APPENDIX

METHODOLOGY

A systematic research process built around repeatability.

Quantivix develops investment strategies through a structured quantitative research process designed to identify repeatable market behavior, test it across multiple environments, and translate validated observations into rules-based trading strategies.

Our research begins with historical market data and progresses through hypothesis development, quantitative testing, validation, robustness analysis, implementation review, and ongoing monitoring. Strategies are evaluated independently and as part of a broader portfolio framework.

Historical Data

Quantivix research may incorporate up to approximately 16 years of historical futures market data, depending on the instrument and availability of reliable historical records.

Testing may evaluate market behavior across multiple timeframes, including data ranging from approximately 1-hour bars down to 1-minute bars. Higher-frequency data may be used to study execution timing, intraday behavior, entry and exit precision, volatility, and market structure.

Historical testing is intended to expose strategies to a broad range of environments, including:

• Bull markets
• Bear markets
• Sideways and range-bound markets
• Low-volatility periods
• High-volatility periods
• Rapid market selloffs
• Recovery periods
• Changing interest-rate environments
• Macroeconomic uncertainty
• Periods of elevated market stress

The objective is not to identify rules that perform well only during one isolated period. The objective is to determine whether a strategy demonstrates repeatable behavior across materially different market conditions.

STRATEGY DEVELOPMENT PROCESS

1. Data Review

Historical price, volume, volatility, momentum, trend, and related market information are reviewed to identify recurring patterns and behaviors.

2. Hypothesis Formation

Potential trading ideas are translated into objective hypotheses that can be evaluated quantitatively.

3. Rule Definition

Entry conditions, exit conditions, timing rules, filters, risk parameters, and stand-aside conditions are expressed as systematic rules.

Where appropriate, indicators may be normalized using percentages, ratios, volatility measures, or other relative calculations so that a strategy can be evaluated across materially different market price levels.

4. Historical Testing

Strategies are tested across historical market data to evaluate:

• Profitability
• Win rate
• Average winning trade
• Average losing trade
• Profit factor
• Maximum drawdown
• Trade frequency
• Performance by calendar year
• Performance by month
• Performance by market regime
• Long-side performance
• Short-side performance
• Sensitivity to entry and exit timing
• Sensitivity to changes in parameters

5. Robustness Analysis

Quantivix seeks to determine whether a result appears dependent on a narrow combination of parameters or whether the underlying behavior remains observable when assumptions are modified.

Testing may include variations in:

• Entry timing
• Exit timing
• Indicator thresholds
• Holding periods
• Volatility filters
• Market-regime filters
• Trade direction
• Risk controls
• Data aggregation
• Historical test periods

A strategy that appears dependent on a single exact parameter combination may be treated as less robust than one that remains viable across a reasonable range of assumptions.

6. Regime Analysis

Markets do not behave uniformly through time.

Quantivix may classify historical periods according to characteristics such as trend, volatility, momentum, macro behavior, or other measurable market conditions.

Strategies may then be evaluated within specific historical market regimes to determine whether their behavior is consistent with the environment for which they were designed.

Some strategies may intentionally remain inactive when market conditions do not meet predefined requirements.

7. Walk-Forward and Out-of-Sample Review

Where appropriate, research may divide historical information into development and validation periods.

Rules developed using one period may be evaluated against later or otherwise separated historical periods to assess whether the strategy continues to behave as expected outside the period used to develop it.

8. Implementation Review

A strategy that survives research is reviewed for practical execution considerations including:

• Contract specifications
• Trading hours
• Liquidity
• Bid/ask spreads
• Slippage
• Order timing
• Futures contract rolls
• Data continuity
• Position sizing
• Market access
• Technology
• Brokerage execution

9. Live / Backtest Parity Review

Whenever possible, Quantivix compares strategy signals generated by the research environment with the signals generated by the intended trading platform.

The objective is to identify differences that may arise from:

• Bar construction
• Session definitions
• Futures contract rolls
• Data adjustments
• Indicator calculations
• Execution assumptions
• Incomplete versus completed bars
• Order timing
• Platform-specific behavior

A historical backtest is not considered equivalent to actual execution merely because identical strategy rules are used.

BACKTESTING

Historical results are research tools, not promises.

Backtesting allows Quantivix to evaluate how a defined strategy would have behaved if the same rules had been applied to historical market data.

Unless specifically identified as actual live trading results, all historical strategy results presented in Quantivix materials should be understood as hypothetical, simulated, modeled, or backtested performance.

Backtested results do not represent actual investor accounts.

Backtesting Assumptions

Depending on the specific strategy, a backtest may assume:

• Trades occur at specified historical prices.
• Orders can be executed when the strategy generates a signal.
• Historical market data accurately represents the relevant market.
• Contract values and futures specifications are correctly applied.
• Position sizing remains consistent with the test definition.
• Strategy rules are applied consistently throughout the historical period.
• Futures contracts are rolled or linked according to the methodology used in the test.
• Commissions, exchange fees, clearing costs, financing costs, market impact, and slippage may be modeled, estimated, or excluded depending on the specific test.

Whenever performance is presented, the applicable assumptions should be identified.

Gross Versus Net Results

Performance may be presented before or after estimated transaction costs, depending on the analysis.

Any presentation should clearly identify whether results are:

• Gross of fees and expenses
• Net of modeled trading costs
• Net of management fees
• Net of performance allocations
• Or otherwise adjusted

Actual investor returns may differ materially because actual fees, trading costs, capital flows, taxes, execution prices, and other expenses may differ from assumptions used in a model.

Futures Contract Rolls

Futures contracts expire and are periodically replaced by later-dated contracts.

Continuous futures series may therefore contain adjustments intended to create consistent historical data. Adjusted prices used for indicators or signal generation may differ from prices at which an actual futures contract could have been executed.

Where relevant, Quantivix seeks to distinguish between data used for signal generation and actual contract prices used for modeled execution.

Slippage and Market Impact

Historical models cannot perfectly replicate actual execution.

Actual trades may experience:

• Bid/ask spreads
• Slippage
• Partial fills
• Delayed execution
• Market impact
• Price gaps
• Reduced liquidity
• Exchange interruptions
• Platform delays
• Order rejection

These factors can materially reduce actual performance relative to a backtest.

Intrabar Assumptions

Backtests using hourly, minute, or other bar data may not know the precise sequence in which prices traded within each bar unless sufficiently granular data is available.

Results may therefore vary depending on whether entry, exit, stop, or other conditions are assumed to occur at the open, close, high, low, or another calculated value.

Look-Ahead Bias

Quantivix seeks to avoid using information that would not have been available at the time a historical trade decision would have been made.

However, errors in historical data, code, data alignment, roll methodology, or implementation may cause unintended forward-looking information to enter a model.

Backtests are reviewed with the goal of identifying and eliminating such effects, but no research process can guarantee that every modeling error has been identified.

Optimization and Overfitting

Strategies may be evaluated using multiple combinations of variables, thresholds, and timing rules.

Testing many alternatives increases the possibility that a strategy may appear successful because it was fit to historical noise rather than because it identified a durable market relationship.

Quantivix attempts to address this risk through robustness testing, parameter sensitivity analysis, out-of-sample evaluation, regime analysis, and practical execution review.

These procedures reduce but do not eliminate overfitting risk.

PERFORMANCE METRICS

Quantivix may evaluate strategies using metrics including:

Net Return

The cumulative gain or loss produced by the modeled strategy during the specified test period, subject to the assumptions stated with the analysis.

Win Rate

The percentage of completed trades that produced a positive modeled result.

Win rate alone does not measure the magnitude of gains or losses and should not be evaluated independently.

Average Win

The average modeled profit generated by profitable trades.

Average Loss

The average modeled loss generated by losing trades.

Profit Factor

Gross modeled profits divided by gross modeled losses.

Maximum Drawdown

The largest modeled peak-to-trough decline experienced during the test period.

Actual drawdowns may exceed historical or modeled drawdowns.

Trades Per Year

The historical average number of qualifying trades produced under the strategy rules.

Future trade frequency may be materially different.

Annualized Results

Where annualized or full-year-equivalent figures are presented, the calculation methodology should be disclosed.

A partial historical period should not be interpreted as an actual full-year result.

IMPORTANT PERFORMANCE DISCLOSURE

HYPOTHETICAL / SIMULATED PERFORMANCE

Performance results generated through backtesting or simulation are hypothetical and do not represent actual trading.

Hypothetical performance has inherent limitations. Simulated results may be prepared with the benefit of hindsight and cannot fully reflect the impact of actual financial risk, changing market liquidity, execution delays, slippage, transaction costs, investor behavior, or the ability to continue following a strategy during periods of loss.

No representation is made that any account, investor, fund, or strategy will achieve profits, losses, drawdowns, win rates, or other results similar to those shown.

Actual results may differ materially.

GENERAL INVESTMENT DISCLOSURES

Not an Offer

This presentation is provided solely for informational and discussion purposes.

It does not constitute an offer to sell, a solicitation of an offer to purchase, or a recommendation regarding any security, commodity interest, futures contract, investment fund, investment strategy, or other financial instrument.

Any offering of an interest in a Quantivix-managed fund would be made only through applicable definitive offering documents, subscription materials, governing agreements, and required disclosures.

In the event of any inconsistency between this presentation and definitive fund documents, the definitive fund documents will control.

No Guarantee of Returns

No investment strategy can guarantee profitability or prevent losses.

Targets, objectives, projections, examples, historical observations, backtests, scenarios, and other forward-looking information are not guarantees of future performance.

Past performance, whether actual or hypothetical, is not necessarily indicative of future results.

Risk of Loss

Investing involves substantial risk.

An investor could lose some or all of the capital invested.

Certain strategies may experience significant volatility, extended drawdowns, sudden losses, or periods in which no profitable opportunities are identified.

Investors should invest only capital they can afford to lose and should independently evaluate whether an investment is appropriate for their financial circumstances.

FUTURES TRADING RISK

Quantivix strategies may trade futures and other derivative instruments.

Futures trading involves a high degree of risk and may not be suitable for all investors.

Futures provide leveraged market exposure, meaning a relatively small movement in the underlying market may produce a disproportionately large gain or loss relative to the capital committed.

Losses may occur rapidly.

Depending on the structure, market conditions, and applicable account arrangements, losses may exceed amounts initially allocated to a particular position.

LEVERAGE RISK

Leverage magnifies both gains and losses.

Periods of elevated volatility may cause a leveraged position to lose value more rapidly than an unleveraged investment.

Risk controls are intended to manage exposure but cannot guarantee that losses will be limited to a predetermined amount.

LIQUIDITY RISK

Although Quantivix generally seeks to trade liquid futures markets, liquidity can deteriorate rapidly.

During periods of market stress:

• Bid/ask spreads may widen.
• Market depth may decline.
• Orders may execute at materially different prices than expected.
• Trading may be interrupted.
• Positions may become difficult to exit efficiently.

VOLATILITY RISK

Market volatility may increase suddenly as a result of economic announcements, geopolitical events, monetary policy changes, earnings, regulatory actions, exchange disruptions, or other events.

Volatility can create opportunity but can also materially increase losses, slippage, and execution uncertainty.

GAP RISK

Futures markets may move sharply between successive trades or trading sessions.

Stop orders and other risk controls do not guarantee execution at a specified price.

A position may therefore experience a loss materially larger than expected.

SYSTEMATIC STRATEGY RISK

Rules-based trading systems depend on the continued relevance of the relationships identified during research.

Market behavior can change.

A pattern that existed historically may weaken, disappear, or reverse.

A strategy may therefore experience losses even if it previously demonstrated strong historical performance.

MODEL RISK

Quantivix uses quantitative models, technical indicators, algorithms, data analysis, and systematic rules.

Models are simplifications of financial markets.

They may contain incorrect assumptions, coding errors, incomplete information, statistical weaknesses, data errors, or relationships that fail under future conditions.

Human review and validation reduce but do not eliminate model risk.

ARTIFICIAL INTELLIGENCE AND TECHNOLOGY RISK

Quantivix may use artificial intelligence, machine learning, automated analysis, software systems, and other technological tools as part of its research and operating process.

These tools may:

• Produce incorrect outputs.
• Misinterpret data.
• Fail to identify relevant information.
• Overfit historical relationships.
• Experience software failures.
• Depend on third-party infrastructure.
• Become unavailable.
• Produce results that require human interpretation.

Artificial intelligence is a research tool and does not eliminate investment risk.

DATA RISK

Research and trading decisions depend on market and reference data supplied by exchanges, brokers, vendors, platforms, and other third parties.

Data may be:

• Incorrect
• Delayed
• Incomplete
• Misaligned
• Adjusted incorrectly
• Subject to vendor methodology changes
• Temporarily unavailable

Errors in data may affect research conclusions, strategy signals, execution, valuation, or reporting.

TECHNOLOGY AND OPERATIONAL RISK

Trading and fund operations depend on technology.

Potential risks include:

• Internet outages
• Hardware failure
• Software errors
• Cloud-service interruptions
• Brokerage outages
• Exchange disruptions
• Cybersecurity incidents
• Data corruption
• API failures
• Order-routing failures
• Human operational errors

Business continuity measures may reduce but cannot eliminate these risks.

CYBERSECURITY RISK

Quantivix, investors, administrators, custodians, brokers, and service providers may be exposed to cybersecurity threats.

Unauthorized access, fraud, ransomware, data theft, phishing, system compromise, or other cyber incidents could cause financial loss, operational disruption, or disclosure of confidential information.

COUNTERPARTY RISK

The fund may rely on futures commission merchants, brokers, custodians, banks, administrators, technology providers, exchanges, and other counterparties.

A counterparty’s failure, insolvency, operational disruption, or inability to perform could negatively affect the fund.

EXCHANGE AND REGULATORY RISK

Futures exchanges, regulators, clearing organizations, governments, and other authorities may change:

• Margin requirements
• Position limits
• Trading hours
• Contract specifications
• Tax rules
• Reporting requirements
• Market-access requirements
• Trading restrictions

Such changes may materially affect a strategy.

CONCENTRATION RISK

A fund or strategy may concentrate exposure in a limited number of markets, trading systems, strategies, or time periods.

Concentration can increase the impact of adverse movements in any single market or strategy.

Diversification does not guarantee against loss.

CORRELATION RISK

Strategies or markets that historically behaved differently may become highly correlated during periods of financial stress.

Portfolio diversification may therefore provide less protection than expected during severe market events.

SHORT-SALE / SHORT FUTURES RISK

Strategies may establish short exposure.

Short positions can experience losses when markets rise.

In some circumstances, losses on short exposure may be substantial and theoretically unlimited.

MARKET REGIME RISK

Quantivix may use market-regime classifications or filters to determine when strategies should trade.

Market regimes are model-based classifications, not objectively observable facts.

A regime may be identified incorrectly, transition unexpectedly, or behave differently from prior historical examples.

STAND-ASIDE RISK

Some Quantivix strategies may remain out of the market when predefined conditions are not satisfied.

As a result, the strategy may miss profitable market movements.

Avoiding a trade can reduce certain risks but can also create opportunity cost.

CAPACITY RISK

Strategy performance may change as capital under management increases.

Larger position sizes may experience increased market impact, execution difficulty, or reduced ability to enter and exit positions at modeled prices.

Historical results generated using smaller modeled position sizes may not reflect results achievable at larger scale.

INVESTOR LIQUIDITY

Investor contributions and withdrawals are subject to the governing documents of the applicable fund.

Descriptions of quarterly contribution or withdrawal windows in marketing materials are summaries only and should not be interpreted as unconditional redemption rights.

Actual timing, notice requirements, restrictions, gates, suspensions, reserves, and other terms will be governed by definitive fund documents.

OWNERSHIP PERCENTAGES

Investor ownership percentages may change as investors contribute or withdraw capital.

Any illustrations describing ownership percentages, quarterly reallocation, or capitalization are examples only.

Actual ownership calculations will be determined pursuant to the applicable fund governing documents, accounting methodology, valuations, capital activity, expenses, and allocation provisions.

FEES AND EXPENSES

Investors may bear management fees, performance allocations, brokerage expenses, exchange fees, clearing costs, administration expenses, legal expenses, audit expenses, tax expenses, technology costs, and other fund expenses.

Any description of a “2 and 20” arrangement, conditional management fee, or other fee policy is a summary only.

The definitive offering and governing documents will determine the actual calculation, timing, conditions, and allocation of fees and expenses.

Fees and expenses reduce investor returns.

TAX CONSIDERATIONS

Investments may have significant federal, state, local, and international tax consequences.

Tax treatment depends on an investor’s individual circumstances and may change.

Quantivix does not provide tax advice through this presentation.

Prospective investors should consult their own tax advisers.

LEGAL AND REGULATORY CONSIDERATIONS

Investment structures, trading activities, investor eligibility, offering exemptions, adviser registration requirements, commodity-pool requirements, disclosure requirements, and other regulatory obligations may vary depending on the final structure and activities of each fund and management entity.

Nothing in this presentation should be interpreted as legal advice.

Applicable offering materials and disclosures should be reviewed by qualified legal and regulatory counsel before use.

VALUATION RISK

Fund values and investor ownership interests depend on valuation procedures.

While exchange-traded futures generally have observable market prices, valuation differences may arise because of timing, open positions, accrued expenses, pending transactions, market closures, data errors, or other circumstances.

FORWARD-LOOKING STATEMENTS

This presentation may contain forward-looking statements, expectations, goals, projections, market views, estimates, and other statements regarding future events.

Forward-looking statements are inherently uncertain.

Actual events and results may differ materially due to market conditions, economic developments, strategy performance, regulatory changes, operational events, and numerous other factors.

THIRD-PARTY INFORMATION

Certain information may be obtained from exchanges, financial-data providers, brokers, research providers, governmental sources, or other third parties believed to be reliable.

Quantivix does not guarantee that third-party information is complete, current, or error-free.

NO RELIANCE

Prospective investors should conduct their own independent investigation and due diligence.

No investor should rely solely on this presentation when making an investment decision.

An investment decision should be based on definitive offering documents, applicable risk disclosures, the investor’s own financial circumstances, and advice from the investor’s legal, tax, accounting, and financial advisers.

CONFIDENTIALITY

This presentation may contain proprietary Quantivix research, strategy concepts, methodologies, models, processes, intellectual property, and confidential business information.

It may not be copied, reproduced, distributed, published, or disclosed to another person without authorization from Quantivix Capital Management.

FINAL DISCLAIMER

Any performance statistics, backtests, simulations, models, illustrations, scenarios, hypothetical portfolios, or strategy examples contained in this presentation are provided for informational purposes only.

They should not be interpreted as a guarantee, forecast, promise, or representation of future investment performance.

Actual investment results may be materially different and may result in substantial loss.