معرفی شرکت ها

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

توضیحات

A simple framework for fast and dirty backtesting

ویژگی	مقدار
سیستم عامل	-
نام فایل	fastbt-0.5.1
نام	fastbt
نسخه کتابخانه	0.5.1
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	UM
ایمیل نویسنده	uberdeveloper001@gmail.com
آدرس صفحه اصلی	https://github.com/uberdeveloper/fastbt
آدرس اینترنتی	https://pypi.org/project/fastbt/
مجوز	MIT license

# Introduction **fastbt** is a simple and dirty way to do backtests based on end of day data, especially for day trading. The main purpose is to provide a simple framework to weed out bad strategies so that you could test and improve your better strategies further. It is based on the assumption that you enter into a position based on some pre-defined rules for a defined period and exit either at the end of the period or when stop loss is triggered. See the [rationale](https://github.com/uberdeveloper/fastbt/blob/master/docs/rationale.md) for this approach and the built-in assumptions. _fastbt is rule-based and not event-based._ If your strategy gets you good results, then check them with a full featured backtesting framework such as [zipline](http://www.zipline.io/) or [backtrader](https://www.backtrader.com/) to verify your results. If your strategy fails, then it would most probably fail in other environments. This is **alpha** Most of the modules are stand alone and you could use them as a single file. See embedding for more details # Features - Create your strategies in Microsoft Excel - Backtest as functions so you can parallelize - Try different simulations - Run from your own datasource or a database connection. - Run backtest based on rules - Add any column you want to your datasource as formulas # Installation fastbt requires python **>=3.6** and can be installed via pip ``` pip install fastbt ``` # Quickstart Fastbt assumes your data have the following columns (rename them in case of other names) - timestamp - symbol - open - high - low - close - volume ```python from fastbt.rapid import * backtest(data=data) ``` would return a dataframe with all the trades. And if you want to see some metrics ```python metrics(backtest(data=data)) ``` You now ran a backtest without a strategy! By default, the strategy buys the top 5 stocks with the lowest price at open price on each period and sells them at the close price at the end of the period. You can either specify the strategy by way of rules (the recommended way) or create your strategy as a function in python and pass it as a parameter ```python backtest(data=data, strategy=strategy) ``` If you want to connect to a database, then ```python from sqlalchemy import create_engine engine = create_engine('sqlite:///data.db') backtest(connection=engine, tablename='data') ``` And to SELL instead of BUY ```python backtest(data=data, order='S') ``` Let's implement a simple strategy. > **BUY** the top 5 stocks with highest last week returns Assuming we have a **weeklyret** column, ```python backtest(data=data, order='B', sort_by='weeklyret', sort_mode=False) ``` We used sort_mode=False to sort them in descending order. If you want to test this strategy on a weekly basis, just pass a dataframe with weekly frequency. See the Introduction notebook in the examples directory for an in depth introduction. ## Embedding Since fastbt is a thin wrapper around existing packages, the following files can be used as standalone without installing the fastbt package - datasource - utils - loaders Copy these files and just use them in your own modules. ========= History ========= v0.5.1 ------ * Simple bug fixes added v0.5.0 ------ * `OptionExpiry` class added to calculate option payoffs based on expiry v0.4.0 ------- * Brokers module deprecation warning added * Options module revamped v0.3.0 (2019-03-15) -------------------- * More helper functions added to utils * Tradebook class enhanced * A Meta class added for event based simulation v0.2.0 (2018-12-26) -------------------- * Backtest from different formats added * Rolling function added v0.1.0. (2018-10-13) ---------------------- * First release on PyPI

نیازمندی

مقدار	نام
>=1.0.0	pandas
<=2.0.0	sqlalchemy
>=2.0.0	pendulum
>1.15.0	streamlit
>0.55.0	numba
-	tables
-	zarr
-	openpyxl
-	xlwt
-	pydantic
>3.0.0	bokeh
-	TA-Lib
-	pytest
-	pytest-watch
-	ruff

نحوه نصب

نصب پکیج whl fastbt-0.5.1:

pip install fastbt-0.5.1.whl

نصب پکیج tar.gz fastbt-0.5.1:

pip install fastbt-0.5.1.tar.gz