Aran Sriaran
Welcome to my internet personal place! I graduated from King Mongkut's University of Technology North Bangkok (KMUTNB), popularly known as the Thai-German University, with a degree in Computer Engineering. I fell in love with investing and cryptocurrencies after working as a consultant at ODDS with the broker bank and stock exchange in Thailand. I am interested in quantitative research, algorithm trading, decentralized finance, and crypto research
Technologies
I like learning new programming languages, frameworks, and libraries. I've worked with the following technologies on side projects.
Projects
Based on my three years of experience as a software engineer and agile consultant, my huge passion has lead me to fall in love with investing. My objective is to develop data with quantitative skill and unearth important insights that can be utilized to make educated investment decisions.
Predicting ETH/USD Trade Signals with Random Forest
Learn how to build a machine learning model for predicting buy and sell signals in the ETH/USD market using the Random Forest algorithm. Gain insights into the application of ML in cryptocurrency trading and improve your strategies.
Stock Analysis and Predicting Returns with Python
Combining Multiple Datasets, Linear Regression, and Visualizing the Results
Currency Pair Correlation Analysis for Strategic Trading
A step-by-step guide to discovering currency pair correlations and leveraging them for informed trading decisions and pair trading strategies.
Analyzing Cryptocurrency Trends: Comparing Bitcoin Price and Google Search Data
A guide to creating a data visualization that compares Google Trends data with Bitcoin price, helping to analyze public interest and sentiment in the cryptocurrency market
SET50 MACD Quandrant
The Stock MACD Quadrant Chart represents an overhead analysis of MACD, including multiple Stock in a single chart.
Analyzing Market Breadth with the Advance/Decline Ratio Using Python
Discover how to analyze market trends and investor sentiment using Python and popular libraries like Pandas and Plotly Express. Learn how to calculate the Advance/Decline Ratio (ADR), an essential market breadth indicator, and create insightful visualizations to identify trends and make informed investment decisions.
Mastering Net Advance Volume Analysis with Python: A Comprehensive Guide for Investors
Discover how to analyze market breadth using the Net Advance Volume indicator in Python. Learn to leverage powerful libraries like Pandas and Plotly to handle large datasets and create insightful visualizations that help you make informed investment decisions. Boost your trading strategies by understanding the overall market sentiment and identifying potential opportunities with this comprehensive guide.
Visualizing SET Index Performance: Creating a Heat Map Chart
Explore how to create a heat map chart for the SET Index, showcasing its monthly percentage changes over the past decade. Utilize Python libraries like pandas, matplotlib, and seaborn to process and visualize SET Index data for a comprehensive analysis.
Stock Price Forecasting with Monte Carlo Simulation
Learn how to create a Monte Carlo Simulation for stock price forecasting
Demystifying the PE Band Chart: A Comprehensive Guide for Stock Valuation
Unlock the secrets of the PE Band Chart and enhance your stock valuation skills with this all-inclusive guide on creating and interpreting PE Bands
The PE Band Chart Analysis - Visualize Historical Stock Valuation
Uncover the potential overvaluation or undervaluation of stocks with our PE Band Chart Analysis. Compare the current P/E ratio with historical trends to make informed investment decisions.
SET Index Valuation Insights: Exploring the PE Band Chart
Discover how to create a PE Band Chart for the SET Index, enabling investors to analyze historical trends, assess market conditions, and make more informed investment decisions. Learn how to use Python, pandas, and matplotlib to process and visualize stock market data for a comprehensive understanding of market valuations.