Capital Budgeting Techniques

VC 101 - Day 7  Post-Investment Interactions: The After Party You did it. Your startup's pitch won over a venture capitalist, and the check with all those zeros just hit your account. The bubbly was uncorked, and for a brief moment, you felt like the king or queen of the entrepreneurial world. The temptation might be to think that you've crossed the finish line, but in reality, the journey has only just begun. How Often Do They Check In? Surprise, surprise! Venture capitalists are much more engaged than you might have initially thought. Around 60% of VCs check in with their portfolio companies at least weekly. You might feel like they’re hovering, but their involvement is generally constructive, unlike that of a clingy ex. What Do They Offer? Strategic Guidance Lost in the maze of scaling, or unsure about entering a new market? Your VC is your go-to sage, a corporate Yoda, guiding you with the wisdom gleaned from years of industry experience. Connections The Rolodex of a VC often reads like a Who's Who of the business world. These connections can provide introductions to potential clients, partnerships, or even future rounds of financing, unlocking opportunities you never thought possible. Operational Advice From fine-tuning your supply chain to navigating HR complexities, your VC is often a fount of practical advice. They’ve been through this rodeo before and can help you avoid common pitfalls. Hiring Assembling the right team can make or break your startup. Whether it's board members or critical managerial positions, your VC's network can be a treasure trove of talent. Takeaway: Think of VCs not as faceless, open wallets but as active, hands-on partners in your journey. The post-investment phase is not a solitary one; it’s a collaborative endeavor. The counsel, connections, and experience a VC provides can often be as invaluable as the capital they initially invested. The venture capital game isn't just about securing that big check; it’s about cultivating a long-term partnership filled with strategic advice, networking opportunities, and operational insights. The relationship you build with your VC after the initial investment could very well be the cornerstone that guides you toward entrepreneurial success. Stay tuned for Day 8! Source: Harvard Business Review ➕ Follow me (Grace Gong) and hit the bell 🔔 icon on my profile to be notified of everything VC

Today I've published an article on Market-Expected Return on Investment (MEROI) - a powerful framework that's transforming how I analyze companies in our increasingly intangible economy. I wrote this piece because I've grown frustrated with how traditional metrics fail us in a world where intangible investments dominate corporate spending. When companies like #Microsoft invest heavily in R&D, software, and brand building, traditional accounting treats these as expenses rather than the investments they truly are. This creates a 𝐟𝐮𝐧𝐝𝐚𝐦𝐞𝐧𝐭𝐚𝐥 𝐝𝐢𝐬𝐜𝐨𝐧𝐧𝐞𝐜𝐭 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐫𝐞𝐩𝐨𝐫𝐭𝐞𝐝 𝐟𝐢𝐧𝐚𝐧𝐜𝐢𝐚𝐥𝐬 𝐚𝐧𝐝 𝐞𝐜𝐨𝐧𝐨𝐦𝐢𝐜 𝐫𝐞𝐚𝐥𝐢𝐭𝐲. MEROI solves this problem by revealing what return the market actually expects a company to generate on its investments. Unlike backward-looking metrics like ROIC, MEROI decodes the expectations embedded in current stock prices. 𝐓𝐡𝐞 𝐤𝐞𝐲 𝐭𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬: - Traditional accounting significantly distorts our understanding of companies with high intangible investments, creating market inefficiencies savvy investors can exploit. - By properly reclassifying portions of SG&A as investments rather than expenses, we get a dramatically different picture of a company's steady-state value versus future growth opportunities. - My detailed case study shows how MEROI for a software company drops from 25% to 16% when properly accounting for intangibles - completely changing how we should view market expectations. I've included a comprehensive framework for implementing this approach in your own analysis, from industry selection to expectation analysis. 𝐖𝐡𝐚𝐭 𝐲𝐨𝐮'𝐥𝐥 𝐥𝐞𝐚𝐫𝐧: - How to distinguish between genuinely unprofitable businesses and those creating substantial value through intangible investments; - how to identify expectation mismatches that could signal investment opportunities; and - how to more accurately assess whether seemingly high valuations are actually justified. For anyone serious about understanding market expectations in today's economy, MEROI provides a systematic edge that traditional metrics simply can't match. #valuation

Think you’ve built a high-alpha investment strategy? Here’s how to truly put it to the test. In quantitative investing, strong backtests can be exciting - but they can also be misleading. Many strategies that appear to generate alpha are simply repackaged exposures to well-known risk factors. That’s why one of the most important steps in validating any strategy is factor analysis, most commonly using the Fama–French family of factors. What are the Fama–French Factors? Eugene Fama and Kenneth French identified several systematic risk premia that explain most equity returns. The modern “FF5 + Momentum” set typically includes: Market (Mkt–RF) – broad equity market exposure Size (SMB) – small-cap tilt Value (HML) – cheap vs. expensive stocks Profitability (RMW) – high vs. low quality Investment (CMA) – conservative vs. aggressive investment Momentum – recent winners vs. losers If you think your strategy generates excess return, the first question is: Is it truly alpha, or just factor beta? What’s the purpose of factor analysis? Factor regression allows you to decompose your strategy’s returns into: Systematic returns explained by known factors Residual return (alpha) that cannot be explained by those factors A positive, statistically significant alpha means your strategy may be adding genuine value - not just loading up on small caps, value, or momentum. How do you run the test? The process is straightforward: Collect your strategy’s daily returns. Download the Fama–French factor data (daily) from the Kenneth French data library. Align the dates and run a regression of Strategy Excess Return = α + β₁(Mkt–RF) + β₂(SMB) + … + β₅(CMA) + ε Interpret the coefficients: Significant betas → factor exposures Significant intercept (α) → true unexplained alpha Why this matters Two strategies can have identical performance, even identical Sharpe ratios, but very different sources of return. A strategy with real alpha is far more robust and scalable than one that simply repackages known factor risks. Before declaring victory in your backtest: Run the factor analysis. Know how much of your “edge” is actually your edge. Follow me Damir Illich for more on systematic, evidence-based, and quantitative investing.

A lot of the internet seems to think that stocks should be expected to return 10% or more on average. This figure hinges on the exceptional recent performance of U.S. stocks. Assuming that exceptional returns are normal is likely a mistake. 1950 - 2023, U.S. stocks delivered a nominal - before inflation - annualized return of 11.32%. For the 20 years ending December 2023, they returned 9.81%. The relatively recent history of U.S. stock returns does support ~10% being the norm. Some context on real vs. nominal returns is important. Take the 15 years ending April 1985 as an example. U.S. stocks returned 10.58% annualized for 15 years, but inflation ran at 7.05%. The real return was tiny. Real returns, not nominal returns, put food on the table. The real return on U.S. stocks 1950 - 2023 was 7.63%, and 7.16% for the last 20 years. The equivalent of the ~10% nominal return in recent U.S. history is a ~7% real return. A 7% real return is still exceptional, both relative to earlier U.S. return history, and global returns. 1900 - 1950 U.S. stocks returned a real annualized 5.57%. Global ex-U.S. returns 1900 - 2023 were 4.35%, or 5.16% including the U.S. market. Block bootstrap drawing on 38 developed markets as far back as 1890 shows a median 5.28% for international and 4.78% for domestic stocks. The recent U.S. real return is around 2% higher than earlier U.S. returns and global returns. The reason matters. The U.S. is special, but that does not mean its return premium will persist. Disasters that could have happened, and have happened elsewhere, have not happened to the U.S. Investors have learned that the U.S. market is safe, driving its discount rate down, and valuations up. Luck and learning explain about 2% of the U.S. equity risk premium 1920-2020. On the premise that it is non-repeatable - or at least should not be counted on since it's reflected in current valuations - U.S. returns 1920-2020 net of the 2% from luck and learning are 5.28%. All roads point to a 7% real return being higher than a reasonable expected return. Assuming that the best historical period for one of the best performing markets will persist does not seem wise, especially with U.S. valuations at their 97th percentile relative to history. At PWL Capital Inc we use a real expected return of 4.62% for financial planning purposes: https://lnkd.in/esiXdNCS Image source: Research Affiliates Asset Allocation Interactive

I have analyzed 5-year, and 10-year rolling returns of Equity Mutual Funds using average, maximum, and minimum return matrices, covering a full 20-year market cycle (16-01-2006 to 15-01-2026). Why rolling returns matter: • Eliminate entry-point bias • Capture bull, bear, and sideways phases • Reveal true risk-adjusted consistency • Highlight downside containment across cycles This dataset provides a framework-level view of how different equity categories and AMCs have behaved across time horizons—offering insights that lump-sum or trailing returns often fail to capture. Use this analysis as a decision-support tool, not a product-selection shortcut. 📊 Data Source: Internal research using publicly available NAV data 📆 Period Covered: Jan 2006 – Jan 2026 🔗 Telegram (Research & Charts): https://lnkd.in/dT9YBgzX Disclaimer: This analysis is for educational and informational purposes only. It does not constitute investment advice or a recommendation to buy or sell any mutual fund or financial product. Mutual fund investments are subject to market risks. Past performance may not be indicative of future results. Please consult a qualified financial advisor before making investment decisions. #EquityMutualFunds #RollingReturns #LongTermInvesting #MutualFundResearch #RiskAdjustedReturns #WealthManagement

Two quick questions for CFOs... Are you maximizing the return on your FP&A digital investments? And ...... How confident are you in your team’s ability to gauge the true value these projects bring to your organization?   Investing wisely in technology that boosts productivity and enhances employee skills is crucial. Yet, deciphering the true impact of these investments on your enterprise’s value presents a challenge. Surprisingly, only a third of CFOs feel their teams have the expertise to accurately evaluate the potential value creation of their digital endeavors. Often, digital projects fail to meet expectations, particularly when their funding and oversight are scattered across various business units.   To bolster the accountability and success of your digital initiatives, consider adopting these strategies:   ✔ Institute Dynamic Project Charters Begin with a comprehensive project charter that outlines the scope and objectives of your digital project. This document should be a living entity, regularly referenced and updated during monthly operational reviews to keep the project aligned with its goals.   ✔ Measure Beyond Financial Metrics Recognize that the benefits of digital investments might not be immediately visible in financial terms. Incorporate non-financial Key Performance Indicators (KPIs) into your evaluation framework, assigning them a quantifiable value. This approach can provide early indicators of whether a project is on the right path.   ✔ Leverage Insights for Future Projects Use the knowledge gained from current projects to enhance future endeavors. Ensure that resource allocation, project timelines, and performance metrics consider the lessons learned, reflecting the interconnectedness and unique demands of digital projects.   Understanding the nuanced impact of digital investments on your organization's overall value requires a strategic and informed approach. By enhancing how projects are chartered, evaluated, and learned from, you can not only increase your confidence in these investments but also drive meaningful, lasting value.   Interested in refining your strategy for digital investment evaluation? Let’s connect and explore effective approaches to unlock the full potential of your technology projects. 🔽 🔽 🔽 👋 Hi, I'm Lisa. Thanks for checking out my Post!   Here is what you can do next ⬇️   ➕ Follow me for more FP&A insights    🔔 Hit the bell on my profile to be notified when I post   💬 Share your ideas or insights in the comments ♻ Inform others in your network via a Share or Repost #digitaltransformation #finance #cfo #data #businessanalytics

For aspiring quants: Last year, I evaluated a strategy that "beat the S&P 500 by 20%." Impressive, right? Then I ran it through a simple CAPM risk model. Turns out, the strategy was just 2x leveraged beta with extra steps. It didn't beat the market - it just borrowed more money to buy the market. Worse: It was delivering only 60% of the return you'd expect for that level of risk. Here's the problem most backtests hide: They show you total return. They don't show you risk-adjusted return. A real example: UPRO (3x leveraged S&P 500 ETF) Edgar Alcántara and I analyzed leveraged ETFs using CAPM for our open-source course and found that:: ·      UPRO takes on 3.04x the volatility (β = 3.04) ·      But delivers only 2.04x the cumulative returns ·      That's 67% of what you'd expect for the risk taken The chart below shows the decomposition: The green line is what CAPM predicts UPRO should return. The blue line is what it actually returns. The gap? Inefficiencies from volatility drag, transaction costs, and behavioral factors. This isn't "alpha." It's inefficient beta. For those building careers in quant finance: Before you present any strategy, decompose it through a risk model: → How much return comes from market exposure? → How much from factor tilts? → How much from genuine alpha? The question isn't "did it outperform?" The question is "was it worth the risk?" Want to learn how to do this analysis? I've built a full tutorial on CAPM and risk-adjusted returns in my open-source Portfolio Management Course (developed with Edgar Alcántara): https://lnkd.in/ebsTPNQ7 Module 4.1-4.4 covers exactly this type of analysis with Python code. Read the full paper: "Leveraged Portfolios Risk Analysis" https://lnkd.in/eVFh-sme This analysis was conducted independently using publicly available data. All views are my own. What's your experience? Where have you seen backtests that looked great but didn't account for risk? #QuantFinance #RiskManagement #PortfolioManagement

ROI, ROE, ROA — same word "return", radically different investors. Most investment debates go wrong because we mix metrics with purposes. This is how actually to use them 👇 Returns are not universal. A VC, a PE fund, a CFO, and a credit analyst can look at the same company and reach opposite conclusions—because they optimize for different constraints. ROI, ROE, and ROA are often treated as interchangeable. They're not. Each metric answers a different economic question and fits a different investor profile. Using the wrong metric leads to: Overpaying for "efficient" but low-quality growth Confusing leverage with value creation Penalizing asset-heavy but strategically sound businesses 🟢 ROI – Return on Investment Best for: 🚀 Venture Capital 🎯 Product / Growth teams 📣 Marketing & GTM leaders What it really measures: Capital efficiency of a specific bet. Typical use cases: New product launch CAC vs LTV decisions Automation / AI investments Economic logic: "If I put €1 here, how fast and how much do I get back?" Rule of thumb: 👉 ROI > 15–20% for risk capital 🔵 ROE – Return on Equity Best for: 📈 Public equity investors 🏦 Private Equity 🧠 Boards & CEOs What it really measures: How aggressively management compounds shareholder capital. Typical use cases: Capital allocation discipline Dividend vs reinvestment decisions Leveraged buyouts Hidden truth: High ROE can come from leverage, not excellence. Economic logic: "How hard is my equity working for me?" Rule of thumb: 👉 ROE > 15%, but always stress-test leverage 🟠 ROA – Return on Assets Best for: 🏭 Industrial investors 💳 Credit analysts 🏦 Banks & rating agencies What it really measures: Operational efficiency before financial engineering. Typical use cases: Comparing asset-heavy businesses Assessing downside protection Debt sustainability Economic logic: "How productive is every euro of assets, regardless of capital structure?" Rule of thumb: 👉 ROA > 5–10%, sector-dependent Before debating returns, ask one question: Who is the marginal capital provider—and what constraint do they care about? Then pick the metric. Benefits Cleaner investment theses Better cross-investor communication Fewer false positives driven by leverage or accounting optics 📌 Bottom line There's no "best" return metric. There's only the right metric for the right investor at the right moment. #Finance #Investing #PrivateEquity #VentureCapital #CapitalAllocation #CorporateFinance #ROE #ROI #ROA

While sustainability assessments increasingly recognize long-term impacts, they often lack the depth and consistency required to effectively inform learning, accountability, and long-term value for investment. The Toolkit for the Ex-Post Evaluation of Adaptation Interventions, developed by the Technical Evaluation Reference Group of the Adaptation Fund (AF-TERG), provides a comprehensive framework for assessing the sustainability and long-term impacts of completed projects. While originally designed for climate adaptation projects, its structured approach, including project selection, data collection, sustainability rating, and resilience analysis, is broadly applicable to various types of projects beyond the climate sector. Key elements of the toolkit include: o Assessing changes in project impacts 3 to 5 years after completion to understand sustained benefits. o Identifying conditions that contribute to sustaining outcomes, such as ownership, capacities, partnerships, and resources. o Evaluating contributions of sustained outcomes to system resilience or overall system improvements. o Employing a mixed-methods evaluation process involving desk review, stakeholder engagement, fieldwork, and co-creation. o Using a six-point sustainability rating scale to classify the extent of outcome persistence and related support conditions. o Recognizing challenges such as data quality, attribution, and contextual changes over time. o Emphasizing stakeholder engagement and learning dissemination to enhance accountability and inform future project design. This toolkit, offers adaptable guidance for ex post evaluations aiming to improve accountability, learning, and evidence-based decision-making across diverse sectors.

Post-Implementation Evaluation: Solution evaluation often follows solution deployment or significant development phases, its timing contingent on project specifics. This process, reminiscent of post-surgery care, ensures solution stability and alignment with business goals and user needs. Like monitoring vital signs post-surgery, solution evaluation assesses a deployed solution's effectiveness, efficiency, and alignment with business objectives and user needs. It involves a comprehensive examination of various aspects of the solution to determine its overall success and identify opportunities for optimization and enhancement.   Key Objectives of Solution Evaluation: Assessing Performance: The evaluation process begins with a thorough assessment of the solution's performance against predefined benchmarks and key performance indicators (KPIs). This includes measuring system uptime, response times, throughput, and scalability to determine if the solution meets operational requirements.   Evaluating Functionality: Solution evaluation entails an examination of the solution's functionality to ensure that it effectively addresses the intended business requirements and user needs. This involves testing individual features and workflows to identify any gaps or areas for improvement in functionality.   Assessing Usability: Usability evaluation focuses on the user experience aspects of the solution, including ease of use, intuitiveness, and user satisfaction. Usability testing methods such as user interviews, surveys, and usability testing sessions are employed to gather end-user feedback and identify usability issues that may impact adoption and productivity.   Alignment with Business Objectives: A crucial aspect of solution evaluation is assessing the degree to which the deployed solution aligns with the organization's strategic goals and objectives. This involves examining whether the solution delivers the expected business benefits, contributes to revenue generation, and supports long-term growth and sustainability.   Identifying Improvement Opportunities: Solution evaluation goes beyond assessing the current state of the solution to identify opportunities for optimization and enhancement. This includes gathering feedback from stakeholders and end-users, analyzing industry best practices, and benchmarking against competitors to identify areas where the solution can be further improved to deliver greater value.   By assessing alignment with business objectives, identifying areas for enhancement, and guiding the implementation of targeted improvement initiatives, solution evaluation ensures that the deployed solution maximizes value and supports organizational goals by addressing performance bottlenecks and usability issues.   #postassessment #solutionevaluation #businessanalysis #value Image credit: Depositphotos