{"repo":"mgao6767/frds","free":true,"listed":false,"github":"https://github.com/mgao6767/frds","clone":"git clone https://github.com/mgao6767/frds.git","description":"Financial research data services for academics.","language":"Python","stars":107,"topics":["corporate-finance","academic","finance","measures","banking","systemic-risk","srisk","garch","garch-ccc","garch-dcc"],"license":"MIT","category":"trading","readme_excerpt":"FRDS - Financial Research Data Services frds is a Python library to simplify the complexities often encountered in financial research. It provides a collection of ready-to-use methods for computing a wide array of measures in the literature. It is developed by Dr. Mingze Gao from the Macquarie University, initially started as as a personal project during his postdoctoral research fellowship at the University of Sydney. Installation Note This library is still under development and breaking changes may be expected. If there's any issue (likely), please contact me at mingze.gao@mq.edu.au Supported measures and algorithms For a complete list of supported built-in measures, please check frds.io/measures/ and frds.io/algorithms. Supported Measures - Absorption Ratio - Contingent Claim Analysis - Distress Insurance Premium - Lerner Index (Banks) - Long-Run Marginal Expected Shortfall (LRMES) - Marginal Expected Shortfall - Option Prices - SRISK - Systemic Expected Shortfall - Z-score Algorithms - GARCH(1,1) - GARCH(1,1) - CCC - GARCH(1,1) - DCC - GJR-GARCH(1,1) - GJR-GARCH(1,1) - DCC Examples Some simple examples. Absorption Ratio For example, Kritzman, Li, Page, and Rigobon (2010) propose an Absorption Ratio that measures the fraction of the total variance of a set of asset returns explained or absorbed by a fixed number of eigenvectors. It captures the extent to which markets are unified or tightly coupled. Bivariate GARCH-CCC Use frds.algorithms.GARCHModel CCC to estimate a bivar","default_branch":null,"files":null,"tree":[],"storefront":"/r/mgao6767","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/mgao6767/frds/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}