|0.2.0||Jul 6, 2021|
|0.1.5||Mar 15, 2021|
|0.1.1||Feb 18, 2021|
#186 in Finance
53 downloads per month
Used in 2 crates
Purpose of this library is to provide over time a comprehensive toolbox for quantitative analysis of financial assets in rust. The project is licensed under Apache 2.0 or MIT license (see files LICENSE-Apache2.0 and LICENSE-MIT) at the option of the user.
The goal is to provide a toolbox for pricing various financial products, like bonds options or maybe even more complex products. In the near term, calculation of the discounted cash flow value of bonds is in the focus, based on what information is given by a standard prospect. Building blocks to achieve this target include time periods (e.g. "3M" or "10Y"), bank holiday calendars, business day adjustment rules, calculation of year fraction with respect to typical day count convention methods, roll-out of cash flows, and calculating valuation and risk figures like internal yield or duration that are useful for an investor in these products.
Functionality to calculate figures like fair values which are primarily of interest in scenarios where one is fully hedged are not in the initial focus, since an investor is by definition not fully hedged. Nevertheless, they might be added later for comparison and estimating market prices.
The Library is structured in a couple of sub-crates.
This crates contains definitions for basic data types, like Currencies, Stocks, Transactions, Quotes, CashFlow, etc., some basic helper tools for dealing with currencies or dates.
This crate also supports storing data, like market data, e.g. market quote information, data related to portfolio and transaction management to be able to support portfolio analysis (e.g. calculation of risk figures), and generic storage of product details (e.g. bond specification). This is done by defining data handler traits for various data categories, with concrete implementations supporting storage in a database in separate crates.
PostgreSQL is used for persistent storage of data types. The implementation is based on sqlx, which uses macros to enable query checking at compile time. In order to achieve this, a valid database must be specified, otherwise the build will fail.
Therefore, please follow the following steps to build the library:
- Setup a postgreSQL server, e.g. following the documentation on https://www.postgresql.org
- Setup a postgreSQL user named
- A small sample database could be crated by uploading the file
database/finqlpg.sqlto a database of your choice, e.g. by
psql <databasename> < data/finqlpg.sql
as some user with write permission to create new databases, e.g. PostgreSQL's default user
- export the database connection string on the command line with
for a http connection or
for a connection via UNIX socket, depending on your setup.
- build the library with
Please note that this database is only used once for building the library and performing all the compile time checks. Once the build is complete, the database handler is able to set up a new empty database.
A couple of examples shall demonstrate different usages of the library.
A simple demo program that lets you add a time period, e.g
3M for three months
-5Y for 5 years before.
This example demonstrate roll out of cash flows for fixed-rate investments by comparing two different bonds based on some key figures, e.g. yield to maturity.
A demonstration for retrieving market quote prices and storing the results persistently in a database.
Explores how to deal with transactions and how to store them in a database.
Transactions mainly define the cash flows that occur over the lifetime of an
finql, a (variable) transactions are the building
blocks for any analysis. In the end, the flow of cash flows is what makes the
distinction between the success and failure.
A demonstration of a certain strategy simulation. Here, we compare the outcome of different investment strategy into a single stock. A static investment is compared with a strategy that re-invests any cash flow into the stock, either with or without taking fee and tax payments into account. The results will be plotted to an image, see for example Total Return image
Market data quotes can be fetched automatically from various vendors and stored into a database. Fetching the (real time) quote or a quote history is implemented for the vendors yahoo! finance, alpha vantage, gurufocus and eodhistoricaldata. Please note that all except yahoo! finance require a user token that is only provided after registration with the service. For gurufocus, this required a paid license.
With version 0.8.x onwards, we use the sqlx crate, which supports compile time checks of SQL queries. This, however, requires that the environment variable DATABASE_URL is set to the appropriate connection string. For Postgres, using a unix socket connection the variable could be set to something like
Alternatively, you could follow the instructions on https://docs.rs/sqlx/0.5.1/sqlx/macro.query.html#offline-mode-requires-the-offline-feature. This requires some preparation, but without the necessity to have a live database connection.
Support for sqlite3 is no longer supported since version 0.11.
Some of the unit tests need access to a properly (but possibly empty) test database.
The access string to the database is read from the environment variable
If this variable is not set, these tests will fail with error
environment variable $FINQL_TEST_DATABASE_URL is not set'.
NOTE: Before running the test the database will be cleaned, destroying all data.
Therefore, make sure to never set this variable to the connection string for a productive database. For the same reason, the tests can not be run safely concurrently. To run the test synchronously, use
cargo test -- --test-threads=1