Algo Trading
6 articles
Statistics
Bitcoin Volatility Estimation with the Parkinson Estimator in Python
Learn how to estimate Bitcoin's volatility using the Parkinson estimator in Python with Binance data. Includes theory, implementation, and comparisons to classic volatility measures.
Statistics
Estimating Bitcoin's Volatility using a GARCH Model
Learn how to estimate and forecast Bitcoin volatility using GARCH models in Python with Binance data.
Statistics
Bitcoin Volatility Estimation with EWMA in Python
Learn how to estimate Bitcoin's realized volatility using the EWMA method in Python with Binance data.
Quantitative Finance
How to Fetch and Store Binance Data Efficiently Using HDF5 in Python
Learn how to fetch Binance candlestick data and store it efficiently using HDF5 in Python. Discover the Binance API and how to keep your data process...
Quantitative Finance
Leveraging Options Data for Stock Sentiment Analysis
Learn how Open Interest, Put/Call Ratio, and the Sizzle Index can enhance your understanding of market sentiment and stock trends
Personal project
An Introduction to Pair Trading and Market Neutral Strategies
This post is the first of a serie about pair trading and market neutral strategies ...
Computer Science
1 article
Data Engineering
1 article
Personal project
1 article
Python
7 articles
Statistics
Estimating Pi (π) with Monte Carlo Simulation in Python
Learn how to estimate the value of π using Monte Carlo simulation in Python. A step-by-step guide with math, code, and visualization.
Quantitative Finance
Merger Arbitrage Explained
Learn how to analyze merger arbitrage opportunities using the Warner Bros Discovery and Paramount deal rumors. Break down market-implied probabilities, downside risk, and expected value like...
Python
Anaconda to Create a Clean Python Environment
Learn how to use Anaconda for your Python setup, allowing you to run .py files and jupiter notebooks.
Statistics
Bitcoin Volatility Estimation with the Parkinson Estimator in Python
Learn how to estimate Bitcoin's volatility using the Parkinson estimator in Python with Binance data. Includes theory, implementation, and comparisons to classic volatility measures.
Statistics
Estimating Bitcoin's Volatility using a GARCH Model
Learn how to estimate and forecast Bitcoin volatility using GARCH models in Python with Binance data.
Statistics
Bitcoin Volatility Estimation with EWMA in Python
Learn how to estimate Bitcoin's realized volatility using the EWMA method in Python with Binance data.
Quantitative Finance
How to Fetch and Store Binance Data Efficiently Using HDF5 in Python
Learn how to fetch Binance candlestick data and store it efficiently using HDF5 in Python. Discover the Binance API and how to keep your data process...
Quantitative Finance
10 articles
Statistics
Is a Random Walk with Drift a Martingale ?
Learn how the risk-neutral measure mathematically transforms a random walk with drift into a martingale by removing its drift, with clear step-by-step explanations.
Quantitative Finance
The SDF Explained: Why Factor Models Actually Work
Learn why factor models work in finance. Beneath their growing complexity in the number of factors lies a deeper unifying idea: factor models are, at their...
Quantitative Finance
Merger Arbitrage Explained
Learn how to analyze merger arbitrage opportunities using the Warner Bros Discovery and Paramount deal rumors. Break down market-implied probabilities, downside risk, and expected value like...
Statistics
Random Walk vs Martingale: What’s the Difference
Learn the key differences between martingales and random walks in finance. Includes intuitive examples, asset pricing theory, and Python code.
Statistics
Bitcoin Volatility Estimation with the Parkinson Estimator in Python
Learn how to estimate Bitcoin's volatility using the Parkinson estimator in Python with Binance data. Includes theory, implementation, and comparisons to classic volatility measures.
Statistics
Estimating Bitcoin's Volatility using a GARCH Model
Learn how to estimate and forecast Bitcoin volatility using GARCH models in Python with Binance data.
Statistics
Bitcoin Volatility Estimation with EWMA in Python
Learn how to estimate Bitcoin's realized volatility using the EWMA method in Python with Binance data.
Quantitative Finance
How to Fetch and Store Binance Data Efficiently Using HDF5 in Python
Learn how to fetch Binance candlestick data and store it efficiently using HDF5 in Python. Discover the Binance API and how to keep your data process...
Quantitative Finance
Leveraging Options Data for Stock Sentiment Analysis
Learn how Open Interest, Put/Call Ratio, and the Sizzle Index can enhance your understanding of market sentiment and stock trends
Quantitative Finance
A closed-form filter for binary time series
The aim of this project is to study and benchmark the performance of the "Optimal Particle Filter" introduced by Fanaso and al. in 2021, with the...
Research
1 article
Statistics
7 articles
Statistics
Estimating Pi (π) with Monte Carlo Simulation in Python
Learn how to estimate the value of π using Monte Carlo simulation in Python. A step-by-step guide with math, code, and visualization.
Statistics
Is a Random Walk with Drift a Martingale ?
Learn how the risk-neutral measure mathematically transforms a random walk with drift into a martingale by removing its drift, with clear step-by-step explanations.
Statistics
Random Walk vs Martingale: What’s the Difference
Learn the key differences between martingales and random walks in finance. Includes intuitive examples, asset pricing theory, and Python code.
Statistics
Bitcoin Volatility Estimation with the Parkinson Estimator in Python
Learn how to estimate Bitcoin's volatility using the Parkinson estimator in Python with Binance data. Includes theory, implementation, and comparisons to classic volatility measures.
Statistics
Estimating Bitcoin's Volatility using a GARCH Model
Learn how to estimate and forecast Bitcoin volatility using GARCH models in Python with Binance data.
Statistics
Bitcoin Volatility Estimation with EWMA in Python
Learn how to estimate Bitcoin's realized volatility using the EWMA method in Python with Binance data.
Statistics
How to cluster time series within a bayesian framework
Let's explore a Bayesian framework enhanced by Monte Carlo simulation methods and hidden Markov chains for time series clustering.
