Analyzing Market Volatility

On the continuum between “shoot-the-lights-out performance” and “I can actually sleep at night,” most real money sits firmly in the second camp. That’s the entire game of investing in one line: push returns higher without pushing human nerves past their limits. Because investors don’t live in spreadsheets - they live in emotions, expectations, and the quiet 2 a.m. doubt that comes with deep drawdowns. The challenge isn’t just earning high returns. It’s earning returns you can stick with. That’s why the quality of the ride matters as much as the destination. A few metrics help map that terrain: CAGR – the long-term truth of your compounding. Volatility – the bumpiness that tests your resolve. Sharpe Ratio – return per unit of total risk taken. Sortino Ratio – return per unit of downside pain. Calmar Ratio – how much performance survives your worst drawdown. Together, they remind us of a simple, deeply human insight: Know thyself. Know how much turbulence you can really handle. Then build a portfolio that maximizes returns within that psychological boundary. Because the best strategy isn’t the one with the highest theoretical return - it’s the one you’ll still believe in when the market stops being polite.

A detailed intuitive and mathematical explanation of Hedging with Implied vs. Actual Volatility *Implied Volatility: Represents the market's expectation of how volatile the stock will be in the future. Derived from the market price of options. It is forward-looking and reflects market sentiment. Traders hedge using implied vol when they trust the market’s view on future volatility. * Actual Volatility Represents the historical volatility of the stock over a past period. Backward-looking and reflects actual price movements. Traders hedge using actual vol when they have confidence in their own forecasts of future volatility based on historical data. *Hedging with Implied Vol: Pros: It provides smoother P&L (Profit and loss) since it aligns with market prices. Easy to observe and obtain from market prices. Profitable if the actual volatility turns out to be higher than implied when buying options, or lower when selling options. Cons: Uncertainty about the actual amount of profit. It can be less accurate if the market's volatility forecast is incorrect. *Hedging with Actual Vol Pros: Predictable profit at expiration No standard deviation in final profit if the forecasted actual vol is accurate Cons Significant P&L fluctuations during the life of the option Relies heavily on the accuracy of the vol forecast *Mathematical Explanation *Expected Profit and Standard Deviation 1. Expected Profit: The profit from hedging an option is influenced by the difference between the actual and implied vol. The formula for expected profit when buying an at-the-money straddle (image attached below) Where: σ = Actual volatility σ~ = Implied volatility S = Current stock price T = Time to expiration t = Current time *Standard Deviation of Profit: The risk associated with the profit is given by the standard deviation of the profit. The formula for the standard deviation of the profit: (Image attached below) This depends on the actual vol and not on the implied vol *Hedging with Different Volatilities *Actual Vol = Implied Vol: When hedging with the same volatility as the market price, the standard deviation of profit is zero. The expected profit is small relative to the market price of the option. *Actual Vol > Implied Vol: Hedging with actual volatility higher than implied can result in expected profit, but also brings a higher standard deviation of profit. The risk of loss exists if hedging is not accurately aligned with actual volatility. *Actual Vol < Implied Vol: When actual volatility is less than implied, hedging with lower volatility ensures no loss until a certain point of underestimation. This scenario tends to have a more dramatic downside compared to the upside. Hedging with implied vol is generally more aligned with market expectations and tends to provide smoother P&L. Hedging with actual vol provides more predictable results at expiration but with higher risk and P&L fluctuations during the life of the option

The Paradox of Financial Markets: Moorad Choudhry's Key Insights One of the most intriguing characteristics of financial markets is how demand behaves in response to price movements. As Moorad Choudhry explains in The Future of Finance (2010): “Consider the following peculiar and virtually unique feature of financial markets: it is the only industry in which rising prices lead to higher demand. In almost every other industry, such as automobiles, energy, airline tickets, white goods, and a whole host of other sectors, holding all else equal, if the price of the product goes up demand will fall. This isn’t so in finance. Here, people treat rising asset prices differently: rising prices lead to increased demand! As equity or house prices rise, more and more customers, the investors, pile into the product. When prices fall, investors pull out, often at a loss. Financial assets are the only asset class where rising prices lead to increased demand. This paradox of finance fuels market booms and busts.” (Choudhry, 2010, p. xxi) This phenomenon—where rising asset prices attract more buyers rather than deterring them—contrasts sharply with traditional supply-demand dynamics. In financial markets, the allure of rising prices often feeds a self-reinforcing cycle of increased demand, speculative behaviour, and heightened market activity. Conversely, falling prices frequently trigger widespread selling, magnifying losses and exacerbating downturns. The behavioural underpinnings of this paradox, including herd mentality and fear of missing out, are significant drivers of market volatility. Understanding these patterns is essential for investors, as they can lead to irrational exuberance during booms and panic selling during busts. This insight reminds us of the importance of disciplined decision-making and prudent risk management in navigating financial markets, which are often influenced as much by human psychology as by economic fundamentals.

There’s technical analysis and there’s fundamental analysis. But guess the most important kind? 𝗠𝗶𝗻𝗱𝘀𝗲𝘁 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀. This is one big lesson I learnt — with a lot of pain — during the recent market volatility. During the March–April volatility, we went fully risk-off. Our models flagged elevated risk, and we pulled the trigger — exited positions, raised cash, and watched from the sidelines. We thought we were being prudent. But in hindsight, we were being reactive. We ended up selling some incredible businesses — stocks our models had strong conviction in. The markets bounced back swiftly, and we missed the recovery. Those two months of underperformance weren’t about bad models. They were about a momentary lapse in conviction. “𝘛𝘩𝘦 𝘣𝘦𝘴𝘵 𝘵𝘳𝘢𝘥𝘦𝘳𝘴 𝘢𝘳𝘦𝘯'𝘵 𝘵𝘳𝘺𝘪𝘯𝘨 𝘵𝘰 𝘣𝘦 𝘳𝘪𝘨𝘩𝘵. 𝘛𝘩𝘦𝘺'𝘳𝘦 𝘵𝘳𝘺𝘪𝘯𝘨 𝘵𝘰 𝘦𝘹𝘦𝘤𝘶𝘵𝘦 𝘤𝘰𝘯𝘴𝘪𝘴𝘵𝘦𝘯𝘵𝘭𝘺.” 🧠 𝗠𝗶𝗻𝗱𝘀𝗲𝘁-𝗯𝗮𝘀𝗲𝗱 𝘁𝗿𝗮𝗱𝗶𝗻𝗴 𝗶𝘀 𝗮𝗯𝗼𝘂𝘁: • Trusting the process when the P&L looks red. Our signals are built on statistical evidence — not emotion — and staying consistent is the real alpha. • Holding winners when your gut says, “Take profits.” Even the best quant models can’t predict every rebound — but they can guide you to stay with strength. • Understanding that risk management doesn’t mean abandoning quality. The process must include a conviction overlay that respects great businesses, not just downside metrics. 🔁 𝗪𝗵𝗮𝘁 𝘄𝗲 𝗰𝗵𝗮𝗻𝗴𝗲𝗱: We’ve now introduced filters that reinforce conviction — ensuring we don’t let volatility shake us out of high-quality holdings. Our new rules aren’t just statistical — they’re psychological safeguards. Sticking to our guns we were able to outperform the market by a margin in the last 3 months on our factor fund. ✅ 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗲𝗱𝗴𝗲 𝗶𝘀𝗻’𝘁 𝗷𝘂𝘀𝘁 𝗶𝗻 𝘁𝗵𝗲 𝗺𝗼𝗱𝗲𝗹. It’s in sticking with it when it’s hardest to. 🤔 𝗬𝗼𝘂𝗿 𝘁𝘂𝗿𝗻: Have you ever made a decision based on fear that cost you more than holding would have? How do you manage conviction vs caution in your process? #tradingpsychology #quantinvesting #investingmindset #riskmanagement #learningfrommistakes

Why do we sell good stocks at the worst possible time? Not because we don’t know enough. But because our brain plays tricks on us—especially during market crashes. Here are 5 common mistakes investors make (with real-life examples): 📉 1. Hot Hand Fallacy “I made money in this stock before; it will work again.” You buy the same stock at a high price—and it crashes. Example: Chasing a penny stock that gave 2x returns last year, expecting a repeat. ✅ Fix: Every trade is a new decision. Don’t assume past success = future gains. 🧠 2. Hindsight Bias “I knew this market fall was coming.” We feel like we predicted the crash and then overreacted in the future. Example: Saying you saw the Adani drop coming—but didn’t exit in time. ✅ Fix: Don’t trust “gut feeling” in hindsight. Stick to real data. 🔁 3. Recency Bias “Markets are falling again—it’ll keep falling.” We panic after a 2-day drop and forget the last 5 years of gains. Example: Selling mutual funds in March 2020, then missing the rebound. ✅ Fix: Look at the long term. Don’t let this week’s headlines shake your plan. 📦 4. Diversification Bias “I’ve invested in 5 mutual funds; I’m safe.” But all 5 are similar. Example: Holding 5 large-cap funds, thinking you’re diversified. ✅ Fix: Choose funds that cover different sectors or styles. 💔 5. Loss Aversion “I don’t want to lose more money!” So we hold bad investments too long or sell good ones too soon. Example: Selling gold ETFs in fear—then watching them rise 20%. ✅ Fix: Review your plan calmly. Don’t let fear make your decisions. During a market dip, your biggest risk isn’t the stock market. It’s your brain. What’s one mistake you’ve made during market volatility? Let’s learn from each other. 👇 Follow Palak Jain (financewithpalak) for more insights. (Disclaimer: This post is for educational purposes only and not financial advice. Always do your own research before investing.) #PersonalFinance #StockMarket #SmartInvesting #FinancialPlanning #InvestingTips #WealthBuilding #InvestmentMistakes #RiskManagement #MarketVolatility #FinanceInsights

Will we see a structural shift in protein prices due to climate change? Last year at Oxford Martin School's LEAP conference, I argued that we are likely to shift towards more plant-rich diets - one way or another. Not primarily because of climate or nature policy, but because of economics. My central point was simply that meat is likely to become more expensive relative to plant proteins - and consumption follows when prices change. It’s still early, and consumption patterns are slow to change, but the price signals are moving in this direction. A new report from Sarah Ison and Madre Brava "Meat’s Affordability Crisis" (link below) shows that in the UK the price gap between meat (especially beef and lamb) and staple plant proteins like beans and pulses has widened significantly in recent years (see the other figure below). Meat prices have risen sharply, while many plant proteins have remained comparatively stable. The Financial Times is also covering the mounting pressures on British beef farmers which are feeding through into higher retail prices (link to article below). My argument last year was that we should probably expect that the pressures from climate and environmental damage would have a disproportionate inflationary pressure on livestock. Animal systems are structurally more input-intensive: more feed, more land, more energy, more housing, more capital assets - and have greater exposure to climate volatility across multiple supply chains. As the climate warms, impacts on feed supply, animal heat stress, flooding, and rising disease pressure all add to that risk. Already, there are discussions across Europe about adding cooling systems to livestock housing during hotter summers. This only adds to costs. Sarah Ison points out in her post that there has recently been a: "🎯🎯double hit: cows are being housed longer due to water-logged pastures, after a dry summer prevented the storage of enough to feed cows when housed over winter." There is, of course, another pathway: governments double down on subsidy protection to insulate animal systems from rising climate and input costs rather than encouraging transition. But that simply moves the bill from supermarket shelves to public budgets. In an era of fiscal strain, it is hard to see how that strategy can hold indefinitely. Absent this sustained public subsidy, this relative price divergence is likely to continue. As I argued last year: we can shift diets by design early and capture the desperately needed health, environmental and resilience benefits. Or we can shift by disaster through climate shocks, supply constraints and rising prices, in a far more chaotic and regressive way. It will be interesting to see if this is a temporary inflation spike or the early stages of a structural shift in protein prices.

When markets crash, amateur traders panic-sell. When startups struggle, founders panic-pivot. The psychology is identical: uncertainty triggers anxiety, and your brain seeks relief through action—any action. Professional traders know this trap well. They don't make decisions during emotional turbulence. They build systems to protect themselves from themselves: → They document their investment thesis before entering positions → They establish exit criteria before they need them → They follow predefined rules regardless of how they feel → They analyze performance patterns, not individual outcomes → They separate market noise from meaningful signals The best founders operate similarly. They know their greatest enemy isn't competition or market conditions—it's their own emotional response to uncertainty. I've seen this repeatedly throughout my career in investments and AI. When traction slows, mediocre founders immediately chase whatever's trending. Different market, different product, different strategy. The new direction feels good because it relieves the immediate discomfort. Elite founders instead rely on decision frameworks: → They establish strategic criteria for evaluating opportunities → They require the same validation rigor for new ideas as original ones → They maintain a "distraction backlog" to capture ideas without pursuing them → They build cooling-off periods into major decisions → They measure their emotional state before changing direction The shiny new opportunity, partnership, or pivot is usually just emotional relief disguised as strategy. Next time you feel that pull toward something new, ask: "Am I making this decision from clarity or discomfort?" The gap between good founders and great founders isn't intelligence—it's emotional regulation during uncertainty. #startups #founders #growth #ai

Volatility often feels like risk. But the two are not the same thing. Imagine you invest in a diversified global equity portfolio. Over the next few years, markets swing sharply. At one point your portfolio falls 15%. A year later it rises 20%. The journey feels uncomfortable, but if you stayed invested, the long-term direction of markets has historically worked in your favour. That movement is volatility. It is the price you pay for equity returns. Now consider a different situation. Markets fall 15%, fear takes over, and you decide to sell everything to “protect” your capital. The loss becomes permanent. A few months later the market recovers, but you are no longer invested. That is real risk. Ironically, most investors try very hard to avoid volatility. And in doing so, they end up increasing the very risk they were trying to escape. Because volatility only tests your patience. But panic decisions damage your wealth. Over long periods, markets have rewarded discipline far more than clever timing. The real skill in investing is not predicting every rise and fall. It is having an allocation you understand, and the temperament to stay invested when the ride becomes uncomfortable.

Could burgers soon become a luxury for the wealthy? What was once an everyday meal is quietly turning into a privilege driven by a phenomena called: “Climate Inflation.” 📊 Behind the numbers: 👉 Over the past two years, red meat prices have surged at an unprecedented pace. 👉 Reports from Bloomberg, CNN, and recent data from FAO and OECD confirm: droughts and rising heat have reduced cattle herds and driven up feed costs. 👉 The result? 👇 Burger and steak prices are at record highs and are expected to keep rising at least through 2025. 🌡 Why is this happening? ✔️ Drought & shrinking herds: each additional drought severity degree = -12% feed yield +5% price. ✔️ Heat stress: Directly impacts cattle health, weight, and milk production. ✔️ Parasites & diseases: Warmer climates expand parasite ranges, adding costly treatment challenges. ✔️ Hidden environmental costs: True Price 2025 estimates the “climate cost” of producing a kilo of beef in the millions of dollars due to greenhouse gas emissions and environmental degradation. 📈 Opportunities & challenges: -Meat accounts for 15% of global emissions. -U.S. and Canadian markets expect an additional 9–11% price hike. -This creates opportunities for investment in climate-smart agriculture (AgTech), and sustainable production models. 💡 Pathways forward: -Integrating trees into grazing systems (silvopasture). -Developing drought-resistant feed crops. -Improving supply chains and reducing food waste. 🚀 Bottom line Meat isn’t disappearing from our plates anytime soon but those who innovate across the value chain will secure both sustainability… and profit. Which do you think will change first: meat prices or consumer eating habits? Share your perspective #ClimateChange #Sustainability #AgTech #SustainableFarming #LinkedInNews

One of the more interesting conversations I have with new clients is around risk. Almost everyone says they are comfortable taking risk if the objective is higher long-term returns. The confidence is usually highest when markets have been performing well, portfolios are growing and volatility feels like something that happens to other people. The real test comes later. A 15% or 20% correction has a way of revealing things that questionnaires and risk profiling exercises never can. The investor who was comfortable with equity exposure six months ago suddenly wants to discuss reducing allocation. The long-term investor starts looking for short-term certainty. The focus shifts from wealth creation to loss avoidance. I don't think this happens because people lack intelligence or financial knowledge. In fact, some of the most emotionally difficult investment decisions I've seen were made by highly accomplished professionals who understood markets perfectly well. The challenge is that most people evaluate risk in theory and experience it in reality. Those are two very different things. When markets are rising, higher returns feel attractive. When markets are falling, the volatility attached to those returns suddenly becomes much more visible. The investment has not changed. What changes is the investor's relationship with uncertainty. Over the years, I've become increasingly convinced that investing success has less to do with identifying the best opportunities and more to do with understanding yourself honestly. Asset allocation, diversification and portfolio construction all matter, but they only work if they are built around a level of risk you can actually live with when markets become uncomfortable. Most wealth destruction I've witnessed did not come from market crashes themselves. It came from investors abandoning a sensible long-term plan because they encountered a level of volatility they thought they could handle, but couldn't.