Read this in full before committing capital

This notice provides critical information regarding the risks associated with the systematic investment strategies managed by Algotoria Limited — the Algotoria Classic Diversified, Algotoria Classic Stable and Custom-Collateral profiles, and any successor strategy generations deployed under the firm's validation protocol.

1.General Investment Risk

Investing in digital assets and futures carries high levels of risk and may not be suitable for all investors.

• Potential for Total Loss: There is a significant chance of losing the entirety of your allocated assets.
• Prudent Allocation: It is recommended that investors do not allocate more than 10% of their total savings to these high-risk strategies.
• No Guarantees: Past performance, whether based on actual trading or historical backtesting, is not indicative of future results.
• No Compensation or Deposit-Protection Scheme: Client assets are not bank deposits and are not covered by any deposit-guarantee, investor-compensation or insurance scheme, in the British Virgin Islands or elsewhere.
• Fees Reduce Returns: Performance figures published by the firm are gross of fees unless stated otherwise; the quarterly performance fee reduces the returns an investor actually receives.
• Investment Horizon: The strategies are designed to be evaluated over a minimum one-year horizon; the probability estimates in Section 4 are stated over a three-year horizon. Short holding periods materially increase the chance of exiting inside a drawdown.

2.Digital Asset and Market Volatility

The strategies primarily involve “Virtual Assets” and perpetual futures, which are subject to extreme price volatility.

• Market Risk: Sudden and drastic price movements in virtual assets can lead to substantial losses in a short period, including gap moves through protective stop levels.
• Liquidity Risk: During periods of extreme market stress, certain instruments may become difficult to value or trade, potentially hindering execution and widening slippage beyond modelled levels.
• 24/7 Market Operations: Digital asset markets operate continuously. Rapid changes in account value can occur at any time, including weekends and holidays.
• Perpetual-Futures Mechanics: Perpetual futures carry instrument-specific risks: periodic funding payments (which may be a persistent cost), divergence between futures and spot prices, exchange-initiated liquidation of under-margined positions, and auto-deleveraging protocols that can close profitable positions without notice during extreme events.
• Adverse Regimes: The strategies' hardest environment is prolonged, wide, sideways (“choppy”) price action, in which trend-following systems incur repeated whipsaw losses. Extended choppy regimes have produced, and should be expected to produce, multi-month drawdowns.

3.Leverage and the Drawdown Budget

Algotoria utilises leverage to implement its strategies, which magnifies both potential gains and losses. Each account is configured to a risk tier expressed as a drawdown budget (previously referred to as the account's “target risk” or “risk setting”): 10%, 20% or 30% for Algotoria Classic Stable and 15%, 25% or 35% for Algotoria Classic Diversified.

• Leverage Limits: Depending on the selected risk tier, maximum leverage can reach up to 300% (×3.0) of the account value; typical average gross exposure at the full tier is 0.8–1.0×, scaled automatically and inversely to prevailing volatility.
• What the Budget Is: The drawdown budget is the maximum peak-to-trough decline of the account's gross value that the selected configuration is engineered to stay within, measured continuously against the account's own historical peak. It is an engineering envelope defended by the controls described below — not a prediction of typical losses and not a contractual guarantee.
• How It Is Defended — the automatic layer: The continuous, automatic risk reduction operates at the level of individual trades: position sizing scales down as volatility rises, and every trade carries stop-losses. These sizing and stop-loss rules may take the portfolio’s prevailing volatility and its drawdown against the budget into account. They run constantly and without human intervention.
• How the Budget Is Monitored — and what does not happen at these levels: An independent monitoring system measures drawdown against the budget continuously and alerts the operations centre and the trading team in real time at 60%, 80% and 100% of the budget. No drawdown-triggered reduction of exposure is implemented in the firm’s trading software, and none is applied by default. At two-thirds of the budget the Investment Committee reviews the account and decides case by case whether to reduce risk; continuing to trade at the selected budget is a legitimate outcome of that review. At the full budget the client is notified and elects whether to continue, to reduce the drawdown budget, or to stop trading — the firm does not make that election on the client’s behalf. Algotoria’s research has repeatedly tested drawdown- and regime-triggered de-risking and does not find that it improves the return-to-risk profile, because recovery tends to begin immediately after the worst of a drawdown. A client who requires an automated hard stop at a specified level should raise it at onboarding, so that it can be configured and evidenced for their account.
• What the Budget Is Not: Because nothing in the standard framework reduces exposure automatically as a drawdown deepens, the budget can be exceeded outright — see the probabilities in Section 4. Extreme price gaps, exchange or stablecoin failures, or other events outside the trading model can carry a drawdown well beyond it. The theoretical maximum loss remains 100% of allocated capital.
• Discretionary Risk Reduction: The Algotoria Investment Committee may reduce the strategy's operating risk below the selected budget on a discretionary basis in response to market conditions, and may subsequently restore it. Client accounts scale with such changes. During periods of reduced risk, realised returns should be expected to be proportionally lower than published targets and than the historical track record.
• Gross versus Net Basis: The budget and all firm risk limits are enforced on the gross trading-account curve, before performance fees. Settling performance fees from the trading account makes the realised net drawdown modestly deeper; funding fees externally keeps the two aligned.

4.Drawdown Expectations and Breach Probabilities

Realised experience. Typical annual gross drawdowns at the full budget are generally observed in the 20–25% range for Algotoria Classic Stable. Since the official track inception on 1 January 2024, the deepest gross drawdown of the Stable reference account has been −23.6%(first half of 2026) — inside its 30% budget; a comparable −23.5% episode in 2025 took approximately five months to recover; the worst calendar month was −14.4% (December 2025). The Algotoria Classic Diversified reference account — which additionally carries managed Bitcoin collateral exposure — has recorded a deepest gross drawdown of −27.4% in the same first-half-2026 regime, still open at approximately −27% as of 30 June 2026, inside its 35% budget. Clients should be financially and psychologically prepared for drawdowns of this magnitude and duration as a normal part of the strategies' operation.

Probability of exceeding given drawdown depths. To make the budgets concrete, the firm estimates the probability that an account at each product's full drawdown budget (30% Stable · 35% Diversified) experiences a gross drawdown exceeding a given depth at least once within a three-year investment horizon:

The median simulated worst drawdown over three years is ≈ −24% (Stable) and ≈ −29% (Diversified); one simulated path in ten reaches −35% / −41% or deeper respectively. Over a one-year horizon, the estimated probability of exceeding the full budget is ≈ 5% (Stable) and ≈ 6% (Diversified). Accounts at lower drawdown budgets experience proportionally shallower drawdowns — a 10% budget is one third of a 30% budget in exposure and in drawdown depth alike. Their probability of using the fullbudget is, however, marginally higher rather than lower, because percentage losses compound sub-linearly: a smaller book’s drawdown consumes a slightly larger share of a smaller budget.

Methodology and limitations. Estimates from a stationary block-bootstrap Monte Carlo simulation (50,000 three-year paths) of each strategy's live daily gross returns since inception, normalised to the account's current risk configuration, as of 30 June 2026. The simulation models no drawdown-triggered de-risking, because none is applied (Section 3). The figures above are therefore the unmitigated distribution, and they are the ones to plan against. For Algotoria Classic Diversified the estimate also does not model the collateral overlay introduced in 2026 — a systematic slow-trend rule that removes the strategy's Bitcoin collateral exposure in sustained downtrends — which is expected to reduce collateral-driven drawdowns relative to the historical configuration reflected in the data. These figures are statistical estimates, not limits or commitments: they assume future market behaviour statistically resembles the limited (2.5-year) live history, are measured on daily closing values (intraday drawdowns run slightly deeper), and exclude exchange-counterparty, stablecoin and operational tail events (Sections 5–6), which are additional sources of loss. The estimates are recalculated when the track record or risk configuration changes materially.

5.Operational and Technical Risks

The management of assets relies on proprietary technology and third-party infrastructure.

• API and Software Failure: Inherent risks exist regarding development failures, bugs, or technical errors in the Application Programming Interface (API) used for trade execution.
• Cybersecurity: Virtual assets and Virtual Asset Service Providers (VASPs) are frequent targets for fraud, market manipulation, and cybersecurity breaches. A compromise of exchange credentials or trading infrastructure could result in loss despite the firm's ISO 27001-aligned controls and trade-only API permissions.
• Infrastructure Reliability: Electronic communications may be delayed, intercepted, or fail due to internet instability or hardware malfunctions. Signal generation and execution depend on data-centre, market-data and connectivity providers.
• Key Personnel: The strategies depend on a small senior team for research, risk oversight and operations. The loss of key personnel could adversely affect the programme's management and development.
• Capacity: Strategy capacity is finite. Growth in assets under management may increase execution slippage; the firm monitors capacity and liquidity limits (Section 8) but capacity risk cannot be eliminated.

6.Third-Party Counterparty Risk

Client assets are held in Separately Managed Accounts (SMAs) with third-party VASPs (e.g., Binance, OKX, Bybit).

• VASP Insolvency: Assets held at an exchange are exposed to that exchange's insolvency, acts, or omissions. Algotoria is not liable for losses arising from the insolvency, acts, or omissions of any third-party exchange.
• Regulatory Intervention: Actions by competent authorities against a VASP may make it impossible for Algotoria to fulfil its management obligations or for the client to access assets.
• Stablecoin Depegging and Issuer Risk: The strategies managed by Algotoria may involve holding up to 100% of the portfolio assets in stablecoins, specifically approved stablecoins, including USDT, USDC, RLUSD, OKUSD and USDG, to serve as primary collateral or liquidity. These instruments are subject to “depegging” risk, where the stablecoin may lose its 1:1 value parity with the underlying fiat currency. Such a loss of peg can occur due to issuer insolvency, loss of underlying reserves, regulatory interventions, or technical failures in the coin's smart contract. In the event of an issuer default or a restriction on circulation, the market value of these assets may collapse, leading to a total loss of the capital held in these instruments regardless of the performance of the underlying trading algorithms.

7.Systematic, Model and Machine-Learning Risks

The strategies are 100% systematic and automated.

• Model Limitations: Strategy parameters are based on historical data. Future market regimes may differ significantly from the past, rendering the models less effective or unprofitable for extended periods.
• Backtest and Simulation Limitations: Backtested and simulated results have inherent limitations: they are constructed with the benefit of hindsight, are subject to parameter-selection and optimisation bias, and do not fully reflect the impact of live execution, liquidity and operational frictions. Live results routinely differ from — and may be materially worse than — simulated results. The firm's published probability estimates (Section 4) inherit these limitations.
• Algorithm Malfunction: Automated systems may fail to function as intended due to malfunctions in execution signals, software defects, or unforeseen interactions between sub-strategies.
• Machine-Learning Strategy Risk: Algotoria researches and may deploy machine-learning (neural-network) signal engines as successor strategy generations, following out-of-sample walk-forward validation, pre-registered forward-window gates, parallel shadow operation against the incumbent production strategy, and Investment Committee approval. Machine-learning models carry specific additional risks: their decision logic is less interpretable than deterministic rules; they may behave unexpectedly in market conditions unlike their training history; and periodic retraining changes model behaviour over time (model-refresh risk).
• Strategy Evolution and Transition Risk: The composition of the production portfolio is revised quarterly, and the firm may replace or blend the production strategy generation with a validated successor. Transitions may temporarily alter the return and correlation profile of client accounts. The drawdown-budget framework, its monitoring and its escalation arrangements (Section 3) apply unchanged across strategy generations.

8.Liquidity and Redemption Risk

• Portfolio Liquidity: The portfolio is algorithmically constrained so that it can be fully liquidated within 24 hours while consuming no more than 33% of the 30-day average daily volume of the underlying instruments. In extreme market stress, liquidation may nonetheless take longer or incur materially higher costs.
• Redemptions: There is no lock-in period; redemptions operate on a 5-day notice standard. Extraordinary market or exchange conditions (trading halts, withdrawal suspensions at a VASP) may delay the return of assets notwithstanding the notice standard.

9.Regulatory and Legal Risks

• Jurisdictional Restrictions: Participation is prohibited for residents or entities in “Restricted States” (see the firm's Prohibited Jurisdictions register, which is incorporated by reference).
• Professional Investor Requirement: These services are strictly for “professional investors” as defined under the laws of the British Virgin Islands and the client's local jurisdiction.
• Limited Regulatory Protections: Algotoria Limited is a BVI Approved Investment Manager under the Investment Business (Approved Managers) Regulations. This regime does not provide the investor protections associated with retail fund regulation; clients have no recourse to a statutory ombudsman or compensation scheme.
• Regulatory Change: The regulatory treatment of digital assets, stablecoins and derivatives is evolving rapidly (e.g., MiCA in the EU and equivalent regimes elsewhere). Future regulatory changes may restrict the firm's ability to operate the strategies, the client's ability to participate, or the availability of particular instruments or venues.
• Tax Responsibility: Clients bear sole responsibility for all tax liabilities and reporting requirements arising from trading activity.

10.Conflicts of Interest

• Performance-Fee Incentive: The firm is remunerated solely through a quarterly performance fee, which could incentivise risk-taking. This is mitigated by the rolling high-watermark (no fee until prior losses are recovered), the drawdown-budget framework, and Investment Committee oversight of all risk-profile decisions.
• Multiple Accounts: The firm manages multiple SMAs pari passu through automated proportional execution; residual timing and sizing differences between accounts may nonetheless occur.
• Policies: The firm maintains Board-approved Conflicts of Interest and Personal Dealing policies, available to clients on request.