Derivatives Trading Basics

Mondelez reported Q4 earnings yesterday and one of their comments made me doubt for a minute. They read in the inverted cocoa futures market that the cocoa S&D eventually balances. This is incorrect. An inverted futures curve reflects -most of the time- underlying physical tightness of a commodity. Market participants are prepared, or forced to pay a premium for nearby delivery of the commodity, as apparently they cannot wait for future deliveries. I say most of the time, as especially cocoa futures, but it happens in other commodities, have been squeezed, meaning, participants have taken a dominant long position to corner bonafide short hedgers, with the sole purpose to move the price. If futures prices invert for this reason, without justification from the physical underlying, what then usually happens is that cash differentials collapse (including product ratios), to pull physical cocoa beans to the exchange for physical delivery. This happened in the famous July 2010 squeeze, which eventually failed as there was no physical shortage, and the inverse collapsed shortly after the July delivery. An inverted futures market, meaning lower prices on the deferred, is not a prediction of lower future prices which people sometimes think. These are current prices for deferred delivery, period. Nor is it a prediction for the S&D to become balanced, after three consecutive deficits and potentially a fourth one. It is a reflection of current (extreme) tightness. And if Mondelez, or other chocolate confectionary companies need futures in exchange of products on 2025 positions, it can't cover that with 2026 futures. If the structural supply issues are not being resolved, and demand destruction does not accelerate faster than their reported minus 2% ish, then the futures market should remain inverted, and elevated. Maybe counterintuitive to Mondelez, but if hypothetically the market would price a large surplus next year, the futures curve could flatten, or even move into a carry, which leads to much less deferred downside price pressure than the nearby. For the rest, "emerge stronger" is obligatory and popular management language to engage employees and investors in tough situations. Time will tell. "Closely monitor and remain agile" is also popular management language. It means something like "Yeah yeah, we are in a tough spot, but at the moment we can't do much more than watching the market and hope for the best". I think this applies to many among the chocolate confectioners at the moment. The cocoa S&D will balance, and move to a surplus over time, slowly but surely. That is the purpose of the futures market, by impacting behavior of producers, processors and consumers. It's a slow, painful, and fascinating process. Seatbelts fastened.

Everyone talks about the swap spread, few explain it. An explainer on how it works and what is says about (il)liquidity. Swap spread = Interest rate swap rate minus (same tenor) US Treasury bond yield Swap spreads should be positive because: a) Treasuries are risk-free b) Swaps have counterparty credit risk (banks offer these swaps, so bank's credit risk) c) Treasuries are more liquid Example: 10yr swap rate: 4.12% 10yr UST yield: 4.18% Swap spread = 4.12% – 4.18% = -0.06% What is a swap? Interest rate swap (IRS) is a contract between 2 parties to exchange cash flows based on different interest rates - Party A pays a fixed interest rate - Party B pays floating interest rate Notional principal is not exchanged, only difference in interest payments. Swap receiver of fixed rate emulates buying a bond Swap pros + Swaps don’t require actual cash investment upfront + Swaps don’t tie up capital (just collateral/margin) and therefore offer leverage Swap cons - Counterparty risk - lower liquidity than bonds - Valuation sensitivity Why would swap spread turn negative? a) Investors are more willing to receive fixed payments in a swap than to hold a Treasury b) Treasuries are sold off (yields ⬆️) c) Swap demand is high because rates are falling If Treasuries are being heavily sold (to meet margin calls) and yields are ⬆️more than swap rates, means: 1. Dealers are not stepping in to buy Treasuries 2. Treasury market has lost depth (forces Fed hand) 3. Regulatory constraints (balance sheet usage) may prevent arbitrage UST are easier to tap liquidity: low price impact/can be repo'd for cash. Swap unwind is harder because swaps aren’t sellable asset (they're contracts) - Selling UST is like selling gold: easy but buyer needs to want it. - Unwinding a Swap is like canceling rental contract: doable but you may owe fees/need to re-negotiate.

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

Agriculture Commodities Markets in the Age of Permanent Turbulence!! Over the past two months across three continents, surrounded by traders, millers, analysts and policymakers, one thing became very clear to me: the agriculture commodities business has entered an era where uncertainty is not a phase – it is the operating system. Learning from some of the sharpest minds reinforced my thoughts. What used to be a neat equation of production + stocks + freight = price is now being rewritten by politics. Wars, sanctions, sudden export bans and policy U-turns are often moving markets faster than fundamentals. If you are not tracking geopolitics as closely as you track crop reports, you are trading half-blind. This is why resilience is no longer a buzzword. Import-dependent countries are quietly rethinking food security – diversifying origins, building (or rebuilding) strategic reserves, and stress-testing “what if the main corridor shuts tomorrow?” scenarios. On the private side, companies are mapping alternate routes, backup ports and flexible sourcing models as seriously as they model yields. In such a world, risk management is not a luxury; it is survival. Futures, options and structured hedging tools are becoming the seatbelt of the trade. Volatility doesn’t just hurt margins – it can wipe out trust between farmers, traders and buyers if not managed with discipline and transparency. Logistics, too, is being reinvented. With traditional channels under stress, we are seeing the rise of new gateways, multimodal solutions and “green corridors” that tie together rail, road and emerging ports. Technology is quietly reshaping this layer – from smarter freight scheduling to better visibility across the chain. Running through all these conversations is a non-negotiable theme: sustainability. Climate stress, water risk, deforestation rules, ESG commitments and the rapid growth of biofuels are no longer side notes; they are changing trade flows, investment decisions and even which crops get planted where. My reflections: We urgently need agriculture commodities intelligence, not just data (provided by a large number of players) – integrated views that combine weather, policy, freight, currency and sentiment into actionable signals. The centre of gravity is shifting toward the Global South. How we integrate producers in Africa, Latin America and the Black Sea with demand centres in Asia will define the next decade. Finally, this is a people business. In rooms full of models and dashboards, the most valuable edge is still humility – the willingness to update your view when the world refuses to behave like last year’s spreadsheet. The “new normal” is noisy, but for those who stay prepared, collaborative and curious, it is also full of opportunity.

Understanding the Receive and Pay Legs of a Swap: Key Components in Risk Management In the world of derivatives, particularly interest rate swaps, the terms "receive leg" and "pay leg" are fundamental concepts that treasury professionals must understand. These two components form the basis of how a swap functions and are crucial in managing financial risks effectively. A swap is a contractual agreement between two parties to exchange cash flows based on different financial instruments. In an interest rate swap, one party agrees to pay a fixed interest rate on a notional amount, while the other party agrees to pay a floating interest rate on the same notional amount. The "receive leg" refers to the cash flows that a party receives, while the "pay leg" refers to the cash flows that the party pays. For example, if a company enters into a swap where it pays a fixed rate and receives a floating rate, the fixed rate payment is the "pay leg," and the floating rate payment is the "receive leg." The purpose of such a swap is typically to hedge against interest rate risk, allowing the company to stabilise its cash flows by locking in a fixed rate while benefiting from potential declines in floating rates. Understanding these legs is essential for treasury managers, as the structure of the swap determines the impact on the company’s financials. The receive leg can provide a hedge against rising costs or falling income, while the pay leg represents the cost of the hedge. By carefully analysing these components, institutions can craft strategies that align with their risk management goals. In summary, the receive and pay legs of a swap are the mechanisms through which risks are managed and financial outcomes are shaped. Mastery of these concepts is vital for anyone involved in treasury management, as they enable the effective use of swaps to protect against market uncertainties and support financial stability.

Good morning. One theme I have followed closely this year is how funding decisions evolve when politics, pricing and liquidity all start pulling in different directions. Borrowers usually remain loyal to a single currency unless the economics give them a clear reason to move. When that pattern changes, it is worth looking at what is happening in the deeper structure of global credit. The chart below is a good illustration. It shows that several large Asian firms now secure a lower all-in cost by issuing in euros and swapping the proceeds back into their home currency than by issuing in dollars. DBJ, NTT, SoftBank, DBS and KOLAHO are aligned on this point. Euro spreads have tightened enough and the swap back into local currency is inexpensive enough that the final cost undercuts the dollar alternative. Once you see that, the larger picture starts to come into focus. Four elements stand out. • European investors have become a more influential part of Asian primary markets. They are seeking diversified credit exposure and have been willing to take tighter pricing on well-known Asian names. • Cross-currency basis conditions now favour euro funding. Swapping euro proceeds back into local currency is efficient, which removes one of the main advantages of the dollar market. • Asian treasurers are adjusting to a more complicated external environment. Tariffs, US policy uncertainty and a softer dollar are all encouraging borrowers to broaden their funding channels. • Pricing is driving the shift. When the post-swap cost in euros is lower, the choice becomes straightforward and orderbooks in Europe are deep enough to take the supply. For me, the value of this chart lies in how clearly it captures the quiet adjustments reshaping global funding flows. Capital gravitates toward the combination of cost, liquidity and predictability that best fits the moment. At the margin, that combination is increasingly pointing issuers toward Europe. I will be watching whether this is a temporary window created by favourable swap levels or the beginning of a more durable division of funding between New York and Europe. The early signs suggest the transition is already underway.

An Intuitive Approach to Implied Volatility Implied volatility is usually introduced through models. Black–Scholes as the benchmark, extended by local volatility, stochastic volatility, jump-diffusion frameworks, or full surface calibrations. These approaches are powerful and necessary — but they are not the most intuitive way to think about option prices. There is a much simpler perspective: Imagine you are the only market maker for options on a completely exotic underlying: Gizmos. There is no option market yet, no implied volatility surface to look at. Clients call you and ask for prices. What volatility would you use? The natural starting point is obvious: you look at the current realized volatility of Gizmos. This is the best empirical estimate of how the underlying behaves right now. From there, you add a risk premium: - Time to maturity: the longer the option’s life, the more uncertainty you need to warehouse. - Known price-relevant events during the life of the option: scheduled announcements, decisions, or structural changes. - Unknown risks: regime shifts, tail events, and shocks that cannot be timed or modeled, but must be priced. This simple logic already explains much of what we observe in real markets: Longer maturities embed more uncertainty → term structure of implied volatility. Downside options require more compensation due to asymmetric and hard-to-hedge risks → volatility skew. One could add that competition, balance sheet constraints, and hedging costs refine these premiums — but they do not change the core intuition. The key point is this: Despite the apparent complexity and the multitude of models, option prices are fundamentally intuitive. Implied volatility is simply the level at which risk is willingly transferred, given observable behavior and unobservable uncertainty. In that sense, options markets are not only sophisticated — they are remarkably efficient. #options #volatility #investing

The hottest commodity reports these days are by far COT/ICE weekly positioning reports which traders use to track "funds/speculators/non-commercials" behavior. What many pundits are missing though that not all funds are created equal. Our recent papers describe how one can get much better insights by following and modelling its constituents, such as "managed money" and "other" for WTI and Brent separately, as they are distinctly different types of speculators, pursuing very different strategies: https://lnkd.in/ear8CucM https://lnkd.in/ef_UT5dd The last two weeks were a particualrly good case in point with large divergence between managed money buying Brent while selling WTI. The difference between the two (red arrows) could be loosely associated with discretionary non-quant traders, highlighting their shift towards the direction of larger geopolotical risks. This could be more a useful data point that simply saying that on average speculators' positions were unchanged, especially during the times when "managed money" (professionals) and "other" (retail) are often on the opposite sides of the trades. The devil is in the details here. Ilia #oiltrading #energymarkets #hedgefunds #algorithmictrading #commodities #quantitativeanalysis

As a mathematician in capital markets, I find that Quanto (quantity-adjusting) options perfectly illustrate what happens when we refuse to accept market risks at face value. For the uninitiated, a Quanto allows an investor to gain exposure to a foreign underlying asset while having the payoff converted back to their domestic currency at a strictly fixed exchange rate. The investor gets the asset exposure while completely immunizing themselves against FX volatility. But as any quant or risk analyst knows: risk doesn't disappear; it just changes form. By fixing the exchange rate, the pricing model can no longer treat the asset and the currency as independent variables. The mathematical heavy lifting comes down to the Quanto adjustment, a textbook application of Girsanov’s Theorem. To price this correctly, we have to change the probability measure and adjust the drift of the underlying asset by the covariance between the asset's returns and the FX rate's returns. If the foreign asset and the FX rate are highly correlated, the cost of that Quanto feature shifts dramatically. The risk management challenge isn't just managing the Delta of the asset, but managing the dynamic, often unstable correlation surface between the asset and the currency pair over the life of the trade. In today’s shifting macro environment, how are you handling the pricing of that correlation parameter? Are you relying on historical covariance, or are you having to push deeper into implied stochastic correlation models to manage your book's risk? #QuantitativeFinance #CapitalMarkets #Derivatives #QuantoOptions #RiskAnalysis #Quants #FinancialEngineering #MathFinance #OptionsTrading #CorrelationTrading

How do you trade when you are not Cargill or Glencore ? 🤔 Unlike large corporations with dedicated hedging desks, mid-level players often have tighter margins and less room for error. A small price swing in a key commodity can significantly impact profitability While there are various strategy, tools ans tactics … I will tell you about the PRICE CHECK tactic. At its core, "Price Check" uses the information from commodity futures exchanges to gain a significant advantage in your physical (spot) market negotiations and inventory management. For many, direct involvement in futures contracts is out of reach but a "Price Check" using commodity futures data is an accessible and indispensable strategy. It tells what the global market is ‘expecting’ for prices, not just what they ‘are’ right now. How to Implement this strategy ? 1. Choose Your Data Source: Use reputable financial platforms (Investing.com Powered AgriCharts Barchart.com Inc CME Group , ICE Exchange websites). Many offer free delayed data or trial access to real-time quotes. 2. Focus on Relevant Contracts: Look at the futures contracts closest to your intended physical transaction date (e.g., if you're buying next month, check the "next month" futures contract). 3. Analyze Trends, Not Just Points: Don't just look at today's price. Observe the daily, weekly, and monthly trends of the futures contracts. Are they consistently rising or falling? What's the "spread" between different contract months? 4. Connect to Fundamentals: Always ask why prices are moving. Is it weather, crop reports, geopolitical events, demand shifts? Futures prices are a reflection of these underlying fundamentals. 5. Develop a "Market Sense": Over time, regularly checking futures will build your intuition about market direction and fair pricing. 6. Try to back test your strategy - use platforms like Vujis to see how others are pricing similar goods. Use this simple "Price Check" into your trading routine and see how differently you are able to close deals ! Have a great week! #CommodityTrading #FuturesMarkets #PriceDiscovery #TradingStrategy #MarketIntelligence #MidLevelTrader #Cocoa #Coffee