Download Price Data

This function returns open, high, low, close, and adjusted close prices as well as volume.

For a few stocks yahoo finance will return nothing for specific timestamps in the price series.

For performance reasons and easier integration with TimeSeries.jl these nothing values are returned as NaNs. Some other packages like python's yahooquery do not return these datapoints at all. We decided to return them to indicate a break in the series and to indicate that Yahoo Finance thinks it should have price information for the specific timestamp but does not have any.

Optional Sink Argument (Julia 1.9+)

For Julia versions 1.9+ optional sink arguments can be given as the first argument. If you want to return a TimeArray from TimeSeries.jl execute get_prices(TimeArray,syombol,...). If you want to return a TSFrame from TSFrames.jl execute get_prices(TSFrame,syombol,...).

You can also covert from the OrderedDict to these by using the following function:

YFinance.sink_prices_to — Method

sink_prices_to(::Type{TimeArray}, x::OrderedDict{String, Union{String,Vector{DateTime},Vector{Float64}}})

Converts an existing OrderedDict output from get_prices to a TimeArray

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YFinance.sink_prices_to — Method

sink_prices_to(::Type{TSFrame}, x::OrderedDict{String, Union{String,Vector{DateTime},Vector{Float64}}})

Converts an existing OrderedDict output from get_prices to a TSFrame

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get_prices

YFinance.get_prices — Function

get_prices(::Type{TimeArray}, symbol::String; kwargs...)

Retrieves prices from Yahoo Finance and stores them in a TimeArray

Arguments

::Type{TimeArray}: Specifies that the output should be a TimeArray
symbol: A ticker (e.g., AAPL for Apple Inc., or ^GSPC for the S&P 500)
kwargs...: Additional keyword arguments passed to YFinance.get_prices
These can include:
- range: A string specifying the time range (e.g., "1d", "5d", "1mo", "3mo", "6mo", "1y", "2y", "5y", "10y", "ytd", "max")
- interval: The data interval (e.g., "1m", "2m", "5m", "15m", "30m", "60m", "90m", "1h", "1d", "5d", "1wk", "1mo", "3mo")
- startdt and enddt: Start and end dates (Date, DateTime, or String in "yyyy-mm-dd" format)
- prepost: Boolean for including pre and post market data
- autoadjust: Boolean for adjusting prices
- timeout: HTTP request timeout in seconds
- throw_error: Boolean for error handling behavior
- exchange_local_time: Boolean for timestamp localization
- divsplits: Boolean for including dividends and stock split data
- wait: Float for specifying wait time between API calls

For detailed information on these parameters, refer to the YFinance.get_prices documentation.

Returns

A TimeArray containing the requested price data

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get_prices(::Type{TSFrame}, symbol::String; kwargs...)

Retrieves prices from Yahoo Finance and stores them in a TSFrame

Arguments

::Type{TSFrame}: Specifies that the output should be a TSFrame
symbol: A ticker (e.g., AAPL for Apple Inc., or ^GSPC for the S&P 500)
kwargs...: Additional keyword arguments passed to YFinance.get_prices
These can include:
- range: A string specifying the time range (e.g., "1d", "5d", "1mo", "3mo", "6mo", "1y", "2y", "5y", "10y", "ytd", "max")
- interval: The data interval (e.g., "1m", "2m", "5m", "15m", "30m", "60m", "90m", "1h", "1d", "5d", "1wk", "1mo", "3mo")
- startdt and enddt: Start and end dates (Date, DateTime, or String in "yyyy-mm-dd" format)
- prepost: Boolean for including pre and post market data
- autoadjust: Boolean for adjusting prices
- timeout: HTTP request timeout in seconds
- throw_error: Boolean for error handling behavior
- exchange_local_time: Boolean for timestamp localization
- divsplits: Boolean for including dividends and stock split data
- wait: Float for specifying wait time between API calls

For detailed information on these parameters, refer to the YFinance.get_prices documentation.

Returns

A TSFrame containing the requested price data

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get_prices(symbol::String; range::String="5d", interval::String="1d", startdt::Union{Date,DateTime,AbstractString}="", enddt::Union{Date,DateTime,AbstractString}="", prepost::Bool=false, autoadjust::Bool=true, timeout::Int=10, throw_error::Bool=false, exchange_local_time::Bool=false, divsplits::Bool=false, wait::Float64=0.0)

Retrieves prices from Yahoo Finance.

Arguments

symbol: A ticker (e.g., AAPL for Apple Inc., or ^GSPC for the S&P 500)

You can either provide a range or both startdt and enddt.

range: A string specifying the time range. It can be one of the predefined values ("ytd", "max") or a custom range using the following suffixes:
- "m" for minutes (e.g., "30m" for 30 minutes)
- "d" for days (e.g., "7d" for 7 days)
- "mo" for months (e.g., "3mo" for 3 months)
- "y" for years (e.g., "1y" for 1 year)
startdt and enddt: Can be of type Date, DateTime, or a String in the format "yyyy-mm-dd". Both must be provided if one is specified.
interval: The data interval. Valid values are "1m", "2m", "5m", "15m", "30m", "60m", "90m", "1h", "1d", "5d", "1wk", "1mo", "3mo". Defaults to "1d".
prepost: Boolean indicating whether pre and post market data should be included. Defaults to false.
autoadjust: Defaults to true. Adjusts open, high, low, close prices, and volume by multiplying by the ratio between the close and the adjusted close prices - only available for intervals of 1d and up.
timeout: The timeout for the HTTP request in seconds. Defaults to 10.
throw_error: Boolean, defaults to false. If set to true, the function raises an error when the ticker is not valid or other issues occur. If false, a warning is given and an empty OrderedDict is returned.
exchange_local_time: Boolean, defaults to false. If set to true, the timestamp corresponds to the exchange local time; otherwise, it's in GMT.
divsplits: Boolean, defaults to false. If set to true, dividends and stock split data are also returned. Split data contains the numerator, denominator, and split ratio. The interval needs to be set to "1d" for this to work.
wait: Float, defaults to 0.0. Specifies the wait time in seconds between consecutive API calls when fetching minute data over extended periods.

Notes

For minute data requests over periods longer than 7 days, the function automatically splits the request into multiple 7-day chunks and combines the results.
When using startdt and enddt, both must be provided.

Returns

An OrderedDict{String, Union{String,Vector{DateTime},Vector{Float64}}} containing the requested data.

Examples

julia> get_prices("AAPL", range="1d", interval="90m")
OrderedDict{String, Union{String,Vector{DateTime},Vector{Float64}}} with 7 entries:
  "ticker"    => "AAPL"
  "timestamp" => [DateTime("2022-12-29T14:30:00"), DateTime("2022-12-29T16:00:00"), DateTime("2022-12-29T17:30:00"), DateTime("2022-12-29T19:00:00"), DateTime("2022-12-29T20:30:00"), DateTime("2022-12-29T21:00:00")]   
  "open"      => [127.99, 129.96, 129.992, 130.035, 129.95, 129.61]
  "high"      => [129.98, 130.481, 130.098, 130.24, 130.22, 129.61]
  "low"       => [127.73, 129.44, 129.325, 129.7, 129.56, 129.61]
  "close"     => [129.954, 129.998, 130.035, 129.95, 129.6, 129.61]
  "vol"       => [2.9101646e7, 1.4058713e7, 9.897737e6, 9.552323e6, 6.308537e6, 0.0]

## Can be easily converted to a DataFrame
julia> using DataFrames
julia> get_prices("AAPL", range="1d", interval="90m") |> DataFrame
6×7 DataFrame
 Row │ ticker  timestamp            open     high     low      close    vol       
     │ String  DateTime             Float64  Float64  Float64  Float64  Float64   
─────┼────────────────────────────────────────────────────────────────────────────
   1 │ AAPL    2022-12-29T14:30:00  127.99   129.98   127.73   129.954  2.9101646e7
   2 │ AAPL    2022-12-29T16:00:00  129.96   130.481  129.44   129.998  1.4058713e7
   3 │ AAPL    2022-12-29T17:30:00  129.992  130.098  129.325  130.035  9.897737e6
   4 │ AAPL    2022-12-29T19:00:00  130.035  130.24   129.7    129.95   9.552323e6
   5 │ AAPL    2022-12-29T20:30:00  129.95   130.22   129.56   129.6    6.308537e6
   6 │ AAPL    2022-12-29T21:00:00  129.61   129.61   129.61   129.61   0.0

## Broadcasting
julia> get_prices.(["AAPL","NFLX"], range="1d", interval="90m")
2-element Vector{OrderedDict{String, Union{String, Vector{DateTime}, Vector{Float64}}}}:
 OrderedDict{String, Union{String, Vector{DateTime}, Vector{Float64}}} with 7 entries:
  "ticker"    => "AAPL"
  "timestamp" => [DateTime("2022-12-29T14:30:00"), DateTime("2022-12-29T16:00:00"), DateTime("2022-12-29T17:30:00"), DateTime("2022-12-29T19:00:00"), DateTime("2022-12-29T20:30:00"), DateTime("2022-12-29T21:00:00")]
  "open"      => [127.98999786376953, 129.9600067138672, 129.99240112304688, 130.03500366210938, 129.9499969482422, 129.61000061035156]
  "high"      => [129.97999572753906, 130.4813995361328, 130.09829711914062, 130.24000549316406, 130.22000122070312, 129.61000061035156]
  "low"       => [127.7300033569336, 129.44000244140625, 129.3249969482422, 129.6999969482422, 129.55999755859375, 129.61000061035156]
  "close"     => [129.95419311523438, 129.99830627441406, 130.03500366210938, 129.9499969482422, 129.60000610351562, 129.61000061035156]
  "vol"       => [2.9101646e7, 1.4058713e7, 9.897737e6, 9.552323e6, 6.308537e6, 0.0]
 OrderedDict{String, Union{String, Vector{DateTime}, Vector{Float64}}} with 7 entries:
  "ticker"    => "NFLX"
  "timestamp" => [DateTime("2022-12-29T14:30:00"), DateTime("2022-12-29T16:00:00"), DateTime("2022-12-29T17:30:00"), DateTime("2022-12-29T19:00:00"), DateTime("2022-12-29T20:30:00"), DateTime("2022-12-29T21:00:00")]
  "open"      => [283.17999267578125, 289.5199890136719, 293.4200134277344, 290.05499267578125, 290.760009765625, 291.1199951171875]
  "high"      => [291.8699951171875, 295.4999084472656, 293.5, 291.32000732421875, 292.3299865722656, 291.1199951171875]
  "low"       => [281.010009765625, 289.489990234375, 289.5400085449219, 288.7699890136719, 290.5400085449219, 291.1199951171875]
  "close"     => [289.5199890136719, 293.46990966796875, 290.04998779296875, 290.82000732421875, 291.1199951171875, 291.1199951171875]
  "vol"       => [2.950791e6, 2.458057e6, 1.362915e6, 1.212217e6, 1.121821e6, 0.0]

## Converting it to a DataFrame:
julia> using DataFrames
julia> data = get_prices.(["AAPL","NFLX"], range="1d", interval="90m");
julia> vcat([DataFrame(i) for i in data]...)
12×7 DataFrame
 Row │ ticker  timestamp            open     high     low      close    vol       
     │ String  DateTime             Float64  Float64  Float64  Float64  Float64   
─────┼────────────────────────────────────────────────────────────────────────────
   1 │ AAPL    2022-12-29T14:30:00  127.99   129.98   127.73   129.954  2.9101646e7
   2 │ AAPL    2022-12-29T16:00:00  129.96   130.481  129.44   129.998  1.4058713e7
   3 │ AAPL    2022-12-29T17:30:00  129.992  130.098  129.325  130.035  9.897737e6
   4 │ AAPL    2022-12-29T19:00:00  130.035  130.24   129.7    129.95   9.552323e6
   5 │ AAPL    2022-12-29T20:30:00  129.95   130.22   129.56   129.6    6.308537e6
   6 │ AAPL    2022-12-29T21:00:00  129.61   129.61   129.61   129.61   0.0
   7 │ NFLX    2022-12-29T14:30:00  283.18   291.87   281.01   289.52   2.950791e6
   8 │ NFLX    2022-12-29T16:00:00  289.52   295.5    289.49   293.47   2.458057e6
   9 │ NFLX    2022-12-29T17:30:00  293.42   293.5    289.54   290.05   1.362915e6
  10 │ NFLX    2022-12-29T19:00:00  290.055  291.32   288.77   290.82   1.212217e6
  11 │ NFLX    2022-12-29T20:30:00  290.76   292.33   290.54   291.12   1.121821e6
  12 │ NFLX    2022-12-29T21:00:00  291.12   291.12   291.12   291.12   0.0

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