Frankline Oyolo, Misango
I am a Quantitative developer with 3+ years of entrepreneurial and contractual experience building high-performance trading systems and financial models. My mission is to democratize access to low-latency markets free to developing world traders through optimized engineering practices.
Lumibot Algorithms
Live SPY Algorithmic Backed bots for Day Trading Stocks by utilizing ALPACA / IBrokers as the REST Agents.
Algorithmic Trading and HFT Research
Quantitative research and Engineering on various promising strategies, existing quant problems and opportunities using Mathematics and Statistics with end-to-end Data Science workflows.
Trading Terminal
A Quantitative Pre-Trading Research tool for stocks, Crypto, Govt Bonds and ETFs hosted on AWS EC2. Migration to JavaScript ongoing.
HFT FPGA Accelerator
FPGA, CuDNN/CUDA & C++ Hybrid infrastructure for ultra low-latency algorithmic trading. Implements market data parsing, order book management, and strategy logic in Verilog/VHDL. Designed for Xilinx boards.
Lync
A Segmented, thin and very light accelerator core implemented in SystemVerilog, featuring ITCH market data parsing, order book reconstruction, and sub-microsecond risk-check logic.
Fluxion
A GPU-accelerated toolkit for HFT analytics. CUDA/cuBLAS/cuDNN workflows applications to financial workloads that demand massive parallel math, high throughput, and near real-time modeling.
Embeddify
A simple app to help find the most relevant job faster using NLP, Typescript, Python, Docker and PostgreSQL.
x86 Router Exploits
Reverse engineering exploit script for mikrotik routers; blueprinting for other routers. Security research on x86 router vulnerabilities.
Data Structures & Algorithms
Scholarly and Self-tutelage on Intermediate and Advanced Data Structures and Algorithms in C, Java and Python.
Congressional Signals: A Systematic Strategy for Event-Driven Market Positioning
A research note exploring how congressional activity can be transformed into a systematic signal for market positioning and event-driven trading decisions.
Crypto Macro-Fundamental Strategy: A Research Note on Macro and Fundamental Signal Integration
A research note on combining macro and fundamental inputs into a systematic framework for cryptocurrency decision-making and positioning.
- • How to Hack CCTV Cameras in a Secured Network by Jamming WPA2/3 Exchange packets (Sep 2024)
- • How to Crack WPA2 WIFI Router Password (Feb 2023)
- • How to Remotely Exploit a Windows 10 PC's Webcam using Metasploit (Feb 2023)
- • Information Gathering Series; Part B: Basic Enumeration → Whois (Apr 2023)
- • Information Gathering Series; Part A: Recon-ng (Apr 2023)
- • How to Kick People Out of a WI-FI Network (Mar 2023)
- • Website Hacking Series; Part E: Cross Site Scripting(XSS) (Mar 2023)
- • Website Hacking Series; Part D: Cross-Site Request Forgery(CSRF) (Mar 2023)
- • Website Hacking Series; Part C: Manual & Automated SQL Injection (Mar 2023)
- • PicoCTF challenges: Easiest way to tackle Transformation: 104 (Feb 2023)
- • PicoCTF challenges: Easiest way to tackle Information: 168 (Feb 2023)
- • PicoCTF challenges: Easiest way to tackle NetCat: 168 (Feb 2023)
- • Website Hacking Series; Part B: Malicious Code injection & File Upload (Feb 2023)
- • Website Hacking Series; Part A: Bruteforcing using Burpsuite (Feb 2023)
- Dec 2025: Granted The All Builders Welcome Grant by Amazon to attend the AWS Re:Invent conference in Las Vegas
- Apr 2025: Granted The All Builders Welcome Grant by Amazon to attend the AWS Reinforce conference in Philadelphia
- Mar 2025: Granted the PyconUS Travel Grant by the Python Software Foundation to attend the PyCON in Pennsylvania
- Jan 2025: Awarded the Summer @ EPFL Grant of CHF 5000 of a 1.6% competitive rate globally to complete the SURF
- Dec 2024: Granted The All Builders Welcome Grant by Amazon to attend the AWS Re:Invent conference in Las Vegas
- Apr 2023: Awarded $5000 for winning the AI Tech4good Hackathon organized by Accenture
- Sep 2022: Awarded $10,000 as African Impact Grant Award for winning the Healthcare theme by Mastercard Foundation
- Aug 2022: Granted $150,000 for 4 years, termed Future Leaders Scholarship by HKU, to study Engineering
- May 2022: Granted CHF 4000 by Glencore to attend the Swiss-African Hydrogen case challenge in Switzerland
- • AWS Machine Learning Specialty
- • AWS Solutions Architect Professional
- • Financial Modeling & Valuation Analyst (FMVA)® - Corporate Finance Institute® (CFI)
- • Android Developer Associate - Google
- • Algorithms - Stanford University
- • Algorithms, Part I - Princeton University
- • Algorithms, Part II - Princeton University
- • Financial Markets - Yale University
- • Analysis of Algorithms - Princeton University
- • Mathematics for Machine Learning - Imperial College London
- • MLOps - Duke University
- • Machine Learning - University of Colorado Boulder
- • Portfolio Construction and Analysis with Python - EDHEC Business School
- • Internet of Things and Embedded Systems - University of California, Irvine
- • Advanced Data Structures, RSA and Quantum Algorithms - University of Colorado Boulder
- • FAKE: Fake Money, Fake Teachers, Fake Assets by Robert T. Kiyosaki (2019)
- • Freakonomics: A Rogue Economist Explores the Hidden Side of Everything by Steven D. Levitt and Stephen J. Dubner (2005)
- • Why the Rich Are Getting Richer by Robert T. Kiyosaki (2017)
- • Chip War: The Fight for the World's Most Critical Technology by Chris Miller (2022)
- • The Intelligent Investor: The Definitive Book on Value Investing by Benjamin Graham (1949)
- • Everything I Know About Love by Dolly Alderton (2018)
- • Think and Grow Rich by Napoleon Hill (1937)
- • Security Analysis by Benjamin Graham and David Dodd (1934)
- • Death: An Inside Story by Sadhguru (2020)
- • Illuminating Silence: The Practice of Chinese Zen by Master Sheng-yen and Dr. John H. Crook (2002)
- • Market Wizards: Interviews with Top Traders by Jack D. Schwager (1989)
- • The Selfish Gene by Richard Dawkins (1976)
- • 1776 by David McCullough (2005)
- • The Real Book of Real Estate: Real Experts. Real Stories. Real Life. by Robert T. Kiyosaki (2009)
- • Principles for Dealing with the Changing World Order: Why Nations Succeed and Fail by Ray Dalio (2021)
- • The Federalist Papers by Alexander Hamilton, James Madison, and John Jay (1787-1788)
- Quantitative research firm managing $1,500,000 USD AUM with 4% MoM growth targeting institutional and high-net-worth clients in APAC markets
- Secured proprietary trading capital from Hong Kong Science and Technology Park alongside structured Limited Partnerships
- Enhanced collaboration with team of quantitative researchers, engineers, and data scientists from Caltech, MIT, EPFL, NUS, NTU, HKUST, and ITAM
- Built high-performance trading systems using Rust, C#, Python, C++ on AWS EC2 achieving 98.7% uptime with sub-250μs latency
- Developed 12 systematic trading strategies generating 67.3% annual returns with 14.2% volatility and max drawdown under 8%
- Implemented crypto-traditional asset correlation trading generating 34.7% annual alpha with 1.89 Sharpe ratio
- Enhanced carry strategies with GARCH forecasts achieving 28.4% annual returns on G10 portfolio with 16.3% volatility
- Implemented Black-Litterman optimization achieving 2.31 information ratio with 95% tracking error within target bands
- Incorporated satellite data, social sentiment achieving 15.7% improvement versus traditional factor models
- Modeled trade policy shocks using panel difference-in-differences with local projection estimators, generating 50k Monte Carlo paths
- Reduced DSO volatility by 42% and improved cash flow forecast RMSE by 18%
- Optimized global supplier networks through CVaR-constrained Monte Carlo simulation, releasing $2.3M working capital
- Developed 300+ SHAP-interpretable automated valuation models (R²=0.92) guiding semiconductor sales strategy with 14% EBIT uplift
- Built metadata enrichment engine processing 2.3M+ Azure Purview assets (F1-score=87.2%), increasing tag coverage from 4% to 65%
- Implemented column-level lineage tracking using Snowflake and GitOps, reducing model onboarding time by 40%
- Automated 300+ data quality checks with Great Expectations framework, reducing critical error rate by 62%
- Built Analytics dashboard using LookerML processing 12k+ user events, improving UI conversion by 75% through A/B testing
- Automated GCP ETL pipelines with Prefect orchestrator, reducing weekly reporting time from 20h to 2h
- Developed distributed web scraper harvesting 8k+/day HK job postings via Python Scrapy/Selenium
- Developed DCRNN-based spatio-temporal forecasting system for Swiss bike-sharing flows achieving 27% RMSE reduction vs baselines
- Engineered geospatial data pipeline integrating 10M+ trips with OpenStreetMap/FSO datasets (99.7% accuracy)
- Designed attention-based interpretability framework revealing station-type specific feature importance patterns
- Deployed containerized inference on EPFL HPC cluster using Kubernetes, achieving 40% latency reduction through GPU-optimized DCGRU kernels
- Engineered Meta SAM transformer-based instance segmentation pipeline (ViT-H backbone, 632M parameters) achieving 91.8% IoU
- Implemented distributed coordination algorithm for 200-node swarm robotics system using ROS2 Galactic with <5ms latency
- Fine-tuned DeepLab 3+ with Xception-65 backbone (26.5M parameters) achieving 0.87 R² on 3-year forecasts
- Architected Kubernetes-orchestrated MLOps pipeline reducing data preprocessing time by 78%
- Implemented BERT-Large (340M parameters) for semantic analysis of 30k+ student responses with 94.2% topic classification accuracy
- Developed Meta BART-based bidirectional transformer sentiment analysis system achieving F1 score of 0.89
- Engineered distributed data lake architecture (S3-compatible, 12TB capacity) enabling sub-second query response