Pinned Repositories
artificial-intelligence-for-trading
Content for Udacity's AI in Trading NanoDegree.
black-scholes
Black Scholes formula and greeks
BootstrapSwapYieldCurve
Get discount factors and zero rates from interest rate swaps
bqplot
Plotting library for IPython/Jupyter Notebooks
bsoption
Package for option pricing and volatility calibration for index (and FX) options
CalibreLibgenStore
A Libgen Fiction store plugin for Calibre
clasemlMP
Clase de Machine Learning para Monte de Piedad
Diplomado_Metodos_cuantitativos
Material para el diplomado de métodos cuantitativos en finanzas
Est_III_2022
Estadistica_iii
Material para la clase de Estadística 3
Claudio911015's Repositories
Claudio911015/Est_III_2022
Claudio911015/Diplomado_Metodos_cuantitativos
Material para el diplomado de métodos cuantitativos en finanzas
Claudio911015/Estadistica_iii
Material para la clase de Estadística 3
Claudio911015/artificial-intelligence-for-trading
Content for Udacity's AI in Trading NanoDegree.
Claudio911015/CalibreLibgenStore
A Libgen Fiction store plugin for Calibre
Claudio911015/clasemlMP
Clase de Machine Learning para Monte de Piedad
Claudio911015/Curso_CIDPYME
Claudio911015/dash-sample-apps
Apps hosted in the Dash Gallery
Claudio911015/DeepBSDE
Deep BSDE solver in TensorFlow
Claudio911015/DeepLearningCoursera
Learning material for the Deep Learning Course
Claudio911015/DEEPSDE
Examples of SDE solved with DEEPLEARNING
Claudio911015/DSCimat
Data Science Workshop held at CIMAT on January 2020
Claudio911015/FinanceOps
Research in investment finance with Python Notebooks
Claudio911015/GMail_class
Class for GMail
Claudio911015/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Claudio911015/IR_Models
Interest Rate Models proyects
Claudio911015/Keras_projects
Claudio911015/OrderBook
Limit Order book Framework
Claudio911015/PCAapplied_and_European_Yield_Curve
This paper aims to explore the time series’ proprieties of the features extracted by using the Principal Component Analysis (PCA) technique on the European AAA-rated Government Bond Yield curve. The PCA can greatly simplify the problem of modelling the yield curve by massively reducing its dimensionality to a small set of uncorrelated features. It finds several applications in finance and in the fixed income particularly from risk management to trade recommendation. After selecting a subset of Principal Components (PCs), this paper first analyzes their nature in comparison to the original rates and the implications in terms of information retained and lost. Then the time-series characteristics of each PC are studied and, when possible, Auto-Regressive Moving-Average (ARMA) models will be fitted on the data. One hundred observations of the original dataset are set aside as a test set to evaluate the predictive power of these models. Eventually, further analyses are performed on the PCs to evaluate the presence of heteroscedasticity and GARCH-ARCH models are fitted when possible. Tests are performed on the fitted coefficient to investigate the real nature of the conditional variance process.
Claudio911015/ProdFinancierosDerivados
Material del curso de productos Financieros Derivados
Claudio911015/Py_Finance
sandbox python for finance
Claudio911015/quantFinanceCourse
Ejercicios relevantes para las clases de finanzas Cuantitativas
Claudio911015/QuantLib
The QuantLib C++ library
Claudio911015/Requests_Banxico
Python Stript to enable automatization of Banxico Data downloading through the SIE API.
Claudio911015/selenium_examples
Claudio911015/simfin-tutorials
Tutorials for SimFin - Simple financial data for Python
Claudio911015/SOFRcurve
A small jupyter notebook that creates a term structure from the implied rates of SOFR futures. Once LIBOR is gone, you might need it
Claudio911015/tcapy
Open source TCA (transaction cost analysis) Python library for FX spot
Claudio911015/tf-quant-finance
High-performance TensorFlow library for quantitative finance.
Claudio911015/UMA
Material for the Lectures given at the UMA