Trading Systems
Trading Systems
Philosophy: Adaptive Over Static
Most trading bots run a single strategy until it stops working. Then you tweak parameters, redeploy, and hope. Ascension takes a different approach.
Our bots don't just execute strategies — they select them. The system constantly evaluates market conditions and chooses the approach most likely to succeed right now. Trending market? Run trend-following. Choppy sideways action? Switch to mean reversion. High volatility with fear spiking? Go defensive or sit out entirely.
This is regime-aware trading. The bots read the room and adapt.
The Bot Fleet
Ascension operates a growing fleet of trading bots across both realms:
TradFi Bots
Trading traditional markets — equities, ETFs, and other regulated instruments — through established broker APIs.
Characteristics:
Operate during market hours (respecting exchange schedules)
Draw on decades of institutional strategy research
Benefit from lower volatility and more predictable patterns
Ideal for steady, systematic approaches
Crypto Bots
Trading digital assets — majors, altcoins, perpetual futures, and high-volatility tokens — across leading exchanges.
Characteristics:
Operate 24/7 (the market never closes)
Handle higher volatility and faster regime shifts
Support both spot and leveraged positions
Adapt to the chaos that defines crypto markets
Specialized Bots
Targeting specific opportunities that don't fit standard categories — momentum plays on trending tokens, arbitrage opportunities, yield strategies, or experimental approaches being tested before broader deployment.
Characteristics:
Narrower focus, often higher risk/reward
Faster iteration and experimentation
Pipeline for proving new strategies before scaling
The Adaptive Engine
What makes Ascension's bots different isn't what strategies they run — it's how they choose.
How It Works
Ingest — Market intelligence flows in continuously: price action, volume, macro indicators, news sentiment, fear/greed readings, on-chain data where relevant.
Classify — The Regime Classifier evaluates current conditions. Is the market trending or ranging? Volatile or calm? Are traders fearful or greedy? This isn't a single indicator — it's a synthesis.
Select — Based on the regime, the Strategy Selector chooses the appropriate approach. Trend-following strategies activate in trends. Mean-reversion strategies activate in ranges. Defensive postures activate when risk signals spike.
Size — Position sizing adjusts based on conviction. High-confidence setups in favorable regimes get fuller allocation. Uncertain conditions get smaller positions or none at all.
Execute — The bot places the trade, sets risk parameters, and monitors for exit conditions or regime changes that would trigger adaptation.
Report — Every decision flows to the Council Data Bus, where personas pick it up and explain it to the community.
Strategy Library
The bots draw from a library of strategy types, each suited to different market conditions:
Trend Following
Clear directional moves
Ride momentum, trail stops
Mean Reversion
Ranging/choppy markets
Fade extremes, target mean
Breakout
Consolidation → expansion
Enter on range breaks
Momentum
High volatility, strong moves
Quick entries, fast exits
Defensive
Uncertainty, risk-off signals
Reduce exposure, preserve capital
The library grows over time. New strategies get tested in paper trading, validated against historical data, and only deployed live once they've proven themselves.
Portfolio Management
Individual bots don't operate in isolation — they're governed by portfolio-level rules that prevent any single system from taking outsized risk.
Core Rules
No single bot dominates. Capital allocation limits prevent any one bot from consuming too much of the portfolio, regardless of recent performance.
No single trade dominates. Position sizing caps ensure that even the highest-conviction setup can't put the portfolio at catastrophic risk.
Dry powder stays dry. A reserve allocation remains uninvested — available for opportunities or drawdown recovery, never fully deployed.
Adapt allocation to conditions. Capital shifts toward bots operating in favorable regimes and away from those facing headwinds. The portfolio itself is adaptive, not just the individual bots.
The Principle
The goal isn't maximum aggression — it's sustainable growth. Survive the drawdowns, stay in the game, let compounding do the work over time. The old realm learned this through painful cycles. We encode it into rules that execute automatically.
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