On-chain analysis week 42/2026: Short-term BTC investors have not yet returned to the market

Analyst Research Team

Group On-chain HCCVenture

1. Overview of Contracts for Difference (CFDs)

1.1. What is a CFD?

CFD, short for Contract for Difference, is a derivative contract under which the parties establish a settlement obligation based on the difference in the value of a reference asset between two points in time. Under a typical CFD structure, participants do not need to own the underlying asset directly; instead, they incur gains or losses based on changes in the reference asset's price, depending on the direction of the trade and the contract terms. For example, if a CFD contract is opened at USD 2,000 and closed at USD 2,050, a long position will gain from the price increase, while a short position will incur a loss, before related costs are taken into account. The actual profit or loss depends on the contract size, number of units or lots, conversion factor, and settlement terms.

According to the approach presented in DNSE's educational material, CFDs provide exposure to price movements across multiple asset classes without requiring direct ownership of those assets. However, the general concept of a CFD must be distinguished from each specific product offered by a platform, as terms relating to pricing, margin, trading counterparties, and settlement may differ.

1.2. The economic nature of CFDs

In essence, a CFD is a derivative agreement whose value depends on movements in a reference asset. Participants do not necessarily receive shares, physical gold, foreign currency, or digital assets when opening a position. Instead, the financial outcome is determined through the contract's calculation and settlement mechanism.

CFDs have three important economic characteristics.

• First, the contract value depends on the reference asset. Changes in the reference asset directly affect a position's profit or loss, but the execution price on a platform may differ from prices observed in other markets.

• Second, trading may involve margin and leverage. An investor needs to provide only a portion of the position's notional value as margin, while profit or loss is calculated on the contract size under the applicable terms.

• Third, rights and obligations depend on the agreement with the provider. Terms governing reference prices, fees, trading hours, overnight adjustments, position closure, and liquidation can materially affect the final outcome.

CFDs should therefore not be viewed simply as a streamlined way of buying and selling assets. They are derivative contractual relationships in which market risk coexists with counterparty risk, execution risk, and platform operational risk.

1.3. Common reference-asset classes

CFDs may be structured around a range of asset classes:

The list above describes asset classes commonly used as reference assets

in the CFD industry; it does not mean that every platform offers all of these products. Nor does the use of an asset as a reference mean that participants own that asset or enjoy the legal rights associated with direct ownership.

2. How CFDs Operate

2.1. Long and short positions

CFDs generally support two position directions:

• Long position: profitable when the closing price is higher than the opening price, provided that the gain exceeds related costs.

• Short position: profitable when the closing price is lower than the opening price, provided that the gain exceeds related costs.

Illustrative example: A long position equivalent to 10 units of an asset is opened at USD 100 and closed at USD 105. If the conversion multiplier is 1 per unit, gross profit is calculated as the price change multiplied by the position size and the conversion multiplier:

(105 − 100) × 10 = USD 50

If total opening and closing costs are USD 4, net profit before other adjustments is USD 46. If the price falls from USD 100 to USD 95, the same position records a gross loss of USD 50.

This example is intended only to illustrate the calculation method; it is not a quote or a specification for any particular CFD product.

2.3. Bid price, Ask price, and spread

In CFD trading, a platform may display Bid and Ask prices:

• Bid: the price quoted by the provider at which it will buy from the trader.

• Ask: the price quoted by the provider at which it will sell to the trader.

• Spread: the difference between the Ask and Bid prices.

Definition: The spread is the amount by which the Ask price exceeds the Bid price and is one of the trading costs that may affect the net result.

Spread = Ask − Bid

If EUR/USD has a Bid of 1.1000 and an Ask of 1.1002, the spread is 0.0002, equivalent to 2 pips under the usual convention for this currency pair. The spread is an economic component of trading costs. For a long position, opening at the Ask and closing at the Bid may create an initial loss even if the reference price has not moved. Actual costs may also include commissions, overnight financing, slippage, and other adjustments.

Therefore, a CFD product should not be compared solely on the basis of a spread advertised at a single point in time. Spread conditions during both normal and volatile markets should be assessed, along with total costs over the position's entire life cycle.

3. Financial Leverage and Margin Mechanisms

3.1. What is leverage?

Financial leverage expresses the relationship between a position's notional value and the capital used as margin.

Definition: The leverage ratio indicates how many times the position's notional value is larger than the margin allocated to it.

L = V / E_m

Where:

• L: leverage ratio.

• V: notional value of the position.

• E_m: margin allocated to open or maintain the position under the applicable rules.

If a position has a notional value of USD 10,000 and requires USD 1,000 in margin, the corresponding leverage is 10 times, or 1:10. Leverage does not directly change the reference asset's price volatility. It increases the account's exposure to price movements relative to the margin used. As a result, even a small price change can cause a large change in the return on the margin capital.

3.2. Initial margin

Initial Margin (IM) is the amount required to open a position under the contract terms.

In a simplified model, initial margin is calculated by dividing the position's notional value by the leverage ratio.

IM = V / L

For a Forex product with a defined contract size, the formula may be implemented as follows. Definition: This version estimates the notional value from the conversion price, contract size, and number of lots, then divides that value by the leverage ratio to estimate the required initial margin.

IM = (P × C × N) / L

Here, P is the conversion price, C is the contract size, N is the number of lots, and L is leverage. This formula applies directly only when all quantities are converted into the same currency and the contract structure is compatible with the calculation. Initial margin is not the maximum possible loss on a trade. Losses can reduce the remaining account equity, trigger a margin call, or lead to forced position closure under the applicable terms.

3.3. Maintenance margin and forced liquidation

Maintenance Margin is the minimum equity required to keep a position open. If account equity falls below the threshold, or the margin ratio breaches the applicable risk-management rules, the platform may request additional margin or carry out forced liquidation.

One commonly used metric is the margin level. Definition: The margin level expresses account equity as a percentage of the required maintenance margin and can be used to monitor how much equity is available relative to the maintenance requirement.

Margin Level = (Equity / Maintenance Margin) × 100%

Equity is the account's current equity value after accounting for unrealized gains and losses and any applicable adjustments. The formula above is a general representation. Some platforms use different definitions, warning thresholds, and liquidation mechanisms. The exact liquidation price therefore cannot be inferred from the leverage ratio alone.

3.4. Example of the impact of leverage

Assume a position has a notional value of USD 10,000 and initial margin of USD 1,000. If the position value moves adversely by 2%, ignoring fees, the loss is equivalent to USD 200. Definition: Return on margin measures the profit or loss as a percentage of the margin initially allocated to the position.

Return on margin = (−200 / 1,000) × 100% = −20%

In this example, an adverse 2% move in the position's value corresponds to a 20% decline in the initial margin. If the market continues to move against the position, the remaining equity may deteriorate faster than expected.

This illustrates why the percentage change in the reference asset must be distinguished from the return or loss on margin capital. These metrics use different denominators and reflect different aspects of risk.

4. Trading Costs and Net Profit

4.1. Cost components

CFD trading costs may include:

• Spread: the difference between Bid and Ask prices.

• Trading commission: a fee charged based on notional value, volume, or number of trades, where applicable.

• Overnight financing: an adjustment that may arise when a position is held beyond a specified time.

• Contract-specific fees or adjustments: potentially related to trading schedules, holidays, reference assets, or product mechanics.

• Slippage: the difference between the expected execution price and the actual fill price.

• Currency-conversion and deposit/withdrawal costs: where applicable, depending on payment methods and terms.

Not every product applies all of the costs listed above. A low fee in one category is not sufficient to conclude that total trading costs are low.

4.2. Net profit formula

P&L_net = P&L_gross − C_total

Here, C_total is the total trading cost and related adjustments for the evaluation period.

For an economic performance assessment, costs must be measured on a basis consistent with gross profit. For example, when analysing a position held over several days, ignoring overnight financing may materially distort the result. Similarly, for high-frequency trading, accumulated spreads and commissions can become decisive factors in net profitability.

4.3. Break-even point

The break-even point is the price or price movement required to offset costs and bring the net result to approximately zero.

For a linear long position, if total costs expressed in money are C, and the position's monetary value per unit of price movement is Q × M, the minimum price increase required to break even can be estimated as:

ΔP_BE = C / (Q × M)

The formula assumes that all costs have been converted into the same currency and do not change with price. If fees depend on notional value, holding period, or market volatility, the break-even point must be recalculated under the specific conditions. Break-even is useful when comparing fee structures, but it does not indicate whether the market is likely to reach that price in practice.

5. Financial Metrics for Evaluating CFD Performance

A CFD trading system should not be assessed solely by its win rate. A system with a high win rate can still lose money if its average loss is substantially larger than its average gain. Conversely, a system with a lower win rate may produce a positive result if its profit-to-risk ratio is managed effectively.

5.1. Win Rate

WR = (N_w / N) × 100%

Here, N_w is the number of net-profitable trades and N is the total number of closed trades during the evaluation period. When calculating Win Rate, it is important to specify whether profit is measured before or after fees. For assessing actual performance, net profit after costs is generally more meaningful.

5.2. Reward-to-Risk Ratio

RR = Target Profit / Expected Loss

In practical analysis, this ratio is often estimated by dividing the target profit by the expected loss under a trading plan. It is a trade-design ratio, not a guarantee that realised profits and losses will exactly match the specified levels.

Considering the entire data series, Bitcoin transitioned from a deep decline at the end of 2022 to a valuation expansion phase in 2024-2025, followed by a correction in 2026. The 2022 bottom was recorded around $15,000-$16,000, while the 2025 cycle peak reached approximately $120,000-$125,000. At the end of the chart, the price hovered around $80,000-$85,000, significantly lower than the peak but still much higher than the base price of the preceding decline cycle.

February 28, 2026, marked a Geopolitical Shock for the market, and after this point, the price of BTC continued to fluctuate sharply, while the geopolitical divergence zone shifted closer to zero at the end of the data series. Compared to the deep negative zone of approximately -60% to -65% during the 2022 bottom, the current divergence has narrowed significantly. This reflects a shift in the indicator pattern, but does not mean that geopolitical risk has disappeared or that the market has fully absorbed the macroeconomic shocks.

The narrowing of the geopolitical deviation from deep negative to near zero indicates that the pattern indicator has returned to a state close to the reference line. If the price continues to remain above the realized price level and market demand improves, the pricing structure will have a more stable basis. Conversely, if the price falls rapidly to the Realized Price zone while demand weakens, the risk of a deeper correction will increase.

The Bitcoin Spot Volume Bubble Map shows that spot trading activity has undergone several cycles of transition between neutral, cooling, increasing intensity, and overheating states since 2017. Overheated clusters often appear during significant acceleration phases, while neutral or cooling states predominate during many corrective phases.

Currently, prices are significantly lower than their 2025 peak, while trading activity is mostly neutral or cooling down. This structure doesn't show signs of widespread trading euphoria as classified by the model. However, a less heated state doesn't necessarily mean Bitcoin's valuation is low, as valuation also depends on the base cost, unrealized profits, new demand, and macroeconomic liquidity conditions.

In the next phase, if the price of BTC increases along with a sustained expansion of spot volume and trading sentiment gradually shifts from neutral to heated, it would reinforce the view that market participation is increasing, the market is not yet showing signs of prolonged overheating as in the pattern, but there is not enough basis to confirm that spot demand is recovering strongly or that pricing has become attractive.

Capital allocation to spot Bitcoin ETFs can remain strong during periods when BTC is trading at high valuations; demand for ETF investment doesn't necessarily only appear when prices fall to low levels. In an uptrend, investors may continue to increase their exposure to BTC as prices break through previous thresholds, especially if long-term expectations and asset accessibility improve.

IBIT has been a prominent contributor to positive capital inflows at high price levels, while GBTC has shown clear outflow pressure in some areas. This suggests the need to analyze ETF capital flows by product and on a consolidated basis, rather than using a single fund as a representative of all institutional investment needs.

The differentiation among funds is significant for assessing institutional investment needs. Observing only the outflow of capital from GBTC might underestimate the extent to which capital is shifting to other ETFs. Conversely, focusing solely on the positive columns of IBIT might overlook outflows from other products. A more appropriate measure for assessing the overall impact is the consolidated net inflow of all spot Bitcoin ETFs, after accounting for both inflows and outflows from each fund.

Assessment and Conclusion

Bitcoin entered a correction phase in late October 2026 after failing to maintain its earlier expected upward momentum, at one point breaking below $80,000 and triggering a wave of leveraged position liquidations. This development reflects a weakening of short-term bullish momentum, especially as the market simultaneously faces uncertainty regarding US monetary policy, inflationary pressure from energy prices, and a decline in risk appetite in financial markets. However, to assess the valuation outlook, price movements need to be considered alongside on-chain indicators of demand, realized profits, supply structure, mining activity, and institutional capital flows.

The Bitcoin MVRV Ratio Z-Score on the historical chart is currently significantly lower than the peak valuation levels of previous bull cycles. This suggests the market has not yet exhibited the same extreme valuation states as the periods of strong euphoria in the past. Simultaneously, the Percent Supply in Profit is around 68.8%, higher than the historical low of 40-45% but still lower than the 90-100% levels seen during periods of rapid market growth.

The key drawback lies in the quality and continuity of demand. The Bitcoin Price and Apparent Demand 30-day Change indicator remains largely in negative territory at the end of the chart, implying that apparent demand has not recovered strongly enough to sustainably absorb supply. Meanwhile, the SOPR is around 0.999, close to the break-even point of 1.0, suggesting that the BTC being spent is realizing near-zero overall returns.

Regarding investor behavior, the Long-Term Holder Activity Levels (using a 30-day CDD) indicator records historical spikes, including periods of strong price increases and periods of high volatility. ETF data should be evaluated in a similar light. The spot ETF flow chart by price range shows significant differences between IBIT, FBTC, ARKB, and GBTC, with IBIT exhibiting large positive flow columns at some high price levels, while GBTC records significant negative columns at some lower price levels.

Finally, the Fed's decision on October 27-28 will influence interest rate expectations and risk appetite, but Bitcoin's reaction will depend on policy guidance and inflation developments, particularly energy prices. At the on-chain level, positive signals need to come from a sustained recovery in apparent demand, SOPR remaining above the break-even point, and positive net ETF inflows confirmed by actual data. If these conditions occur simultaneously, the market will have a stronger basis to shift from rebalancing to a valuation recovery.

Disclaimer

This report was prepared by HCCVenture Research with the aim of providing information, research, and market analysis. The entire content of the report is based on publicly available data, on-chain data, market data, venture capital (Venture Capital) data, macroeconomic data, and HCCVenture's internal research methodologies at the time of publication. Data sources are compiled from numerous reputable research platforms and organizations, including but not limited to Glassnode, CoinGecko, TradingView, Dune Analytics, CoinGlass, CryptoRank, RootData, PitchBook, DefiLlama, CryptoQuant, Messari, Token Terminal, Artemis, CoinMarketCap , public blockchain data, reports from financial institutions, investment funds, blockchain companies, and other publicly available information sources. HCCVenture strives to select reliable data sources and applies a verification and cross-checking process throughout its research. However, HCCVenture does not guarantee the completeness, accuracy, timeliness, or error-free nature of all data due to differences in statistical methods, data collection scope, update times, or adjustments from data providers.

All opinions, assessments, valuation models, cyclical analysis, on-chain data, capital flow analysis, Venture Capital activity, ETFs, Digital Asset Treasury Companies (DATs), technical indicators, macroeconomic indicators, and scenarios presented in this report reflect only the research views of HCCVenture Research at the time of publication, based on available assumptions and data. These contents are not investment advice, financial advice, legal advice, accounting advice, tax advice, brokerage advice, portfolio management advice, or recommendations to buy, sell, or hold any digital asset, security, financial product, investment fund, blockchain protocol, or business. The digital asset and blockchain markets are highly volatile and are influenced by global liquidity, monetary policy, regulatory regulations, macroeconomic conditions, and many other unpredictable factors. Therefore, the trends, patterns, correlations, or historical cycles mentioned in this report are not guaranteed to repeat in the future and should not be considered reliable predictions of market developments. Readers should conduct their own independent research ( DYOR – Do Your Own Research ) and consult with qualified financial, legal, tax, or investment professionals before making any decisions. Any investment decisions or actions arising from the use of information in this report are the sole responsibility of the reader.

HCCVenture, its affiliates, research team, personnel, or related parties may own or will own digital assets, invest in blockchain projects, investment funds, technology companies, or maintain commercial, research, media, consulting, or collaborative relationships with the organizations, protocols, businesses, or platforms mentioned in this report. These relationships may create actual or potential conflicts of interest, although HCCVenture always applies internal research standards to maintain objectivity and independence in its analysis. Nothing in this report is construed as an offering, brokerage, promotion, fundraising, or provision of investment services as regulated by any country or territory. The entire content of this report is protected under intellectual property and copyright law. It is strictly prohibited to copy, modify, reproduce, distribute, or use all or part of this report for commercial purposes in any form without the written consent of HCCVenture. Accessing, using, or quoting this report signifies that the reader has understood, accepted, and agreed to the entire content of this disclaimer.

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