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Kronos Field Guide

Free preview · Chapter 2

What you are building, and the words you'll need.

Two full sections from the beginner path of the Kronos Field Guide, free to read. Launching soon.

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Educational only; not financial advice. Start with pretend money. You can lose money even when every rule works as intended. Paper results do not promise live results.

1. What you are building

Imagine three separate jobs. One part watches past market prices and draws possible future prices: that is Kronos. A second part follows rules about when to buy, hold, reduce or close a position: that is the Prometheus-style strategy and risk layer. A third part sends orders to a broker and checks what actually filled. A coding agent can help build these parts, but a confident explanation from an agent does not prove that the software works or that its strategy makes money.

A forecast is a guess about a future price. An order is a request to buy or sell. A fill is a completed purchase or sale. Those are different events. The most damaging bugs can happen between an order being requested and a fill being confirmed.

The first version should only observe. The second should replay saved prices. The third may submit orders to a broker's paper account after you explicitly choose and accept your settings. This package does not switch you to a real-money account.

2. The words people use

TermPlain meaningWhy it matters
Asset / symbolThe thing being observed, such as a stock or cryptocurrencyThe same asset can have different symbol names at different providers
PositionHow much of an asset you currently ownSeveral purchases can grow one position beyond your intended limit
LongOwning an asset and benefiting if its price risesSelling that asset closes or reduces your long
ShortBorrowing an asset to sell first and hoping to buy it back cheaperThis is not the same thing as a stop-loss, and is disabled in the template
EquityCash plus the marked value of positions, minus liabilitiesIt moves even when nothing is sold
Realized lossLoss locked in through a completed saleDifferent from a temporary mark on an open position
Unrealized lossCurrent marked loss on something still heldStill economically important; may worsen before you can sell
ExposureHow much of the account is invested in a categoryMultiple coins can all fall together
DrawdownDecline from an earlier account peakRecovering the same percentage does not restore the account
Candle / barA period's opening, highest, lowest and closing price and volumeAn hourly bar and a daily bar describe very different horizons
OHLCVOpen, high, low, close, volumeThe market-history inputs used by the forecasting system
SpreadGap between the best quoted buying and selling pricesCrossing it creates an execution cost
SlippageDifference between expected and actual executionIt can get much worse when markets move fast
LiquidityHow easily an order can trade without moving the price muchA price on a screen does not guarantee a buyer for your quantity
RebalanceAdjust holdings toward chosen target proportionsDoing it too often can turn a quiet strategy into a fee machine
CalibrationComparing forecast uncertainty with actual outcomesModel agreement with itself is not evidence it is correct

The full guide continues with 81 configuration fields, the incident record and both coding-agent briefs.

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From the guide's resources chapter

Choose a deployment path

Hardware figures below are planning allowances, not measured Kronos minimums or throughput guarantees. Your model, history length, samples, assets, dependencies and concurrent processes determine actual requirements. A bigger computer does not establish a better investment strategy.

PathWhat it is forPlanning allowanceWhat you must test
Your existing Mac or PCReading, replay and a small Kronos-mini observation experimentStart by checking available memory; 8 GB total RAM may be constrained, 16 GB gives more working room. Allow 10–20 GB free disk for an initial Python/model workspace.Load one model, forecast one symbol, then measure peak RAM and cycle time before increasing workload.
Small Linux VM for orchestrationJournals, scheduler and broker-paper integration; inference can remain on another machineIllustrative 2 vCPU / 4 GiB RAM / 40+ GB disk allocation; not a validated all-in-one inference specificationVerify memory with your dependencies; ensure network failures between inference and execution fail safely.
Linux VM for a small all-in-one research setupOne model worker plus local journals and a small paper universeIllustrative 4 vCPU / 8 GiB RAM / 80+ GB disk allocation; benchmark firstConfirm worst-case inference finishes before the next cycle without starving the independent protection worker.
Larger model / many assets / large sample batchesDeliberately expanded researchSize from measured CPU/RAM/VRAM demand; a GPU is optional and workload-dependentCompare throughput and model quality separately. Measure cost per completed forecast, not only cost per machine-hour.

These are starting budgets, not purchasing recommendations or performance claims. No hardware is required just to read this guide.

Gear we run this on

The guide's always-on path describes a small always-on Mac or Raspberry Pi, an external SSD for the workspace, and a UPS so a scheduled stop can still fire during a power blip.

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