Insight Data Issue 03|FMZ Quant OKX: How do ordinary people master quantitative trading?

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In the cryptocurrency market, data is always an important basis for trading decisions. How to see through the complex data and discover valuable information to optimize trading strategies has always been a hot topic in the market. To this end, OKX has specially planned the Insight Data column, and cooperated with mainstream data platforms such as AICoin and Coinglass and related institutions to start from common user needs, hoping to dig out a more systematic data methodology for market reference and learning.

Insight Data Issue 03|FMZ Quant  OKX: How do ordinary people master quantitative trading?

In this issue of Insight Data, the OKX Strategy Team and the inventor of quantitative trading (FMZ) have an in-depth discussion on the concept of quantitative trading and how ordinary people can get started with quantitative trading. I hope it will be helpful to you.

OKX Strategy Team: The OKX Strategy Team is composed of a group of experienced professionals dedicated to promoting innovation in the field of global digital asset strategies. The team brings together experts in market analysis, risk management, financial engineering and other fields, and provides solid support for OKXs strategic development with deep professional knowledge and rich business experience.

FMZ Quantitative Team: Inventor Quantitative is a company that focuses on providing professional solutions for cryptocurrency quantitative trading users. Inventor Quantitative not only provides users with a full range of quantitative trading functions such as strategy writing and backtesting, quantitative trading engines, algorithmic trading services, and data analysis tools, but also has an active developer community where users can communicate and share experiences.

1. What is quantitative trading?

OKX Strategy Team: Quantitative trading is essentially a way of automatically executing trading strategies through programs using mathematical models and statistical methods. Unlike manual trading, which relies on personal decisions, quantitative trading relies on historical data, algorithms and technical indicators to analyze the market, find trading opportunities, and trade automatically. OKXs strategy robot provides powerful and flexible automated trading tools, supports multiple strategies (such as grid, Martingale strategy, etc.), and can also perform strategy backtesting and simulated trading to help users find the most suitable tools in different market environments.

FMZ Quantitative Team: Quantitative trading is also called programmatic trading, and it is not mysterious in nature. When users operate on the exchange website or software, whether it is to obtain market information, check accounts, place orders, etc., they are connected to the exchanges server through the corresponding API, so that the server can return the data required by the user. API can be loosely understood as accessing a specific network link to obtain return information. For example, opening https://www.okx.com/api/v5/public/funding-rate?instId=BTC-USDT-SWAP in a browser will get:

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

Among them, fundingRate:0.0001510608984383 is the current funding rate of the BTC-USDT perpetual contract. Modify instId=BTC-USDT-SWAP in the link to other currencies to get the corresponding funding rate information. Similarly, you only need to access the corresponding API link and fill in the appropriate parameters to basically complete the operations we complete on the website or APP. If all these processes are controlled by the program to achieve our preset purpose (trading or other), this is also quantitative trading.

In short, all the information acquisition and order-placing trading decisions were originally completed by our brains. Now, all or part of this process can be handed over to a program to execute.

2. Which type of users is it suitable for?

OKX Strategy Team: Taking OKX as an example, our quantitative trading tools are suitable for users with different backgrounds/preferences. Both novice and advanced users can quickly get started with strategies.

• For novice users (traders with little or no quantitative trading experience), we currently offer:

1) Easy-to-use interface and preset strategies. You can choose the preset strategies of the platform, such as grid strategy, fixed investment strategy, etc. These strategies usually do not require complex settings and deep market knowledge. Users only need to select and configure a small number of parameters to start using them. No programming or in-depth technical knowledge is required.

2) Simulate trading and backtesting to understand the potential performance of strategies under different parameter settings and reduce risks in real transactions. These functions help users accumulate experience before actually investing funds.

• For advanced users (traders with certain quantitative trading experience or technical capabilities), OUYI’s strategy robots also have highly customized strategies, such as grid and Martin strategies that provide rich advanced parameters, or signal strategies that can execute Trading View PineScript, which are suitable for users with programming and data analysis capabilities.

FMZ Quantitative Team: We often come into contact with the following four types of users:

• Professional traders. As a professional trader, trading is the foundation of life. They must master all advanced tools to assist themselves. Therefore, quantitative trading is almost a must for them. Professional traders often have mature and profitable strategies. By programming the strategies, they can be applied to more exchanges and trading products, multiplying the trading efficiency.

• Programming enthusiasts. For individual traders with a programming background, quantitative trading tools provide an excellent opportunity to combine programming skills with the digital currency market. They can customize trading strategies and develop trading tools according to their needs, and optimize strategy effects through backtesting. This saves a lot of learning time in the early stages.

• Traders who need effective strategies. Some traders may not have a stable trading strategy yet, and quantitative trading tools can also help them. These tools usually include strategy libraries and strategy markets, where traders can test other open source strategies and find strategies that suit them through data analysis and backtesting optimization methods.

• Ordinary traders with learning ability. Even ordinary traders without a programming background can benefit from the automation functions provided by quantitative trading tools. By using ready-made quantitative trading platforms such as FMZ Quant, they can easily set up trading strategies and use the backtesting function to evaluate the effectiveness of the strategy, thereby improving trading efficiency and reducing human errors in actual operations.

3. What are the advantages and disadvantages compared to manual trading?

OKX Strategy Team: The advantage of quantitative trading is that it is more systematic and objective. It executes transactions through preset algorithms and rules, avoiding the interference of emotions in decision-making. The trading efficiency is also very high. It can process large amounts of data and conduct high-frequency transactions, capturing market opportunities 24/7. Users can also test and optimize strategies through historical data to enhance the reliability and testability of strategies.

But quantitative trading is not perfect. First, it has a certain degree of complexity. Some advanced strategies require professional statistical and financial knowledge, and the threshold is relatively high. Second, quantitative trading may rely too much on historical data to optimize strategy parameters, and the actual market performance may not be as expected. Since market prices change according to the random walk hypothesis, past performance may not necessarily indicate future profit potential, which is called strategy overfitting. Finally, the performance of quantitative trading strategies may fluctuate under different market conditions, and constant adjustment and optimization are needed to adapt to market changes.

FMZ Quantitative Team: In fact, manual trading and quantitative trading are not in opposition. An excellent quantitative trader is often also a qualified manual trader. These two trading methods can complement each other and can be used in combination to achieve greater advantages. Excellent quantitative traders need to have a deep understanding of the market. The market is complex and changeable. Although quantitative trading relies on data and algorithms, the basis of these data and algorithms is still a deep understanding of the market. Only by understanding the operating mechanism of the market, the influencing factors, and the relationship between various assets can quantitative traders design effective trading strategies. Therefore, quantitative traders must have solid market knowledge, which is usually accumulated through manual trading.

According to our experience, there are three advantages:

1. Automate execution strategies and avoid manual intervention.

Sometimes the strategy itself is profitable, but constant human intervention leads to losses. Program trading can automatically execute preset trading strategies without human intervention. This means that traders 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 errors. The program is executed 24 hours a day, eliminating the need to watch the market for a long time.

2. It can meet the needs of transactions that rely on low latency, high frequency, and complex calculations.

Manual trading is limited by human reaction and calculation speed, which is far from comparable to program execution. These requirements can only be met by quantitative trading.

3. Quantitative trading can use historical data to backtest and optimize trading strategies.

By simulating the performance of strategies in the past market, the effectiveness of strategies can be evaluated. This method can help traders optimize strategies before real trading and increase the probability of profit. However, many manual traders trade based on their feelings and use the high time and money costs of real trading to trial and error. In fact, most quantitative strategies are dug out from data analysis.

Of course, quantitative trading is not perfect and has some disadvantages:

1. High technical requirements:

Compared with manual trading, quantitative trading requires additional programming and data analysis skills, and the threshold is relatively high. It will undoubtedly take a lot of time for quantitative novices to learn, and there is no guarantee of returns on investment.

2. Higher cost:

The construction and maintenance costs of quantitative trading systems are high, especially for high-frequency trading, which requires a lot of hardware and data resources. These fixed costs will be a hard expense regardless of whether the strategy is profitable or loss-making.

3. Market Risk:

Although quantitative trading can reduce human errors, market risks still exist and strategy failure may lead to serious losses. Quantitative strategies are written in advance and backtested based on historical data, which has certain limitations and cannot keep up with changes outside the market. Manual traders can quickly make comprehensive judgments on various information in the market and are more sensitive to changes in the market.

4. How do novice users get started?

OKX Strategy Team: In general, quantitative trading is challenging for novices, but it is not impossible to get started. Here are some suggestions to help novice users better master quantitative trading:

1. Learn the basics: First, understand the basic strategy principles and the impact of different parameter settings on strategy performance. This is the first step to success.

2. Choose a suitable strategy robot: Choose a suitable strategy robot based on your judgment of the market situation. For example, in a volatile market, the grid strategy may be a good choice.

3. Start with simple strategies: Start with the most basic trading strategies, learn and implement them step by step, and then gradually introduce more complex strategies.

4. Focus on risk management: Learn to establish and implement effective risk management and stop-loss strategies.

FMZ Quant Team: As long as program trading is mentioned, many people think that the threshold is high and the technology is complicated. In fact, learning program trading has become very simple now. The exchange integrates common strategies, and quantitative teams such as FMZ Quant will provide one-stop services. Coupled with large language models like ChatGPT to assist in programming, novice users have a very realistic and feasible path to get started or even master program trading. The only obstacle is the ability to act. If you are a user who is new to trading and has a lot of trading ideas, learning program trading will give you more power. The following are the entry steps that we think are suitable for digital currency traders without any programming foundation:

1. Be familiar with basic quantitative strategies:

Understanding the strategy trading module of OKX Exchange will help you have a preliminary understanding of strategy trading. For most traders, these functions are sufficient. If you have more ideas to implement, you can continue to learn in depth.

2. Learn a programming language:

It is recommended to learn Javascript (JS) and Python. You only need to master the basic usage. When writing strategies, you can improve quickly by learning and practicing. The JS programming language is relatively simple. There are many open source strategies from simple to complex on the FMZ platform for reference. Python is the most commonly used language for data processing. It is very convenient to combine Jupyter Notebook for statistical analysis. You can also learn some data analysis during this period. There are many related Python books and tutorials. Using Python for Data Analysis is recommended). Based on the learning foundation, it takes about 1-2 weeks to study 4 hours a day.

3. Read basic quantitative trading books:

There are many related books, which can be searched by yourself. You can read them quickly to understand the types of strategies, risk control, strategy evaluation, etc. Quantitative trading involves finance, mathematics and programming, and the content is very rich. The strategies that can really be applied to the market will not be found directly in the books. Reading related books, research reports and papers is a long process.

4. Study the exchange API documentation and related examples, and make some real-time deployment strategies:

It is recommended to get started through the FMZ quantitative platform. The rich documentation and examples greatly reduce the threshold for real trading. This step requires mastering the basic strategy framework and solving common problems, such as error handling, access frequency control, strategy fault tolerance, risk control, etc. Write some simple modules, such as price push, iceberg commission, etc., to exercise the ability to write real-time strategies. Backtest some basic strategies, such as grid, balance strategy, etc. Join relevant groups, learn to ask questions correctly and search for relevant posts.

5. Verify the strategy through backtesting and simulated trading, continuously improve it, and finally start real trading:

Skilled traders already have their own strategic ideas, and can verify and improve their strategies through backtesting and simulated trading, and finally start real trading. It is indescribable to complete a complete strategy and watch the orders automatically placed. If you don’t have your own strategy yet, you can first complete some backtesting arbitrage of open source strategies, grid strategies for multiple trading pairs, etc., to exercise your real-time programming ability.

6. Keep reading, thinking, communicating, analyzing, backtesting and practicing:

As the difficulty gradually increases and learning becomes more in-depth, your abilities will continue to improve.

5. What should you pay attention to when using quantitative trading?

OKX Strategy Team:

In fact, we believe that users need to pay attention to the following three points when using quantitative trading:

1. Quantitative trading is bound to be profitable:

Many people believe that quantitative trading relies on complex algorithms and data analysis, so it will definitely be able to make stable profits. However, quantitative trading cannot guarantee certain profits. Although quantitative strategies optimize trading decisions through data and algorithms, factors such as market uncertainty, errors in model assumptions, and overfitting of strategies may lead to losses. Quantitative trading still faces market risks and the risk of strategy failure. The key is to choose appropriate trading strategies in different market conditions and reasonably set the parameters of the corresponding strategies.

2. Quantitative trading is only suitable for large institutions and high net worth users:

Individual investors can also use the quantitative trading platforms and open source tools on the market to participate in quantitative trading. For example, the grid strategy, Martin strategy and signal strategy tools provided by OKX are all free to use. Although high-frequency trading does require high capital and technical thresholds, the above-mentioned types of strategies do not necessarily require huge amounts of capital.

3. Backtest results represent future performance:

Backtesting is only a means of evaluating a strategy, but it does not guarantee future performance. Changes in the market environment, deviations from model assumptions, and overfitting of strategies (over-optimization based on historical data) may all result in actual trading results being less than expected. Backtesting results need to be evaluated for their reliability in combination with real market conditions and robust risk management.

FMZ Quant Team: In fact, most people do not have a deep understanding of quantitative trading, which can easily lead to some misunderstandings. We have summarized these common misunderstandings and shared them with readers:

1. Will quantitative trading definitely be profitable?

Many traders turn to quantitative trading after losing money in manual trading, hoping to make a quick profit and seeing it as a lifeline. However, whether or not you make a profit depends more on the logic of the trading strategy than the tool itself. Even if you develop an ideal automatic trading strategy, you may encounter various unexpected problems in actual trading, resulting in unsatisfactory strategy results. Therefore, programmatic trading is not a guarantee of profit, but requires continuous optimization and adjustment of strategies.

2. Quantitative trading will not make mistakes?

Although quantitative trading reduces human errors, it can also introduce other errors. For example, the leakage of API-keys may lead to malicious manipulation of account funds. In addition, bugs in strategies or unhandled exceptions may lead to erroneous transactions or even catastrophic consequences. To avoid these problems, traders need to take strict security measures and conduct sufficient testing and verification before deploying trading programs to ensure the robustness and reliability of the programs.

Conclusion

The above is the third issue of the Insight Data column launched by OKX, focusing on core issues such as how to get started with quantitative trading and precautions, hoping to help interested traders understand quantitative trading more systematically and make wise trading decisions. In future series of articles, we will continue to explore more practical data usage/analysis methods to provide reference for traders with different trading preferences.

Risk Warning and Disclaimer

This article is for reference only. This article only represents the authors views and does not represent the position of OKX. This article is not intended to provide (i) investment advice or investment recommendations; (ii) an offer or solicitation to buy, sell or hold digital assets; (iii) financial, accounting, legal or tax advice. Holding digital assets (including stablecoins and NFTs) involves high risks and may fluctuate significantly. You should carefully consider whether trading or holding digital assets is suitable for you based on your financial situation. Please consult your legal/tax/investment professionals for your specific situation. Please be responsible for understanding and complying with local applicable laws and regulations.

This article is sourced from the internet: Insight Data Issue 03|FMZ Quant OKX: How do ordinary people master quantitative trading?

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