In this brief video, we walk you through a case study from one of our early advisors – how in minutes Nebo can help you build a strategic glide path, test its viability and then build a portfolio based on today’s market conditions.
Building on our first case study, we explore more deeply how Nebo incorporates your investment schema, capital market assumptions, and preferred methods of implementation. Nebo then uses these inputs for its proprietary, multi-period shortfall optimization allowing you to test your intuition and better understand the key decisions that are driving today’s portfolio allocation.
Highlighting Nebo’s flexible framework, we show how easy it is to integrate cash flow work done from major financial planning software directly into Nebo. We also explore Nebo’s next-generation Monte Carlo simulations in assessing the viability of a personalized glide path and additional savings, withdrawal, and retirement age scenario planning.
Risk is often defined as 'volatility,' but it is more aptly defined as 'not having what you need when you need it.' GMO's Needs-Based Allocation platform, “Nebo,” allows financial advisors to build portfolios that minimize this risk. Matt Kadnar and Martin Tarlie explain this framework, and how it differs from other more traditional measures of risk and walk you through a real-life case study for a high-net-worth client.
In this webcast, Ben Inker, James Montier, and Martin Tarlie discuss the genesis of their latest whitepaper.
In this webcast, James Montier and Martin Tarlie discussed the genesis of their latest White Paper, “Investing for Retirement II: Modelling Your Assets – Are Financial Planners Stuck in the 1970s?” We believe an approach to retirement investing that better models and understands how financial markets differ from the outdated academic assumptions of market efficiency and random walks will result in substantially superior portfolios.
Martin Tarlie demonstrates how the science underpinning Nebo helps advisory firms generate better portfolios for their clients.
At the 2021 GMO Fall Conference, Martin Tarlie demonstrated how Nebo helps advisory firms generate better portfolios for their clients. Over the past year, we have had the good fortune to work with a handful of innovative financial advisors as design partners, achieving significant usage milestones along the way.
At the 2020 GMO Fall Conference, Martin Tarlie redefined risk more intuitively as “What do you need and when do you need it?” and demonstrated our first application of this concept, Nebo, which builds customized portfolios that minimize the risk of falling short of what you need when you need it. Nebo is a flexible, open-architecture platform that financial advisors can use to build customized portfolios for each client by combining GMO, third-party and their market views.
At the 2019 GMO Fall Conference, Martin Tarlie reveals how you can manage for better outcomes (in expectation) by “asking the right question” and “moving your assets.” Also, he demonstrates a GMO-built tool (early stage!) to help you understand the trade-offs between short-term safety and long-term compounding of wealth, among other things.
At the 2018 GMO Fall Conference, Matt Kadnar and Martin Tarlie frame the retirement problem around a simple question: What do you need and when do you need it? They discuss the importance of a flexible framework and the significant impact that mean reversion has on expected returns for a portfolio.
Sequence of return risk is entirely ignored in much of academic finance. But it is a meaningful risk for the vast majority of investment portfolios and there are useful tools that can mitigate its effects.
Standard financial industry practice builds retirement portfolios using mean-variance optimization and validates them using Monte Carlo simulations that assume asset returns are a random walk. The unsurprising result of a process stuck over 50 years in the past is portfolios that burden future retirees with an unnecessarily high risk of financial ruin. We believe an approach to retirement investing that better models and understands the ways in which financial markets differ from the outdated academic assumptions of market efficiency and random walks will result in substantially superior portfolios.
The retirement landscape has changed. The risk of failure with the traditional glide paths and savings/spending assumptions seems to us to be disturbingly high.
Retirement plan participants are haunted by an invisible risk called sequence risk (sometimes called sequence-of-returns or path dependency risk), that is, getting the “right” returns but in the “wrong” order.
Foundational research: Most people in finance and economics mistakenly believe the only way to solve a multi-period optimization problem is to use dynamic programming. Dynamic programming is not wrong, but it is unnecessarily complicated for the use case – what portfolio should I own today?
Foundational research: We study the basic problem of allocating amongst a set of equity strategies given a policy benchmark from an expected shortfall perspective. We find that portfolios that minimize expected shortfall differ substantially from portfolios generated using conventional methods.
Foundational research: we introduce a method of portfolio selection based on the idea that investment risk is not having enough wealth when you need it. Not having enough wealth translates into a required return. When you need wealth translates into an investment horizon.
We know from a behavioral perspective that the framing of questions can radically alter the answers given and that it is incredibly hard to remove people’ biases. In this paper, we explore how framing, nudges and re-biasing can influence answers to questions, and how at the philosophical heart of Nebo is a focus on the importance of asking the right questions.
People have a strong tendency to favor the present over the future – we are poor emotional time travelers. This has obvious investment implications, especially when saving and investing for retirement. In this paper, we explain this “present bias” and why Nebo is particularly well-suited to helping advisors address it with their clients.
We know from a behavioral perspective that the framing of questions can radically alter the answers given and that it is incredibly hard to remove people’ biases. In this paper, we explore how framing, nudges and re-biasing can influence answers to questions, and how at the philosophical heart of Nebo is a focus on the importance of asking the right questions.
The retirement landscape has changed. The risk of failure with the traditional glide paths and savings/spending assumptions seems to us to be disturbingly high.
Standard financial industry practice builds retirement portfolios using mean-variance optimization and validates them using Monte Carlo simulations that assume asset returns are a random walk. The unsurprising result of a process stuck over 50 years in the past is portfolios that burden future retirees with an unnecessarily high risk of financial ruin. We believe an approach to retirement investing that better models and understands the ways in which financial markets differ from the outdated academic assumptions of market efficiency and random walks will result in substantially superior portfolios.
Sequence of return risk is entirely ignored in much of academic finance. But it is a meaningful risk for the vast majority of investment portfolios and there are useful tools that can mitigate its effects.
Retirement plan participants are haunted by an invisible risk called sequence risk (sometimes called sequence-of-returns or path dependency risk), that is, getting the “right” returns but in the “wrong” order.
Foundational research: we introduce a method of portfolio selection based on the idea that investment risk is not having enough wealth when you need it. Not having enough wealth translates into a required return. When you need wealth translates into an investment horizon.
Foundational research: We study the basic problem of allocating amongst a set of equity strategies given a policy benchmark from an expected shortfall perspective. We find that portfolios that minimize expected shortfall differ substantially from portfolios generated using conventional methods.
Foundational research: Most people in finance and economics mistakenly believe the only way to solve a multi-period optimization problem is to use dynamic programming. Dynamic programming is not wrong, but it is unnecessarily complicated for the use case – what portfolio should I own today?
We know from a behavioral perspective that the framing of questions can radically alter the answers given and that it is incredibly hard to remove people’ biases. In this paper, we explore how framing, nudges and re-biasing can influence answers to questions, and how at the philosophical heart of Nebo is a focus on the importance of asking the right questions.
People have a strong tendency to favor the present over the future – we are poor emotional time travelers. This has obvious investment implications, especially when saving and investing for retirement. In this paper, we explain this “present bias” and why Nebo is particularly well-suited to helping advisors address it with their clients.
We know from a behavioral perspective that the framing of questions can radically alter the answers given and that it is incredibly hard to remove people’ biases. In this paper, we explore how framing, nudges and re-biasing can influence answers to questions, and how at the philosophical heart of Nebo is a focus on the importance of asking the right questions.
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