. Beyond Modern Portfolio Theory

Part 1 - Risk Management Framework

2. A Modern Risk Management Perspective

3. The Probability Measure

4. Real Securities and Re-Investment Strategies: Fixed Income, Structured Products and Inflation-linked

5. Elicitation and Modeling of Risk/Return Time Profiles

Part 2 - Portfolio Optimisation Methods

6. à la Markowitz’s: a Tale of Simple Worlds

7. Black-Litterman’s Approach: a Tale of Subjective Views

8. Probabilistic Scenario Optimisation (PSO)

Part 3 - Portfolio Optimisation Case Studies
9. Case studies: Mean-Variance and Black-Litterman

10. Case studies: Probabilistic Scenario Optimisation


"This book features an excellent description of Modern Portfolio Theory, which still forms the basis for many investment decisions. It also does an excellent job of describing the Black–Litterman methodology, a more modern enhancement. Paolo Sironi’s key contribution, however, is in making scenario analysis and the very general Mark-to-Future approach accessible to goal-based investing. He describes in great detail how to simulate investment strategies overtime while accounting for an investor’s risk–return profile. This is not only a theoretical treatise but one based on many years of experience of real-world investment decision making. I believe it will be an excellent addition to any portfolio manager’s library."

From the Foreword by Ron Dembo

"This book is a true eye opener, which I really recommend to any practitioners of asset or wealth management.  While investment professionals as a whole do not and cannot add value by beating the market (because, by and large, they are the market), they can certainly add even more significant value by paying full attention to the Client’s objectives and constraints.  To do this, they must have a long term focus, and consider multiple scenarios. All of this was not really possible when Markowitz published his portfolio selection work, as the main tool was mathematics with explicit solutions. Now, however, we have at our disposal the full panoply of probabilistic optimization techniques, enabled by omnipresent computer power, as explained in this book.

Not only do those techniques enable really customized long-term portfolio selection, but they also result in a much more intuitive and visual understanding of risk and return over the long term,  overcoming stumbling blocks in client communication."

Dr. Giuseppe Ballocchi, CFA, University of Lausanne

"Paolo’s book is an invaluable read for anyone interested in presenting investment decisions intuitively and as closely to the actual thought process of investors as possible. The central idea of the book is very powerful: expressing portfolio choice based on the probability of achieving a desired target return naturally accommodates the explicit definition of investment goals over time. Combined with a scenario based approach, this enables  superior insights and improved decision making. Probabilistic scenario optimization removes the simplistic assumptions of traditional portfolio management methodologies and accurately captures stress events, asymmetric payoffs and realistic reinvestment strategies.

Reading Modern Portfolio Management has the potential to change the way you look at investment decisions. It provides the foundation to ask the right questions in the asset selection process and establishes a new standard for assessing the potential upside and downside of complex investment choices."

Michael Zerbs, former president of Algorithmics and Head of Risk Management Information technology at ScotiaBank

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