eBest OPEN API > API가이드 > 주식 > [주식] 시세
https://openapi.ebestsec.co.kr/apiservice?api_id=54a99b02-dbba-4057-8756-9ac759c9a2ed

• eBest OPEN API > API가이드 > 주식 > [주식] 종목검색
  https://openapi.ebestsec.co.kr/apiservice?api_id=6b67369a-dc7a-4cc7-8c33-71bb6336b6bf

• eBest OPEN API
  • API 가이드 > 주식 > [주식] 투자정보 > 재무순위종합

• Reference

  • LS증권 OPEN API > API가이드 > 주식 > 실시간 시세 (Websocket)

• Sample code

  • KOSPI호가잔량(H1_)

    from urllib2 import Request, urlopen
    from urllib import urlencode, quote_plus
    url = '/websocket/stock'
    values  = ''
    headers = {  }
    request = Request(url
    , data=values
    , headers=headers)
    request.get_method = lambda: 'POST'
    response_body = urlopen(request).read()
    print response_body

  • KOSDAQ호가잔량(HA_)

    from urllib2 import Request, urlopen
    from urllib import urlencode, quote_plus
    url = '/websocket/stock'
    values  = ''
    headers = {  }
    request = Request(url
    , data=values
    , headers=headers)
    request.get_method = lambda: 'POST'
    response_body = urlopen(request).read()
    print response_body

https://github.com/sharebook-kr/mojito

• Sequel to R : Simulation to Compare Arithmetic Mean and Geometrical Mean #30
• Try a kind of extreme distribution to get a geometric mean mean larger than its arithmetic mean

• eBest OPEN API
  • API 가이드 > 주식 > [주식] 외인/기관 > 외인기관종목별동향 (t1716)

• Improvements
  • Iterate over an array argument
  • Add text to a filename with flexibility

• 실전 투자 전략 (115) - 신용잔고 금액 전략 (systrader79)

An old request from my dear friend. I haven't forgotten ……

• Improvements
  • Resolve the issue of temporarily displaying #N/A when the stock is changed
  • Change the time display format : hhmmss -> hh:mm:ss
  • Insert a comma for thousands in the change rate

by ChatGPT

tidyquant 패키지를 사용하여 KODEX 레버리지 및 KODEX 200선물인버스2X의 일정 기간 동안의 주가, 거래량, 기관/외국인/개인 순매수 등을 다운로드하여 CSV 파일로 저장하는 예시 코드입니다:

# 필요한 라이브러리를 로드합니다
library(tidyquant)

# 다운로드 받을 종목의 심볼을 정의합니다
symbols <- c("122630.KS", "252670.KS")  # KODEX 레버리지, KODEX 200선물인버스2X

# 데이터를 다운로드할 기간을 설정합니다
start_date <- "2022-01-01"
end_date <- "2022-12-31"

# 종목 데이터를 다운로드합니다
data <- tq_get(symbols, from = start_date, to = end_date)

# 데이터프레임을 CSV 파일로 저장합니다
write.csv(data, file = "stock_data.csv")

위의 코드를 실행하면 tidyquant 패키지를 사용하여 KODEX 레버리지와 KODEX 200선물인버스2X의 주가 데이터를 다운로드하고, stock_data.csv라는 파일로 저장합니다. 다운로드 받을 기간을 start_date와 end_date 변수로 설정하고, symbols 변수에 종목 심볼을 입력하여 필요한 종목을 선택할 수 있습니다. 데이터를 다운로드한 후에는 write.csv 함수를 사용하여 데이터를 CSV 파일로 저장합니다. tidyquant 패키지는 quantmod보다 데이터 다운로드 및 가공을 간편하게 수행할 수 있는 기능을 제공합니다.

• Receive data for multiple years
• Merge them into a single DataFrame
• Save the data to a single CSV file

• eBest OPEN API
  • OAuth 인증 > 접근토큰 발급

• from ChatGPT

Here is some R code that demonstrates how to compare the arithmetic mean and geometric mean using Monte Carlo simulation:

# Set the number of simulations
n_simulations <- 10000

# Set the sample size
sample_size <- 10

# Set the range of values for the random sample
sample_range <- c(1, 10)

# Initialize vectors to store the results of the simulations
arithmetic_mean <- numeric(n_simulations)
geometric_mean <- numeric(n_simulations)

# Run the simulations
for (i in 1:n_simulations) {
  # Generate a random sample
  sample <- runif(sample_size, min = sample_range[1], max = sample_range[2])
  
  # Calculate the arithmetic mean of the sample
  arithmetic_mean[i] <- mean(sample)
  
  # Calculate the geometric mean of the sample
  geometric_mean[i] <- exp(mean(log(sample)))
}

# Calculate the mean and standard deviation of the arithmetic means
arithmetic_mean_mean <- mean(arithmetic_mean)
arithmetic_mean_sd <- sd(arithmetic_mean)

# Calculate the mean and standard deviation of the geometric means
geometric_mean_mean <- mean(geometric_mean)
geometric_mean_sd <- sd(geometric_mean)

# Print the results
print(paste("Arithmetic mean:", arithmetic_mean_mean, "±", arithmetic_mean_sd))
print(paste("Geometric mean:", geometric_mean_mean, "±", geometric_mean_sd))

This code will generate n_simulations random samples of size sample_size from a uniform distribution with a range of sample_range, and calculate the arithmetic and geometric means of each sample. It will then calculate the mean and standard deviation of the arithmetic means and the mean and standard deviation of the geometric means, and print the results.

I hope this helps! Let me know if you have any questions.

• References
  • https://numpy.org/doc/stable/reference/routines.linalg.html
  • https://www.geeksforgeeks.org/numpy-linear-algebra/
  • https://www.coursera.org/specializations/linear-algebra-data-science-python

get digests by ChatGPT

파이썬으로 배우는 오픈API 트레이딩 초급 예제 https://wikidocs.net/book/7559

03. 서비스 연결 (Oauth) https://wikidocs.net/159328

 01) 보안인증키 발급 https://wikidocs.net/159336
 02) 해쉬키(Hashkey) 발급 https://wikidocs.net/159337

• Improve this a little more, not much

  

• 업비트 개발자 센터 https://docs.upbit.com/docs

crazy