The Intelligent Investor's Almanac
Your Bi-Weekly Guide to Markets, Movements, & Money.
Presented By Ken Majmudar & Ridgewood Investments
Issue 21 • January 20 to January 31, 2026
Never miss another valuable edition of The Intelligent Investor's Almanac again.
✦ TL;DR — Your Institutional Intelligence in Minutes
We cover two major wealth dynamics in this issue:
How Productivity and Margins Expansion Drive Long-Term Earnings
Core Insight: As AI shapes every industry, long-term earnings growth may be driven more by margin expansion as operating costs grow slower than revenues.
Additional Insight: Sustained productivity gains enable earnings to compound even during moderate revenue growth, making margin expansion a key driver of long-term returns.
Actionable steps to consider:
- Evaluating sources of productivity improvements and reviewing the consistency of operating margin expansion across multiple years.
- Assess whether earnings growth increasingly converts into free cash flow.
Decoding Recency Bias
Market Insight: Recent periods of equity performance can anchor investor expectations to return ranges that are misaligned with long-term data.
Additional Insight: Rolling returns show that similar time horizons can produce different returns, so recent performance offers limited guidance.
Actionable Steps to consider:
- Assess whether recent performance is shaping expectations more than long-term historical return patterns.
Validate assumptions using rolling multi-year returns rather than single period or point-to-point returns.
✦ Action: Re-Evaluate Portfolio Assumptions Independent of Recent Returns.
Schedule a private discovery call with Ken and the Ridgewood team.
The Value Investor
Ken Majmudar, CFA & Founder of Ridgewood Investments
“The four most dangerous words in investing are: ‘This time it’s different.’”
– Sir John Templeton
Periods of relatively high returns often influence investor expectations more than underlying fundamentals. When recent performance persists, it is often treated as a reference point for future performance, even though market fundamentals continue to evolve.
This change in expectations can lead investors to position portfolios toward asset classes that have performed well recently. Long-term investment performance depends less on recent performance and more on the underlying durability of earnings growth.
Moreover, AI-driven improvements in employee productivity and business efficiency will allow profits to grow faster than revenues, and lead to margin expansion across several industries.
How Productivity and Margins Expansion Drive Long-Term Earnings
Long-term earnings growth is determined by both internal and external forces. While external conditions are beyond a company’s control, internal operating decisions are in the hands of management.
Understanding Profit Margins and Why They Matter
Profit margin is a common measure of how efficiently a company or business operation converts revenue into profit. Typically expressed as a percentage, it represents the portion of a company’s sales revenue that it retains as a profit after subtracting all of its costs. For example, a 35% profit margin means that for every dollar of sales, about $0.35 is left over after paying the costs of running the business.
In this discussion, profit margins primarily refer to operating profit margins, the profits generated from core business activities before financing and taxes, reflecting efficiency and productivity improvements.
The Golden Age of Margin Expansion
Over the past decade, earnings growth across public markets was primarily driven by revenue growth supported by a low interest rate environment. While profit margins improved gradually, they were largely viewed as an outcome of revenue growth rather than a driver. During that period, earnings growth was more closely linked to revenue expansion than to incremental productivity gains.
An increasing share of earnings growth is coming from productivity gains that allow companies to generate more profit from an existing revenue base. Many businesses have transitioned from investing primarily in physical assets to investing in intangible assets such as technology, data, brands, and internal processes. This shift is reflected by the changing composition of the S&P 500, which has become more concentrated in large technology and software-enabled companies, with the largest technology firms now accounting for over 30% of index exposure, compared with less than 10% a decade ago.
How AI-Driven Productivity Expands Margins
The central structural shifts in today’s operating-leverage cycle are increasingly reflected in technology-enabled scale across functions without proportional cost growth. Artificial intelligence is no longer limited to a narrow set of tasks or pilot projects. Instead, it is increasingly becoming embedded into the core of business processes, allowing companies to increase output.
In day-to-day operations, AI-driven productivity is reflected across several business functions simultaneously:
Customer support: A growing share of customer inquiries can be handled by AI systems, reducing the need for additional customer service staff as volumes increase. Example: HubSpot reports AI resolves 75% of web chats and over 50% of support tickets.
Software development: AI-assisted coding tools allow engineers to write, test, and deploy code faster, increasing output per developer. Example: Shopify states 92% of code changes are AI-assisted, shipping 46% more code per engineer.
Workforce productivity: Generative AI tools are increasingly used across functions to draft documentation, summarize information, and prepare materials, raising output per worker without adding employees. Example: Atlassian reports 2.3 million AI monthly users, with AI usage growing over 5× compared to the previous quarter.
Analytics and decision-making: AI tools enhance data analysis, allowing smaller teams to operate more efficiently while improving speed and accuracy. Example: Salesforce states AI now performs up to 50% of internal analytical workflows.
As AI handles higher incremental workloads, companies can grow without adding employees at the same rate. This allows operating costs to rise more slowly, allowing a larger share of incremental revenue to be retained as profit. Over time, this shift in cost base becomes a fundamental source of margin expansion rather than a temporary efficiency gain.
The key distinction in this cycle from previous periods of efficiency gains is not merely cost reduction, but the durability of the operating leverage it potentially creates. By processing incremental workload across multiple functions simultaneously, AI redefines the scalability of labor, decision-making, and execution, making margin expansion more structural, less cyclical, and less dependent on revenue growth.
At an aggregate level, S&P 500 operating margins have increased from a long-term average near 9% to approximately 13.5% by early 2025, reflecting broad improvements in cost efficiency.
Source: S&P Dow Jones Indices, as of Q3 2025.
When earnings growth is supported by margin expansion, it tends to be more durable. Improved operating leverage, disciplined cost structures, and efficient capital use allow profits to compound more consistently across varying economic conditions.
Dynastic Wealth – Tips on Preserving and Building Your Legacy
Decoding Recency Bias
Recency bias is a type of cognitive bias that causes us to overemphasize the importance of recent experiences or the latest information when estimating future outcomes. It limits perspective by overweighting recent information.
Why Does Recency Bias Occur?
Recency bias occurs due to how our brains work in prioritizing recent memory and is closely related to the availability heuristic, which is the tendency to rely more heavily on information that comes most easily to mind. Because recent information is more accessible in memory, it is often given greater importance than historical information.
The challenge arises when this bias is applied to activities where outcomes evolve gradually and in a non-linear way over long periods. Investing is a prominent example. Markets are inherently forward-looking, as prices continuously reflect expectations about future cash flows. As a result, they typically do not respond to short feedback loops (except when fundamentals change), and recent outcomes often provide limited insight into long-term investment performance.
How Recency Bias Shapes Market Expectations
When recent performance or market conditions have been favorable, investors often begin to anchor what feels “normal” even as the underlying conditions contributing to that performance may have been driven by exceptions or cyclical reasons.
Over the past three years, the S&P 500 has delivered strong returns across 2023, 2024, and into 2025 (approximately +26.29%, +25.02%, and +17.88%, respectively), reinforcing confidence in U.S. equities, particularly large, well-established companies. Over time, this causes a recency bias which influences investor expectations.
Investors think that the future will resemble the recent past, and make decisions accordingly.
As recency bias takes hold, expectations tend to shift in subtle but consistent ways:
Recent performance is often treated as a reliable indicator of future returns.
The continuity of recent performance is expected without careful evaluation.
Perceived risk tolerance tends to increase as the future is assumed to resemble good periods.
What Market History Reveals in Practice
The table below shows extended periods of positive and negative performance, highlighting how returns have varied over time rather than following a consistent pattern.
This unpredictability in returns is a key reason why recency bias is challenging to identify as the market environment evolves. This expectation often resembles the “hot hand” phenomenon, the belief that recent success implies ongoing momentum, even when recent performance may be driven more by careless risk taking than probability.
In markets, investors are similarly tempted to favor mutual funds or stocks that have shown strong recent performance, favoring investment strategies that have performed well recently.
How Recency Bias Influences Investment Decisions
When certain assets outperform, their share in the overall portfolio increases. Yet most investors continue to hold these positions without rebalancing, often failing to consider whether that performance is likely to continue.
The chart below shows rolling 10-year returns, highlighting how long-term results differ across market conditions. At various periods, 10-year returns have ranged from roughly -2% to about 20%, despite covering the same 10-year investment period.
When favorable results extend for several years, they can begin to feel “normal,” leading investors to anchor expectations to recent experience.
Source: NYU.edu
Between 2008 and 2019, it went through a prolonged period of inconsistent performance with negative returns in 2008, 2011, and 2013-2015, and only marginal gains in years such as 2012, 2017, and 2019.
After this extended stagnation, silver delivered a cumulative return of roughly –11.5% between 2021 and 2023. That narrative reversed quickly in the following two years, with gains of approximately 22% in 2024 and over 100% in 2025, resetting expectations after several years of underperformance.
Strategies to Overcome Recency Bias in Investment Decisions
1. Focus on long-term data:
Rolling returns show an investment’s annualized performance over multiple overlapping periods (such as 1, 3, or 5 years). Unlike single point-to-point returns like CAGR, rolling returns provide better insight into consistency across market cycles, reducing the impact of short-term volatility or year-specific distortions.
For example, a 5-year rolling return from 2010 to 2020 would measure returns from 2010–2015, then 2011–2016, 2012–2017, and so on. Rolling returns give better insight into consistency and risk, helping investors avoid being misled by short-term performance or one-off strong periods.
2. Adopt a systematic rebalancing approach:
When certain assets outperform, their share of the portfolio increases, and recency bias influences investors to favor them. A systematic rebalancing rule helps counter this bias by automatically reducing exposure to recent outperformers and reallocating to undervalued segments, reinforcing long-term strategy over short-term sentiment.
3. Benchmark Against Long-Term Goals, Not Recent Performance:
Instead of assessing performance by short-term returns, align your investment decisions with long-term objectives, like retirement income, future spending needs, or healthcare needs. Evaluating investment performance based on financial goals helps reduce the temptation to chase momentum fads.
Here’s to building lasting wealth,
Ken Majmudar, CFA
Founder & Chief Investment Officer Ridgewood Investments
P.S. If you’re ready to explore how our institutional-grade investment approach can work for your portfolio, let’s schedule a time to talk below.
Gain Industry – Level Intelligence For Your Investment Strategy
Transform your approach to wealth building with institutional-grade insights. Schedule a private discovery call with Ken and the Ridgewood team to:
- Analyze your current portfolio positioning
- Explore sophisticated investment opportunities
- Design your personalized wealth architecture
Building generational wealth requires institutional-grade thinking. Let’s discuss how our sophisticated approach can work for your family’s future.
Important Disclosure: Ridgewood Investments is a registered investment adviser. This newsletter is for informational purposes only and does not constitute investment advice. Past performance is not indicative of future results.