Expand description
Data management module.
‘Data’ includes data used for pricing, such as curves and surfaces.
Disabled by default, due to Polars increasing compile times.
You can:
- Download data from Yahoo! Finance into a Polars
DataFrame
. - Compute returns on the
DataFrame
you just downloaded.
use RustQuant::data::*;
use time::macros::date;
// New YahooFinanceData instance.
// By default, date range is: 1970-01-01 to present.
let mut yfd = YahooFinanceData::new("AAPL".to_string());
// Can specify custom dates (optional).
yfd.set_start_date(time::macros::datetime!(2019 - 01 - 01 0:00 UTC));
yfd.set_end_date(time::macros::datetime!(2020 - 01 - 01 0:00 UTC));
// Download the historical data.
yfd.get_price_history();
// Compute the returns.
// Specify the type of returns to compute (Simple, Logarithmic, Absolute)
// You don't need to run .get_price_history() first, .compute_returns()
// will do it for you if necessary.
yfd.compute_returns(ReturnsType::Logarithmic);
println!("Apple's quotes: {:?}", yfd.price_history);
println!("Apple's returns: {:?}", yfd.returns);
Apple's quotes: Some(shape: (252, 7)
┌────────────┬───────────┬───────────┬───────────┬───────────┬────────────┬───────────┐
│ date ┆ open ┆ high ┆ low ┆ close ┆ volume ┆ adjusted │
│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │
│ date ┆ f64 ┆ f64 ┆ f64 ┆ f64 ┆ f64 ┆ f64 │
╞════════════╪═══════════╪═══════════╪═══════════╪═══════════╪════════════╪═══════════╡
│ 2019-01-02 ┆ 38.7225 ┆ 39.712502 ┆ 38.557499 ┆ 39.48 ┆ 1.481588e8 ┆ 37.994499 │
│ 2019-01-03 ┆ 35.994999 ┆ 36.43 ┆ 35.5 ┆ 35.547501 ┆ 3.652488e8 ┆ 34.209969 │
│ 2019-01-04 ┆ 36.1325 ┆ 37.137501 ┆ 35.950001 ┆ 37.064999 ┆ 2.344284e8 ┆ 35.670372 │
│ 2019-01-07 ┆ 37.174999 ┆ 37.2075 ┆ 36.474998 ┆ 36.982498 ┆ 2.191112e8 ┆ 35.590965 │
│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │
│ 2019-12-26 ┆ 71.205002 ┆ 72.495003 ┆ 71.175003 ┆ 72.477501 ┆ 9.31212e7 ┆ 70.798401 │
│ 2019-12-27 ┆ 72.779999 ┆ 73.4925 ┆ 72.029999 ┆ 72.449997 ┆ 1.46266e8 ┆ 70.771545 │
│ 2019-12-30 ┆ 72.364998 ┆ 73.172501 ┆ 71.305 ┆ 72.879997 ┆ 1.441144e8 ┆ 71.191582 │
│ 2019-12-31 ┆ 72.482498 ┆ 73.419998 ┆ 72.379997 ┆ 73.412498 ┆ 1.008056e8 ┆ 71.711739 │
└────────────┴───────────┴───────────┴───────────┴───────────┴────────────┴───────────┘)
Apple's returns: Some(shape: (252, 7)
┌────────────┬────────────┬───────────────┬───────────────┬───────────────┬──────────────┬──────────────┐
│ date ┆ volume ┆ open_logarith ┆ high_logarith ┆ low_logarithm ┆ close_logari ┆ adjusted_log │
│ --- ┆ --- ┆ mic ┆ mic ┆ ic ┆ thmic ┆ arithmic │
│ date ┆ f64 ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │
│ ┆ ┆ f64 ┆ f64 ┆ f64 ┆ f64 ┆ f64 │
╞════════════╪════════════╪═══════════════╪═══════════════╪═══════════════╪══════════════╪══════════════╡
│ 2019-01-02 ┆ 1.481588e8 ┆ null ┆ null ┆ null ┆ null ┆ null │
│ 2019-01-03 ┆ 3.652488e8 ┆ -0.073041 ┆ -0.086273 ┆ -0.082618 ┆ -0.104924 ┆ -0.104925 │
│ 2019-01-04 ┆ 2.344284e8 ┆ 0.003813 ┆ 0.019235 ┆ 0.012596 ┆ 0.041803 ┆ 0.041803 │
│ 2019-01-07 ┆ 2.191112e8 ┆ 0.028444 ┆ 0.001883 ┆ 0.014498 ┆ -0.002228 ┆ -0.002229 │
│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │
│ 2019-12-26 ┆ 9.31212e7 ┆ 0.000457 ┆ 0.017709 ┆ 0.006272 ┆ 0.019646 ┆ 0.019646 │
│ 2019-12-27 ┆ 1.46266e8 ┆ 0.021878 ┆ 0.013666 ┆ 0.011941 ┆ -0.00038 ┆ -0.00038 │
│ 2019-12-30 ┆ 1.441144e8 ┆ -0.005718 ┆ -0.004364 ┆ -0.010116 ┆ 0.005918 ┆ 0.005918 │
│ 2019-12-31 ┆ 1.008056e8 ┆ 0.001622 ┆ 0.003377 ┆ 0.014964 ┆ 0.00728 ┆ 0.00728 │
└────────────┴────────────┴───────────────┴───────────────┴───────────────┴──────────────┴──────────────┘)
§Read/write data
ⓘ
use RustQuant::data::*;
// New `Data` instance.
let mut data = Data::new(
DataFormat::CSV, // Can also be JSON or PARQUET.
String::from("./file/path/read.csv"), // Path to read from.
);
// Read from the given file.
data.read().unwrap();
// New path to write the data to.
data.path = String::from("./file/path/write.csv");
data.write().unwrap();
println!("{:?}", data.data);
Re-exports§
pub use io::*;
pub use yahoo::*;
pub use curves::*;
pub use market_data::*;
pub use context_data::*;
Modules§
- context_
data - Context data structures and implementations. Contextual (reference) data container.
- curves
- Base curve data structure and implementations. Curves (in the financial sense) are functions that map a time to a value, such as a yield curve or a swap curve. They may also be known as term structures depending on the context. Curves module.
- io
- File reading and writing.
- market_
data - Market data structures and implementations. Market data container.
- yahoo
- Yahoo! Finance data reader. Module to fetch data from Yahoo! Finance, and store it in a Polars DataFrame object.