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Edgaras Kamandulis
High-Frequency Decision Architect for Zero-Latency Business
New to Contra
Edgaras is ready for their next project!
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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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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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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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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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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Huntsman: Real-Time Crypto Data Aggregator
Engineered a high-performance asynchronous data aggregator using Python asyncio and ccxt.
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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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