AI Trading

Monetize this groundbreaking innovation

Are you looking to capitalize on one of the biggest technological developments in the history of mankind? Jump on the AI train with Oxido Solutions and grow your wealth with our AI-driven trading bot solutions.

A 360-view on AI Trading

To succeed in finance today, it’s important to keep up with the most recent advancements in the field of artificial intelligence, and use them in ways that fit your investment goals and risk level. If you don’t, others will. That’s where Oxido Solutions comes in. We’re leading the way in the AI revolution, keeping a close eye on the latest developments, and turning them into cutting-edge AI trading solutions. This positions us as the go-to party for your AI trading needs.

Multidisciplinary AI Team

Equipped with seasoned IT, legal, and AI trading experts, we build AI-driven trading bot solutions from various angles. As a result, we can offer the most comprehensive AI trading suite.


Whether you’re an experienced investor, a trader, a trading bot developer, or someone who loves new tech, we’re here to guide you through the exciting world of AI trading.


Our aim is to give you a full understanding of AI trading, AI bots and related topics. We cover their benefits, risks, and everything in between, to ensure you have the complete picture.


Long before the recent AI trading hype spurred by ChatGPT, Oxido Solutions was already using artificial intelligence in our trading strategies and key elements of our IT infrastructure, such as our middleware and hosting. This has given us a head start in understanding the opportunities and challenges that this technology brings to the financial markets. We notice that AI is a buzzword that isn’t clear to everyone, especially how it can help digital asset traders succeed.

To make your learning easier, we’ve put together a unique content program for you. It covers ten essential topics:

✓ History
✓ Platforms
✓ Types
✓ Pros
✓ Cons
✓ Demo
✓ Features
✓ Use
✓ Services


Artificial intelligence

To understand what AI trading entails, we first need to define Artificial Intelligence. At its core, AI is a term that includes a variety of subtypes, which we will define later. However, fundamentally, AI is a simulation of human intelligence processes by machines, specifically computer programs. These processes include three steps: learning (the acquisition of information and rules for using this information), reasoning (using rules to draw approximate or definite conclusions), and self-correction. In simple terms: Artificial Intelligence is like teaching a machine or a computer to think and learn like a human. Every subtype of AI embodies a unique method to empower a machine or computer to mimic human thought processes.

Application financial markets

AI trading is one of the most popular applications of AI. It refers to the practice of utilizing artificial intelligence technologies to devise trading strategies for the crypto market, stock market, and other financial markets. This emerging field merges advanced AI techniques like machine learning, data analysis, and predictive modeling to create trading opportunities with minimal human intervention.

AI trading systems

AI trading systems are designed to analyze vast amounts of financial data, including historical price patterns, market trends, news articles, and social media sentiment. By leveraging powerful computational capabilities, these systems can quickly process and interpret complex data sets, identifying potential trading opportunities accordingly.

Jarno’s take on AI trading


As our Chief Technical Officer, Jarno de Vries holds responsibility for all technical aspects within Oxido Solutions. He is the creator of our trading bots, the underpinning IT infrastructure, and Alpha Shifter, our middleware layer. To maintain our leading edge in the trading space, Jarno keeps a close eye on AI trends. This focus has shaped his unique perspective on AI trading.

Transforming finance

Over 80% of all trades are driven by computers, and with the latest AI advancements, this percentage is set to rise rather than decline. This dynamic will make it increasingly challenging for manual traders to achieve success and will require investors to stay updated on the latest AI trends. Those already employing algorithmic trading strategies must, at the very least, continue testing new AI applications. This will ensure they have an alternative if the tech behind their current strategies becomes obsolete.


Anyone involved in algorithmic trading should aim to have a diversified portfolio of various trading strategies that ideally hedge each other as much as possible. This increases the chance of stable profits and decreases the chance of significant losses. Take, for instance, an AI-driven strategy that produces trading alerts based on a complex set of real-time social media data. This could serve as a hedge for a rule-based strategy that identifies trading opportunities based on fewer parameters and less data.


The rapid advancements in AI trading make everyone’s role at our company more engaging yet challenging to stay abreast of all developments within our three key verticals: Trading, IT, and Legal. Our trading setup and corresponding architecture must be constantly tested and adapted to meet the latest AI innovations. Furthermore, AI legislation impacts our legal services. Consider, for example, how to handle the intellectual property of a strategy partly developed with ChatGPT.

Overview AI subsets

Artificial intelligence is an umbrella term for a variety of algorithm-based technologies that solve complex tasks by performing functions previously requiring human cognition. To understand how AI can be used to benefit from volatility in the financial markets, you need to gain insight into the most relevant subsets of Artificial intelligence. Oxido Solutions has compiled these subsets for your convenience.


Machine learning (ML) is a method where systems learn from data and make decisions using mathematical models. It can learn in different ways, including supervised, unsupervised, or through trial and error, called reinforcement learning.


Deep learning (DL) is a type of machine learning that mimics the human brain using layered networks, known as “deep” neural networks. It’s able to understand unorganized data, which makes it suitable for recognizing images or speech.


Natural Language Processing (NLP) helps computers understand, respond to, and talk like humans. It helps machines make sense of our language, including the meaning of words, context, and even emotions, making our interactions with them more natural and easier.


Large Language Models (LLMs) are a mix of ML and NLP. LLMs are designed to process, understand, and generate human language in a way that is both meaningful and contextually relevant. They work by learning patterns in data and can generate text that is surprisingly human-like, given enough input data.


Robotics uses machines, or “robots”, to automate tasks, typically those that are repetitive, dangerous, or physically demanding for humans. These robots can operate autonomously or semi-autonomously, depending on their programming and human oversight.


Experience how we apply AI for our signal service for Bitcoin Futures on Bybit.

History of AI trading

The concept of Artificial intelligence can be traced back to ancient times with myths and stories about artificial beings endowed with intelligence. However, the birth of AI as a field of computer science dates back to a conference at Dartmouth College in 1956, where John McCarthy coined the term artificial intelligence. Yet, the first application of AI in trading didn’t occur until the 1980s. Step into our time capsule and experience the journey of AI in trading, from its modest origins to its modern uses, providing valuable insights into its capacity for intelligent financial decision-making.

1980: Advisor, first AI-based trading system

The early 1980s saw the first AI-powered trading system developed by a team at the University of California, Berkeley, using advanced algorithms and machine learning to analyze financial data and make autonomous trading decisions. This marked the dawn of a new era where AI became a critical part of the financial industry.

1982: Renaissance Technologies

Founded by mathematician James Simons,  New York-based Renaissance Technologies was the first AI hedgefund. It used data-driven mathematical models to analyze statistical probabilities and trends in securities prices. By April 2021, the firm had amassed a market capitalization of $165 billion.

2010s: Adoption financial institutions

BlackRock, one of the world’s largest asset managers, started heavily investing in AI and data science in 2016 to provide better insights and potentially improved returns for their clients. One year later, JP Morgan Chase & Co. launched LOXM, an AI program to execute client trades more efficiently.

2022+: The ERA of Ai CHAT BOTS

Since 2022, numerous LLM-based AI chatbots were introduced and used in AI trading, including OpenAI’s ChatGPT (Chat Generative Pre-Trained Transformer), which was launched on November 30, 2022. Following its release, Google, Baidu, and Meta swiftly developed their own competing chatbots: Bard, Ernie Bot, and LLaMA.


An AI trading bot, also known as an artificial intelligence trading bot, is a computer program that uses artificial intelligence to detect trading opportunities in financial markets. They are able to process vast amounts of data quickly and efficiently while mimicking human decision-making. AI bots are designed to analyze market data, identify patterns, and generate buy and sell alerts without the need for direct human intervention. Additionally, AI bots can automatically adapt and improve trading strategies over time by learning from past market data and performance. A well-made AI trading bot can help your capital grow and limit your risks. To end up with the right artificial intelligence robot, you need to know its key parts. At Oxido Solutions, we think these parts include:


Exchanges offer a wide range of products for all types of users. These are split into two kinds of exchanges: Spot and Derivatives.


An AI bot uses trading data to study and find trading opportunities on an exchange. This data covers market conditions, past trends, and other important factors.


There are different AI technologies and methods to create an AI trading bot, including using technical analysis, fundamental analysis, or a mix of both.


Your investment goals decide the technical setup of your AI trading bot. This involves selecting programming languages, backtesting tools, and middleware.




In order to make a profit with an AI trading strategy, exchanges and broker platforms play a crucial role. These platforms enable AI trading of digital assets between buyers and sellers. Ideally, they provide a user-friendly interface, sufficient liquidity, and a reliable way to exchange data. This can be done through an API connection, which allows large amounts of AI trading data to be exchanged quickly and accurately. There are two main types of exchanges: Spot and Derivatives. Selecting the right type for your AI trading bot is crucial, and understanding the differences between Spot and Derivatives exchanges can guide your choice.

However, it’s important to note that as a non-financial entity, we do not provide specific trading advice or evaluate your trading qualifications. We strongly encourage you to conduct your own in-depth research and seek advice from a finance professional.

DefinitionBuying and selling of digitals assetsBuying and selling of financial contracts
Contract typesSpotCFD's, perpetual futures, options
CollateralDigital assetDifferent types of digitals assets
LeverageNAAmplify profit or loss with leverage
Trading feesHigherLower
Risk management featuresLessMore
Trading feesTransaction feeTransaction fee, liquidation fee, funding fee
HedgingNot supportedSupported


Comprehensive and reliable data is at the heart of a successful AI trading bot. It’s vital to have access to thorough and trustworthy data for a winning AI strategy.

Trading data comes in two forms: historical and real-time. Historical data lets you look back and see how your strategy would have played out in the past, offering precious insights. Real-time data, on the other hand, is essential for successful live trading. Up-to-date information is key to making well-informed decisions and adjusting to the present market conditions.

Historical price data


When it comes to developing an AI trading bot, you’ve got three main approaches to choose from: technical analysis, fundamental analysis, or a mix of both. To guide you in picking the best approach, let’s explore the key differences between technical and fundamental methods by providing examples of AI bot applications.


Analysis of quantitative data based on technical indicators.


The AI bot would start by gathering extensive historical price data. This data forms the basis for the AI’s training and learning process.


Using Deep Learning techniques – specifically, a type of neural network known as a Convolutional Neural Network (CNN) – the AI bot is trained to recognize specific patterns in the data. CNNs are particularly suited to pattern recognition in visual data, making them perfect for identifying chart patterns in price data.


Once trained, the AI bot can then analyze real-time market data, recognizing the patterns it has been trained to identify. When a pattern is recognized, the bot uses this as a sign to generate a trading opportunities. For example, if it recognizes a “Head and Shoulders” pattern, which is typically a bearish signal, it might decide to provide a sell alert.


The AI bot also continues to learn and adapt over time. As it receives new data and feedback, it adjusts its own internal model to improve its pattern recognition and trading decisions. This process, known as backpropagation, is a key part of the machine learning process.


Analysis of qualitative data with fundamental indicators.


The AI bot first gathers extensive textual data, including company reports, financial news articles, social media posts, and more.


Utilizing Natural Language Processing (NLP), an AI field that interprets human language, the bot can comprehend and extract meaning from textual data. A specific NLP feature, Sentiment Analysis, allows the bot to determine whether the expressed sentiment about a stock is positive, negative, or neutral.


Based on the sentiment analysis, the bot can make informed trading decisions. For example, if the bot determines that the overall sentiment for a particular company is increasingly positive, it could decide to create an alert to buy shares in that company, anticipating a potential price increase.


Through Machine Learning techniques, the AI bot is not only able to make decisions based on current data, but it can also learn from past actions and improve its decision-making processes over time. This process of continuous learning helps the bot to adapt to new information and changes in the market environment.

AI trading technology

To roll out a profitable AI trading strategy that meets your risk appetite, the right technology is essential. At Oxido Solutions, we have all the knowledge and techniques to compete with other AI trading bots. From this expertise, we’ve outlined the key tech components that are a requirement for every AI Trading Infrastructure. Dive in to understand the technology that makes AI trading work.

AI tool

AI trading tools are designed to execute the AI component of a trading strategy using artificial intelligence. These tools employ algorithms that constantly analyze trading data using techniques such as machine learning and NLP, subsequently generating trading alerts that improve over time through continuous learning.

Strategy software

Trading strategy software assists you in building a trading strategy. It can receive input from AI tools, has pre-installed technical indicators and a code editor for custom strategy creation. It also includes a backtest to learn how a strategy could have performed it the past. Additionally, it can generate trading alerts and forward them to an endpoint.


Middleware plays a vital role in AI trading as it acts as a bridge for data exchange. It begins by receiving trading alerts from the strategy software, then transforms the data into a format that’s compatible with your chosen exchange. Finally, the middleware forwards the transformed data to your exchange account.


Exchanges support AI trading by supplying liquidity and allowing data exchange with third-party systems like middleware software. Upon receiving buy and sell information from a middleware, users can manually process it into an order or allow automatic order conversion by the exchange.


When it comes to getting an AI trading bot, you have options. Some platforms and providers offer ready-made AI bots that you can buy and configure to fit your needs. In such situations, you don’t really need to know how to code, but it helps to understand how your bot works. If, however, you’re keen on creating your own AI trading bot, you’ll need solid coding skills. Coding languages fall into two categories: closed-source and open-source. Closed-source languages are platform-specific, while open-source ones can be used across various platforms. Knowing these categories can help you decide the best way to develop your trading bot.




PineScript is a programming language based on C, offered by TradingView, a popular charting platform for creating artificial intelligence trading bots. With PineScript, you can create your own AI strategies and custom technical indicators that match your trading style.


MetaTrader5 (MT5) is a closed platform that a lot of developers use to build AI trading bots. With MT5’s software kit, which is based on the Python programming language, developers can create personalized AI bots and indicators that perfectly mirror their unique AI trading strategies.


If a closed platform doesn’t provide the necessary tools for making an AI trading bot, you can opt to create a strategy from scratch or use open-source libraries. Python is the go-to-programming language for machine learning and gives you plenty of options for developing your own tailored AI trading bot.


JavaScript is an open-source language that’s relatively easy for beginners to pick up. However, it might not be the best choice for creating AI trading bots that focus on high-frequency trading strategies like arbitrage or market making, which demand superior speed and performance abilities.

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    AI bots for different asset classes

    AI trading robots can operate in diverse financial markets. This gives traders who are active in both traditional and alternative asset classes the opportunity to create a well-balanced AI trading portfolio, effectively managing their financial risks. At Oxido Solutions, we specialize in artificial intelligence bots across various assets and have put together a list of the most sought-after ones for your benefit:

    AI crypto trading bot

    An AI crypto bot is designed to use artificial intelligence to monetize the fast and volatile world of cryptocurrencies. It can process large quantities of trading and social media data and other type of information to spot trading opportunities for Bitcoin, Ethereum, and other cryptocurrencies.

    AI stock trading bot

    An AI stock trading bot uses artificial intelligence to analyze vast amounts of financial data, news, and market trends and detects buy and sell opportunities for stocks like TSLA and APPL. Its goal is to take advantage of potential gains from market inefficiencies on exchanges like NASDAQ.

    AI forex trading bot

    AI forex trading bots are made for the foreign exchange market, where currencies are traded with a daily trading volume of 6.6 trillion USD. An AI forex bot identifies trading opportunities in currency pairs like EUR-USD and AUD-GBP, based on artificial intelligence.

    AI gold trading bot

    Gold CFDs, a method of leveraging gold, were first introduced in Britain in 1974 and gained popularity during the 1990s. The recent rise of AI trading has led to the emergence of AI gold trading bots, introducing a new way to profit from CFD trading.


    At Oxido Solutions, we found that existing middleware solutions fell short of our precise AI trading needs. In response, we decided to develop Alpha Shifter, a state-of-the-art middleware trading system. It effectively transmits buy and sell signals from various AI trading strategies to any specified endpoint. Recognizing the growing demand for a robust enterprise middleware layer among hedge funds, family offices, banks, and other professional entities within the finance sector, we’ve decided to offer Alpha Shifter as a standalone software solution. Here is a list of the key features:

    ✓ ALERTS
    ✓ LOGS
    ✓ SECURE
    ✓ CRYPTO
    ✓ STOCKS
    ✓ FOREX


    When you use an AI trading bot, you’ll be entering a competitive environment alongside numerous other AI bots in the financial markets. But what sets an AI trading bot apart from other investment options? Let’s delve into its key advantages.

    Earn passive income

    AI trading bots help generate passive income by automatically producing trading opportunities according to set rules and strategies.


    AI bots help mitigate the emotional pressures associated with manual trading in volatile markets, while still offering the potential for financial gains.


    AI trading bots work tirelessly in the background, leaving you free to focus on other tasks. They operate without the need for constant supervision, potentially yielding profits in the finance world.


    AI bots can produce buying and selling opportunities with reduced transaction costs compared to manual trading, thanks to their efficient data processing.


    With the capacity to operate 24/7, AI trading bots help you tap into market opportunities and generate potential profits, even when you’re not actively watching the financial markets. This can enhance the efficiency and productivity of your trading operations.


    A trading bot can diversify your investments by simultaneously generating trading opportunities for multiple exchanges, asset classes and trading pairs. This allows you to spread your investments across different assets and markets.


    One of the key advantages of using an AI trading bot is its backtesting feature. It lets you test your AI trading strategies against historical market data, revealing how effective they might have been in the past. This simulation of trades and analysis of outcomes can help hone your trading skills for the future.


    AI Trading bots can be programmed to generate stop-loss orders automatically and include various other risk management features, like dynamic take-profit opportunities. These features aim to protect your trades and prevent significant losses by ensuring timely exits from positions.


    Some AI trading bots offer copy trading, allowing you to automatically mirror the bot’s trades in your own broker account. This eliminates the need for individual research or strategy development, as you’re essentially following the AI bot’s trading decisions. This can be a convenient way to enhance your trading outcomes and leverage the AI bot’s expertise.

    AI trading bot services

    Here at Oxido Solutions, our expertise spans across IT, trading, financial markets, and legal domains, enabling us to  produce AI trading bots for a variety of strategies. We serve a diverse group of clients, including professional investors, beginners, and experienced traders. We offer a range of AI services and products to meet the needs of this varied group. However, please note that certain services may be subject to regulatory restrictions, limiting their availability.

    AI trading signals

    With our AI trading signal service, you have the chance to generate extra income while keeping full control of your assets. Our exclusive trading bots, the Range Maker and the ATR, use artificial intelligence to provide high-quality buy and sell signals, helping you make the most of your trading.

    AI & IT Consultancy

    Are you looking for a reliable partner to help with the AI and IT aspects of your AI trading bot strategy? Or, do you need help reviewing the code of your existing AI bot or IT infrastructure? At Oxido Solutions, we are ready to provide all the AI and IT consultancy services you need for your AI trading bot.

    IT development

    Our IT team is made up of experienced AI traders and machine learning experts with strong analytical and coding skills. Depending on your specific needs, we can help with the IT development of your AI bot using a variety of programming languages, such as Python, TradingView, and JavaScript.


    If your AI trading bot isn’t delivering the performance you expected, don’t worry. Sometimes, adding a single feature can make a huge difference in unlocking its full potential. We offer machine learning tools and technical indicators that could be just what you need to improve your AI bot’s performance.


    Discover the results of our AI trading signal service for BTC Perpetual Futures.


    New AI tools are being launched constantly. At Oxido Solutions, we continuously test these applications to see how they can provide us with new insights for improving our existing trading strategies and developing new trading bots. In this section, we share an example of an AI technology that we have successfully applied for all of our crypto trading bots.


    Oxido Solutions employs the renowned Transformers library for AI in its Bybit bot, Binance bot, and other cryptocurrency bots. This library, developed by Hugging Face, is an open-source Python-based tool for Natural Language Processing (NLP) tasks, such as text classification, extraction and generation.


    We leverage the Transformers library to supplement and validate our rule-based system, which generates buying and selling signals based on technical analysis. For instance, if a buying signal for Bitcoin is generated but the AI validation system indicates a negative sentiment for Bitcoin, this insight is incorporated into the final decision-making. 


    Our AI validation system consists of sentiment analysis and event extraction. Sentiment analysis interprets the sentiment from Bitcoin-related news, social media posts and other text data. It generates a sentiment score and feeds it into our trading strategy. Meanwhile, event extraction pulls vital information from Bitcoin events, aiding our trading decisions.


    The technological advancements of AI trading are coinciding with evolving legislation. Since 2023, several nations, including those within the European Union, Brazil, and China, have been developing or implementing various regulations related to artificial intelligence, including AI trading systems. In addition to specific AI legislation, existing financial laws also apply to AI trading. This makes artificial intelligence trading a complex but interesting subject from a legal perspective, an area in which Oxido Solutions has specialized. We have a team of AI lawyers and a partner network that can support in all areas of artificial intelligence trading. Whether you operate an AI hedge fund, offer AI trading services, or if you’re an AI trading customer facing legal issues, allow us to guide you through every step of your legal journey.

    ✓ comPliance
    ✓ IP
    ✓ investigations
    ✓ Fundraising
    ✓ KYC & AML


    Building a successful AI trading strategy needs both skill and experience. If you’d like to avoid the detailed work of creating and managing your own AI bot strategy, you might want to consider using the AI trading strategy from Oxido Solutions. It’s packed with innovative features aimed at improving your chances of success in the financial markets. Here’s why our artificial intelligence strategy is special:


    Our AI trading strategy is built around a trend-following approach, where we keep a close eye on the direction of market trends. We firmly believe that if an asset is moving in a certain direction, it’s more likely to keep moving that way rather than make a sudden switch. This lets us take advantage of both rising and falling market trends. To spot and track these trends effectively, our AI bots use advanced technical and fundamental analysis as well as artificial intelligence.

    3 risk levels

    Our AI trading strategy offers three risk levels: low, medium, and high, which match risk levels of 2%, 4%, and 6% of the trading capital per trade. Keep in mind that these calculations don’t factor in slippage, the gap between the expected price of a trade and the price at which it actually executes. The low-risk level aims for smaller profits but also experiences smaller drops, giving a more cautious approach to AI trading.

    Range Maker

    In 2017, Jarno developed the Range Maker, a trend-following trading algorithm that became available to the public in 2019. Unlike other algo traders who depend on common methods like Bollinger Bands to set the trading range, we’ve taken a unique path. Our way of calculating the trading range, combined with custom features, ensures steady stability and makes it less susceptible to market manipulation.

    ATR trading bot

    In 2020, we rolled out another AI trading bot: the Average True Range (ATR). The ATR algorithm is designed to respond quickly to minor trend movements and excels over shorter timeframes. By pairing the ATR with the Range Maker, we boost the monthly performance of our strategy, as they provide a safety net for each other. This combined approach allows our AI bot to adapt more effectively to shifting market conditions.

    Sideways filter

    The sideways filter is an advanced technical indicator that tackles one of the biggest hurdles in our industry. While trend-following strategies often do well in strong trending markets, they can struggle during times of choppy price action. The sideways filter measures the market’s strength effectively and adjusts our algorithms to match. When the market’s trend is weak, it stops our strategies from taking positions. This groundbreaking feature has reduced our strategy’s drawdowns by up to 50%, boosting its overall performance.

    Continuous learning

    One issue with trend-following trading strategies is the risk of over-optimization. This occurs when strategy parameters are adjusted too closely to historical market data, leading to a drop in performance when applied to new, unseen data. Traders often run into this problem when they continually fine-tune the strategy to fit the past data perfectly. To avoid this, our strategy supports continuous learning, a machine learning-based function that dynamically adjusts the algorithm parameters based on current market conditions. This flexible approach ensures steady performance in changing market landscapes.


    Sign up for a one-on-one 30-min presentation of our trading strategy.


    While AI trading bots can boost your capital, it’s important to understand the risks involved. In our journey at Oxido Solutions, we’ve navigated numerous hurdles before setting our artificial intelligence services into motion. We have integrated solutions into our signal service, IT infrastructure, and other offerings to tackle these risks. Whether you’re considering designing your own AI trading robot or exploring options from other providers, getting a clear understanding of the potential risks and how we’ve countered them is crucial.


    The process of crafting and running an AI trading bot comes with technical components that may lead to IT-related complications. These complications can emerge in forms such as receiving no or incorrect input due to factors like wrong data sets, coding errors, or server interruptions. Moreover, there’s a chance of delayed or missed generation of buying and selling opportunities. These issues can spark a series of problems where the middleware receives faulty information from the AI trading bot, resulting in inaccurate or postponed transmission of signals to your broker account. Consequently, this can lead to incorrect order placement and possible financial losses.


    At Oxido Solutions, preventing IT issues by establishing a reliable IT infrastructure is our top priority. Every component is subjected to stringent testing and frequent updates to ensure their dependability. If any input discrepancies arise, our error management application promptly detects and records them, enabling us to take instant automated corrective actions like generating new trading opportunities. We have backup mechanisms, including MetaTrader5 and mirrored environments for the middleware and hosting, to effectively manage any interruptions. While completely eliminating issues might be unachievable, our enterprise IT infrastructure greatly reduces their impact.


    An AI bot’s success is closely tied to the opportunities that the market offers and your bot’s capacity to respond effectively to them. Financial markets are dynamic, continually shifting between upward, downward, and sideways movements, along with variations in trading volumes. Additionally, the market dynamics can be influenced by the activities of market makers. Therefore, it’s essential for an AI trading robot to adjust to these ever-changing market conditions to prevent possible drawbacks. Market risks can arise from factors such as market volatility, economic condition shifts like recessions, inflation, or interest rate fluctuations, or unforeseen events like natural disasters.


    While we cannot control market situations, we focus on taking proactive measures to predict and effectively respond to them. Our AI trading bots are equipped with robust risk management features to ensure adaptability to market changes. These include a pre-set maximum loss per trade (excluding slippage), a dynamic stop-loss mechanism that adapts based on market direction, and an automatic take-profit feature. Moreover, our bots incorporates a sideways filter that identifies choppy market conditions and potential market manipulation, preventing the generation of buying and selling opportunities during these periods. Through these risk management measures, we aim to decrease the chances of setbacks when faced with unexpected market events.


    Using an AI trading bot involves considering regulatory risks. Regulatory risks arise from the laws and regulations that oversee financial markets and automated trading systems, presenting potential obstacles and limitations. Such risks might involve access restrictions to certain platform services due to regulatory constraints.
    Additionally, if you operate your own service, you could be barred from advertising it if it’s considered illegal or if you lack the required operating license. Furthermore, there’s a possibility of algorithmic trading being entirely banned or restrictions imposed on factors like maximum leverage, which could impact the effectiveness of numerous existing trading bot strategies.


    At Oxido Solutions, we maintain close communication with the management teams of many exchanges and regulators worldwide to make sure we are complying with the rules for trading bots. Our know-how in digital assets, AI trading and IT lets us adjust our services quickly to meet any regulatory requirements. If you’re up against regional limits or unsure about licensing as a crypto service provider, we can link you with the right professionals to tackle your issues. While we don’t offer financial advice, we’re here to help with any other concerns you might have.



    If you’re looking for a simple and effective way to take advantage of the volatility of the cryptocurrency market, Oxido Solutions’ AI-driven crypto trading bots might be what you need. They can find the best buy and sell opportunities for crypto derivatives.  This could help you earn extra income on the top three cryptocurrency derivative exchanges: Binance, Bybit, and OKX.

    Signal service

    To receive AI trading opportunities for crypto derivatives, you can subscribe to our signal services for Binance trading bot, Bybit bot, and OKX bot. Our AI crypto trading robot detects opportunities, sends them to a middleware layer, which then forwards them to your crypto account for you to manually turn into orders. We cannot automate the conversion of these opportunities into orders because we are not a financial institution. However, you can allow your crypto broker to turn the signals into orders through their API.

    Trading pairs

    Our AI bots only create buy and sell opportunities for Bitcoin and Ethereum Derivatives trading pairs. We focus on these due to their high liquidity, which is vital for smooth and efficient trading. Furthermore, the rich historical price data for these specific trading pairs lets us do thorough backtesting, ensuring our crypto trading bots’ trustworthiness. For example, even before we started collecting live data in 2019, our backtesting showed that our AI crypto bots were doing very well.

    Perpetual Futures

    Our AI cryptocurrency bots produce trading opportunities for perpetual futures, also known as perpetual swaps. This derivative product lets you speculate on future asset prices without expiry dates, unlike traditional futures contracts. There are two types: BTC-USDT-SWAP and BTC-USD-SWAP. If you prefer to earn more USD Tether stablecoins rather than Bitcoin or Ethereum, choose BTC-USDT-SWAP and provide USDT for our crypto signal service. Or if you want to use Bitcoin as collateral and gather more of it, go for BTC-USD-SWAP.

    Isolated margin

    Oxido Solutions’ crypto AI robots are built to find opportunities that include isolated margin, a helpful feature that assists you in managing the risk of each individual trade. It’s like setting aside a specific amount of money for different expenses. With isolated margin, you assign a particular amount of funds for each trade and only use those funds for that trade. This ensures that a trade that doesn’t perform well won’t impact the rest of your trades, giving you better control over your risk.


    Ready to take the next step? With Oxido Solutions’ signal service, you can receive AI-driven buy and sell signals to help you generate extra income on your preferred exchange and asset class. You can receive the signals by email, Telegram, API or any other preferred channel. Please be aware that as a non-financial service provider, our signals are not customized, and all subscribers receive the same signals. We also do not execute orders on your behalf. We believe in our AI robots and are happy to give you a free trial for 14 days. If you’re satisfied with the signals, you can move to a paid subscription with us.

    Duration14 daysNo limit
    Entry1000 USD≥ 50,000 USD
    Performance feeNone25-35%
    Asset typecrypto, stocks, commoditiescrypto, stocks, commodities
    Notice PeriodDailyMonthly
    Algo featuresAllAll
    SupportE-mailAll channels


    Eager to learn more about our AI trading services or have some questions? Please drop me a line directly or leave a message via our contact form. I’ll be more than happy to assist you.
    Guido Lassally
    Guido Lassally (CEO)