기술적 분석 이론, 기술적 분석 지표와 같은 이론
판다스 기본, 백테스트 개발, 트레이딩 봇 개발과 같은 프로그래밍
트레이딩 봇 개발이 궁금한 분들은 주목!
나만의 수익 모델을 구현해보세요 💸
알고리즘 트레이딩을 위한 기본 기술적 분석 이론,
오픈 API 사용법, 백테스팅, 프로그램 구현 등을 학습하며
트레이딩 봇 개발에 필요한 위험과 시간을 줄여드립니다.
저는 새로운 미래를 위해 비트코인 알고리즘 트레이딩 프로그램(트레이딩 봇)을 개발하고 있습니다. 많은 시행착오를 겪었으며, 몇 번의 실패를 경험했습니다. 저와 같이 자신만의 트레이딩 봇을 개발하거나 개발하고 싶어하는 분들을 위해 이 강의를 만들었습니다. 제가 과거에 지불했던 시간과 비용을 절약해 드리겠습니다.
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24시간 365일 가동
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✅ 프로그램을 활용해서 새로운 수익 모델을 만들고자 하는 분
✅ 데이터에 기반한 합리적 투자를 원하시는 분
학습 내용 📖
학습 대상은
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프로그램을 활용해서 새로운 수익 모델을 만들고자 하는 열정 있는 분
데이터에 기반한 합리적 투자를 원하시는 분
839
명
수강생
48
개
수강평
112
개
답변
4.7
점
강의 평점
4
개
강의
멀티코어는 프로그래머이자 인공지능 전문가입니다. 프로그래머로서 다양한 분야에서 활동했으며 현재는 기업에서 데이터분석과 강화학습을 활용한 비즈니스 환경 개선 업무를 담당하고 있습니다. 인공지능이 학위를 받은 소수의 전문가만을 위한 영역이 아니라 프로그래머도 충분히 도전할 수 있음을 후배들에게 보여주기 위해 부단히 노력하고 있습니다. "프로그래머를 위한 강화학습"을 집필했습니다.
집필 및 자격사항
개발자 답게 코드로 익히는 강화학습 (2025) / 프리렉
딥페이크 모델 분석을 통한 딥페이크 이미지 분류 개선에 대한 고찰 (2024) / 한국융합보안학회
비트코인 선물 자동매매시스템 집필 (2022) / 프리렉
프로그래머를 위한 강화학습 집필 (2021) / 프리렉
멀티플 DOM 트리를 활용한 브라우저 퍼징기법 연구(2017) / 연세대학교
정보시스템 수석감리원 자격증 취득(2015) / 정보시스템감리협회
컴퓨터시스템응용기술사 (2013) / 한국산업인력공단
기업 및 개인 강의 문의 : multicore.it@gmail.com
전체
19개 ∙ (8시간 22분)
해당 강의에서 제공:
전체
26개
4.6
26개의 수강평
수강평 1
∙
평균 평점 5.0
5
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.
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.
수강평 1
∙
평균 평점 5.0
5
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.
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.
수강평 1
∙
평균 평점 5.0
5
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.
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.
수강평 3
∙
평균 평점 5.0
5
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.
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.
수강평 20
∙
평균 평점 4.8
5
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.
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.
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