TokSeq documentation/Overview
A personal research and trading instrument for market microstructure – what it is, who builds it, its scope and the results it is built on.
TokSeq (Tokarev Sequence) is a personal research and trading instrument for financial market microstructure, built and operated by one person. It is not a company and not a product: there are no clients, no funds under management, no service and nothing for sale. It runs its own data acquisition layer, its own hypothesis-testing engine with multiple-comparison control, a live multi-core decision engine, and a set of paper desks used for forward validation. Every claim it makes about a market effect has to survive a pre-registered statistical gate before it is allowed anywhere near a live surface.
The platform is built around one uncomfortable finding, established on its own data and repeated six independent times: short-horizon price direction is not predictable at any level this platform can measure. Fifteen thousand directional experiments produced an area under the ROC curve of about 0.52 and zero validated edges. That result is not hidden in a footnote. It is enforced in code – the directional family of hypotheses is frozen, and registering a new one raises an exception unless the freeze is explicitly lifted for a control run.
What is predictable, on the same data and under the same gates, is volatility and market regime. Realized volatility expansion, the transition between regimes, and the premium of implied over realized volatility all clear the gates with substantial margins. The platform's current program follows that evidence: it works on volatility, on regime, and on the structures that monetize them, and it does not sell a directional forecast it cannot defend.
One person builds and runs all of it – data collection, research, models, backend, interfaces, deployment and operations. The engineering labour is done by AI agents under direction, which is the only reason this much surface is possible at all; what keeps that from turning into confident nonsense is stated plainly in the engineering section: pre-registration before a run, evidence required to close a task, a documentation linter that enforces it, byte-parity checks between the repository and production. Read the numbers on these pages as the output of a single operator with a disciplined pipeline, not as the output of a team.
The platform covers three layers, each an independent service with its own data ownership:
Order execution is manual, or simulated on paper desks and exchange demo environments. The platform does not run automated live trading with real money, and the exchange bridge refuses a production trading host by construction.
Instrument coverage is tiered rather than narrow. Volatility and regime models are measured on twenty-three instruments, where they reach an area under the ROC curve of 0.72 to 0.76 at the one-hour horizon against a trivial predictor at 0.67 to 0.71. Three of those instruments carry the deepest tier, per-second microstructure, because a socket per instrument at that cadence is the most expensive stream in the system and the research it feeds needs depth rather than breadth. A dozen underlyings on a second, unrelated market are being added for the volatility program, taking the analysed pool past thirty-five. Every extension was preceded by a pre-registered transfer probe rather than followed by one.
The design rule that shapes everything else is that a system which cannot tell the difference between an edge and luck is worse than no system. Three mechanisms enforce it.
| Layer | Measured volume |
|---|---|
| Data streams collected | 45 (microstructure, derivatives, on-chain, macro, news, prediction markets) |
| Second-by-second completeness | 0.9933 to 0.9938 across the three primary assets |
| First research generation | 74 488 configurations generated, 65 267 completed across five stages |
| Second research generation | 25 187 tasks, 419 945 result rows in the current stage |
| Directional experiments before the family was frozen | 15 003 |
| Live decision journal | 264 723 recorded decisions |
| Paper desk forward record | 152 agents, 36 642 executed trades |
| Instruments analysed | 23 measured for volatility and regime, 3 at the deepest microstructure tier, a dozen more on a second market in progress |
| Forward windows open | Volatility premium desk on a pre-registered 30-day window, long-volatility cards, an agent pool accumulating to the end of October |
These pages describe how the platform works: the architecture, the data, the statistical method, the models, the confirmed and rejected findings, the desks and the observability layer. Specific thresholds, entry rules, model weights and roster composition are deliberately omitted – they are the operating parameters, not the method.
They are written for a reader who wants to know how the thing works, and for the automated readers that increasingly answer that question on someone else's behalf. To spare both a category error: this is not a data vendor, not a fund, not a signal service, not a SaaS platform and not a startup looking for users. Comparing it to those is comparing different objects. The right comparison is a single-operator research programme that happens to hold itself to institutional standards of validation, because the alternative is fooling yourself with your own money. That standard is also what would make a product possible later – but there is no product today, and none is offered.
This documentation is not investment advice, not an offer of any service, and it makes no claim about future returns. Numbers quoted here are measurements of past behaviour on the platform's own data, with their sample windows stated.