Understanding Economic Cycles

Labubu isn’t just cute — it’s a case study. There’s a consumer psychology principle called The Lipstick Effect — coined after economists noticed that during economic downturns, lipstick sales surged. Why? Because when people can’t afford big ticket luxuries, they shift to affordable indulgences. A $40 lipstick instead of a $400 handbag. Emotional spending doesn’t disappear during recessions — it just changes form. People still crave comfort & joy, but they express it through smaller, more attainable purchases. 🔍 According to studies, 45% of consumers report "treating themselves" more during economic uncertainty — even while cutting back in other areas. In the 2001 recession, Estée Lauder reported an uptick in lipstick sales, while luxury fashion slumped. In 2023, Toy collectibles (like POP MART’s Labubu) became a $14.3B global market — growing despite inflation and financial stress among Gen Z and millennials. 💡 For brand builders: now is the time to rethink how your “small luxuries” show up — packaging, storytelling, product drops, collabs. Because in uncertain times, it’s not that people stop spending. They just spend smarter — and more emotionally.

Forecasting is hard. Finding analysts who do it well is even harder. Too often, I see forecasting either: 1. Overcomplicated: Applying complex ML models just to predict a moving average (?!), or 2. Oversimplified: Running regressions without understanding what the coefficients even mean. I personally use 4 forecasting methods to model a range of outcomes, from conservative to aggressive: 1. ARIMA - Smooths time series data, w/o seasonality adjustment. 2. SARIMAX -  Like ARIMA, but accounts for seasonality. Likely to be the safest and conservative forecast. 3. Prophet -  Captures non-linear trends and seasonality. Often the most accurate. My favorite model for growth forecasts. 4. Manual Projection – aka Olga's secret, overly complicated manual projection. I plot every available metric’s historical D/D, W/W, M/M, and Y/Y % change and analyze their: (a) correlations and relationships (b) seasonal thresholds. It takes ages to complete, but it delivers the most precise forecast. If done right. If I can account for everything the teams are doing. Which is rarely the case. 😬 When reporting, I typically present only Prophet alongside my Projection, keeping ARIMA and its variations for myself as checks. There are many time series models out there: MA, AR, ARMA, ARIMA, SARIMA, Exponential Smoothing, VAR, and more. Forecasts are fun.

I’ve been running my own econometric model of the U.S. economy for almost 30 years now. The basic structure is simple. You start by forecasting the components of demand, that is to say, consumption, investment, trade and government spending. This gives you an initial projection of real GDP growth. You then feed this into labor market equations, along with some demographic assumptions, to forecast the growth in jobs, the unemployment rate and wage growth. All of this, along with assumptions about energy prices and the dollar, then drive forecasts of inflation. Given this outlook for growth and inflation, you make an assumption about the path for the federal funds rate and then run forecasts of other interest rates. With all of this in hand, you can forecast productivity, corporate profits, the federal budget deficit and household net worth. And then you go back to the start to see how all these changes impact your original demand forecast. You repeat the process until you arrive at a reasonably consistent solution. #markets #economy #investing

A Primer on how to use the Yield Curve to become a better macro investor. The yield curve is one of the most important macro variables to watch: it contains a lot of information regarding the status of the business cycle and the degree of monetary policy tightening or easing perceived by markets. Inverted yield curves have famously predicted all recessions over the last 50 years with varying time lags. I would add that a big steepening of the yield curve is also an important signal which can explain whether monetary policy is excessively loose and/or whether the economic cycle is accelerating. But one of the key issues of ''reading'' the yield curve is that people tend to do that in isolation, while instead they should apply another angle. The trick here is to look and interpret yield curve moves within the context of the business cycle! So: here is your Yield Curve Cheat Sheet which allows you to do just that. Let's use a recent example. In the early part of 2024 the yield curve has mostly bear flattened while economists were busy revising growth prospects higher. 👉 Take a look at ''Growth Up + Bear Flattening''. What does that imply, and what asset classes benefit the most from this combination? 1️⃣ Cyclical stocks 2️⃣ Commodities In an environment where growth is moving higher and the market is busy repricing away cuts (= the curve bear flattens as rates move up mostly at the front-end), the ''Old Economy'' does well: value, cyclical, energy-related stocks deliver solid performance as the growth cycle is re-rating higher. And these sectors don't need lower rates to thrive: they just need strong economic activity. But now let's take another example: what if growth slows down, and the Fed is forced to cut rates faster? 👉 Take a look at ''Growth Down + Bull Steepening''. Well, in that case cyclical stocks and commodities actually do poorly. The yield curve bull steepens as the Fed is called to urgently cut interest rates because economic conditions are deteriorating. And finally, another example: what if the Fed decides to cut rates anyway despite growth holding up? 👉 Take a look at ''Growth Up + Bull Steepening''. In that case the yield curve bull steepens: Fed cuts push short-term interest rates lower, but traders have to incorporate term premium and uncertainty about future inflation into the long-end of the curve - hence, the bull steepening. Understanding how Yield Curve movements relate to the economic cycle and influence other asset classes is a key macro skill to acquire. In which regime do you think we are today? P.S. Enjoyed this macro analysis? Follow me (Alfonso Peccatiello) so you don't miss any post & stay updated on the launch of my Macro Hedge Fund! P.P.S. FREE TRIAL to my Institutional Macro Research? Join the biggest institutional investors in the world reading it every day - send me a DM and I'll set you up!

I’ve had to lead companies through three macroeconomic downturns: the financial crisis, COVID, and the end of ZIRP. Here is my advice to founders/CEOs about what they should be doing right now to prepare and respond in case the stock market/economic turmoil gets worse, which it seems like it will. The mistake I’ve made in the past, and I’ve seen many others make is that we say, “Let’s wait and see, it can’t be that bad, right?” and we keep saying that until we’re face to face with some very hard facts and lose-lose decisions. So this advice is in the vein of: how do we hope for the best but plan for the worst (this is a summary of a longer email with more details I sent to a bunch of the founders over the weekend, if you want the full version just comment “send it” or message me and I’ll get it to you). This is wartime. It is exhausting, I know. But no one is coming to save you. Every investor, every advisor, every customer is/will be dealing with their own fire. The hard reality is that this moment is on you. Get yourself in the headspace to lead through it. It will hit every part of your business. New sales will slow first. Sales cycles will slow down or stop all together. But do not let silence fool you. Churn is coming too, it just lags. Each function needs to prepare for impact now. Make the plans now. Build three: (1) Cut to profitability. (2) Extend runway by at least 12 months. (3) Trim fat without damaging the core. You may never use the plans. But if you do, you will be glad they are ready. And if you need to cut, go deeper than you think you need to and do it once. Multiple rounds break teams. I have made that mistake. Support your customers. They are feeling the same pressure you are. Help them make the case to their CFO. Offer flexible terms. Cover implementation. Do whatever you can to help them buy/keep you. Lean into ROI. If your product saves money, now is your time. Show it. Prove it. Make it undeniable. Renegotiate everything. Every contract, every vendor. Assume it is all on the table. Do not wait. Do not be shy. Communicate with your team (more than you usually do). Your team is watching. Silence breeds fear. Transparency builds trust. You do not need to pretend to have all the answers. But you do need to be honest. And do not make promises you cannot keep. Talk to your investors. Tell them your plans. Ask what they are seeing. Let them know where you may need help. The earlier you know what support is realistic, the better. Secure cash now. If you can draw down venture debt or raise a bit of money, do it. Even if you do not need it yet. And remember, it will pass. The only question is when. Your goal is to make sure your company is around when it does. Sometimes the reward is survival. Sometimes it is efficiency. Sometimes it is winning big while everyone else is distracted.

EY Macro Pulse US consumers spend, but become more picky even as inflation cools 📉 Real consumer spending grew a moderate 0.2% m/m in June, following an upwardly revised 0.4% gain in May, as households favored prudence over exuberance in a high price, high interest rates environment. Households did not retrench but they pulled back their spending on autos, restaurants and hotels while spending cautiously on furniture, clothing, recreational services, and transportation services. 🔙 Most of the good news for #consumers is now in the rearview mirror with spending revised up in April and May, but disposable #income growth revised lower. In fact, with real disposable income only rising 0.1% m/m in June, the personal savings rate fell 0.1ppt to 3.4%, its lowest since November 2022. 📊 On an annual basis, real consumer #spending growth was unchanged at a healthy 2.6% y/y in June. Still, with real disposable income growth having slowed to only 1.0% y/y in June, consumers are exercising more discretion with their spending. Lower and median-income household with higher debt burdens and weaker savings buffers are showing more price sensitivity and caution in their purchases while higher-income families are still spending relatively freely. We project that real consumer spending will grow around 2.0% in 2024 and slow to 1.7% in 2025. 📈 The headline PCE deflator rose 0.1% as a modest 0.2% in core PCE prices, led by services, was offset by plunging gas prices. Durable goods prices were unchanged while transportation and recreation prices fell and food services, accommodation, and housing prices only rose 0.1% and 0.2%, respectively. 📉 As a result, headline PCE #inflation fell 0.1ppt to 2.5% y/y – its lowest since February 2021 – while core inflation held at 2.6% y/y – its lowest since March 2021. 🌱 Softer consumer spending growth due to increased pricing sensitivity, reduced business markups, moderating wage growth, and declining rent inflation will continue to provide a healthy disinflationary impulse. We foresee headline and core PCE inflation ending the year around 2.5% y/y. ⏳ The #Fed will hold the federal funds rate unchanged at 5.25-5.50% at next week’s Federal Open Market Committee (#FOMC) meeting, but we suspect policymakers will have a long and lively debate about whether and how to signal a September rate cut. In fact, some policymakers may even argue, as we have, that a July rate cut would have been optimal and preferable given current and expected economic conditions. We expect two 25bps rate cuts in 2024 (September and December) and 125bps of policy easing in 2025. Read the full note here via EY-Parthenon: https://lnkd.in/dmpGXN_m

There is a lot of pessimism in the business and financial news cycle these days due to the uncertainty related to the administration's moves on trade, immigration, foreign policy, and other matters important to our nation's future. The dreaded "R" word (#recession) is appearing more and more. What I find missing is the discussion of the momentum visible in the US #economy coming into 2025. Take the consumer for example. Although #consumerconfidence has taken a steep dive in recent months, we were out there spending money at a healthy clip through February. Compared to last February, seasonally adjusted Advanced Retail Trade and Food Services were up 3.1% last month. Quarterly growth was even higher at 3.8%. Yet all the headlines talked of a whiff in consumer spending. The B2B economy, as reflected in US #industrialproduction data released this week, was also on the rise (from a business cycle perspective - see chart below) through February. In fact, the annual growth rate entered positive territory for the first time since late 2023, while the quarter-over-quarter #data implies further cyclical rise in the months ahead. Why is no one talking about this? At the very least we must recognize that the economy was accelerating before all the trade-related shenanigans began. Alex's Analysis: Leading indicators like Capacity Utilization (6-month lead), Copper Futures (9-month lead) and ISM's PMI (12-month lead) continue to point to further rise in the US industrial economy into the second half of the year. Most consumers, who account for nearly 70% of our economy in GDP terms, remain employed (outside of DOGE cuts), and thus should be able to continue spending in the near-term future if the trend holds. My current assessment is if the policy volatility and uncertainty can be contained to the first half of the year, with decisions on reciprocal #tariffs and specific product categories made soon after the April 2nd research deadline, we should not see a recession in the US in 2025. However, if we can't get out of our own way and the chaos continues past Q2, then the headwinds may become strong enough to result in a contraction of economic activity this year. I will eagerly await the developments and keep you updated if my expectations change.

A Dramatic Drop in Consumer Credit Signals a Shift in U.S. Spending Behavior In a week packed with volatility from tariffs, inflation concerns, interest rate speculation, and stock market turbulence, one quiet signal may be the most important of all: consumer credit shrank in February, the first contraction since the height of the pandemic in April 2020. The latest data from the Federal Reserve shows that total consumer borrowing fell by $810 million, compared to expectations for a $15 billion increase. That’s not just a miss. It’s a reversal. A hard turn away from expansion. It tells us that consumers, facing uncertainty on multiple fronts, are pulling back. What makes this especially noteworthy is that both key components of consumer credit weakened. Revolving credit (primarily credit card usage) was flat, rising just 0.1%. Non-revolving credit, which includes auto and student loans, fell by 0.3%, the first drop in almost a year. In a consumer-driven economy like the U.S., that kind of across-the-board hesitation doesn’t happen without a shift in sentiment. Consumers were already facing high borrowing costs and elevated prices before the recent escalation in trade tensions. Credit card interest rates remain near historic highs, averaging over 21%. And subprime auto delinquencies have climbed to levels not seen since 1994. Even among higher-income households, the sharp stock market pullback and renewed recession talk may be leading to more guarded financial behavior. This shift isn’t just financial. It’s psychological. When consumers start avoiding credit, they’re not just tightening budgets - they’re signaling doubt about the future. Confidence is fragile. Spending slows. And businesses that rely on financed purchases from home improvement to health services to durable goods will feel the impact first. The implications are broad. Retailers may see softer conversion, even if traffic holds. Brands that rely on promotional financing may find it harder to close sales. Decision cycles lengthen. Price sensitivity intensifies. Even categories insulated from economic shocks can find themselves pulled into a more value-driven mindset. This is how slowdowns begin—not all at once, but in signs like these. For the Federal Reserve, this creates a challenge. Inflation remains elevated. But with the consumer retreating, the credit environment tightening, and uncertainty rising, the central bank’s path forward becomes more complicated. At Havas Edge, we’re watching this closely. Because in direct response marketing, data like this is directional. It tells us not where the economy is, but where the consumer mindset is going. #ConsumerCredit #EconomicSignals #ConsumerBehavior

Forecasting in Banking: Techniques for Accurate Financial Projections Accurate financial forecasting is a cornerstone of sound banking practice, providing a foundation for effective decision-making and strategic planning.At its core, forecasting in banking involves predicting future financial outcomes based on historical data, current market trends, and well-informed assumptions. This task, although challenging, is imperative for banks to ensure liquidity, manage risks, and plan for growth. One prevalent method is historical trend analysis. This approach involves examining past financial data to identify patterns and trends that are likely to continue. Banks often use this method to forecast revenue, expenses, and cash flow. It’s a straightforward technique, but it assumes that past trends will persist, which may not always be the case, especially in a rapidly changing economic landscape. Another key technique is scenario analysis. This involves considering various potential future states of the world and evaluating how each would impact the bank's finances. Scenario analysis helps in preparing for a range of possible outcomes, making it a prudent approach in today’s uncertain economic environment. Financial modelling is also central to forecasting in banking. This involves creating detailed models that simulate a bank's financial performance under different scenarios. These models can be complex, integrating various factors like interest rates, loan defaults, and market volatility. Effective financial modelling requires not only technical expertise but also a deep understanding of the banking sector and economic forces. It is also essential to incorporate econometric modelling into the forecasting process. This involves using statistical methods to analyse economic data, allowing banks to make more accurate predictions about future market conditions and customer behaviour. Econometric models can be particularly useful for forecasting inflation rates, GDP growth, and other macroeconomic variables that have a direct impact on banking operations. Moreover, technology plays a critical role in modern banking forecasts. Advanced software and analytics tools enable banks to process vast amounts of data more quickly and accurately than ever before. Sophisticated technology is increasingly being used to predict customer behaviour, identify market trends, and even forecast economic downturns. In conclusion, accurate forecasting in banking is not just about applying the right techniques; it's about understanding the limitations of each method and using them in combination to gain the most comprehensive view possible. It requires a balance between quantitative analysis and qualitative judgement. As the financial world becomes more complex and interconnected, the ability to forecast accurately becomes ever more critical. Banks that excel in this area will be better positioned to navigate the challenges and opportunities that lie ahead.

Cracks in Spending and Manufacturing Begin to Form as Tariffs Filter Through the Economy 📉 What we expected for April retail sales has now materialized: a sharp pullback in consumer spending at retail stores and restaurants following months of stockpiling ahead of tariffs. 🏭 In a separate report from the Federal Reserve, manufacturing output declined by 0.4% in April—the first drop since October 2024. Even though prices have not risen as sharply as anticipated, falling confidence and weakened expectations have pushed consumers into a more cautious stance—particularly when it comes to durable goods, which are especially sensitive to both tariffs and income volatility. Within the retail sales report, the decline in the control group—used as a proxy for goods consumption in GDP—is a concerning signal as we head into the second quarter. 📊 Retail sales weren’t the only data pointing to softening demand. The unexpected drop in producer prices also reflected weakening spending, especially for discretionary services like air travel, financial services, and trade services—a proxy for retail and wholesale margins. The wide gap between CPI and PPI data suggests that, in April, businesses relied on existing inventories to shield consumers from rising input costs. But that came at the expense of business margins, which were compressed. That buffer may not last much longer. According to Walmart, the company plans to raise prices later this month in response to rising tariffs. ⚠️ We are now witnessing the first-order effects of tariffs on the economy—through reduced spending. The second-order impact—on prices—will likely emerge in the coming months, adding further pressure on demand. While a recession is no longer our base case over the next 12 months due to the recent reduction in tariffs, the likelihood has increased that the U.S. economy will endure several quarters of sluggish growth, with inflation remaining high enough to prevent the Fed from cutting interest rates.