Pinned Repositories
-Banking-Credit_Risk_Model
Credit risk modeling is the place where data science and fintech meet. It is one of the most important activities conducted in a bank, with the most attention since the recession. At present, it is the only comprehensive credit risk modeling course in Python available online – taking you from preprocessing, through probability of default (PD), loss given default (LGD) and exposure at default (EAD) modeling, all the way to calculating expected loss (EL).
-Banking_Finance-Portfolio-Risk-Management
evaluate basic portfolio risk and returns . fully automate portfolio (Banking )construction and management processes. Discover what factors are driving portfolio returns, construct market-cap weighted equity portfolios,forecast and hedge market risk via scenario generation.
500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
500 AI Machine learning Deep learning Computer vision NLP Projects with code
finance
funds are the future!
FinanceOps
Research in investment finance with Python Notebooks
financial-machine-learning
A curated list of practical financial machine learning tools and applications.
Financial-Modeling
Financial Models using vba script and Python
GARCH_Neural_Network
The estimation of GARCH parameters using neural networks
Long-Term-Stock-Price-Growth-Prediction-using-NLP-on-10-K-Financial-Reports
A 10-K FInancial Report is a comprehensive report which must be filed annually by all publicly traded companies about its financial performance. These reports are filed to the US Securities Exchange Commission (SEC). This is even more detailed than the annual report of a company. The 10K documents contain information about the Business' operations, risk factors, selected financial data, the Management's discussion and analysis (MD&A) and also Financial Statements and supplementary data. I have been expected to build an NLP pipeline that ingests 10-K reports of various publicly traded companies and build a machine learning model which can uncover the hidden signals to predict the long term stock performance of a company from the 10-K docs using the ‘Loughran McDonald Master Dictionary’. The Dictionary contain words that are specifically curated in the context of financial reports
modeling-volatility
Modeling volatility project for ODSC East 2019
AMAYadav's Repositories
AMAYadav/MTH9879-Market-Microstructure-Models
A collection of homeworks of market microstructure models.
AMAYadav/SGX-Full-OrderBook-Tick-Data-Trading-Strategy
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
AMAYadav/Barra-Multiple-factor-risk-model
Barra-Multiple-factor-risk-model
AMAYadav/CEN4020
AMAYadav/CodingInterviews
This repository contains coding interviews that I have encountered in company interviews
AMAYadav/creditR
A Credit Risk Scoring Modeling and Validation Package
AMAYadav/CVAE-Financial-Anomaly-Detection
AMAYadav/deep-algotrading
A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading
AMAYadav/deep-learning-for-order-book-price-and-movement-predictions
Limit Order Book data analysis and modeling using LSTM network
AMAYadav/FED-Interest-Rate
Prediction of the FED interest rate using features like unemployment and inflation.
AMAYadav/IbPy
Python API for the Interactive Brokers on-line trading system.
AMAYadav/Integrated-Credit-Modeling-CCAR-to-CECL
• Calculated the Capital Ratios,Risk Weighted Assets, Capital requirement over projected time horizon for both CCAR and CECL. • Created PD model using Time Series,Logistic regression,Random Forests,Neural Networks,Markov transition Matrix. • Software used various SAS 9.4, Python.
AMAYadav/Introduction-to-Python-Numerical-Analysis-for-Engineers-and-Scientist
Introduction to Python: Numerical Analysis for Engineers and Scientist. In 2017, Python became the world's most popular programming language. This course covers the basic syntax, linear algebra, plotting, and more to prepare students for solving numerical problems with Python.
AMAYadav/IPythonScripts
Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning
AMAYadav/Market-Neutral-Model
A Market Neutral Equity Model based on Barra's model
AMAYadav/MLfinance
AMAYadav/MTH9815-Asset-Backed-Security-Modeling
A project of implementing, modeling, and simulating asset-backed securities.
AMAYadav/multi-factor-model
Build a statistical risk model using PCA. Optimize the portfolio using the risk model and factors using multiple optimization formulations.
AMAYadav/neural-network-from-scratch
A Neural Network implemented from scratch (using only numpy) in Python.
AMAYadav/nn-from-scratch
Implementing a Neural Network from Scratch
AMAYadav/readings
AMAYadav/rnn-from-scratch
A Recurrent Neural Network implemented from scratch (using only numpy) in Python.
AMAYadav/scikit-learn-videos
Jupyter notebooks from the scikit-learn video series
AMAYadav/smart-beta-portfolio-optimization
Built a smart beta portfolio and compared it to a benchmark index by calculating the tracking error. Built a portfolio using quadratic programming to optimize the weights..
AMAYadav/Statistical-Models-and-Methods-for-Financial-Data
Statistical Models and Methods for Financial Data
AMAYadav/statsmodels
Statsmodels: statistical modeling and econometrics in Python
AMAYadav/Stock-Movement-Prediction-Using-LSTM
Using News to Predict Stock Movements
AMAYadav/Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
AMAYadav/Tensorflow-Tutorial
Tensorflow tutorial from basic to hard
AMAYadav/vae-dimRedFinance