Trading tools
Train and test algorithms, run Monte Carlo and risk grids, and ship strategies—with the same restraint expected in English private wealth and exchange-grade infrastructure.
Deep dives
Tan accents and institutional green hover states—each card links to the detailed chapter below.
Backtesting
Stress strategies across regimes, slippage curves, and borrow costs before capital touches the tape. Your hypotheses meet history—not hope.
Segment time into train, validate, and hold-out blocks so edge isn't a curve-fit artifact. Out-of-sample metrics stay pinned beside in-sample—no silent leakage.
regime: volatility_cluster_v2 slippage: adaptive_bps borrow: HTB_curve runs: 10_000 paths OOS Sharpe: 1.84
Queue position, partial fills, and cancel/replace semantics that mirror live routes.
Intraday surface shifts replayed so delta-hedge P&L isn’t smoothed away.
Decompose P&L into vol, carry, skew, and execution—know what actually worked.
Strategy
Compose legs, triggers, and roll rules in a versioned graph. Every branch is diffable—audit trails stay as sharp as your edge case tests.
Promote experiments from sandbox to paper to production with signed approvals. Roll back a deployment without losing the lineage of signals that fired.
Parameter sweeps and scenario matrices live next to the graph—no context switching into ad-hoc notebooks.
Spreads, condors, and ratio rolls as first-class blocks—constraints propagate to risk and execution automatically.
Feature stores and label definitions travel with the strategy ID so research and live never drift apart.
Risk Management
Net Greeks, concentration, and scenario P&L in one surface. Limits breathe with volatility—static thresholds don't lull you into a false calm.
Shock skew, term structure, and correlation blocks simultaneously. Book-level what-ifs propagate to desk-level action items—who must hedge what, and by when.
Real-time breach routing: escalate to risk lead, throttle new risk, or flatten—policy-driven, not manual heroics.
Single-name, sector, and factor caps with depth-aware unwind estimates so limits match what you can actually trade.
Immutable audit of limit changes, acknowledgements, and exceptions—regulators and CIOs read the same timeline.
Execution
Slice size, venue selection, and cancel/replace cadence tuned for options liquidity maps. Every child order traces back to the parent intent—no orphaned tickets.
Drop in broker adapters without forking your strategy layer. Latency histograms and reject reasons surface next to the blotter—ops and PMs share one pulse.
Smart routing respects your risk checks: nothing hits the wire until limits and notionals pass.
Execution isn't a black box—it's the contract between your model and the market.
Automation
Cron rolls, signal-driven webhooks, and circuit breakers that halt flows when variance or connectivity drifts. Automation amplifies discipline—it doesn't replace it.
Visual flows for open, adjust, roll, and flatten—each step gated by risk checks and dual approval where required.
Push fills, breaches, and research signals to Slack, PagerDuty, or your data lake—signed payloads, idempotent handlers.
Market-open routines, expiry week rolls, and EOD reconciliations with timezone-aware clocks and holiday calendars.
Every automated path emits structured logs and replay bundles—when something breaks at 3 a.m., you reconstruct it before the open.
Performance
Roll up realized and mark-to-market P&L with clean attribution to vol, carry, skew, and execution. Compare to your benchmark and risk budget—not just yesterday's print.
Slice performance by strategy, book, or single-name complex. See which legs contributed and which hedges paid for themselves—without exporting to a spreadsheet fire drill.
net P&L: +14.2% benchmark: +6.1% max DD: -4.8% IR vs bench: 1.31
Drawdown clocks, recovery time, and streak stats sit next to live exposure so performance reviews match how the desk actually ran the book—not how the slide deck wished it had.
General Exchange merges mathematics, data science, and risk management into a unified framework. It serves as a quant-driven layer between theoretical models (like Black-Scholes) and practical market execution.
Our platform integrates mathematical concepts into actionable signals through Delta and Gamma sensitivity modeling, volatility surface interpolation, dynamic hedging via payoff symmetry, and time-series anomaly detection for volatility regime shifts.
Modular engines that can evolve independently within the platform, each managing a specific part of the trading process.
Evaluates how option Deltas change relative to underlying price movements, identifying when Delta acceleration signals directional momentum.
Computes theoretical option values using the Black-Scholes-Merton model and integrates volatility skew data to normalize risk.
Uses deviations from Bollinger midlines to define entry and exit thresholds, combined with Delta analysis for dynamic rebalancing.
Analyzes probabilistic state transitions in historical market data to determine likely next-phase price behavior.
Runs stochastic simulations across Delta shifts and implied volatility levels to visualize potential payoff outcomes.
Utilizes k-means and PCA-style clustering to identify latent structures in time-series price and volatility data.
General Exchange collects, cleans, and feeds market data into its learning pipeline. We use historical bid/ask spreads, implied volatility metrics, and realized volatility for adaptive model calibration.
The system continuously refines signal weighting based on live data streams and backtested model accuracy, learning from past trade efficiency to improve its signal-to-risk ratio over time.
Generate intuitive risk visuals that help traders understand potential outcomes before executing strategies.
Visualize potential profit/loss scenarios across multiple time horizons with statistical confidence intervals.
Identify volatility clustering patterns and regime shifts through interactive heatmap visualizations.
Rolling Monte Carlo projections show forward-looking risk distributions and confidence intervals for position sizing.
General Exchange serves diverse trading professionals and institutions seeking advanced algorithmic capabilities.
Advanced modeling and risk management for institutional trading strategies.
Statistical edge and professional-grade analysis tools for individual traders.
Applied finance research and market data visualization for risk assessment.
Portfolio risk assessment and dynamic hedging strategies for institutions.
All trading involves risk. No algorithm can guarantee profits. Past performance does not predict future results.
Our platform follows best practices for model interpretability, ensuring transparency in algorithmic decision-making.
User data privacy is protected with enterprise-grade security and compliance with financial regulations.
Join the waitlist for early access or connect your brokerage APIs for simulation testing.