taoshidev/proprietary-trading-network
Nov 2024 – Jul 2025
5 Months active
Languages Used
PythonMarkdown
Technical Skills
BacktestingCode RefactoringFinancial AnalysisFinancial MetricsPerformance MetricsPython
Derek Awender
PROFILE
Derek Awender
Derek Awender developed and maintained core components of the taoshidev/proprietary-trading-network repository, focusing on robust performance metric evaluation and risk management for algorithmic trading systems. Over five months, he enhanced scoring systems, refactored drawdown and penalty logic, and improved edge-case handling for metrics like Sharpe, Sortino, and Omega. Derek applied Python and rigorous unit testing to ensure accuracy, maintainability, and transparency, introducing comprehensive test coverage and clear documentation. His work addressed both feature development and bug resolution, such as refining ledger calculations and filtering closed market days, resulting in a more reliable, maintainable, and analytically sound trading backend.
Overall Statistics
Feature vs Bugs
62%Features
Repository Contributions
30Total
Bugs
5
Commits
30
Features
8
Lines of code
4,170
Activity Months5
Your Network
10 people
Work History
July 2025
3 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary focusing on key accomplishments across taoshidev/proprietary-trading-network, including feature enhancements to scoring with AssetSegmentation testing and a bug fix for Forex closed market day filtering. This month delivered improved scoring accuracy across asset classes, expanded test coverage, and more reliable performance metrics.
3 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary focusing on key accomplishments across taoshidev/proprietary-trading-network, including feature enhancements to scoring with AssetSegmentation testing and a bug fix for Forex closed market day filtering. This month delivered improved scoring accuracy across asset classes, expanded test coverage, and more reliable performance metrics.
July 2025
February 2025
3 Commits • 1 Features
Feb 1, 2025February 2025 Monthly Summary for taoshidev/proprietary-trading-network. Focused on strengthening the accuracy and transparency of miner performance metrics and stabilizing edge-case calculations in the omega weighting utility.
February 2025
3 Commits • 1 Features
Feb 1, 2025February 2025 Monthly Summary for taoshidev/proprietary-trading-network. Focused on strengthening the accuracy and transparency of miner performance metrics and stabilizing edge-case calculations in the omega weighting utility.
January 2025
12 Commits • 2 Features
Jan 1, 2025January 2025 (2025-01) summary: Delivered two core features and fixed a critical bug in the proprietary-trading-network repository. Features include a drawdown-based Miner Elimination policy overhaul with centralized drawdown checks, updated challenge period rules, and enhanced logging; and a Scoring System Simplification and Maintenance effort that removes unused metrics and deprecated parameters while cleaning up tests. Major bug fix addressed Short-Term Risk-Adjusted Return calculation by ensuring the correct short-term lookback window and proper subset of miner returns and checkpoints. Impact includes improved accuracy of short-term performance analytics, more reliable risk controls, and a cleaner, more maintainable codebase. Technologies demonstrated include risk modeling, Python refactoring, logging instrumentation, linting with Ruff, and comprehensive test/documentation hygiene.
12 Commits • 2 Features
Jan 1, 2025January 2025 (2025-01) summary: Delivered two core features and fixed a critical bug in the proprietary-trading-network repository. Features include a drawdown-based Miner Elimination policy overhaul with centralized drawdown checks, updated challenge period rules, and enhanced logging; and a Scoring System Simplification and Maintenance effort that removes unused metrics and deprecated parameters while cleaning up tests. Major bug fix addressed Short-Term Risk-Adjusted Return calculation by ensuring the correct short-term lookback window and proper subset of miner returns and checkpoints. Impact includes improved accuracy of short-term performance analytics, more reliable risk controls, and a cleaner, more maintainable codebase. Technologies demonstrated include risk modeling, Python refactoring, logging instrumentation, linting with Ruff, and comprehensive test/documentation hygiene.
January 2025
December 2024
8 Commits • 3 Features
Dec 1, 2024December 2024 performance summary for taoshidev/proprietary-trading-network. Focused on strengthening correctness, reliability, and maintainability of the ledger and PositionManager components, with a strong emphasis on test coverage and clear documentation. Delivered actionable improvements that reduce risk, improve deployment confidence, and clarify scoring metrics for stakeholders.
December 2024
8 Commits • 3 Features
Dec 1, 2024December 2024 performance summary for taoshidev/proprietary-trading-network. Focused on strengthening correctness, reliability, and maintainability of the ledger and PositionManager components, with a strong emphasis on test coverage and clear documentation. Delivered actionable improvements that reduce risk, improve deployment confidence, and clarify scoring metrics for stakeholders.
November 2024
4 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for taoshidev/proprietary-trading-network: Implemented metrics reliability and robustness enhancements for Sharpe, Sortino, and Omega calculations and reworked the performance scoring system. This included edge-case handling improvements (single-day returns, zero variance), updates to risk-free rate/configuration values and standard deviation thresholds, and consolidated testing to ensure stable and reliable performance evaluation.
4 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for taoshidev/proprietary-trading-network: Implemented metrics reliability and robustness enhancements for Sharpe, Sortino, and Omega calculations and reworked the performance scoring system. This included edge-case handling improvements (single-day returns, zero variance), updates to risk-free rate/configuration values and standard deviation thresholds, and consolidated testing to ensure stable and reliable performance evaluation.
November 2024
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Quality Metrics
Correctness87.0%
Maintainability88.4%
Architecture81.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
Algorithm DevelopmentAlgorithmic TradingBack-end DevelopmentBackend DevelopmentBacktestingCode CleanupCode OrganizationCode RefactoringData AnalysisData ValidationDocumentationFinancial AnalysisFinancial MetricsFinancial SystemsLogging
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