Center for Strategic Insights
Review a curated collection of high-quality PDFs, offering deep insights and expert knowledge to support your strategic goals.
Fresh Perspective on Signal Weighting Methodology
In 2019, a significant upgrade was implemented to enhance the portfolio construction process, specifically in the use of Investment Signals. This improvement focused on refining Signal weightings and increasing the modularity of the models and tools used. The upgraded approach goes beyond traditional techniques, offering a more efficient and flexible method for portfolio optimization. This new methodology improves risk control, transparency, and customization. For a detailed explanation of these advancements and their impact on portfolio construction, click below to read more.
Multidisciplinary Approach to Portfolio Management
Financial markets are inherently volatile, often experiencing periods of disruption and uncertainty triggered by both endogenous and exogenous events. Economic crises, geopolitical tensions, and unforeseen shocks such as the global financial crisis of 2007-2009 or the COVID-19 pandemic, can lead to significant market upheaval. These events not only alter the expected risks and returns of various investment strategies, but also pose unique challenges for investors, policymakers, and researchers who must navigate this uncertainty. Traditional risk measures, while useful, have often been insufficient for capturing the true dynamics of these market shifts, especially in times of crisis.
Inflation-linked Investment Objectives & Liquid Asset Portfolios
This document analyzes the construction and performance of "Inflation Plus" portfolios, designed to outperform inflation (CPI+3.5% and CPI+4.5%) over a 25-year horizon. It explores how inflation, GDP growth, and active management strategies, including tracking error and alpha, impact the expected real assets and worst-case scenarios. The results demonstrate that lower inflation favors real assets, while adding alpha improves both expected and worst-case outcomes. Active management, particularly through tracking error and alpha combinations, can enhance performance, depending on the information ratio and other factors.
Liability Driven Investing (LDI) and Asset Allocation
Liability Driven Investing (LDI) is used by pension plans and insurance companies to manage liabilities, often alongside Asset-Liability Management (ALM). LDI focuses on risks from market factors, such as interest rates and inflation, that affect liabilities. This paper examines how LDI and Strategic Asset Allocation (SAA) interact, highlighting the importance of asset allocation in designing effective LDI strategies, with a focus on pension plans in Australia. Key factors include the structure of liabilities, funded status, and risk management considerations in determining the optimal hedge ratio.
Linear equivalence of scattered metric spaces
This paper explores the complex relationship between scattered metric spaces and function spaces, offering a detailed analysis of their linear equivalence in the context of \( C^*_u \) spaces. It investigates the role of ordinal embeddings and their profound implications within the framework of functional analysis. By examining the interaction between these mathematical concepts, the paper provides new insights into their theoretical underpinnings and practical applications. For a deeper understanding of how these areas intersect and influence modern mathematical theory, download the full PDF now.
Target Benefit Retirement Schemes
Securing a comfortable retirement is becoming more difficult globally, with underfunded defined benefit schemes and underperforming defined contribution funds. The key issue? A lack of clear target outcomes and proper risk measures. Without this, asset allocations often lack direction. What if there was a solution that could create more stable, reliable pension outcomes? This paper explores how borrowing techniques from defined benefit systems could offer a "target benefit" approach, transforming retirement planning. Curious to learn more?
McKinsey What Is Tokenization?
Tokenization is the process of converting assets—such as real estate, equities, or intellectual property—into digital tokens on a blockchain. This innovation has the potential to streamline transactions, reduce costs, and enhance transparency within financial markets. While still evolving, tokenization is poised to reshape how assets are exchanged and managed.
For a deeper dive into tokenization and its implications for the future of finance, download the full report.
Revolutionizing Asset Management
What Happens When Active Strategies Meet Strategic Benchmarks? Securing a comfortable retirement is challenging due to underfunded pensions and poor investment returns. The issue? A lack of clear targets and risk management. Without these, asset allocations often lack direction. This paper explores how borrowing from defined benefit systems could offer a "target benefit" approach to retirement planning, improving outcomes. Read more!
Asset Management Tokens UK
U.S. Treasuries Go On-Chain
BlackRock’s BUIDL is reshaping finance by bringing U.S. Treasuries into the world of blockchain. Offering seamless settlements, dollar-pegged stability, and monthly dividends, it’s a glimpse into the future of tokenized investing. Discover how this innovation is paving the way for a new era in asset management.
JP Morgan, Apollo use fund tokenization
JP Morgan and Apollo are transforming portfolio management with blockchain-powered fund tokenization, unlocking new opportunities in a $5.5 trillion market. This innovation enables automated, personalized portfolios and real-time settlements, offering wealth managers a smarter, more efficient way to serve their clients. Could this be the future of asset management? Find out more!
