QuantitativeDerivativeModels
InterestRateModelsCpp
MonteCarlo-MeanReversionTrading
StochasticModelsAssetPricing
Python-For-Quants
MultiLangMonteCarloSim
Topological-Risk-Measure-for-Equities
Financial-Statement-Analysis-using-Python
FXQuantPricing-Cpp
Intrinsic-Value-of-stocks
Config files for my GitHub profile.Portfolio-Management-Analysis-and-Optimization-using-Python
Nth-to-Deafult-CDO-Pricing-using-MC-with-Gaussian-Capula-Model
Investment-Portfolio-Optimisation
Hi, Do you have some savings and you wants to invest in shares but do not have any idea of how much shares to buy of which company with the minimal risk and highest return. Here you can calculate your discrete allocation of portfolio means your investmentShort-Interest-Rate-Model-Calibration
R-for-Quants
Risk-Management-Analysis-using-python-VaR-
Calculating future value at risk for Tesla stocks using historical bootstrp method.Time-difference-between-Julia-and-Python-for-option-price-valuation-
Counterparty-Credit-Risk-Model-Validation
Interest-rate-stochastic-models-prediction-
-Yield-Curve-Construction-and-IR-Analysis
Financial-Engineering-Codes
QuantConnect-Trading
Stochastic_Calculus_For_Quants
Interactions-among-default-risk-output-and-an-equilibrium-interest-rate
The model describes interactions among default risk, output, and an equilibrium interest rate that includes a premium for endogenous default risk. The decision maker is a government of a small open economy that borrows from risk-neutral foreign creditors. The foreign lenders must be compensated for default risk. The government borrows and lends abroad in order to smooth the consumption of its citizens. The government repays its debt only if it wants to, but declining to pay has adverse consequences. The interest rate on government debt adjusts in response to the state-dependent default probability chosen by government. The model yields outcomes that help interpret sovereign default experiences, including countercyclical interest rates on sovereign debt countercyclical trade balances high volatility of consumption relative to output Notably, long recessions caused by bad draws in the income process increase the governmentโs incentive to default. This can lead to spikes in interest rates temporary losses of access to international credit markets large drops in output, consumption, and welfare large capital outflows during recessions Such dynamics are consistent with experiences of many countries.Forex-Stochastic-Model
Bond-Analytics-Wrapper
Statistics-For-Quants
Scenario-and-Stress-Testing-Analysis-
Markov_Quant_Trading
Quantitative-Backtest
AIM-IT4
PPNR-Model-development-and-prediction-using-LSTM-
Exploratory-Data-Analysis
EconTracker
Yield-Curve-Construction-Using-Nelson-Siegel-Model
Bullet-Ladder-strategy-for-a-bond-portfolio
Stochastic-Volatility-and-RSI-Based-Trading-Strategy-
learning
Econometrics-in-R
Financial-Analytics-Assignment-1-AR-1-Model-
Financial-Econometrics-Resources
Libor-Market-Model-in-R
Hedging-with-the-Black-Scholes-model
FX-Swap-Credit-Exposure-Simulation
Semi-Markov-Regime-Switching-Model
Simple-RSI-strategy-on-TESLA-
YouTubeGPT
Interest-Rate-Caps-and-Floors-Valuations
Calculating-CVA-Using-Merton-and-Credit-Model
LegalAI
Ph.D-Job-Interview-Resourses
Geometric-Brownian-Paths-and-Corresponding-Greeks
Option-pricing-using-Monte-Carlo-Simulation
AnimalAI-App
Prediction-of-iris-data-sets-using-decision-tree-ML-model
IIM-Data-Science-Notebooks
Here you can see the codes executed by me during my summer internship in IIM ShillongOptimum-number-of-clusters-using-python
GATE-Economics-Resources
DSA-Codes
Here you can find codes of all data structures and algorithm using C++Explaining_DSGE_Model_with_Python_Implementation
CustomDerivative
Mathematical-Finance-Cheat-sheet
ConvertibleBondMonteCarloSim
Heart-Attack-Prediction-Using-ML
Deployed All Ml algorithms to predict whether patient will have heart disease or not.The best model is logistic regression with approximately 85% accuracyPySpark-Airport-Data-Analysis
Running some Spark SQL queries to answers some of the important use cases of this datasetForecasting-Inflation-using-VAR-Model
Quantitative-Finance---Technical-Analysis-to-VaR-uisng-Indian-Stocks
Quantitative Finance - Technical Analysis to VaR uisng Indian StocksCoVIDRBI
Portfolio-simulation-efficient-frontier-MPT-using-Python
Tha user has to specify: the list of symbols of stocks or the ETFs of interestย Recommended max number of entries: 10 a short description of each stocks or ETFs (in the same order as above) the number of portolios she/he wants to simulate. Recommended number of portfolios to simulate > 5000Marks-Prediction-based-on-study-hours-using-machine-learning.
MyResume
ResumeMy-First-Android-App
Pandas-Introduction
here you can find notes of data analysis using pandasGUI-Calculator-App
I created an App which is GUI based calculator using tkinter in pythonhull_white_swap_project
IRSim
Finalytics-App
Financial App analysis on the goNashpy-deomnstration
Myntra-reviews-analysis-using-LDA-topic-modelling-in-machine-learning
Financial-Analytics-Assignment-2-Prophet-Model
Web-App-using-Dash
This is my first web app created using Dash package in pythonCheck-file-similarity-using-this-code-
Hi, Sometimes we have a number of programming files(letโs say 20) in which some lines of codes are common. So we need to check how much percentage of similarity index between different combinations. Today I am going to give you a simple way to check the similarity percentage between python files or any files in general.Always be sure , your files should in a folder and folder should be in correct directory. Just run the above shared code and see the magic you will get csv file containing similarity value between the files.PyBlackScholes
BermudaOptionPricer
simple-chatbot-using-python-NLP
timeseries_mc
Elevated-default-risk-across-bond-markets-changes-in-interest-rates
Discretization-Methods-for-Geometric-Brownian-Motion
PyFinance
Data-Science-Projects
Handwriting-Digits-Recognizer
I got 99.6% accuracy and i used random forest model. Machine is now able to predict the digitsHistorical-analysis-of-the-Forex-market-USD-INR-using-Python
The foreign exchange market has seen significant movement in recent years. The dollar has appreciated in value relative to other currencies, especially compared to the yen. In this article we will use historical data to analyze how the dollar has changed and whether there is a relationship between the dollar and INR and Indian interest rates. The analysis will be conducted using Python. Throughout this article we will learn 1. How to get and analyze financial data 2. How Dollar-Yen exchange rate have been changing 3. Relationship between the U.S.-Japan interest rate differential and the exchange rateRegulatory-Capital-Calculation
Times-series-Forecasting-using-ARIMA-Model
Create-Beautiful-Financial-Data-Charts-in-R
Option-Pricing-GBM-vs-fGBM
QuadraticGaussianModelSimulator
Benchmarking-Pandas-CUDF-and-Polars
ZIGRAM_Data-Science_Work
NumericalPDESolver
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