We’ve always tried to give a balanced view when things are not set on stone since at the end of the day, everything is an opinion rather than a fact and if the opinion serves its purpose (educated decisions for the opinionated), then why not?

A discussion between a broker dealer and a client this morning regarding technical vs fundamental analysis piqued our interest and these discussions usually miss a critical part. That is the underlying reasons that drive the prices we see on charts, rather than the analysis itself. That’s because those reasons are liquid, yet the analysis process is always the same.

Most price charts available to the retail investor, show price, time, and volume. Indicators are layered on top or oscillate below. And although technical view is extremely important, there are structural elements of how markets function that influence price behaviour long before it becomes visible on a chart.

 

Price is the final output, not the input

A popular grounding approach to trading, is that no one can predict consistently and with 100% accuracy what the markets will do. Multiple reasons to outline here, but we’ll only mention the human element which in our view, is a catalyst when it comes to unpredictability. People operate via emotions and tend to act on those, even if the decision is what should be.

Evidently, a chart shows the result of trading, not the process. Before any candle forms, limit orders are placed or removed, liquidity gets deep or shallow, or limitations force certain participants to act (some when they should, some when they shouldn’t, more on this below).

By the time price behaviour actually updates and materializes on charts, these processes have already occurred.

So professional focus tends to search for the conditions that must exist for price to move the way it does.

 

Inventory and positioning (not sentiment)

Retail story telling often relies on “bullish” or “bearish” sentiments. Professionals, focus instead on who is already positioned.

Positioning refers to net exposure held by participants, a concentration of similar bets. When it gets concentrated, it gets crowded and we’ve heard a great statement by a chief dealer on this who said “moves often happen on position adjustments, not when they were initiated in the first place”.

 

Who is forced to trade (and who isn’t)

As mentioned above, limitations force certain participants to act. These limitations depending on the asset class (if asset-specific), can be margin requirements, redemptions, rebalancing schedules, compliance constraints, expiring contracts and so on.

What this means is that price is again irrelevant. Action will take place nonetheless, and it would be very challenging for a chart to predict and show these in real time, for retail traders to base their decisions on. Other than taking actions regardless of price, these participants create pressure without expressing directional opinion.

Therefore again, charts will show the result of the forced act, not the educated decision to position.

 

Liquidity conditions, maybe not volume

Another important point professionals look for is liquidity conditions. The order book depth is a good starting point, with the size available at each price level. Crowded or thin liquidity can speak wonders, much more than volume could potentially do. Any volatility spikes without reason (new information or other), fast moves on small flows, or sudden price gaps are a good indicator of thin liquidity.

 

Time based constraints

Another important point candles don’t explain, is time constraints related to time-in-force orders (TIF), expiration dates, settlement cycles, roll periods, reporting deadlines, funding resets etc.

The price shown on a chart (e.g., a 1-minute candlestick) is an aggregation of all trades that occurred during that minute. Individual trade prices, which might have varied due to latency or TIF constraints, are averaged or represented by the high/low/open/close of that candle, masking the micro-level price movements that occur in milliseconds.

When thinking TIF orders, you think day order, good-til-cancelled (GTC), fill-or-kill (FOK), immediate-or-cancel (IOC): Any portion of the order that can be filled immediately is, and the remainder is cancelled.

The effects of these constraints are primarily related to the difference between the intended price and the actual executed price (known as slippage). These factors influence the actual transaction price before it is ultimately recorded and displayed on a chart.

 

Funding rates, carry, and holding pressure

Funding, carry, and holding pressure create temporary price distortions and influence the spot and futures price relationship, through real-time supply and demand dynamics and financing costs. These pressures are a factor in the actual execution price, which is the data point that eventually forms the chart we analyze.

Funding rates are periodic payments between long and short position holders. The price adjustments happen within the market’s live order flow. When arbitrageurs (as an example) act on price discrepancies, they cause moves to help prices converge before they even appear on the chart.

The cost of carry includes interest costs for financing the positions, storage/insurance costs for physical commodities, subtracting any income generated by dividends or the convenience yield. Same with funding, traders act on discrepancies, adjusting the prices before appearing on a chart.

When a large volume of an asset is held by a few participants it creates potential for significant price fluctuations when those holders decide to trade. Buying or selling pressure drives prices up or down respectively. Think of a large, sudden order from a major holder clearing multiple price levels in the order book almost instantly. Maybe high-speed algorithms can react to such an event, but general market participants will only act after charts record it.

 

Using volatility as a behaviour alternator, and not how it “plots”.

It’s true that volatility is “plotted” through technical indicators, but this only reflects what has already happened. Volatility is often described as the “fear index”, it directly triggers psychological biases, drives impulsive decisions and overreactions to “noise”.

Technical indicators that “plot” volatility are primarily historical tools that summarize past behaviour. They tell you the market was volatile and lag in nature.

How to act on this? As an example, professionals in volatile times reduce position sizes and readjust to stay “in” the market. They also exploit irrational discounts, and purchase high quality assets when others dump them.

So think volatility plots as the “what”, and volatility behaviour as the “why”. Indicators Vs sentiment analysis, lagging Vs anticipatory data reactions.

 

Look at asset correlations under stress, not in smooth sailing

Asset correlations are very important, some might say the cornerstone of diversification. But unless the correlations are structural, something is bound to break during volatile conditions. Where historically asset relationships spoke the same language, under stress one speaks English and the other Finnish.

Temporary asset correlations behave differently, while structural ones reassert themselves (especially if they disconnected for a minute). Charts average these events and speak after the fact.

 

Who is providing liquidity right now

Are market makers active or defensive? Any changes in quoting behaviour? What about the spreads?

When liquidity providers become defensive, price becomes sensitive, there is an acceleration in fluctuations, and technical levels might lose relevance.

 

The difference between trading an instrument and trading a system

An instrument exists inside a clearing system, a margin system, a regulatory system and a funding system. Prices on charts might reflect changes and shifts, but don’t necessarily explain them. As rules change, as capital requirements change, these changes affect behaviour.

A lot of this information stays away from retail charts because it is contextual, qualitative and requires interpretation. Charts are great in providing a visual representation of what happened. But they are limited at showing everything else.

 

Final thoughts

Paying attention to structure and behaviour defines professional traders. Answering questions like who is acting, who is waiting, what limits the behaviour and where pressure accumulates, these are all forces that shape markets long before they appear in the candles of a chart.

*this article is provided for educational purposes only. It is not to be construed as investment advice and all visitors are encouraged to keep learning while understanding that trading is exciting but also carries unlimited risk. Lets all be responsible investors to make the most out of the experience.

Portfolio diversification, is probably the first (sometimes only) advice investors receive, to calibrate their thoughts towards risk mitigation.

The concept is sound (although not flawless), and relates to the chaotic behaviour of markets during different economic cycles, and how placing all your eggs in one basket can lock a portfolio in situations difficult to manage.

At the same time, when certain asset classes fall, others rise, allowing for cushions against drawdowns and a more balanced approach to investments.

A big part of diversification, falls in understanding how asset classes behave with one another, in different environments, to know what to expect. In other words, knowing the asset correlations.

 

What is correlation and what does it actually measure?

Correlation measures how similar, different assets move at any given time. Mathematically, they are displayed using binary numbering from -1 to 0 to 1.

Here’s how. A correlation of:

• +1 means two variables move perfectly together
• 0 means no measurable linear relationship
• –1 means they move in exact opposite directions

 

Two assets can show high correlation simply because they are reacting to the same external factor, or they are traded by the same participants, or they are funded the same way. The problem is that none of these reasons guarantee the relationship (correlation) will persist.

 

Therefore, correlation measures co-movement, but not causation. Not knowing what triggers the correlation, beats diversification principles at their own court because correlation is backward-looking, it is time-window dependent (more on this below), and most importantly it does not explain why assets move together.

 

Correlations are reliable until they aren’t. For that we need to understand the two correlation types. Structural and temporary. These are two concepts that are often commingled, but behave very differently under stress.

 

Structural correlations

These types of correlations are present by default. The “mechanics” behind them are anchoring the relationships allowing them to persist. Think of a stock index future and its underlying cash index. Think of a bond price and its yield, or a currency pair and its interest rate differential, or an ETF and the basket it must physically track.

 

There is no changing of the relationship between a bond price and its yield, because mechanically they are inversely connected. The bond has a fixed coupon (interest payment), so a lowering of the price will always raise its yield and vice versa. A cash index is meant to track the behaviour of its futures counterpart, so they will always move together because they were built to do so.

 

These designed relationships that persist across different economic environments, can only break if the structure (their design) changes, and even if there are periods of short-term dislocations, they will reassert themselves.

 

Temporary asset correlations

These types of asset correlations are not designed or structured in any way. They are organically caused by the prevailing conditions and sentiment, and they are present because they share these conditions. They are created and driven by risk on / risk off behaviour, central bank policies, positioning, leverage, narratives or economic environments (inflationary / deflationary).

 

Think of stocks and crypto moving together, or tech stocks and long duration bonds, or commodities and emerging markets equities, or different asset classes reacting the same way to monetary policies.

Everything mentioned above is situational and heavily depend on the current environment. They can appear strong and stable one day, and break abruptly the next. These are not embedded or engineered relationships like the structural ones.

 

Why temporary correlations feel so convincing

Temporary correlations can create a false sense of permanence. They often coincide with strong trends, clear narratives and high confidence environments that seem obvious even to the trained eye. Correctly so though, but the trained eye knows better than to take numbers -1, 0 and 1 for granted, without looking at the bigger picture.

 

The bigger picture involves economies that move in cycles, and these cycles have short-term debt cycles that are embedded in long-term debt cycles, external and internal partnerships / conflicts, all of which exist within developed or under-developed countries as well. A correlation number speaks, but not loud enough.

 

Temporary asset correlations may feel reliable because when many participants hold similar trades, price movements align, so they tend to reinforce their positioning. Also deleveraging, forces multiple assets to move together amplifying them through leverage. Lastly, narratives create coherence even when mechanics are absent, explaining the relationships by stories.

 

How asset correlations break

Asset correlations often increase during crises, then collapse afterward. Not set in stone, but there are two clearly defined reasonings to how asset correlations break.

 

An oversimplified example would be to think how markets move together under monetary policy expectations. Then inflation suddenly becomes the dominant constraint and assets once positively correlated begin diverging.

 

So the dominant force that drove the relationship, changed.

 

In the second reasoning we need to think stress scenarios where participants sell what they can, but not necessarily what they should. All investors try to reason and time their decisions, but emotional drivers are another factor of erratic behaviour. This shared activity spikes asset correlations toward 1 and structural differences are temporarily ignored.

 

So liquidity overrode logic, evidently changing the relationship.

 

The most overused case example: The relationship between stocks and bonds

For decades, stocks and bonds often showed negative correlation. How?

• Growth weakens; bonds rally due to their safer nature
• Growth strengthens; stocks rally due to their riskier but rewarding nature

This relationship felt structural, and gave rise to portfolio allocation percentages like the 60 / 40 (60% on stocks, 40% on bonds to maintain balance). But the relationship was anything but structural. It depended on stable inflation, central bank credibility through predictable policy reactions.

When inflation returned as a constraint in multiple occasions, both assets fell together and the correlation flipped. The structure of bonds did not change. The dominant macro variable did.

 

Asset correlations vs. dependency

Asset correlations do not capture the situation dependence. It captures linear movement, but markets often exhibit non-linear dependency. This is highly related to whether markets are calm or stressed. They might uncorrelated during calm times, then correlate during stressful times, and then decouple again. This is not a statistical error but a reflection of conditional behaviour.

Markets behave differently when volatility rises, when funding tightens, when margins increase, or when risk limits are hit. These important rolling windows are not captured in asset correlations that say more about recent conditions, than how strong and enduring the relationship is.

 

Structural relationships that survive stress

Structural asset correlations tend to reassert themselves even after breakdowns. As mentioned in their definition above, they are designed to behave in a mechanical way. Futures prices converge to meet spot at expiration. Irrespective of contango or backwardation conditions, the design is convergence. Other examples include arbitrage relationships enforced by balance sheets and hedged instruments tied by contractual obligations.

In contrast temporary asset correlations, often don’t return once broken.

This explains why diversification sometimes fails and a wider narrative should always accompany a narrow one. It explains why “safe” bets on relations reverse and why sometimes historical asset correlations disappoint. As investors we constantly interpret, we don’t predict.

 

How should we think of asset correlations?

Instead of asking whether two assets are correlated, a more informative question is what mechanism forces this relationship to exist in the first place.

Find the answer in between by examining the relationship’s design and if it follows the mechanical approach (by default, legal obligation, settlement, arbitrage), it makes it structural and hard to break.

If the answer is more abstract and relies on rolling windows (policy decisions, narratives, risk sentiment, positioning, economic environments), it makes it temporary and prone to break.

 

Final thought

Asset correlations is a description, not an explanation. Understanding why assets move together is more durable than measuring how much they have done so in the past.

*this article is provided for educational purposes only. It is not to be construed as investment advice and all visitors are encouraged to keep learning while understanding that trading is exciting but also carries unlimited risk. Lets all be responsible investors to make the most out of the experience.

8 powerful points outlining the dynamics between spot Vs futures prices.

What we’ll be covering:

1. Difference in timing
2. Impact of carry costs and convenience yield
3. Hedging vs. speculation
4. Price convergence (spot and futures)
5. Liquidity and trading strategy
6. Basis risk
7. Arbitrage opportunities
8. Influence of market news and events

 

A relatively innocent question from a junior dealer yesterday showed how necessary it is for all of us involved in the financial services, to understand how the markets work so we can serve our clients better.

The question related to whether the quotation on an asset provided to clients was derived from futures or spot liquidity and why the answer is important. It gave us a reason to outline 8 powerful points that outline their dynamic relationship, that reflects different aspects of the market. These aspects can influence trading decisions, risk management, and overall strategy.

 

Difference in timing

• Spot price: The spot price is the current market price for immediate delivery of the asset. It’s the price you would pay if you bought or sold the asset right now (on the spot). For example, if you’re trading the spot price of gold, it reflects the price you’d pay for physical delivery of gold today.
• Futures price: The futures price is the agreed-upon price for buying or selling the asset at a specified date in the future. Futures contracts allow traders to lock in a price today for a transaction that will take place later (often months down the line).

Why it matters: Traders need to understand this difference to manage timing risk. The spot price changes instantly based on current market conditions, while futures prices reflect expectations about where the market will go in the future. For traders holding positions over time, the futures price is more relevant, whereas spot price trading applies to immediate, short-term trades.

 

Impact of carry costs and convenience yield

Futures prices often incorporate inherent costs that can be expensive or cheap, causing the futures price to be higher or lower than the spot price, depending on whether the market is in contango (futures price is higher) or backwardation (futures price is lower).

• costs of carry (such as storage fees, financing costs, or dividends that will be paid in the future)
• convenience yield (for commodities, this is the benefit of holding the physical asset).

Why it matters: Traders need to understand these factors to assess whether the futures market is pricing in more expensive holding costs or is reflecting supply/demand imbalances that make future delivery more or less valuable than immediate delivery.

 

Hedging vs. speculation

• Hedging: Traders use futures prices to hedge against price fluctuations in the underlying asset. For example, a farmer might sell futures contracts for wheat to lock in a selling price for their crop months before harvest. The spot price doesn’t help with hedging because it reflects the current price of wheat, while the futures price locks in the price for future delivery.
• Speculation: Traders looking to speculate on price movements often trade futures contracts in hopes that they can profit from price changes. If they’re only looking for short-term movements, they may focus on the spot price.

Why it matters: Hedgers attempt to mitigate uncertainty seeking insurance against future price fluctuations by transferring the price risk to speculators. Speculators place bets to capture price swing opportunities adding liquidity volumes. Current spot and future prices reflect the market sentiment in real time, so being aware of where they both stand speaks volumes.

 

Price convergence (spot and futures)

Spot and future prices are always different. Under normal conditions, futures price is higher than spot known as contango, and at times they reverse known as backwardation.

But as a futures contract approaches its expiration date, the futures price tends to converge with the spot price. This process is known as convergence.

At expiration, the futures price and spot price should be nearly identical for the same asset.

Why it matters: The dynamics between futures and spot prices are in constant push-pull mode. Different economic environments (or seasons for agricultural contracts), can shock both prices. During convergence, prices might or might not behave as predicted (disconnection) yet its still a big element when trading either side.

 

Liquidity and trading strategy

• Spot Markets: In some cases, the spot market may have more liquidity, especially for highly traded assets like currencies and major commodities. Traders in the spot market typically aim for immediate price movements and often make quicker, short-term trades.
• Futures Markets: Futures contracts may offer greater liquidity for certain assets, especially for hedgers or speculators seeking to manage longer-term exposure or leverage.

Why it matters: Understanding whether you’re trading in the spot or futures market helps you design a trading strategy that matches the available liquidity, your time horizon, and the level of leverage you’re willing to take on.

 

Basis risk

This is the risk that arises from the difference between the spot price and futures price (called the “basis”). Traders who hedge with futures contracts face the risk that the futures price and the spot price may not move in perfect correlation. For example, a trader might sell a futures contract to hedge against a falling price, but if the futures price and spot price diverge unexpectedly, the hedge could be ineffective.

Why it matters: Traders need to understand how the basis works because the discrepancy between the spot and futures prices can affect their ability to properly hedge or make the most out of a position.

 

Arbitrage opportunities

Traders looking to exploit arbitrage opportunities rely on the price discrepancy between the spot and futures markets. If there’s a mismatch between the spot and futures prices (e.g., futures are priced too high or too low relative to the spot), arbitrage traders can execute strategies to ride the difference by buying the underpriced asset and selling the overpriced one.

Why it matters: Spot and futures prices can sometimes diverge significantly in markets with inefficiencies. Traders who are looking for arbitrage opportunities need to recognize when the price difference is large enough to make the trade profitable. For all the rest, large enough price differences signal arbitrage trading influx to be expected.

 

Influence of market news and events

• Spot Prices: Spot prices are directly affected by real-time market news such as supply disruptions, weather events, geopolitical news, that causes immediate price changes.
• Futures Prices: Futures prices reflect expectations about how news and events will affect future prices, which can lead to price movements based on predictions or forecasts.

Why it matters: Traders need to understand how to react to market-moving news based on whether they’re trading spot or futures prices. Spot price trading requires quick reactions to real-time events, while futures price trading may require more analysis and interpretation of future market expectations.

 

Our 20 year visibility in the space taught us that education is important, but without awareness it is not enough. Terms and definitions should be accompanied by an understanding of why things work, but also why they don’t. And although there is no consistent 100% accuracy in predicting what will happen next, everyday carries new lessons to be carried forward. Understanding spot vs futures dynamics is yet another important milestone in our trading travels.

*this article is provided for educational purposes only. It is not to be construed as investment advice and all visitors are encouraged to keep learning while understanding that trading is exciting but also carries unlimited risk. Lets all be responsible investors to make the most out of the experience.