In this primer, SAM takes you through the essential role of Monte Carlo analysis, highlighting its significance as a driving force behind modern financial planning, and complementing the core mission of our investment management approach.
By Ryan Walker, Client Relationship Manager
Introduction
In the world of investment management, where volatility and opportunities are ever-present, the combination of accurate projections and resilient strategies is paramount. At the core of this landscape lies SAM—an independently-minded wealth management firm committed to improving our client’s financial outcomes.
In this primer, SAM takes you through the essential role of Monte Carlo analysis, highlighting its significance as a driving force behind modern financial planning, and complementing the core mission of our investment management approach.
Expanding Perspectives through Financial Planning
In today’s volatile economic landscape, effective financial planning is crucial. It goes beyond mere number crunching or Excel predictions; it’s a sophisticated roadmap aligning your aspirations with inevitable challenges for a secure financial future. As the global economy grows more complex, traditional planning struggles with handling these uncertainties.
Financial planning involves holistic strategies encompassing investment strategy, risk management, retirement, tax efficiency and legacy planning. The challenge is drafting effective plans that acknowledge market uncertainties. We address this by advocating precise projections that consider market cycles, macro shifts, and unforeseen events. This transition embraces modern statistical analysis to strengthen financial planning.
Monte Carlo stress test analysis is a dynamic tool turning static plans into adaptable strategies for an evolving financial landscape.
Monte Carlo Simulation: An Overview and Analogy
Enter Monte Carlo simulation—a dynamic computational technique that helps us understand the likelihood of a client reaching their retirement and other financial aspirations. Unlike static models using “straight line” return assumptions that present a single outcome, Monte Carlo simulation explores a multitude of possibilities, each guided by varying inputs and probabilities. By generating a range of potential outcomes through a thousand different scenarios, this approach paints a more complete picture of possible financial futures. We thoroughly explore the complexities of this technique, unveiling its advantages over traditional methods and solidifying its role in reshaping financial planning practices.
An Analogy
Imagine you have a bag filled with marbles of different colors, and each color represents a potential annual return for a specific type of investment. You’re tasked with predicting how your investment portfolio might perform over the years, but you know that the future is uncertain and full of surprises.
Instead of just blindly grabbing one marble and hoping it accurately represents your future returns, you decide to play a sophisticated game of chance. You reach into the bag, pick a marble, note the color and its corresponding annual return, and then carefully put the marble back into the bag. Then you mix the marbles up before picking another one. This process is repeated over and over, creating an extensive simulation of scenarios.
Each marble in the bag corresponds to a different asset class, like stocks, bonds, or real estate. SAM utilizes Monte Carlo simulation, running 1,000 random iterations to simulate various years and possible investment returns. This is based on the performance variances of the selected asset classes.
To provide a visual representation, refer to the chart below showing annual S&P 500 stock returns and intrayear declines:
Data from FactSet – 2023 data is 01/01/2023-06/30/2023. S&P 500 Index Price returns.
Through this exercise, you gradually accumulate a collection of possible scenarios. Some marbles might represent high returns, representing prosperous investment years, while others might symbolize negative returns, mirroring more challenging financial periods.
In essence, just as you wouldn’t rely on a single marble to predict the future of your investments, the use of SAM’s advanced Monte Carlo simulation, with its 1,000 iterations of return data empowers you to explore a wide variety of investment routes. These different paths are represented by the confidence zones in the accompanying illustration. By embracing uncertainty and variability at this depth, you equip yourself to make more informed financial decisions that account for a comprehensive spectrum of possibilities.
Return Assumptions & SAM’s Investing Philosophy
When crafting financial plans, SAM uses a carefully selected range of assumptions for returns across various asset classes. We cover 14 asset classes divided into six equity categories, five fixed income and real estate categories, as well as cash and other investments.
Within each class, we define annual dividend, total return, and volatility assumptions based on historical data and forward-looking insights. These form the foundation of our predictive models, enhancing analysis accuracy. Feeding these variables into our Monte Carlo simulations generates a range of possibilities, offering clients insightful potential outcomes that reflect market dynamics and economic factors.
At SAM, we believe in an active and adaptable approach to investments. We don’t believe in investing in all asset classes all the time. Instead, we actively manage our strategies to adjust weightings and exposure to risk based on market conditions.
Rather than adhering to traditional asset classes like Large Cap Growth or Emerging Markets, we choose to invest based on thorough company-specific research. Our strategy involves opportunistically owning companies aligned with specific investing rationales, categorized into themes such as ‘Capital Efficient Compounders,’ ‘Innovation & Secular Change,’ or ‘Merger Arbitrage & Change of Control,’ among others.
A real-world example of this occurred when SAM foresaw heightened volatility in interest rates and the bond market in 2022. We proactively eliminated exposure to most bonds across all of our strategies, with the exception of holding short-term U.S. Treasuries in some instances. This decision proved valuable and helped mitigate some of the negative volatility seen in traditional bond pricing throughout that time. Our investment philosophy across our strategies hinges on our client’s investment objectives and not on static asset allocation models based on age or risk tolerance alone. This goals-based approach allows us to dynamically adjust our portfolio weightings in order to manage risk given our market insights.
While assumptions can’t predict the future with certainty, they provide guidance for financial planning. We acknowledge the unpredictability of markets and base our assumptions on historical data and expert insights. These assumptions provide perspective on potential outcomes and inform decisions. However, we remain cautious of biases from historical trends, market conditions, or cognitive factors. We regularly review these return assumptions to align with economic changes. By using assumptions for informed decisions rather than predictions, we navigate uncertainties with confidence.
Image Source: RightCapital
Exploring Extreme Scenarios
Running a Monte Carlo simulation is like a basic building block to figure out how likely your financial plan will succeed. It turns this chance into a percentage. This “likelihood of success” shows how often, out of 1,000 test scenarios, your plan holds up without running out of money within the time you expect. But if the simulation shows your portfolio going down to $0 in any year, even if you end up with money later on, the overall success probability drops. SAM sets a general 80% mark for a solid chance of success.
Image Source: RightCapital
Image Source: RightCapital
Now, envision a scenario where our future encounters more formidable challenges – higher taxes, reductions in Social Security benefits, a longer lifespan than anticipated, or heightened inflation. What unfolds in these potential scenarios? These additional risks can be seamlessly integrated into your financial plan with SAM, offering an in-depth understanding of their possible implications. SAM’s approach extends to embracing these potential scenarios, ensuring your plan remains resilient in the face of an ever-changing financial landscape.
Incorporating stress testing computations and a comprehensive approach to financial planning can also help recognize opportunities to adjust your investment strategy across different account types, enhancing the likelihood of achieving your financial goals. This process considers your specific objectives, risk tolerance, and expected investment time horizon. When combined with SAM’s expertise in investment management, we aim to optimize performance relative to risk measures.
To guide our recommendations for investment changes in creating your financial plan, we consider several metrics, such as maximum drawdown, beta, and volatility calculations. SAM designs portfolios to align with these factors, ensuring that your investments are well-suited for various market conditions, both favorable and challenging. Our goal is to instill a sense of confidence in how your investments perform across different market cycles, promoting peace of mind and what we fondly refer to as the “sleep at night” factor.
Conclusion
In a landscape of uncertainties, the role of Monte Carlo stress test analysis becomes a pillar of deeper understanding. This primer has walked you through an exploration of this essential role, demonstrating its relevance in modern financial planning—a mission that stands hand in hand with our investment management practices.
As the landscape of investment management unfolds, the need for strategic financial planning becomes more vital. Navigating economic volatility necessitates strategies grounded in precision, while considering the possible variables. This paper has uncovered the critical nature of considering the uncertainties that shape financial markets, and through it, the journey from traditional models to the dynamic embrace of probabilistic analysis.
The exploration of extreme and unexpected scenarios reminds us that while success is measured in probabilities, readiness extends beyond the familiar. The consideration of potential adversities ensures resilience in the face of these challenges. Our approach remains rooted in strategic adaptability—a stance that echoes our commitment to your financial well-being.
Interested in Learning More About Financial Planning at SAM?
If you are an existing client of SAM and you’d like to work with us to develop a financial plan incorporating these points, just reach out to your relationship manager.
If you are not yet a client but you’d like to learn more, a colleague at SAM would be more than happy to walk you through how we help clients achieve their longterm financial goals every day.
SAM
420 Lexington Avenue, Suite 2216
New York, NY 10170
646.854.2995
info@stansberryam.com
SCHEDULE A CALL:
https://stansberryam.com/contact/
About the Author
Ryan Walker
Client Relationship Manager
Ryan began his career in the financial services industry during the bear market of 2008; helping investors navigate a difficult economic environment. Prior to joining SAM, he was with Prosperity Wealth Planning as the firm’s Associate Financial Planner. Ryan also spent about eight years with Fisher Investments as an Advisor supporting clients progressing towards their financial and retirement goals.
Ryan holds a bachelor’s degree from Bridgewater State University in Massachusetts in Operations Management (Finance concentration) and is currently studying to sit for the CERTIFIED FINANCIAL PLANNER™ examination.
Ryan was born and raised in the Boston-area and has called the West Coast home since 2013. He is a father of one, a daughter named Juliana, and now lives in Southwest Washington state with his partner. He likes spending free time hiking in the gorge, boating along the Columbia River, and exploring the flavors of cuisine & cultures across the globe.