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Frequently Asked Questions

Frequently Asked Questions

4 min read

This page provides insights into common errors encountered while developing and executing algorithmic trading strategies, along with their possible causes and solutions. These errors are often logged in the user.log file.

Execution time exceeded timeout_duration duration of 60 sec.

What is Execution time exceeded timeout_duration duration of 60 sec.?

Possible Causes

  • Historical Data Fetching Duration:

    Fetching historical data may take longer, especially if the duration is set to a large number of days.

  • Suboptimal Decision-Making Logic:

    The decision-making logic might be suboptimal, leading to increased processing time.

  • Sequential Execution Approach:

    A sequential approach of fetching historical data and then making the decisions in case of multiple instruments can contribute to delays.

  • Real-Time Calculations:

    If there are calculations that could be pre-conditioned or pre-calculated before the market opens, optimizing real-time calculations might help.

Solutions

  • Optimize Historical Data Fetching:

    Consider reducing the number of days for which historical data is fetched. A shorter duration, like 5 days, can be a reasonable compromise.

    @staticmethod
def get_historical_data_duration():
    return 5

  • Optimize the Decision-Making logic:

    Revisit your strategy logic and check if any code block can be optimized.

  • Batch Processing for Decision-Making:

    In case of multiple instruments, lets say you are fetching the historical data for the instrument, and have implemented the decision-making logic for whether this instrument should get selected for order placement or not. Once this is done, you repeat the same process for the next instrument. Instead of a sequential approach, try fetching historical data for all instruments in one loop and then making decisions for all instruments in another loop.

  • Pre-Calculate Conditions:

    Identify conditions that can be pre-calculated before the market opens. Adjust the strategy start time to accommodate these pre-calculations. If certain conditions can be chcked before the market starts, set the trading start time of the strategy to a value before the market start time. Add specific checks inside the strategy to ensure that the actual order placement, etc. are executed after the market starts.

No Data in Charts

What is No Data in Charts?

Description

Encountering the "NO data in charts" error while running a strategy is a common issue. This problem arises when using a small quantity with very large funds. Scenario 1 Limited visibility on charts due to large funds with a small quantity setting.

Possible Causes

  • Scale Discrepancy:

    The large fund amount may lead to extremely small values on the y-axis, which are not visible, causing charts to appear empty.

  • Default Quantity and Funds:

    Default quantity and funds settings, if not adjusted, may lead to similar issues with empty charts.

Solutions

  • Normalize Values:

    Normalize values by using larger quantities or scaling to ensure meaningful data display across various scenarios.

  • Adjust Default Settings:

    Consider adjusting default values to something more suitable for common scenarios. Scenario 2 Charts displaying proper data with suitable funds and quantity settings

OpenAI API Quota Depletion

What is OpenAI API Quota Depletion ?

Description

The "OpenAI API current quota exceeded" error indicates that the current quota or available credits for the OpenAI API has been exhausted. This typically occurs when the allotted usage limit for the API key has been reached.

Possible Causes

  • Credit Depletion:

    The API key has utilized its entire quota or available credits.

Solutions

  • Purchase More Credits:

    To continue using the OpenAI API, consider purchasing additional credits or upgrading your plan to increase the quota. Click here to add more credits. openAI credit

  • Alternative Key:

    If available, switch to a different API key that still has unused credits.

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Trading in financial products involves significant risk and may not be suitable for all investors. The use of our services, including algorithmic trading strategies, Phoenix and Odyssey (Algo Marketplace), carries the risk of substantial losses, potentially exceeding your deposited funds. It is crucial to fully understand these risks before engaging in trading activities.

AlgoBulls (AlgoBulls Technologies Private Limited) does not guarantee the accuracy or completeness of any information provided on our platform, including third-party content. Such information should not be relied upon without thorough independent investigation by the investor. Investments in securities and equity-related instruments are subject to various market risks, which can be influenced by specific security factors, broader market conditions, and economic, political, and global developments.

Past performance of any strategy, model, or advice provided by AlgoBulls does not guarantee future results. Actual returns may vary significantly due to various factors, including but not limited to, impact costs, expenses, entry and exit timings, additional flows or redemptions, client-specific mandates, and unique portfolio construction characteristics. There is no assurance that the objectives of any strategy, model, or advice will be achieved.

AlgoBulls, its partners, officers, and employees do not guarantee any specific return on investments made based on the strategies or advice provided. The value of investments can fluctuate, influenced by market forces and conditions. AlgoBulls and its associates are not responsible for any losses or shortfalls arising from market conditions.

Investors are encouraged to thoroughly read and understand the terms and conditions outlined in the relevant advisory agreement before subscribing to any services. AlgoBulls and its associates/employees shall not be held liable for any risks or losses associated with the strategies, models, or advice provided. Trading in securities is subject to market risks, and AlgoBulls makes no representation or guarantee that the objectives of any model, strategy, or advice offered will be achieved in the future.

Risk Disclosure: Futures and forex trading contains substantial risk and is not for every investor. An investor could potentially lose all or more than the initial investment. Risk capital is money that can be lost without jeopardising ones’ financial security or lifestyle. Only risk capital should be used for trading and only those with sufficient risk capital should consider trading. Past performance is not necessarily indicative of future results.

Hypothetical Performance Disclosure: Hypothetical performance results have many inherent limitations, some of which are described below. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown; in fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any particular trading program. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk of actual trading. for example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all which can adversely affect trading results.

Testimonial Disclosure: Testimonials appearing on this website may not be representative of other clients or customers and is not a guarantee of future performance or success.

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