Risk Disclosure Statement

1. Market Risk

Algorithmic trading is subject to the same market risks as any other form of trading. Market conditions can change rapidly and unpredictably, leading to significant fluctuations in asset prices. Past performance is not indicative of future results.

2. Technology Risk

Algo trading relies on complex software and hardware systems. Technical failures, including software bugs, hardware malfunctions, and connectivity issues, can occur and may result in the inability to execute trades at desired prices or times, potentially leading to financial losses.

3. Model Risk

The performance of algo trading strategies is based on mathematical models and historical data. These models may not accurately predict future market behavior, and their effectiveness can degrade over time. Changes in market conditions, unforeseen events, and inaccuracies in the data used can adversely impact trading outcomes.

4. Execution Risk

There is no guarantee that orders generated by our trading algorithms will be executed at the desired prices. Slippage, latency, and other factors can lead to discrepancies between expected and actual trade execution prices, potentially resulting in losses.

5. Liquidity Risk

Certain markets or assets may have limited liquidity, making it difficult to enter or exit positions without significantly impacting prices. This can increase the risk of losses, especially in volatile or illiquid market conditions.

6. Leverage Risk

Using leverage can amplify both gains and losses. While leverage can enhance potential returns, it also increases the risk of substantial losses. It is important to understand the implications of leverage and manage it carefully.

7. Regulatory Risk

Algorithmic trading is subject to regulatory oversight, which can change over time. New regulations or changes to existing regulations may impact the ability to execute certain trading strategies or require changes to our systems and processes.

8. Counterparty Risk

Algo trading often involves interactions with various financial institutions and counterparties. There is a risk that a counterparty may default on its obligations, leading to financial losses.

9. Operational Risk

Operational risks include failures in internal processes, human errors, and external events. These risks can result in delays, financial losses, and other adverse outcomes.

Conclusion

Engaging in algorithmic trading involves significant risk and may not be suitable for all investors. It is important to carefully consider your financial situation, investment objectives, and risk tolerance before participating in algo trading. Crown Research recommends consulting with a qualified financial advisor to assess the appropriateness of algo trading for your specific circumstances.

By participating in Crown Research's algorithmic trading services, you acknowledge that you have read, understood, and accepted this Risk Disclosure Statement and the risks associated with algorithmic trading.