Julia interface to Yahoo Finance, inspired by Python's yfinance.
- Historical and intraday prices
- Fundamentals and quote summary data
- Options chains
- FX, futures, ETFs, and mutual funds
- Easy conversion to DataFrames, TimeArray, and TSFrame
using YFinance, DataFrames
prices = get_prices("AAPL", range="1mo", interval="1d")
DataFrame(prices)The package is registered in the General registry and so can be installed at the REPL with ] add YFinance or by running:
using Pkg
Pkg.add("YFinance")Yahoo!, Y!Finance, and Yahoo! finance are registered trademarks of Yahoo, Inc.
YFinance.jl is not endorsed or in any way affiliated with Yahoo, Inc. The data retrieved can only be used for personal use. Please see Yahoo's terms of use to ensure that you can use the data:
There are more examples in the Docs.
Apple monthly stock price over the past 5 years, with dividend and stock split information in local user time.
using YFinance
get_prices("AAPL",range="5y",interval="1mo",divsplits=true,exchange_local_time=false)OrderedCollections.OrderedDict{String, Any} with 8 entries:
"ticker" => "AAPL"
"timestamp" => [DateTime("2019-09-01T04:00:00"), DateTime("2019-10-01T04:00:00"), DateTime("2019-11-01T04:00:00"), DateT…
"open" => [49.9955, 54.5099, 60.4363, 64.9247, 71.9621, 73.92, 68.7337, 60.0214, 69.7003, 77.5799 … 189.83, 186.6…
"high" => [54.8369, 60.4872, 64.9072, 71.4106, 79.6407, 79.4877, 74.0224, 71.7165, 78.9507, 90.918 … 199.096, 195…
"low" => [49.4603, 52.1026, 60.3443, 62.2575, 71.1143, 62.2769, 51.7694, 57.6839, 69.6029, 77.448 … 186.958, 179…
"close" => [55.9925, 62.19, 66.8125, 73.4125, 77.3775, 68.34, 63.5725, 73.45, 79.485, 91.2 … 192.53, 184.4, 180.75…
"adjclose" => [54.2435, 60.2474, 64.7255, 71.3329, 75.1856, 66.4041, 61.9183, 71.5387, 77.4167, 89.0673 … 192.024, 18…
"vol" => [2.10248e9, 2.35721e9, 1.73731e9, 2.32113e9, 2.85125e9, 2.93375e9, 6.11666e9, 3.18033e9, 2.73292e9, 3.167…Bitcoin USD, 5 minute data points for an entire day.
DataFrame(get_prices("BTC-USD",range="1d",interval="5m",exchange_local_time=true))147×7 DataFrame
Row │ ticker timestamp open high low close vol
│ String DateTime Float64 Float64 Float64 Float64 Float64
─────┼─────────────────────────────────────────────────────────────────────────────
1 │ BTC-USD 2024-08-08T00:00:00 55139.5 55254.3 55139.5 55254.3 7.3769e6
2 │ BTC-USD 2024-08-08T00:05:00 55229.6 55355.9 55229.6 55355.9 0.0
3 │ BTC-USD 2024-08-08T00:10:00 55273.2 55273.2 55121.3 55121.3 1.9198e7
4 │ BTC-USD 2024-08-08T00:15:00 55099.8 55272.9 55099.8 55232.8 0.0
⋮ │ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮
145 │ BTC-USD 2024-08-08T12:00:00 57346.1 57406.9 57346.1 57406.9 0.0
146 │ BTC-USD 2024-08-08T12:05:00 57384.4 57384.4 57364.8 57364.8 0.0
147 │ BTC-USD 2024-08-08T12:08:00 57330.2 57330.2 57330.2 57330.2 0.0
140 rows omittedRolls-Royce daily stock price between 2020-01-01 and 2020-05-30
using TimeSeries
get_prices(TimeArray,"RR.L",startdt="2020-01-01",enddt="2020-05-30")103×6 TimeArray{Float64, 2, DateTime, Matrix{Float64}} 2020-01-02T08:00:00 to 2020-05-29T07:00:00
┌─────────────────────┬─────────┬─────────┬─────────┬─────────┬──────────┬───────────┐
│ │ open │ high │ low │ close │ adjclose │ vol │
├─────────────────────┼─────────┼─────────┼─────────┼─────────┼──────────┼───────────┤
│ 2020-01-02T08:00:00 │ 236.374 │ 238.845 │ 232.874 │ 233.766 │ 233.766 │ 1.12197e7 │
│ 2020-01-03T08:00:00 │ 232.668 │ 233.629 │ 229.03 │ 232.599 │ 232.599 │ 1.2363e7 │
│ 2020-01-06T08:00:00 │ 231.295 │ 233.766 │ 228.932 │ 232.325 │ 232.325 │ 1.13855e7 │
│ 2020-01-07T08:00:00 │ 234.041 │ 234.26 │ 227.658 │ 229.305 │ 229.305 │ 9.56679e6 │
│ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │ ⋮ │
│ 2020-05-27T07:00:00 │ 110.5 │ 126.904 │ 110.06 │ 118.771 │ 118.771 │ 7.7212e7 │
│ 2020-05-28T07:00:00 │ 109.814 │ 114.035 │ 104.049 │ 109.471 │ 109.471 │ 1.33343e8 │
│ 2020-05-29T07:00:00 │ 103.294 │ 103.946 │ 93.2044 │ 93.2044 │ 93.2044 │ 1.60135e8 │
└─────────────────────┴─────────┴─────────┴─────────┴─────────┴──────────┴───────────┘
96 rows omittedEURO-USD (EURUSD=X) daily price since start of data
using TSFrames
tsf = get_prices(TSFrame,"EURUSD=X",startdt=Date(1900,1,1),enddt=today())5399×7 TSFrame with DateTime Index
Index open high low close adjclose vol ticker
DateTime Float64 Float64 Float64 Float64 Float64 Float64 String
──────────────────────────────────────────────────────────────────────────────────────
2003-12-01T00:00:00 1.2034 1.20401 1.1944 1.1965 1.1965 0.0 EURUSD=X
2003-12-02T00:00:00 1.1961 1.2109 1.1946 1.2089 1.2089 0.0 EURUSD=X
2003-12-03T00:00:00 1.209 1.213 1.2077 1.2123 1.2123 0.0 EURUSD=X
2003-12-04T00:00:00 1.212 1.2144 1.2044 1.20809 1.20809 0.0 EURUSD=X
⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮
2024-08-05T23:00:00 1.0951 1.09631 1.09046 1.0951 1.0951 0.0 EURUSD=X
2024-08-06T23:00:00 1.09262 1.09364 1.09069 1.09262 1.09262 0.0 EURUSD=X
2024-08-08T12:41:04 1.09266 1.09481 1.09039 1.09039 1.09039 0.0 EURUSD=X
5392 rows omittedusing Plots
plot(tsf[:,[:Index,:adjclose]])
get_Fundamental("NFLX", "valuation","annual",today()-Year(3) , today()) |> DataFrame3×10 DataFrame
Row │ timestamp PegRatio ForwardPeRatio MarketCap PeRatio EnterprisesValueRevenueRatio PbRatio EnterprisesValueEBITDARatio PsRatio EnterpriseValue
│ DateTime Any Any Any Any Any Any Any Any Any
─────┼────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
1 │ 2021-12-31T00:00:00 1.4751 46.5116 267461134181 54.3228 9.6192 17.4644 14.914 9.57841 275427617181
2 │ 2022-12-31T00:00:00 2.1982 27.027 131227643270 26.3993 4.4166 6.39726 6.7377 4.238 139002027270
3 │ 2023-12-31T00:00:00 1.951 30.6748 213097477242 48.5908 6.7047 9.53074 10.686 6.71235 219530399242is=get_Fundamental("AMD", "income_statement","annual",today()-Year(1) , today()) |> DataFrame
stack(is, Not(:timestamp))49×3 DataFrame
Row │ timestamp variable value
│ DateTime String Any
─────┼─────────────────────────────────────────────────────────────────────
1 │ 2023-12-31T00:00:00 InterestExpenseNonOperating 106000000
2 │ 2023-12-31T00:00:00 CostOfRevenue 12220000000
3 │ 2023-12-31T00:00:00 TotalRevenue 22680000000
4 │ 2023-12-31T00:00:00 EarningsFromEquityInterestNetOfT… 16000000
⋮ │ ⋮ ⋮ ⋮
47 │ 2023-12-31T00:00:00 NormalizedIncome 854000000
48 │ 2023-12-31T00:00:00 EBIT 598000000
49 │ 2023-12-31T00:00:00 TotalUnusualItems 0
42 rows omittedop = get_Options("AMD")OrderedCollections.OrderedDict{String, OrderedCollections.OrderedDict{String, Vector{Any}}} with 2 entries:
"calls" => OrderedDict("contractSymbol"=>["AMD240809C00075000", "AMD240809C00080000", "AMD240809C00085000", "AMD240809C0…
"puts" => OrderedDict("contractSymbol"=>["AMD240809P00075000", "AMD240809P00080000", "AMD240809P00085000", "AMD240809P0…DataFrame(op["calls"])65×16 DataFrame
Row │ contractSymbol strike currency lastPrice change percentChange volume openInterest bid ask contractSi ⋯
│ Any Any Any Any Any Any Any Any Any Any Any ⋯
─────┼─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
1 │ AMD240809C00075000 75 USD 59.65 0 0 1 26 0 0 REGULAR ⋯
2 │ AMD240809C00080000 80 USD 52.61 0 0 1 11 0 0 REGULAR
3 │ AMD240809C00085000 85 USD 49.69 0 0 2 0 0 0 REGULAR
4 │ AMD240809C00090000 90 USD 44.54 0 0 3 12 0 0 REGULAR
⋮ │ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋱
63 │ AMD240809C00285000 285 USD 0.01 0 0 15 16 0 0 REGULAR ⋯
64 │ AMD240809C00290000 290 USD 0.08 0 0 7 10 0 0 REGULAR
65 │ AMD240809C00295000 295 USD 0.01 0 0 1 19 0 0 REGULAR
6 columns and 58 rows omitted