As an adaptable professional with a solid background in technology, I am eager to apply my analytical and problem-solving skills to the financial market sector as an Analyst/Trader. My experience in developing and optimizing complex systems has given me a proven ability to learn new concepts and tackle challenges quickly. I am looking forward to bringing my technical expertise and a genuine curiosity to a new role where I can contribute to a financial market team and continue to grow.
Research and develop the firmware and hardware design for AIS (Automatic Identification System) transmitters and receivers. This product is utilized by maritime and ocean-fisheries institutions to track their mobile assets, such as vessels and barges, and monitor nearby maritime traffic.
Research and develop the hardware design and physics calculation for the e-feeder units, to calculate and predict the amount of fish food that should be poured into the pond automatically. Developed a new algorithm/calculation to detect how much fish food had been poured by measuring the motor's electric current consumption.
Research the minimum height and antenna configurations for the hot-air-balloon-based internet hotspot.
GPA: 3.06 Final Assignment: Design and Development of the Multi Mode Simultaneous Multi Channel Modulator Based on Software Defined Radio.
Developing a real-world trading strategy based on the insights from our Markov Chain study. The strategy presented is a live trading strategy that I personally use, with only minor parameter differences from my own settings.
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This project provides a robust Python solution for determining optimal portfolio allocations based on a set of user-defined stock tickers and historical data. Utilizing the Monte Carlo Simulation technique, this tool identifies portfolios that excel across several key risk-adjusted metrics, moving beyond just the traditional Sharpe Ratio to offer a more nuanced view of capital efficiency and risk management.
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This repository hosts a robust Python simulation designed to quantitatively backtest the performance of a custom-defined stock portfolio against a major market index over a specified historical period. The portfolio's asset allocation—defined by the stock tickers and their corresponding weights—is sourced directly from a data-driven Optimal Portfolio Allocation model developed in a prior project.
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Python script to implement a backtesting simulation for a simple trading strategy using two common technical indicators: the 200-day Simple Moving Average (SMA) and a 2-period Relative Strength Index (RSI). The strategy is designed to identify and capitalize on potential buy and sell signals based on the confluence of these indicators.
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Python script to implement and backtests a multi-asset trading strategy on a portfolio of many different stock tickers. It leverages common technical indicators to generate buy and sell signals and simulates portfolio performance over historical data.
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An Example of How to Improve the Existing Trading Strategy in MQL5
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This repository contains a simple, yet robust, Pine Script trading strategy designed for use on TradingView. The strategy combines two popular technical indicators—a long-term Exponential Moving Average (EMA) for trend identification and a short-term Relative Strength Index (RSI) for entry signals—to manage buy and sell positions
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Generating "Market Seasonality" Chart for Any Market listed on Yahoo Finance
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Python script designed to backtest a monthly seasonality trading strategy for a given stock or financial instrument. A "monthly seasonality strategy" is a simple trading approach that takes advantage of historical patterns where a security's price tends to perform better during specific months of the year.
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Download and convert price data from Yahoo Finance into Metatrader 5 daily bar format
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Using markov chain to analyze first insight of a forex pair, index, or any market
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Demonstration of assessing market volatility risk using Markov Chain
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