Navigating Investment Risk

10 red flags I look for as an angel investor. I’ve invested in 50+ startups and seen what works (and what doesn’t). If you’re raising money, avoid these mistakes: ~~ 1. No real customers A deck, a landing page, and a “vision” don’t impress me. Show me paying customers. Even better, show me customers coming back. == 2. No path to profitability I don’t care if you raise $100M—if there’s no plan to make money, you’re just burning oxygen. Growth is great, but cash flow keeps you alive. == 3. Founders who won’t sell If you’re scared to get on sales calls, that’s a red flag. The best founders sell in the early days—whether it’s to customers, employees, or investors. == 4. No differentiation “Like X, but cheaper” isn’t a strategy. If your only edge is price, you’ll get crushed. What do you have that no one else does? == 5. No urgency The best founders operate like time is running out. If you’re “exploring ideas” or “thinking about raising next year,” you’ve already lost. == 6. Raising money before proving anything Too many founders try to fundraise their way out of bad ideas. If you need VC to get off the ground, you’re building the wrong business. == 7. No clear distribution strategy Product alone doesn’t win. First-time founders obsess over features. Second-time founders obsess over distribution. How are you getting customers? == 8. No ownership mentality If I hear “I need to hire someone to do that” too early, I’m out. Founders who win figure things out before they delegate. == 9. A CEO who can’t attract talent Your first hires are everything. If great people aren’t willing to join, either the vision is weak—or you are. == 10. No skin in the game If a founder won’t invest their own money or take a pay cut to make it work, why should I? ~~ Enjoyed this post? Follow Josh Payne for more content like this!

I spent several years underwriting real estate private credit funds. Here are three red flags that you should avoid when investing in these funds: 🚨- Lack of experience. If the management team and support staff do not have experience as real estate lenders, you should understand that they are unlikely to be capable of understanding the nuances of the risks involved in becoming a lender. 🚨🚨- Lack of discipline. If the PPM is overly broad, the investment thesis is not consistent, and you are seeing random asset types in tertiary markets, run, do not walk to the exit. 🚨🚨🚨- Poor governance. If the fund has difficulty producing historical data, does not plan to (or pass) an audit, makes loans to insiders, or does not use a third party fund administrator, these should be signs that your investment is likely at higher risk. Here are 3 things you should always ask to see: 1️⃣ - Audited financial statements 2️⃣ - Current loan tape 3️⃣ - Loan Case Studies If these cannot be produced in a timely and professional manner, consider it an additional red flag. Anything you would add Paul Shannon, Bradley Laddusaw, CPA, or Leyla Kunimoto?

Wall Street isn’t the only place economic shifts are felt. Main Street feels it too. With key economic reports around the corner, here’s what passive investors—especially in commercial real estate (CRE)—need to pay attention to: 📌 April 4 – March Employment Report • Why it matters: A slowdown in job growth might impact the Fed’s rate strategy—and that affects borrowing costs on CRE projects. • What to watch: Unemployment trends + wage growth = signals of future tenant demand and rental strength. 📌 April 10 – Consumer Price Index (CPI) 📌 April 11 – Producer Price Index (PPI) • Why it matters: Inflation pressures don’t just hit your grocery bill. They can eat into operating costs but may also justify rent escalations in certain leases. 📌 April 30 – Personal Spending & Income • Why it matters: High consumer spending = stronger retail CRE prospects. Decline? Time to assess risk exposure to that sector. These economic indicators aren’t just headlines—they shape the landscape for every passive real estate investor. 🔍 As someone who teaches busy professionals how to confidently diversify outside of Wall Street, I focus on helping you understand how to read these signals—and make informed decisions on your own terms. 📊 Some of our past projects outperformed expectations because we understood these economic signals early. Others didn’t go exactly as planned—because, like any investment, real estate has variables outside of anyone’s control. But here’s what I’ve learned: having the right framework and education helps you adapt, protect your downside, and make better long-term decisions. Are you currently tracking how macroeconomic trends impact your non-Wall Street investments? Or is this a new perspective? Let’s compare notes. Drop your thoughts below 👇 And if you’re just getting started, DM me “INSIGHTS” and I’ll send you a free guide that walks you through how to confidently take your first step into passive real estate investing—without feeling overwhelmed. #PowerOfPassiveRealEstateInvesting #YourLegacyOnMainStreet #BuildingWealth

Here's my cheat sheet for a first-pass quantitative risk assessment. Use this as your “day-one” playbook when leadership says: “Just give us a first pass. How bad could this get?” 1. Frame the business decision - Write one sentence that links the decision to money or mission. Example: “Should we spend $X to prevent a ransomware-driven hospital shutdown?” 2. Break the decision into a risk statement - Identify the chain: Threat → Asset → Effect → Consequence. Capture each link in a short phrase. Example: “Cyber criminal group → business email → data locked → widespread outage” 3. Harvest outside evidence for frequency and magnitude - Where has this, or something close, already happened? Examples: Industry base rates, previous incidents and near misses from your incident response team, analogous incidents in other sectors 4. Fill the gaps with calibrated experts - Run a quick elicitation for frequency and magnitude (5th, 50th, and 95th percentiles). - Weight experts by calibration scores if you have them; use a simple average if you don’t. 5. Assemble priors and simulate - Feed frequencies and losses into a Monte Carlo simulation. Use Excel, Python, R, whatever’s handy. 6. Stress-test the story - Host a 30-minute premortem: “It’s a year from now. The worst happened. What did we miss?” - Adjust inputs or add/modify scenarios, then re-run the analysis. 7. Deliver the first-cut answer - Provide leadership with executive-ready extracts. Examples: Range: “10% chance annual losses exceed $50M.” Sensitivity drivers: Highlight the inputs that most affect tail loss Value of information: Which dataset would shrink uncertainty fastest. Done. You now have a defensible, numbers-based initial assessment. Good enough for a go/no-go decision and a clear roadmap for deeper analysis. This fits on a sticky note. #riskassessment #RiskManagement #cyberrisk

Achieved 50% less risk in my portfolio in just one year. Here’s how I did it: Most investors think they're diversified. They're not. I see the same mistake everywhere I look. The real estate agent with 3 rental properties. All in the same neighborhood. All bought the same year. The tech worker with their entire 401k in company stock. The entrepreneur who only invests locally. Here's what real diversification actually looks like. **The Single-Basket Problem** Picture this scenario: You own 3 rental properties worth $600,000. Same street. Same market. Same risk. The local factory closes. Unemployment spikes. All three properties lose 30% of their value overnight. Your entire real estate portfolio just got crushed. This isn't diversification. It's concentration disguised as diversification. **Why Most People Get This Wrong** We invest in what we know. We buy where we live. We stick with what's comfortable. But comfort is the enemy of true wealth building. Real diversification means spreading risk across: Different geographic markets Multiple asset classes Various time periods Different management teams Multiple economic drivers **The Syndication Advantage** When you invest in a multifamily syndication, you get instant diversification. One $50,000 investment gives you exposure to: 200+ different tenants Multiple income streams Professional management Diversified local economy Compare that to buying one rental property. Same investment amount. Exponentially less risk. **Real Numbers, Real Difference** Investor A: $200,000 in one rental property 1 property 1 tenant at a time 1 local market 100% concentration risk Investor B: $200,000 across 4 syndications 776 total units 4 different markets Multiple management teams Diversified risk profile Which investor sleeps better at night? **Your Portfolio Reality Check** Ask yourself these questions: What percentage of your wealth is tied to your local market? If your industry had a downturn, would both your job AND investments suffer? Are you comfortable betting your financial future on one geographic area? **The Texas Diversification Strategy** Smart investors spread across multiple Texas markets: Austin: Tech-driven growth Dallas: Corporate headquarters hub San Antonio: Military and healthcare stable Houston: Energy and port commerce Different economic drivers. Different risk profiles. Better sleep at night. **Your Next Move** Look at your current portfolio concentration. Identify your biggest risks. Start building true diversification. Success isn't about finding the perfect investment. It's about building a portfolio that survives any storm. **What's your biggest concentration risk right now?** **PS:** What's holding you back from diversifying beyond your local market? I'd love to hear your biggest challenge in the comments.

Liquidity-Adjusted VaR and Expected Shortfall in Bond Portfolios -- When managing a bond portfolio, traditional Value at Risk (VaR) provides an estimate of potential losses under normal market conditions. However, it ignores one critical factor — liquidity. In fixed-income markets, liquidity risk often spikes during stress events, with widening bid-ask spreads and reduced market depth. This can significantly increase the cost of unwinding positions. -- Consider a portfolio holding corporate bonds and government bonds. Under normal market conditions, the liquidity cost of selling Treasuries is negligible, while investment-grade and especially high-yield bonds carry wider spreads. Liquidity-adjusted VaR (LVaR) builds on standard VaR by adding these costs. For instance, a portfolio with a $100 million exposure may show a VaR of $3 million at 99% confidence, but once adjusted for bond spreads, LVaR could rise to $3.5 million — a 17% increase simply due to transaction costs. -- The effect is even more pronounced in stressed markets. During liquidity shocks (such as the 2008 crisis or the March 2020 selloff), credit spreads widen sharply. High-yield bonds that normally trade with a 50 bps bid-ask spread may suddenly see spreads exceed 200 bps. This pushes the liquidity-adjusted VaR much higher, as forced liquidation would mean selling into a thinner market at deeper discounts. -- Expected Shortfall (ES), or Conditional VaR, further strengthens this picture by measuring the average loss beyond VaR. Liquidity-adjusted ES (LES) captures not just the tail losses from market volatility, but also the additional fire-sale costs of liquidating bonds in illiquid conditions. For example, if ES on the same $100 million portfolio is $5 million, liquidity adjustments under stress could increase it to $6 million or more. -- For bond portfolio managers, these metrics matter because they reflect the true cost of risk — not just from market movements, but also from liquidity constraints. Incorporating LVaR and LES into stress testing and risk frameworks ensures that portfolios are not only market-resilient but also liquidity-resilient, which is crucial in fixed income markets where liquidity can vanish exactly when it’s needed most. -- The below analysis is based on hypothetical numbers and is just provided as an example. #RiskManagement #LiquidityRisk #BondMarkets #VaR #ExpectedShortfall #FixedIncome #StressTesting #MarketRisk #LVaR #LES #Volatility #Treasury #CreditSpreads

🧠 Two Credit Spread Indicators to Watch Even if you are not a direct investor in credit bonds, sometimes it pays to watch the credit spreads for signs of cracks in the market before equity markets fully react. We'd rather be early than late right? When assessing the general credit health of the market, two signals deserve close attention: the #CDX Investment Grade Spread and the ETF I-Spread (as seen in #LQD). 📌 1. CDX Investment Grade (White Line on Chart) A synthetic measure of credit risk, CDX represents the cost to buy protection on a basket of investment grade (IG) names via credit default swaps (CDS). A rising CDX = rising fear. Since it is a synthetic, liquid market, it is often the fastest-moving credit risk barometer, reacting instantly to macro shocks, liquidity crunches, or systemic risk. Think of it as the "credit VIX" — high-frequency and highly sensitive. 📌 2. ETF I-Spread (Orange Line) The I-Spread compares the yield of a bond ETF like LQD to a duration-matched Treasury. Higher I-Spreads = investors demanding more compensation for credit risk in cash bonds. This spread reflects supply/demand pressures, ETF flows, downgrade concerns, and broad credit appetite in the cash bond market. 📉 Why These Indicators Matter When both CDX and I-Spreads are rising, the market is flashing broad credit concern. But when they diverge, it tells you something deeper: ➡️ CDX > I-Spread: synthetic markets are more risk-averse than the cash market — possibly signaling hedging activity or fear before it's priced into bonds. Less noise more signal. ➡️ I-Spread > CDX: cash bonds may be under pressure due to ETF outflows or idiosyncratic stress — technical selling, not systemic risk, may be driving the move. This can still be useful as you tells you to look for OTHER reasons why the ETF I-Spread diverges. This month's chart shows that the seas are calm in credit. Notice that spreads are near the bottom of the range for the month, likely a reflection of the subsidence of turmoil related to permanent tariffs. CDX tightening modestly while LQD’s I-Spread compressed even faster, suggesting ETF demand is absorbing credit risk more aggressively than the CDS market. 🧭 Interpretation: Cash is healing faster than CDS — perhaps a sign of yield-hungry investors stepping back into IG. All this is a signal of constructive credit sentiment — for now. 💡 For Fixed Income Investors Whether you're managing duration, evaluating risk-on/risk-off signals, or assessing dislocation opportunities — tracking both synthetic and cash credit spreads offers a fuller picture of the market's true credit tone. Nothing screams #activemanagement more than investing in credit. 📊 *FICM Chart sourced from Bloomberg #CreditMarkets #FixedIncome #ETFs #BondMarket #MarketSignals #InvestmentGrade #MacroRisk #SanJacAlpha #SpreadTrading #PortfolioInsights

For a family office investment office, the foundational task is to clearly define the family's investment objectives and risk tolerance. This critical analysis lays the groundwork for all subsequent portfolio decisions. Determining Investment Objectives - Align objectives with the family's overarching goals and values - Considerations may include capital preservation, growth, income, impact investing, etc. - Establish clear, measurable targets for portfolio performance Assessing Risk Tolerance - Evaluate the family's willingness and ability to withstand portfolio volatility - Consider factors like time horizon, liquidity needs, and the family's risk profile - Develop a risk management framework to mitigate undesirable outcomes Analyzing Investment Outcomes - Model the impact of different investment strategies on the family's finances - Stress test portfolios against potential market conditions and scenarios - Understand how investment results may affect the family's operations Documenting the Investment Policy Statement - Codify the family's objectives, risk parameters, and decision-making processes - Use this as a guiding framework for all investment activities By thoughtfully defining the investment objectives and risk tolerance upfront, the family office investment team can construct a portfolio aligned with the family's unique circumstances and long-term goals.

Black swan events are rare, unpredictable, and have massive impacts. Standard risk models, which rely on historical data and assume normal distributions, fail to capture these extreme outliers. Banks should recognize that financial returns often have “fat tails,” meaning extreme events are more common than standard models predict. Instead employ risk models that account for fat tails and non-linear interactions, such as Monte Carlo simulations with fat-tailed distributions. These allow banks to better capture the real risk of rare, high-impact events and improve stress testing. Taleb argues that the focus should be on building systems that are robust to negative black swan events, rather than trying to predict them. This means designing risk management frameworks that can withstand shocks and limit exposure to catastrophic losses. While diversification works for regular risks, it is often ineffective against black swan events, which can cause simultaneous, correlated failures across assets or sectors. Banks must recognize that in "Extremistan" (Taleb's term for domains dominated by outliers), a single event can overwhelm diversification strategies. Taleb suggests it is preferable to take risks you understand and to contractually limit those you do not, rather than assume you can model or predict them. Use contractual tools (such as caps, exclusions, and limits) to restrict potential losses from extreme events. Banks can adopt similar practices to better manage tail risks. Taleb warned that if one bank fails, others may follow due to interconnectedness, making systemic risk management crucial. Just because something has worked in the past does not mean it is safe; repeated success can breed dangerous complacency (like the turkey fed daily until Thanksgiving). Banks should remain skeptical of prolonged periods of stability and avoid assuming continued success means low risk. Design portfolios and business models that not only withstand shocks but can benefit from volatility and disorder. This means limiting downside exposure while keeping upside potential open, a concept Taleb calls “antifragility”. Antifragility refers to systems that improve and grow stronger when exposed to shocks, volatility, and uncertainty, rather than merely resisting them (resilience) or breaking under stress (fragility). Regularly conduct robust stress tests that simulate extreme but plausible scenarios. Use new heuristic measures of fragility and tail risk to identify vulnerabilities in bank portfolios and operations. Avoid becoming “too big to fail.” Large, complex institutions create systemic risk externalities that can amplify the impact of black swan events. Smaller, less interconnected banks are less fragile and pose fewer risks to the financial system. Acknowledge that not all risks can be predicted or quantified. Build buffers, maintain conservative leverage, and avoid overconfidence in risk models.

John Heltman's recent op-ed on capital stress testing hit the nail on the head. As someone deeply involved in helping community banks navigate the complexities of stress tests, I couldn't agree more with the points he and Dan Tarullo raise. The reliance on CCAR scenarios as the be-all and end-all has its pitfalls. Case in point: the assumption that interest rates would plummet back to zero during a crisis. While this might have been true in 2008, it's out of sync with today's concerns about prolonged higher rates. What's more, recent bank failures like SVB and First Republic illustrate the blind spots in the CCAR approach. It's not just about credit risk in a recession; liquidity and interest rate risks matter too. And let's not forget NYCB's woes, where a CCAR-style recession might have actually helped some customers. At our firm, we don't rely solely on CCAR. We run multiple scenarios, including "higher for longer" and stagflation, to craft tailored stress capital buffers. Yet, we acknowledge the challenge of predicting the next crisis — it could be anything from a pandemic to other black swan events. Looking ahead, AI holds promise for stress testing, but we're not there yet. Even if we were, there's no preparing for every eventuality. It's like driving a car: you take precautions, but there's always risk. Stress testing isn't perfect, but it's the best tool we have for measuring capital adequacy. Putting all our eggs in one scenario isn't wise, especially when that scenario has proven blind spots. #CapitalStressTesting #RiskManagement #BankingIndustry #FinancialServices #StressTesting #CCAR