MF_MBS_Default_Risk | Analysis of multifamily mortgage backed security default

by bentruitt Python Version: Current License: No License

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

kandi X-RAY | MF_MBS_Default_Risk Summary

MF_MBS_Default_Risk is a Python library typically used in Financial Services, Banks, Payments applications. MF_MBS_Default_Risk has no bugs, it has no vulnerabilities and it has low support. However MF_MBS_Default_Risk build file is not available. You can download it from GitHub.

The focus of this analysis is to approximate the probability of default for multifamily mortgages. I have worked in the area of multifamily lending for about 10 years. I have done everything from underwrite to originate to the sale of securities to large investment banks that would re-securitize the loans for consumers such as large institutional investors and hedge funds. The loan data that I will be using for this analysis represents the performance of Freddie Mac multifamily loans. Freddie Mac is the nickname used for the Federal Home Loan Mortgage Corporation (FHLMC). Freddie Mac works in partnership with a network of nationwide lenders to provide loans for both single-family and multifamily mortgages. A single-family property is defined as 1-4 units. A single-family mortgage is what you think of if you were to get a mortgage on your home. You may already have a Freddie Mac mortgage and not know it. A multifamily mortgage is what is provided for an apartment building or complex. A multifamily property is 5 units or more. An example of a multifamily property is 1600 Glenarm Place in Denver, CO. The focus of this analysis will be only multifamily mortgages.

Support

Quality

Security

License

Reuse

Support

MF_MBS_Default_Risk has a low active ecosystem.

It has 27 star(s) with 10 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

MF_MBS_Default_Risk has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of MF_MBS_Default_Risk is current.

Quality

MF_MBS_Default_Risk has 0 bugs and 0 code smells.

Security

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

MF_MBS_Default_Risk code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

MF_MBS_Default_Risk 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

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

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

Installation instructions are not available. Examples and code snippets are available.

MF_MBS_Default_Risk saves you 352 person hours of effort in developing the same functionality from scratch.

It has 841 lines of code, 17 functions and 6 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed MF_MBS_Default_Risk and discovered the below as its top functions. This is intended to give you an instant insight into MF_MBS_Default_Risk implemented functionality, and help decide if they suit your requirements.

Plot confusion matrix .
Map Pandas DataFrame to Pandas dataframe
Clean dataframe .
Plot ROC curve .
Plot histograms .
Plot the ROC curve .
Perform a grid search using the grid search .
Bootstrap a dataset .
Load data from freddie_data .
Print a table of columns .

Get all kandi verified functions for this library.

MF_MBS_Default_Risk Key Features

No Key Features are available at this moment for MF_MBS_Default_Risk.

MF_MBS_Default_Risk Examples and Code Snippets

No Code Snippets are available at this moment for MF_MBS_Default_Risk.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install MF_MBS_Default_Risk

You can download it from GitHub.
You can use MF_MBS_Default_Risk 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: