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Bitcoin Algorithm Trading Bot Development

Create your own revenue model with programming.

(4.6) 수강평 26개

강의소개.상단개요.수강생.short

난이도 입문

수강기한 무제한

Pandas
Pandas
Investment
Investment
Quant
Quant
Pandas
Pandas
Investment
Investment
Quant
Quant

먼저 경험한 수강생들의 후기

먼저 경험한 수강생들의 후기

4.6

5.0

배코드

89% 수강 후 작성

Pros It was a lecture that packed a lot into a short period of time. Because the breathing was short, I was able to learn a lot in a short period of time. 1. In the technical analysis theory, the background and explanation for each indicator were well explained, so the explanation was short, but it was easy to understand because only the necessary parts were explained concisely. It was good to be able to learn the numbers and meanings of each indicator in a short period of time. 2. The explanation of the data analysis library Pandas was easy to understand. 3. I think I understood the theory of algorithm improvement (grid search, Bayesian probability), but it was not as easy as I thought when actually coding. 4. It was easy to modify the trading bot by looking at the actual completed code. Cons I confirmed that the algorithm related to long-term trends, short-term price fluctuations, and short-term trading volume provided here did not generate profits no matter how well the parameters were given and the backtesting period was extended during the backtest. I learned that trading strategies are important, but I wish there were lectures related to trading strategies later.

5.0

기후니

21% 수강 후 작성

I was wondering what a trading bot was, but after watching the whole lecture, I now have a feel for it. I think you can make a profit by using Bollinger Bands.

5.0

조정교

84% 수강 후 작성

I'm a complete beginner, but this was a helpful lecture. I think you explain it well and easily. I need to study a little more and make my own trading bot.

강의상세_배울수있는것_타이틀

  • Theory of technical analysis, theories such as technical analysis indicators

  • Programming such as Pandas basics, backtest development, and trading bot development

Attention to those curious about developing trading bots!
Implement your own revenue model 💸

Course Overview 📖

Create a trading bot for asset investment!

Basic technical analysis theory for algorithmic trading,
Learn how to use open APIs, backtest, and implement programs.
We reduce the risk and time required to develop trading bots.

I'm developing a Bitcoin algorithmic trading program (trading bot) for a new future. I've gone through a lot of trial and error, and experienced a few failures. I created this course for those who, like me, have developed or want to develop their own trading bot. I'll save you the time and money I spent in the past.

Why Algorithmic Trading? 📖

In emotions and greed
Unswayed
rational investment

Unlike people
Without getting tired
24/7 operation

data, algorithms
The influence is absolute
Advantageous for cryptocurrency investment

Due to high volatility
With the trading system
High profit expectations OK

  • Algorithmic trading allows you to invest rationally without being swayed by emotions and greed .
     To succeed in investing, you must trade against human desires. Algorithmic trading frees you from psychological burdens, as the program automatically invests according to established rules.
  • Algorithmic trading programs become your loyal employees, working 24/7 .
     Rather than hiring more staff to use different algorithms or invest in more assets, you can simply replicate the program and modify its logic. A well-designed trading bot will become a competent employee who won't disobey your boss.
  • Cryptocurrencies have no underlying assets , so the influence of data and algorithms is absolute .
     Cryptocurrencies have no underlying asset to analyze. Investors rely solely on data. This advantage is shared by everyone. If you develop a good algorithm based on this data, your chances of generating profits are far higher than with other assets.
  • Cryptocurrencies have the advantage of high returns due to their high volatility .
     Cryptocurrencies are inherently more volatile assets than stocks. If you develop an efficient trading algorithm, this is a field with high potential for high returns.

I recommend this to these people!

✅ Those who want to create a new revenue model using the program

✅ For those who want to make rational investments based on data

Course Features 📖 

  • We will explain the basic theories and indicators for technical analysis.

  • We'll explain step-by-step how to use the Upbit trading screen and how to utilize the open API.

  • Explains practical backtesting techniques.

  • We provide a sample of a scalable trading bot.

  • We provide algorithms that are profitable based on backtesting.       

What you'll learn 📖

  • Technical Analysis Theory and Indicators
    • Essential basic theories for developing trading algorithms
    • Technical analysis theories such as Dow Theory, Elliott Wave Theory, and Wyckoff Method
    • Basic terms such as trends, support and resistance lines, divergence, and oscillators.
    • Moving Average (MV), Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI),
    • Stochastic RSI (StochRSI), Bollinger Bands,
    • Volume Weighted Average Price (VWAP), Parabolic SAR (PSAR), etc.
  • How to use Upbit
    • From opening an account to easily understanding Upbit, the largest cryptocurrency exchange in Korea
    • Coin types, coin purchases, and how to use various screens.
  • Setting up the development environment and Pandas basics
    • How to use the programs and development tools required to develop algorithmic trading programs.
    • How to easily use Pandas, a key tool for data analysis and utilization.
  • Collecting data
    • How to automatically collect 1-minute transaction data from the Upbit site
    • How to save and load collected data files
  • Technical Indicator Programming
    • How to Calculate Technical Indicators Using 1-Minute Trading Data and How to Use the TA (Technical Analysis) Package
  • Upbit Open API
    • A comprehensive review of the open API provided by Upbit.
    • Testing various trading and inquiry functions through direct coding
  • Trading Strategies, Backtesting, and Tuning
    • Implementation of a counter-trend strategy algorithm, a representative trading strategy.
    • Virtually test (backtest) whether the collected data can be used to generate profits.
    • Grid search and Bayesian optimization for algorithm optimization
  • Implementing a Trading Bot
    • Implement data collection, technical indicator calculations, and other common functions as reusable modules.
    • Implement a counter-trend strategy using take-profit and minimize-loss orders.

Note 📖

  • After sufficient testing, you should gradually increase your investment assets.
    • You can generate profits for a certain period of time using the trading bot provided in this course , and you can also generate profits with a program you have improved yourself .
    • However , since a profitable model can immediately incur losses when market conditions change, we recommend that you increase your investment assets after accumulating sufficient practical experience over a long period of time (more than 3 months ) .
  • The robobits program provided in this lecture is not a program that guarantees profits .
    • It's not enough to just listen to the lectures and test the program to see if it works.
    • The robobits program provided in this course only provides the basic framework for algorithmic trading.
  • You must create your own algorithm .
    • You need to create your own algorithm using various technical analysis indicators.
    • To create a profitable model, you need to continuously monitor and optimize your algorithm.
  • MacBook users can also take this course without any problems. Please note.

강의소개.콘텐츠.추천문구

학습 대상은 누구일까요?

  • Passionate about creating new revenue models using the program

  • For those who want to make rational investments based on data

강의소개.지공자소개

909

수강생

59

수강평

115

답변

4.7

강의 평점

6

강의_other

Multicore is a programmer and AI expert. He has been active in various fields as a programmer and currently works at a company improving business environments using data analysis and reinforcement learning. He strives to show his juniors that AI is not a field reserved only for a few experts with advanced degrees, but an area that programmers can also successfully challenge. He is the author of "Reinforcement Learning for Programmers."

 

  • Publications and Certifications

  1. Reinforcement Learning Through Code, Like a Developer (2025) / Freelec

  2. A Study on Improving Deepfake Image Classification through Deepfake Model Analysis (2024) / Korea Institute of Convergence Security (KICS)

  3. Writing a Bitcoin Futures Automated Trading System (2022) / Freelec

  4. Reinforcement Learning for Programmers (2021) / Freelec

  5. Research on Browser Fuzzing Techniques Using Multiple DOM Trees (2017) / Yonsei University

     

  6. Obtained Information System Principal Auditor Certification (2015) / Korea Information System Audit Association

     

  7. Professional Engineer Computer System Application (2013) / Human Resources Development Service of Korea

  • Corporate and individual lecture inquiries: multicore.it@gmail.com

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수강평

전체

26개

4.6

26개의 수강평

  • nanamjk8391님의 프로필 이미지
    nanamjk8391

    수강평 3

    ∙

    평균 평점 5.0

    5

    16% 수강 후 작성

    This is a lecture I found while looking for a Bitcoin automatic trading lecture. While other lectures focus on explaining theories, this lecture has the unique feature of providing a program that operates like an actual trading bot. If I study the trading technique a little, I might see results. The Bollinger Band trading technique you added additionally feels a little frustrating because trading doesn't happen often. Is there a way to shorten the trading time a little? I think this program could be applied to stocks. It seems that not developing a separate user screen has the advantage of saving time, but on the other hand, it feels a little frustrating. Anyway, it was an interesting lecture.

    • multicoreit
      지식공유자

      Hello, Baguette. Thank you for taking the course and giving me good opinions. First, I will talk about the Bollinger Band trading technique. The Bollinger Band technique is inherently not traded frequently. It is not common for the asset price to fall below the band, and in the code, it is purchased when the current price falls below the band at a timing when the 120-minute weighted moving average is greater than the 240-minute weighted moving average. This happens even less often. The core of the Bollinger Band trading technique is to purchase at an accurate timing rather than frequent trading. However, if you lower the stop loss and take profit ratio a little, you may be able to reduce the trading time a little. Next, you gave me an opinion about the UI, and I also thought about this when I first created the course. Although it is convenient to have a UI, it takes a lot of time and effort for those who are not familiar with Python UI to learn it. So I thought about focusing on the algorithm rather than the UI. I am thinking of adding full-scale UI development in the next course. Providing a UI means that you have to provide many functions that users can conveniently use, such as data collection, backtesting, various algorithm option management, and coin selection through the UI. Therefore, I think you should create a lecture for intermediate and advanced users, not beginners. Thank you again for your good opinion, Baguette. I will always try to develop the lecture into one that is helpful to students.

  • willable6748님의 프로필 이미지
    willable6748

    수강평 1

    ∙

    평균 평점 5.0

    5

    21% 수강 후 작성

    I was wondering what a trading bot was, but after watching the whole lecture, I now have a feel for it. I think you can make a profit by using Bollinger Bands.

    • multicoreit
      지식공유자

      Hello, Ki-Gi-nim. Thank you for taking the course. There are various technical indicators other than Bollinger Bands. It is important to analyze several technical indicators together on the Upbit chart screen and find an indicator that explains the trading timing well. This is the beginning of algorithmic trading. You can create an algorithm using these indicators, then verify the algorithm through backtesting and integrate it into a trading bot. I hope you have good results in the future. Thank you.

  • sumiface6726님의 프로필 이미지
    sumiface6726

    수강평 1

    ∙

    평균 평점 5.0

    5

    89% 수강 후 작성

    Pros It was a lecture that packed a lot into a short period of time. Because the breathing was short, I was able to learn a lot in a short period of time. 1. In the technical analysis theory, the background and explanation for each indicator were well explained, so the explanation was short, but it was easy to understand because only the necessary parts were explained concisely. It was good to be able to learn the numbers and meanings of each indicator in a short period of time. 2. The explanation of the data analysis library Pandas was easy to understand. 3. I think I understood the theory of algorithm improvement (grid search, Bayesian probability), but it was not as easy as I thought when actually coding. 4. It was easy to modify the trading bot by looking at the actual completed code. Cons I confirmed that the algorithm related to long-term trends, short-term price fluctuations, and short-term trading volume provided here did not generate profits no matter how well the parameters were given and the backtesting period was extended during the backtest. I learned that trading strategies are important, but I wish there were lectures related to trading strategies later.

    • multicoreit
      지식공유자

      Hello, Baecode. Thank you for your detailed course review. I tried hard to reduce unnecessary content during the theory lecture and convey only the essential content. Looking at Baecode's course review, I think my efforts are effective and it gives me a lot of strength. I am currently preparing various contents related to algorithm trading. I will actively reflect Baecode's opinions (supplementing the trading strategy part) to create better lectures. Thank you. * Added algorithm lecture using Bollinger Band. I confirmed that about 70% profit was generated over 9 months through backtesting. I will develop a more improved algorithm and upload additional lectures in the future. * Added trend adaptive algorithm. Based on backtesting, it is more efficient than the Bollinger Band algorithm.

  • hyukster90666님의 프로필 이미지
    hyukster90666

    수강평 21

    ∙

    평균 평점 4.6

    5

    100% 수강 후 작성

    I listened to this lecture almost 4 times. At first, I didn't understand it, so the lecture was too difficult. However, after reading the lecture content quickly, listening to the concept, and implementing it myself, it really became mine. I think many people will get stuck in the beginning part of the backtest. (You have to spend a lot of time and implement it yourself) (In my case, I did this and that in the backtest part, so there was a part where I did the backtest for almost a week, and it was a good opportunity to think about many things.) After watching it again and again, I realized that this lecture was more informative than other lectures. Other coin or stock lectures don't have much content, but the price is really expensive. However, this lecture explains the basic indicators in detail, and teaches how to do backtesting, and how to apply it to the actual coin market. After listening to this lecture, I thought I would study TA. If you are good at TA, you can set up a strategy and make it into a bot. In my case, after completing this course, I thought I had nothing more to do with programming (making bots), so I am gifting from Binance to train my TA. (I am studying DJANGO to make my own bot in the future) If there is a future course, I hope it will be focused on TA. (And Binance gift bots) Thank you.

    • multicoreit
      지식공유자

      Hello, Dong-hyuk Kim. Judging from your review, it seems like your skills have improved a lot. It seems like you are going in the right direction. The core of algorithmic trading is technical indicators. At first, I tried making algorithms using various methods (statistics, machine learning, artificial neural networks, etc.), but the algorithm that utilized technical indicators was the most efficient. TA (Technical Analysis) is an easy-to-use implementation of technical indicators in Python. If you study TA in depth, you will be able to create algorithms with higher returns. You said you are currently trading futures, but I am also investing in Bitcoin spot (Upbit) and futures (Binance) at the same time. In theory, futures can make profits in both rising and falling markets by utilizing long/short options, but in reality, this is often not the case. Rather, there are many cases where spot investment has better returns. Of course, this is also a problem depending on the algorithm and the product you are investing in. However, in the case of futures, there is a risk of account liquidation when using a lot of leverage, and legal issues have not been resolved. I think the following article will help you make a decision. https://www.coindeskkorea.com/news/articleView.html?idxno=75446 Mr. Dong-hyuk Kim requested additional lectures on TA, so I will consider it when I make the revised lecture. Since this is my first time making a lecture on algorithmic trading, I have many regrets. I will listen to the opinions of the students and make a better lecture. I wish you success, Dong-hyuk Kim. Thank you.

  • chojungkyo2609님의 프로필 이미지
    chojungkyo2609

    수강평 1

    ∙

    평균 평점 5.0

    5

    84% 수강 후 작성

    I'm a complete beginner, but this was a helpful lecture. I think you explain it well and easily. I need to study a little more and make my own trading bot.

    • multicoreit
      지식공유자

      Hello, Jo Jeong-gyo. Thank you for taking the class. I tried hard to explain it easily, and it is encouraging to receive good reviews about it. I will try to make better classes in the future. Thank you.

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