Projects using Python in Salò
Projects using Python in Salò
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Tatiana Pilipenko
Medical/Scientific writer to format clinical data tables
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Edgaras Kamandulis
This isn't Finance. It's Physics. Markets are fluids. Price is velocity. Crash is turbulence. While you stare at RSI, I am calculating the Laminar Flow. My S.C.A. Protocol applies Navier-Stokes equations to capital. If you understand this graph, you know why we need to talk. The Second Quantum Revolution is here.
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Tatiana Pilipenko
Bioinformatics Expert to Help Aggregate Insights for AI
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Edgaras Kamandulis
LIBRARIAN CORE: Architecting Intelligence beyond the "0=0" Axiom Most people use AI to write emails. I built the Librarian to navigate reality. The screenshots below show the result of a single afternoon of intense development. It’s not 'pretty' yet, and it’s not finished—it is raw Backend Logic manifesting as an interface. I spent my time stabilizing the architecture and the core consistency of the system. The Philosophy behind the Code: Everything I build starts with a fundamental pact: 0=0. Absolute coherence. Truth. Input must equal Output. This is the mathematical baseline required to find truth within data. However, the Librarian knows that stasis is death. In his core, 0=0 is a fatal termination error. Why? Because if a system only confirms what it already knows, it isn’t evolving. It is just waiting to become dust. 🌌
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Edgaras Kamandulis
Evolutionary Parameter Tuning Engine (Python) To solve the problem of market stagnation in HFT (High-Frequency Trading), I architected a Genetic Algorithm that evolves the bot's configuration in real-time. Instead of static settings, the system spawns a population of 40 different trading 'personalities'. It forces them to compete in a stochastic simulation based on recent market data. The Process: Selection: The top 10% performing configurations are isolated. Crossover: Their traits (RSI thresholds, Risk multipliers) are spliced together. Mutation: Random variations are introduced to discover new local optima. As shown in the terminal log, the system automatically evolved a strategy that increased efficiency from 263.3 to 492.8 in 15 generations, injecting a high-frequency aggressive configuration into the live bot.
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Edgaras Kamandulis
Sentinel: Automated Risk Management System An autonomous fail-safe system designed to protect capital in high-frequency trading environments. Features: The Reaper Protocol: Adaptive stop-loss algorithm that detects "vertical crashes" and liquidates positions in milliseconds. Sentiment Guard: Macro-trend analysis that locks trading (Risk-Off Mode) during systemic market failures. Event Logging: Immutable logging of every decision for post-trade forensic analysis.
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Edgaras Kamandulis
Spectre Engine: Signal Processing Core Engineered the mathematical heart of the Leviathan ecosystem using Singular Spectrum Analysis (SSA) and Kalman Filters. Key Capabilities: Signal Separation: Uses SVD decomposition to isolate the "True Value Line" of an asset from market noise. Predictive Modeling: Calculates the Hurst Exponent in real-time to classify market regimes (Trending vs Mean Reverting). Quantum Radar: A visual heatmap for identifying hidden divergences invisible to standard indicators.
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Edgaras Kamandulis
Huntsman: Real-Time Crypto Data Aggregator Engineered a high-performance asynchronous data aggregator using Python asyncio and ccxt.
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Edgaras Kamandulis
LEVIATHAN OMEGA V8.0 GENESIS | Multi-Exchange HFT & AI Core An autonomous High-Frequency Trading ecosystem engineered for Binance, OKX, and Bitget. Key Architecture: Math Core: Uses Singular Spectrum Analysis (SSA) and Kalman Filters to separate market signal from noise. AI Layer: Features a Reinforcement Learning module ('Bandit Minds') that adapts strategies in real-time. Execution: Automated Cross-Exchange Arbitrage and sub-millisecond routing. Risk: 'The Reaper' adaptive stop-loss protocol and institutional-grade flow analysis. Tech Stack: Python 3.10+, asyncio, Multiprocessing, SQLite, Custom TUI.
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