THE CORE PROBLEM
01 - PREDICTION
Most financial risk models are trained on 5 to 15 years of market data. A genuine tail event like a liquidity crisis, a correlated asset collapse may appear once in 20 years of that data. One occurrence is not enough to build a model that can handle the next one.
Stress it before it breaks. Simulate the extreme, so your model is ready
02 — STRESS TESTING
Stress test requires severe but plausible scenarios, simultaneous asset class stress, liquidity freeze, credit contagion. These either do not exist cleanly in recent historical data or appear only once. Building them manually requires significant risk team resources and produces results that are hard to defend statistically because they are not grounded in real observed market behavior.
Stress testing requires scenarios your data does not naturally contain. Synthesize thousands of them before the regulator asks.
03 — TAIL RISK
Value at risk fails in tail events not because the math is wrong, but because the training data never contained enough tail events to calibrate the model properly. A genuine black swan appears once in 20 years of market history. The standard response is historical simulation and hoping the next crisis looks like the last. It never does.
Your risk model has never seen a real liquidity freeze. Now it can prepare for one with thousands of synthesized variations of it.
04 — NEW INSTRUMENTS
When entering a new market or launching a new instrument with limited price history, your risk model has almost no data to work with. Waiting for real-world history to accumulate takes years and leaves your model uncalibrated in the meantime. Remix Labs synthesizes realistic time-series from related market data, giving your risk team a valid foundation of test scenarios from day one.
A new instrument with limited months of price history is not enough to build a reliable risk model. Remix Labs changes that.
Built for time-series. Not transaction records.
Time-series stress scenario synthesis
Not designed for time-series data
Core capability. Built for this
Tail event extraction and variation
No event extraction workflow exists
Built-in visual event selector
No-code visual pipeline editor
SDK / developer-only access required
Risk teams use independently
Time-series specific ML algorithms
General ML is not time-series specific
Purpose-built for time-series
USE CASES
Every scenario your risk model needs to see.
01 — TAIL RISK & VAR MODELLING
The 2008 crisis happened once in your data. Your model needs to have encountered it in thousands of variations, different amplitudes, durations, and recovery trajectories to be properly calibrated for the next one. Remix Labs extracts real tail events from your historical market data and synthesizes the test scenarios your model is currently missing.
Extract real tail events from historical market data
Synthesize thousands of variations, different amplitudes, durations, recovery trajectories
Build a tail event test library for VaR recalibration
Stress test models against scenarios that have never occurred but statistically could
02 — NEW INSTRUMENT RISK
New instruments and market entries with limited price history leave risk models without a calibration basis. Remix Labs synthesizes realistic time-series from related market data, giving your risk team a bank of statistically valid test scenarios before real history accumulates so that decisions do not have to wait.
Synthesize price history from related instruments or markets
Model credit risk for new instruments without waiting for real defaults
Build risk baselines for new market entries from existing data patterns
Calibrate risk models on day one with thousands of synthesized test scenarios
Remix labs is in beta phase. Not all features and functions described here will be available or fully operational during the beta phase.
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