Ali Azary - Quantitative Finance & Development

About Me

Hi, I'm Ali Azary – a passionate professional exploring the fascinating world of quantitative finance, data analysis, and software development. With a strong foundation in mathematics and computer science, I bridge the gap between complex financial models and practical software solutions.

My work focuses on developing algorithmic trading strategies, building financial models, and creating data-driven applications that provide actionable insights. I believe in sharing knowledge and empowering others through clear explanations and open-source contributions.

📧 For inquiries, please contact me at contact@aliazary.com.

Quantitative Finance

Data Analysis

Software Development

Algorithmic Trading

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Books & Guides

Explore my collection of books and comprehensive guides on quantitative finance and software development.

Apps & Codes

Discover my applications and codes for quantitative finance and data analysis.

Backtester

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Latest Articles

Insights, tutorials, and research on quantitative finance and software development.

About Me

Books & Guides

Advanced Quantitative Trading (PDF Ebook + Source Codes)

App Development With PyQt5 (PDF Ebook + Source Codes)

Backtrader Essentials (PDF Ebook + Source Codes)

Moving Average Convergence (PDF Ebook + Source Codes)

The Complete Technical Analysis Guide (PDF Ebook + Source Codes)

Apps & Codes

Backtester

Latest Articles

A Bitcoin Trading Strategy With State Space Models With Python And Backtrader

A Guide To Live Trading With Backtrader On Alpaca

A Simple Long Momentum Portfolio Strategy 15% To 2400% Annual Returns!

Bitcoin Trends Stationary Wavelet Transform (SWT) With Python

Breakout Strategy With OBV And ATR Confirmation

Build Your Own AI Coding Assistant From Plan To Execution With Python And Ollama

Building And Backtesting A Multi Indicator Trading Strategy With Backtrader

Can EMA, Accumulation Distribution Oscillator, And ADX Deliver Reliable Signals

Can Kalman Filters Improve Your Trading Signals

Can The Hurst Exponent Reliably Identify Trends

Can This Adaptive Average Boost Your Strategy Full VAMA And Backtrader Example

Cointegration For Hedging

Creating A Standalone And Deployable Dash App Using PyQt5 WebEngine

Credit Risk Modeling And Credit Scores Using Logistic Regression With Python

Crypto Trading Strategy Using The Sharpe Ratio With Python Code

DCF Valuation In Excel With VBA

DCF Valuation With Python

Decision Tree Learning

Decision Trees And EMA Crossover 50% Average Annual Returns

Detrended Fluctuation Analysis (DFA)

Do Price Extremes Hold Trading Clues

Easy Entry Into Algorithmic Trading With Backtrader And Backtester

Efficient Data Management Excel Files To SQL Database

Enhancing ADX Trend Strategy With Ranging Filters, And Trailing Stops From 36% To 182% Profit

Enhancing Bollinger Bands Mean Reversion With ADX And RSI Transforming $7000 Loss Into $57000 Profit

Enhancing RSI Mean Reversion With ATR And ADX From $48000 To $131000 Profits

Extreme Value Analysis Of Stock Prices

Forecasting Bitcoin Autocorrelation With 74% Directional Accuracy Using LSTMs

How To Properly Bakctest Trading Strategies With Backtrader In Python

Integrating Live Binance Data Feed Into Backtrader For Real Time Trading Strategies

Intraday Trading Strategies

Is The Hilbert Sine Wave Effective For Timing Trend Pullbacks

MA Crossover With MACD Confirmation Building Custom Strategies With Backtester

Market Regime Detection Using Hidden Markov Models

Mastering Technical Indicators In Backtrader RSI, MACD, Bollinger Bands

Monte Carlo Simulations With Geometric Brownian Motion

Neural Networks With Kalman Filter For Trading

Practical Application Of Decision Trees In Financial Risk Management (FRM Exam Topics) With Python

Precision, Limits, Filters, Core Binance Trading Rules Every Algo Needs

Predicting Bitcoin’s Weekly Moves With 68% Accuracy Using Random Forests In Python

Quick Start Python For Finance

RSI Trend Confirmation Strategy In Backtester

Regime Filtered Risk Adjusted Momentum Strategy With Inverse Volatility Weighting 12% To 655% Annual Returns

Risk–Return Trade‑Off MPT And CAPM With Python

Significant Turning Points With Zig Zag Indicator In Python

Simulating Geometric Brownian Motion (GBM) In Python

Simulating Mean Reverting Processes In Python The CIR Model For Interest Rates

Smoothing Financial Time Series Using Kalman Filter In Python

Streamlit App For Backtesting Trading Strategies

Taming The RSI From A 60% Loss To 15% Profit By Adding Trend Filters

Time Series Forecasting With Holt Winters Theory And R Implementation

Trading Bitcoin With Adaptive Volatility

Trading Using Neural Networks

Volatility Adjusted Accumulation Distribution Oscillator For Analyzing Bitcoin Trends

Volatility Timing For Portfolio And Risk Management

What If Darwin Traded Crypto An Experiment With Evolutionary AI & Neural Nets

When Volume & Volatility Align Regression Channel Breakout With Python

Which Bitcoin Indicators Actually Predict The Next Move

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