籌碼面
在台股籌碼面，我們擁有 7 種資料集，如下:
- 個股融資融劵表 TaiwanStockMarginPurchaseShortSale
- 整體市場融資融劵表 TotalMarginPurchaseShortSale
- 個股三大法人買賣表 InstitutionalInvestorsBuySell
- 整體市場三大法人買賣表 InstitutionalInvestors
- 外資持股表 Shareholding
- 股權持股分級表 TaiwanStockHoldingSharesPer
- 借券成交明細 SecuritiesLending
融資融劵表 TaiwanStockMarginPurchaseShortSale¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "TaiwanStockMarginPurchaseShortSale",
"stock_id": "2330",
"date": "2020-04-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id MarginPurchaseBuy MarginPurchaseCashRepayment MarginPurchaseLimit ... ShortSaleCashRepayment ShortSaleLimit ShortSaleSell ShortSaleTodayBalance ShortSaleYesterdayBalance
0 2019-01-02 2330 1013 7 6482595 ... 0.0 6482595 66 2782 3179
1 2019-01-03 2330 830 0 6482595 ... 0.0 6482595 133 2475 2782
2 2019-01-04 2330 2153 2 6482595 ... 0.0 6482595 496 2164 2475
3 2019-01-07 2330 296 7 6482595 ... 0.0 6482595 198 2154 2164
4 2019-01-08 2330 264 4 6482595 ... 0.0 6482595 150 2219 2154
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockMarginPurchaseShortSale",
stock_id= "2330",
date= "2020-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id MarginPurchaseBuy MarginPurchaseCashRepayment MarginPurchaseLimit
1: 2019-01-02 2330 1013 7 6482595
2: 2019-01-03 2330 830 0 6482595
3: 2019-01-04 2330 2153 2 6482595
4: 2019-01-07 2330 296 7 6482595
5: 2019-01-08 2330 264 4 6482595
6: 2019-01-09 2330 173 10 6482595
MarginPurchaseSell MarginPurchaseTodayBalance MarginPurchaseYesterdayBalance Note OffsetLoanAndShort
1: 221 13389 12604 None 6
2: 120 14099 13389 None 16
3: 1163 15087 14099 None 25
4: 1188 14188 15087 None 7
5: 201 14247 14188 None 2
6: 1147 13263 14247 None 3
ShortSaleBuy ShortSaleCashRepayment ShortSaleLimit ShortSaleSell ShortSaleTodayBalance
1: 463 0.0 6482595 66 2782
2: 440 0.0 6482595 133 2475
3: 807 0.0 6482595 496 2164
4: 208 0.0 6482595 198 2154
5: 85 0.0 6482595 150 2219
6: 136 0.0 6482595 342 2425
ShortSaleYesterdayBalance
1: 3179
2: 2782
3: 2475
4: 2164
5: 2154
6: 2219
台灣市場整體融資融劵表 TotalMarginPurchaseShortSale¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "TotalMarginPurchaseShortSale",
"stock_id": "2330",
"date": "2020-04-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
TodayBalance YesBalance buy date name sell
0 7394954 7355321 173277 2019-01-02 MarginPurchase 129650
1 7359773 7394951 132298 2019-01-03 MarginPurchase 157962
2 7279580 7359772 156698 2019-01-04 MarginPurchase 230462
3 7297059 7279573 203646 2019-01-07 MarginPurchase 180036
4 7299390 7297056 133556 2019-01-08 MarginPurchase 127360
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="TotalMarginPurchaseShortSale",
stock_id= "2330",
date= "2020-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
TodayBalance YesBalance buy date name sell
1: 7394954 7355321 173277 2019-01-02 MarginPurchase 129650
2: 7359773 7394951 132298 2019-01-03 MarginPurchase 157962
3: 7279580 7359772 156698 2019-01-04 MarginPurchase 230462
4: 7297059 7279573 203646 2019-01-07 MarginPurchase 180036
5: 7299390 7297056 133556 2019-01-08 MarginPurchase 127360
6: 7243011 7299388 205733 2019-01-09 MarginPurchase 256017
法人買賣表 InstitutionalInvestorsBuySell¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "InstitutionalInvestorsBuySell",
"stock_id": "2330",
"date": "2020-04-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id buy name sell
0 2019-01-02 2330 183000.0 Dealer_Hedging 344000.0
1 2019-01-02 2330 742000.0 Dealer_self 1375000.0
2 2019-01-02 2330 0.0 Foreign_Dealer_Self 0.0
3 2019-01-02 2330 13633825.0 Foreign_Investor 22365017.0
4 2019-01-02 2330 175000.0 Investment_Trust 166000.0
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="InstitutionalInvestorsBuySell",
stock_id= "2330",
date= "2020-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id buy name sell
1: 2019-01-02 2330 183000.0 Dealer_Hedging 344000.0
2: 2019-01-02 2330 742000.0 Dealer_self 1375000.0
3: 2019-01-02 2330 0.0 Foreign_Dealer_Self 0.0
4: 2019-01-02 2330 13633825.0 Foreign_Investor 22365017.0
5: 2019-01-02 2330 175000.0 Investment_Trust 166000.0
6: 2019-01-03 2330 1114000.0 Dealer_Hedging 81000.0
台灣市場整體法人買賣表 InstitutionalInvestors¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "InstitutionalInvestors",
"date": "2020-04-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
buy date name sell
0 3997640 2019-01-02 Foreign_Dealer_Self 7825870
1 21588186132 2019-01-02 total 31594136973
2 7084620 2019-01-03 Foreign_Dealer_Self 5933140
3 32376561148 2019-01-03 total 38612010183
4 6378810 2019-01-04 Foreign_Dealer_Self 5684420
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="InstitutionalInvestors",
date= "2020-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
buy date name sell
1: 3997640 2019-01-02 Foreign_Dealer_Self 7825870
2: 21588186132 2019-01-02 total 31594136973
3: 7084620 2019-01-03 Foreign_Dealer_Self 5933140
4: 32376561148 2019-01-03 total 38612010183
5: 6378810 2019-01-04 Foreign_Dealer_Self 5684420
6: 38029457325 2019-01-04 total 43592013337
股東結構表 Shareholding¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "Shareholding",
"stock_id": "2330",
"date": "2020-04-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id ChineseInvestmentUpperLimitRatio ForeignInvestmentRemainingShares ForeignInvestmentShares ... InternationalCode NumberOfSharesIssued RecentlyDeclareDate note stock_name
0 2019-01-02 2330 100.0 5912146944 20018233344 ... TW0002330008 25930381312 2018-05-28 None 台積電
1 2019-01-03 2330 100.0 5931491328 19998887936 ... TW0002330008 25930381312 2018-05-28 None 台積電
2 2019-01-04 2330 100.0 5957547520 19972833280 ... TW0002330008 25930381312 2018-05-28 None 台積電
3 2019-01-07 2330 100.0 5953922560 19976458240 ... TW0002330008 25930381312 2018-05-28 None 台積電
4 2019-01-08 2330 100.0 5953176576 19977203712 ... TW0002330008 25930381312 2018-05-28 None 台積電
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="Shareholding",
stock_id= "2330",
date= "2020-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id ChineseInvestmentUpperLimitRatio ForeignInvestmentRemainingShares
1: 2019-01-02 2330 100.0 5912146944
2: 2019-01-03 2330 100.0 5931491328
3: 2019-01-04 2330 100.0 5957547520
4: 2019-01-07 2330 100.0 5953922560
5: 2019-01-08 2330 100.0 5953176576
6: 2019-01-10 2330 100.0 5944186368
ForeignInvestmentShares ForeignInvestmentUpperLimitRatio InternationalCode NumberOfSharesIssued
1: 20018233344 100.0 TW0002330008 25930381312
2: 19998887936 100.0 TW0002330008 25930381312
3: 19972833280 100.0 TW0002330008 25930381312
4: 19976458240 100.0 TW0002330008 25930381312
5: 19977203712 100.0 TW0002330008 25930381312
6: 19986194432 100.0 TW0002330008 25930381312
RecentlyDeclareDate note stock_name
1: 2018-05-28 None 台積電
2: 2018-05-28 None 台積電
3: 2018-05-28 None 台積電
4: 2018-05-28 None 台積電
5: 2018-05-28 None 台積電
6: 2018-05-28 None 台積電
股東持股分級表 TaiwanStockHoldingSharesPer¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "TaiwanStockHoldingSharesPer",
"stock_id": "2330",
"date": "2020-04-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id HoldingSharesLevel people percent unit
0 2019-01-19 2330 1-999 144921.0 0.12 31366096
1 2019-01-19 2330 1,000-5,000 153113.0 1.19 311094603
2 2019-01-19 2330 10,001-15,000 9248.0 0.43 112987890
3 2019-01-19 2330 100,001-200,000 1585.0 0.85 220910983
4 2019-01-19 2330 15,001-20,000 4411.0 0.29 77704397
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockHoldingSharesPer",
stock_id= "2330",
date= "2020-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id HoldingSharesLevel people percent unit
1: 2019-01-19 2330 1-999 144921.0 0.12 31366096
2: 2019-01-19 2330 1,000-5,000 153113.0 1.19 311094603
3: 2019-01-19 2330 10,001-15,000 9248.0 0.43 112987890
4: 2019-01-19 2330 100,001-200,000 1585.0 0.85 220910983
5: 2019-01-19 2330 15,001-20,000 4411.0 0.29 77704397
6: 2019-01-19 2330 20,001-30,000 4715.0 0.44 115199487
借券成交明細 SecuritiesLending¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "SecuritiesLending",
"stock_id": "2330",
"date": "2020-04-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id transaction_type volume fee_rate close original_return_date original_lending_period
0 2019-01-02 2330 競價 122 0.1 219.5 2019-07-02 181
1 2019-01-03 2330 議借 600 0.17 215.5 2019-07-03 181
2 2019-01-04 2330 競價 178 0.1 208.0 2019-07-04 181
3 2019-01-07 2330 競價 64 0.1 213.0 2019-07-05 179
4 2019-01-08 2330 議借 450 0.59 211.0 2019-07-08 181
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="SecuritiesLending",
stock_id="2330",
date= "2020-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id transaction_type volume fee_rate close original_return_date
1: 2019-01-02 2330 競價 122 0.1 219.5 2019-07-02
2: 2019-01-03 2330 議借 600 0.17 215.5 2019-07-03
3: 2019-01-04 2330 競價 178 0.1 208.0 2019-07-04
4: 2019-01-07 2330 競價 64 0.1 213.0 2019-07-05
5: 2019-01-08 2330 議借 450 0.59 211.0 2019-07-08
6: 2019-01-09 2330 議借 3000 0.59 215.5 2019-07-09
original_lending_period
1: 181
2: 181
3: 181
4: 179
5: 181
6: 181