quantitative | Quantitative trading : python3

by Jack-Cherish Python Version: Current License: No License

X-Ray Key Features Code Snippets(6)Community Discussions Vulnerabilities Install Support

kandi X-RAY | quantitative Summary

quantitative is a Python library. quantitative has no bugs, it has no vulnerabilities and it has medium support. However quantitative build file is not available. You can download it from GitHub.

Quantitative trading: python3

Support

Quality

Security

License

Reuse

Support

quantitative has a medium active ecosystem.

It has 1523 star(s) with 318 fork(s). There are 33 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 1 have been closed. On average issues are closed in 4 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of quantitative is current.

Quality

quantitative has no bugs reported.

Security

quantitative has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

quantitative does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

quantitative releases are not available. You will need to build from source code and install.

quantitative has no build file. You will be need to create the build yourself to build the component from source.

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quantitative Key Features

No Key Features are available at this moment for quantitative.

quantitative Examples and Code Snippets

VeloDyn -- Quantitative analysis of RNA velocity

Python

Lines of Code : 17

License : Permissive (Apache-2.0)

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@article{kimmel_latent_2021,
	title = {Differentiation reveals latent features of aging and an energy barrier in murine myogenesis},
	volume = {35},
	issn = {2211-1247},
	url = {https://www.cell.com/cell-reports/abstract/S2211-1247(21)00362-4},
	doi

A Tool-Chain for Quantitative Evaluation of Uncertainty-Aware Hybrid AADL Designs,Structures:

Java

Lines of Code : 14

License : No License

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src
├── aadl2upaal
│   ├── Application.java (main function)
│   ├── aadl
│   ├── parser
│   ├── upaal
│   └── visitor
└── examples
    ├── CTCS_MA
    │   ├── MA_with_U_uppaal.xml
    │   └── MA_

Binance Futures

Python

Lines of Code : 12

License : Strong Copyleft (GPL-3.0)

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  "entry_pricing": {
      "use_order_book": true,
      "order_book_top": 1,
      "check_depth_of_market": {
          "enabled": false,
          "bids_to_ask_delta": 1
      }
  },
  "exit_pricing": {
      "use_order_book": true,
      "order_bo

qlib - multi freq handler

Python

Lines of Code : 55

License : Permissive (MIT License)

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#  Copyright (c) Microsoft Corporation.
#  Licensed under the MIT License.

import pandas as pd

from qlib.data.dataset.loader import QlibDataLoader
from qlib.contrib.data.handler import DataHandlerLP, _DEFAULT_LEARN_PROCESSORS, check_transform_proc

qlib - hyperparameter 360

Python

Lines of Code : 40

License : Permissive (MIT License)

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import qlib
import optuna
from qlib.constant import REG_CN
from qlib.utils import init_instance_by_config
from qlib.tests.data import GetData
from qlib.tests.config import get_dataset_config, CSI300_MARKET, DATASET_ALPHA360_CLASS

DATASET_CONFIG = ge

qlib - hyperparameter 158

Python

Lines of Code : 39

License : Permissive (MIT License)

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import qlib
import optuna
from qlib.constant import REG_CN
from qlib.utils import init_instance_by_config
from qlib.tests.config import CSI300_DATASET_CONFIG
from qlib.tests.data import GetData


def objective(trial):
    task = {
        "model": {

Community Discussions

No Community Discussions are available at this moment for quantitative.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install quantitative

You can download it from GitHub.
You can use quantitative like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: