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.

5.3. Expectancy

E = p × W − (1 − p) × D

Where:

• p: probability that a trade is profitable.

• W: average profit on a winning trade.

• D: absolute value of the average loss on a losing trade.

For an accurate assessment of economic performance, W and D should be measured after costs, or costs should be deducted separately in the formula. If expectancy is negative over a sufficiently representative sample, the system is showing an unfavourable result under the assumptions measured. However, historical performance does not guarantee future results.

5.4. Maximum Drawdown

Maximum Drawdown (MDD) measures the largest decline in account value from a previous equity peak to a subsequent trough over a given period.

MDD = max_t [((Peak_t − Equity_t) / Peak_t) × 100%]

Here, Peak_t is the highest equity level recorded up to time t, while Equity_t is the account value at that time.

MDD helps assess the cumulative losses experienced by a trading system. It is particularly useful when comparing strategies with similar returns but different risk profiles.

5.5. Sharpe Ratio

The Sharpe Ratio measures excess return over the risk-free rate per unit of return volatility.

S = (R_p − R_f) / σ_p

Here, R_p is portfolio return, R_f is the corresponding risk-free rate, and σ_p is the standard deviation of portfolio returns. When calculating Sharpe, the data frequency, annualisation method, and return basis must be consistent. For leveraged CFD systems, Sharpe should be considered alongside MDD, margin utilisation, and tail risk rather than used in isolation.

5.6. Notional value and capital utilisation

Another metric is the margin utilisation ratio:

MU = (Used Margin / Equity) × 100%

This ratio indicates the share of account equity allocated to maintaining positions according to the platform's calculation method. High margin utilisation can reduce the account's ability to absorb adverse price movements and limit its capacity to open additional positions.

In addition to these metrics, CFD analysis should consider total notional exposure, concentration in each reference asset, correlations between positions, volatility, actual costs, and the possibility of liquidation under stressed market conditions.

6. CFD-Specific Risks

6.1. Market risk and price volatility

Reference-asset prices can move rapidly due to economic data releases, monetary-policy changes, geopolitical events, declining liquidity, or unexpected information. For leveraged positions, even a relatively small adverse move can cause a significant loss relative to margin capital. A stop-loss order does not eliminate risk entirely. During periods of high volatility or reduced liquidity, an order may be filled at a price different from the expected level.

6.2. Liquidity and execution risk

Liquidity affects spreads, market depth, and the ability to execute orders. When liquidity declines, execution costs may rise and fill prices may differ materially from the levels observed before an order was placed. For CFDs quoted through a platform, it is important to assess how the platform aggregates price data, its liquidity providers, execution rules, and procedures for handling abnormal price conditions.

6.3. Counterparty and platform risk

CFDs involve more than risk arising from movements in the reference asset. Participants also depend on the counterparty's ability to perform its contractual obligations, order-processing procedures, margin-management systems, and settlement mechanisms. Issues to assess include the service provider's legal status, the scope of regulatory supervision, complaint-handling mechanisms, segregation of client assets where required, procedures for insolvency, and the coverage of any compensation scheme. It should not be assumed that all CFD platforms provide the same protections.

6.4. Accumulating cost risk

A position may move in the predicted direction yet generate less net profit than expected because of spreads, commissions, financing costs, and slippage. When holding periods are long or trading frequency is high, the cumulative impact of costs must be incorporated into the performance model.

6.5. Behavioural risk

Leverage may increase the tendency to overtrade, increase position size after losses, or delay closing an adverse position. Such behaviours can cause actual risk to exceed the initially intended limits. Risk management should therefore include limits on position size, maximum loss, aggregate margin utilisation, and rules for evaluating after-cost performance. These measures can help control risk but cannot guarantee the avoidance of losses.

7. CFDs on Bitunix: Product Features and Service Model

7.1. Understanding CFDs on Bitunix

According to the CFD Service Agreement published by Bitunix, a CFD is a leveraged derivative instrument under which settlement is based on the difference between the reference asset's price when a position is opened and when it is closed, without requiring the actual transfer of ownership of the reference asset. The document also describes functions related to CFD accounts, order intake, margin management, position monitoring, and forced liquidation.

This agreement is a primary source for studying how Bitunix describes its service. However, the inclusion of a feature in a service agreement does not by itself establish that every feature is available in every country or to every user group. The legal entity providing the service, the scope of reference assets, and the applicable terms must be identified for each jurisdiction.

Refer to CFD information at Bitunix and related documents...

7.2. Service structure described in published documentation

One point to note is that a platform's CFD price does not necessarily match exactly the price displayed by an exchange or another data provider. Differences may arise from data sources, update timing, spreads, price-aggregation methods, and execution conditions. Therefore, execution quality should be assessed by comparing fill prices with an appropriate reference benchmark at the same time, while accounting for spreads, latency, and slippage. Execution quality cannot be established from a price chart or product description alone.

7.3. Leverage and margin requirements

Bitunix's CFD Service Agreement describes the use of margin, leverage, and forced-liquidation mechanisms. The document also lists indicative maximum leverage levels by asset class, while stating that the actual level depends on the product and the platform's configuration. The leverage levels in the document should not be interpreted as applying uniformly to all users, at all times, or in every jurisdiction. Before interpreting a specification, the effective terms, specific reference asset, account type, and relevant risk limits should be checked. From a financial perspective, leverage indicates only the relationship between notional value and margin capital under a particular calculation method. It does not fully describe actual risk without information about maintenance margin, liquidation thresholds, pricing methodology, financing costs, and order handling during periods of significant volatility.

7.4. Costs, pricing, and counterparty risk

The Bitunix CFD agreement refers to costs that may include transaction-processing fees, financing or overnight holding fees, deposit and withdrawal fees, and other fees under applicable terms. Specific fees should be verified against the current fee schedule and terms for the relevant product.

Another important issue is the trading-counterparty relationship. Under the agreement, the platform or a designated counterparty may act as the trading counterparty in certain CFD transactions. This is a factor to consider when assessing counterparty risk and dispute-resolution mechanisms.

Accordingly, an analysis of Bitunix's CFD service should focus on verifiable questions: which entity enters into the contract; which regulator has jurisdiction over that entity; how prices are determined; what rules govern order execution and cancellation; how margin and liquidation are calculated; what fees apply; how complaints are handled; and how assets are treated if an incident occurs. Raising these questions is neither an adverse finding nor a positive endorsement of the platform; it is a necessary due-diligence framework for a leveraged derivative product.

7.5. CFDs versus ownership of the underlying asset

CFDs should be distinguished from spot trading. In spot trading, a buyer may obtain ownership or control of an asset according to the market's rules and the applicable custody arrangement. In a CFD, the participant primarily has contractual rights and obligations under a derivative, with the outcome depending on the price difference.

This distinction matters for ownership, custody, settlement, counterparty risk, and dispute resolution. For example, a CFD position based on the price of Bitcoin does not automatically mean that the participant owns Bitcoin or can withdraw Bitcoin from that position.

Therefore, the name of the reference asset is not sufficient to determine the legal nature of the product. The contractual terms must be reviewed to identify the precise instrument being considered.

8. A Research Framework for Evaluating CFDs

To reduce reliance on impressions or marketing messages, a CFD study can be structured around five groups of criteria.

• First, product structure: identify the reference asset, contract unit, pricing method, settlement mechanism, trading hours, and position-closing conditions.

• Second, actual costs: collect spreads at different times, commissions, financing costs, slippage, and other adjustments. Costs should be analysed relative to notional value and holding period to support comparisons between products.

• Third, risk-adjusted performance: calculate net returns, Win Rate, Expectancy, Maximum Drawdown, and Sharpe using a consistent methodology and dataset. Historical backtesting results must be distinguished from live trading results, and potential data biases should be assessed.

• Fourth, resilience under adverse conditions: test scenarios involving sharp price moves, wider spreads, lower liquidity, delayed fills, and higher costs. The objective is to assess potential equity deterioration rather than measure performance only under normal market conditions.

• Fifth, legal and counterparty risk: verify the provider's status, the scope of its licences and supervision, contractual terms, dispute-resolution mechanisms, and the extent of customer protection. This is part of product due diligence and cannot be replaced by an assessment of interface design, popularity, or trading metrics.

9. Conclusion

CFDs are derivative instruments that provide exposure to price movements without necessarily requiring ownership of the underlying asset. This structure allows participants to express views in both market directions, but it also exposes them to significant risks involving leverage, margin, forced liquidation, trading costs, execution, and contractual counterparties. A systematic evaluation of CFDs requires looking beyond whether prices are expected to rise or fall. Variables such as notional value, margin ratio, break-even point, net profit, Expectancy, Maximum Drawdown, and Sharpe help describe performance and risk using quantitative criteria. However, no single metric can fully capture the risk of a derivative product.

For Bitunix, the published service agreement provides a basis for identifying several components of its CFD model, including pricing, order execution, margin management, and forced liquidation. Nevertheless, this information must be considered in the context of the specific terms, service provider, legal scope, and actual conditions applicable to each user. Describing a product is not equivalent to confirming its safety, suitability, or legal status in every country. From a financial research perspective, CFDs should be treated as contractual instruments with their own cost and risk structures, requiring due diligence based on data, calculation methods, contractual terms, and relevant law. This approach helps readers understand how CFDs operate and assess the issues that require clarification, rather than relying on promotional messages or assuming that the ability to trade necessarily provides a financial benefit.

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.

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