FMZ Quantify & OKX: How can ordinary people play Quantify?

In the cryptocurrency market, data has always been an important basis for transactional decisions. How to find and extract valuable information in the complexity of data to optimize trading strategies has always been a hot topic in the market. To this end, OKX has specifically designed a column titled "Insight on Data" and combined mainstream data platforms such as AICoin, Coinglass and related institutions based on common user needs, hoping to dig out more systematic data theory methods for market reference learning.

In this edition's Insight Data Pie, the OKX Strategy team, together with the inventors of Quantitative (FMZ) institutions, explored in depth the concept of Quantitative Trading and discussed in detail how ordinary people enter into Quantitative Trading.

OKX strategy team:OKX Strategy Team consists of a group of experienced professionals dedicated to driving innovation in the global digital asset strategy space. The team brings together experts from a wide range of fields, including market analysis, risk management and financial engineering, with deep expertise and extensive business experience to provide solid support for OKX's strategic development.

FMZ quantified teamInventors Quantify is a company focused on providing professional solutions for users of cryptocurrency quantitative trading. Inventors Quantify not only provides users with a full range of quantitative trading capabilities such as strategy writing and feedback, a quantitative trading engine, algorithmic trading services and data analysis tools, but also has an active developer community where users can exchange and share experiences.

First, what is a quantitative transaction?

OKX strategy teamQuantitative trading is essentially a way of using mathematical models and statistical methods to automatically execute a trading strategy through programs. Unlike manual trading, which relies on individual decisions, quantitative trading relies on historical data, algorithms and technical indicators to analyze the market, find trading opportunities, and automatically execute trades. OKX's strategy robots provide powerful and flexible automated trading tools that support multiple strategies (e.g. grid, Martin strategies, etc.) and can also perform strategy back testing and simulated trading to help users find the most appropriate tools in different market environments.

FMZ quantified teamQuantitative trading, also known as programmatic trading, is not inherently mysterious. When a user operates on an exchange's website or software, whether it is to access a market, view an account, place an order, etc., they are connected to the exchange's server via the corresponding API, so that the server can return the data the user needs.https://www.okx.com/api/v5/public/funding-rate?instId=BTC-USDT-SWAPThis is the first time I have seen this video.

{“code”:“0”,“data”:[{“fundingRate”:“0.0001510608984383”,“fundingTime”:“1717401600000”,“instId”:“BTC-USDT-SWAP”,“instType”:“SWAP”,"maxFun

The "fundingRate": 0.0001510608984383 is the current funding rate for the BTC-USDT perpetual contract, and the corresponding funding rate information can be obtained by modifying the link instId=BTC-USDT-SWAP for other currencies. Similarly, just accessing the corresponding API link and filling in the appropriate parameters can basically complete everything we do on the website or in the app. If this process is controlled by the program, it completes the transaction we intended (transaction or otherwise), which is also a quantified transaction.

In short, all the information that was originally acquired and all the transactional decisions that were made by our brains can now be handed over, in whole or in part, to a program to execute.

2 What type of user is it for?

OKX strategy team: With OKX as an example, our quantitative trading tools are suitable for users of different backgrounds/preferences, and both beginners and advanced users can quickly learn the strategies. • For beginners (traders with little or no experience in quantitative trading), we currently offer:

1. Easy-to-use interface and pre-set strategies, which can be selected from the platform's pre-set strategies, such as grid strategies, settlement strategies, etc. These strategies usually do not require complex settings and deep market knowledge, and users simply select and configure a small number of parameters to get started, without programming or deep technical knowledge.
2. Simulated trading and retesting, understanding the potential performance of strategies under different parameter settings, reduce the risk in real trading. These features help users to accumulate experience before actually investing funds.
3. Aimed at advanced users (traders with quantitative trading experience or technical ability), the strategy robot also features highly customized strategies, such as grid, Martin strategies that provide rich progression parameters, or signal strategies such as the ability to execute Trading View PineScript, suitable for users with transformation and data analysis capabilities.

FMZ quantified teamThe following four types of users are generally contacted:

• Professional traders. As a professional trader, trading is essential and must have all the advanced tools to help themselves, so it is almost necessary for them to master quantitative trading. Professional traders often have mature and profitable strategies that can be applied to more exchanges and trading varieties, doubling trading efficiency.
• Programming enthusiasts. For individual traders with a background in programming, quantitative trading tools offer an excellent opportunity to combine their programming skills with the digital currency market. They can customize trading strategies according to their needs, develop trading tools, and optimize the effectiveness of strategies by retesting.
• Traders who need an effective strategy. Some traders may not have a stable trading strategy yet, and quantitative trading tools can help them. These tools often include a strategy library and a strategy marketplace, where traders can test other open source strategies and find strategies that work for them through data analysis and retesting.
• Ordinary traders with the ability to learn. Even ordinary traders without a programming background can benefit from the automation features provided by quantitative trading tools. By using ready-made quantitative trading platforms such as FMZ Quantitative, they can easily set up trading strategies and evaluate the effectiveness of strategies using feedback functions, thus improving trading efficiency and reducing human error in actual operations.

3 What are the advantages and disadvantages of manual trading?

OKX strategy teamQuantitative trading has the following advantages: it is more systematic and objective, it is executed with predefined algorithms and rules, avoiding emotional interference with decision-making. It is also highly efficient, it can process large amounts of data and perform high-frequency trading, and it seizes market opportunities 24/7. Users can also test and optimize strategies through historical data, enhancing the reliability and testability of strategies.

However, quantitative trading is not perfect. First, it has a certain complexity, some advanced strategies require specialized statistical and financial knowledge, and the thresholds are relatively high. Second, quantitative trading may rely too heavily on historical data to optimize strategy parameters, while actual market performance may not be as expected.

FMZ quantified teamIn fact, manual trading and quantitative trading are not opposites. An excellent quantitative trader is often also a qualified manual trader. The two trading methods are complementary and can be used to greater advantage in combination. Good quantitative traders need a deep understanding of the market. The market is complex and variable, and although quantitative trading relies on data and algorithms, the data and algorithms are still based on a deep understanding of the market.

In our experience, there are three main advantages:

1. Automate the execution of strategies and avoid manual intervention. Sometimes the strategy itself is profitable, but constant human intervention leads to losses, and programmatic trading can automate the execution of the pre-set trading strategy without human intervention. This means that the trader can set the conditions for buying and selling, and the program will automatically trade when the conditions are met, thus avoiding emotional fluctuations and human error.
2. It can handle transactions that rely on low latency, high frequency, and complex computation. Manual transactions are limited by human reactivity and computational speed, and are far less efficient than programmatic execution, which can only be met by quantitative transactions.
3. Quantitative trading can use historical data to retest and optimize trading strategies. This method can help traders optimize strategies before real-time trading, increasing the probability of profits. Many manual traders trade on a hunch, using real-time time and money costs to try and fail. In fact, most quantitative strategies are derived from data analysis.

Of course, quantitative trading isn't perfect either, and there are some disadvantages:

1. The technology demands are high: Quantitative trading requires additional programming and data analysis skills and a higher threshold than manual trading. Quantitative trading is undoubtedly a time-consuming and costly learning for beginners and does not guarantee a return on investment.
2. The cost is high: Quantitative trading systems have high costs to build and maintain, especially for high-frequency trading, which requires a large amount of hardware and data resources. These fixed costs are a tough expense regardless of strategic profits or losses.
3. Market risks: Although quantitative trading can reduce human error, there is still market risk, and strategy failure can lead to serious losses. While quantitative strategies are written in advance, based on historical data retrospective, there are certain limitations, and can not keep up with changes outside the market.

4 How do new users get started?

OKX strategy teamIn general, quantitative trading is challenging for beginners, but not impossible. Here are some tips to help beginners master quantitative trading:

1. Learning the basics: First, understanding the basic principles of strategy and the impact of different parameters on strategy performance is the first step to success.
2. Choose the right strategy robot: Depending on your judgment of the market, choose the right strategy robot. For example, in a volatile market, a grid strategy may be a good choice.
3. Start with simple strategies: Start with the most basic trading strategies, learn and implement them gradually, and then gradually introduce more complex strategies.
4. Focus on risk management: Learn to establish and implement effective risk management and loss prevention strategies.

FMZ quantified teamMany people think that the threshold is high and the technology is complex. In fact, learning programmatic trading has become very simple. Exchanges integrate common strategies, FMZ quantification and other quantitative teams provide a one-stop service, plus a large language model programming assistant like ChatGPT, and the only obstacle to initiating even proficient programmatic trading is a realistic path.

1. The following are some of the most common quantitative strategies: Learning about the strategy trading modules used on the OKX exchange will help you to have a preliminary understanding of strategy trading. For most traders, these features are sufficient. If you have more ideas to implement, you can continue to learn in depth.
2. Learn programming languages: It is recommended to learn Javascript (JS) and Python, just need to master the basic use of it. In writing strategies, side-learning practice, will improve quickly. The JS programming language is relatively simple, FMZ platform has many open source strategies from simple to complex to reference. Python is the most commonly used data processing language, combined with Jupiter Notebook for statistical analysis is very convenient.
3. Read the basic quantitative trading books: There are many books on the subject, which can be searched by yourself. You can read faster and learn about the types of strategies, risk control, strategy evaluation, etc. Quantitative trading involves finance, mathematics and programming, and is very rich.
4. Learn about the API documentation and related paradigms and do some real-world deployment strategies: Recommended entry to the FMZ quantification platform, rich documentation and examples greatly reduce the threshold for real-time; this step requires mastering the basic strategy architecture, solving common problems such as error handling, access frequency control, error tolerance policy, risk control, etc.; writing some simple modules, such as price push, iceberg commissioning, etc.; exercising the writing skills of real-time strategies; retesting some basic strategies, such as grid, balance strategy, etc.; joining relevant groups, learning to ask the right questions and search for relevant posts.
5. The strategy of verifying trades through retesting and simulation was constantly refined, and finally began to trade in real time: Skilled traders already have their own strategic ideas, can verify and perfect the strategy by retesting and simulated trading, and finally start trading in real time. Completing a complete strategy and seeing the orders automatically drop is a joy that is hard to describe. If you do not have your own strategy, you can first complete some open source strategy retesting suite, multi-trade pair grid strategy, etc.
6. Continue reading, thinking, communicating, analyzing, retesting, and practicing: As the difficulty gradually increases, the learning gradually deepens, and the ability continues to improve.

5 What are the precautions when using quantitative trading?

OKX strategy teamI'm not going to lie. In fact, we believe that users should pay attention to the following three things when using quantitative trading:

1. Quantified trading is definitely profitable: Many people believe that quantitative trading relies on complex algorithms and data analysis to ensure stable profitability. However, quantitative trading does not guarantee certain profitability. Although quantitative strategies optimize trading decisions through data and algorithms, market uncertainty, mistaken model assumptions, over-matching of strategies, and other factors can cause losses.
2. Quantitative transactions are only suitable for large institutions and high net worth users: Individual investors can also engage in quantitative trading using market-based quantitative trading platforms and open-source tools. For example, OKX's grid strategy, Martin strategy, and signal strategy are all free to use. Although high-frequency trading does require high capital and technical thresholds, these types of strategies do not necessarily require large amounts of capital.
3. The results of the retest represent future performance: Retracement is only a means of evaluating strategies, but it does not guarantee future performance. Changes in the market environment, deviations from model assumptions, and over-fitting of strategies (over-optimization for historical data) can lead to less than expected actual trading results. Retracement results need to be combined with realistic market conditions and robust risk management to assess their reliability.

FMZ quantified teamIn fact, most people don't have a deep understanding of quantitative trading, which can easily lead to some misunderstandings.

1. Is it possible for quantitative trading to be profitable? Many traders turn to quantitative trading after manual trading losses, hoping to make quick profits, seeing it as a way to make money. However, profitability depends more on the logic of the trading strategy than on the tool itself. Even if the ideal automated trading strategy is developed, there may be a variety of unexpected problems in actual trading that lead to unpleasant strategy results.
2. Quantified transactions can't go wrong? While quantified transactions reduce the number of human errors, they also introduce other errors; for example, the leakage of an API-key can lead to malicious manipulation of account funds. In addition, bugs or unaddressed abnormalities in the policy can lead to erroneous transactions or even catastrophic consequences. In order to avoid these problems, traders need to take strict security measures and conduct adequate testing and verification before deploying a trading program to ensure the robustness and reliability of the program.