Open trading R&D project

Trading intelligence,
built together.

An evolving research platform where AI, blockchain infrastructure and community-built strategies meet automated trading.

01  Community strategies02  Multi-market03  Transparent logic
Strategy signalMomentum + AI
CoinRobot.AI robot logo
Execution layer
CEXDEXSTOCKS
AI-MANAGED STRATEGIESCOMMUNITY RESEARCHNON-CUSTODIAL DEX VAULTSCEX + DEX + US STOCKS

Not another black box.
An open field for better strategies.

CoinRobot.AI is an independent research and development project exploring how automation, artificial intelligence and blockchain can improve the way trading strategies are created, evaluated and executed.

01

Create

Build private or public strategies with readable, editable formulas—not hidden decision logic.

02

Connect

Link your own account or vault and keep assets on the platform you choose.

03

Learn

Compare results, iterate on methods and turn community experience into shared research.

Platform-independent
by design.

A unified workflow connects strategy logic to a growing range of execution environments. CoinRobot.AI is not an exchange, broker, wallet or custodian.

C
LIVE

Centralized exchanges

Connect supported exchange accounts through purpose-limited API access.

BinanceOKX
D
LIVE

Decentralized markets

Trade through user-owned vault infrastructure across supported blockchain networks.

ArbitrumSolana
S
LIVE

US equities

Apply the same strategy-first approach to US stock trading through broker integration.

AlpacaUS stocks
+
EVOLVING

Built to expand

More platforms, networks and asset classes can join the same modular system over time.

From performance data
to reproducible insight.

Weekly reports will examine a different strategy, market period or analytical method—documenting what was tested, how it behaved and what can be learned.

CR-R-2026-W44
Research report · English full text

More asset units and profitable completed trades can look encouraging, yet neither guarantees a growing portfolio. This edition examines that tension across crypto rotation, selective momentum and stock swing trading. CONVERT - Relative Momentum Rotation included a Plan with substantial gains relative to holding, but the wider cohort still lost cash value. The stock swing cohort produced strong realized profitability while its Plans delivered opposing benchmark outcomes. Selective momentum remained vulnerable to large losses, and several protective exits were followed by brief rebounds. Meanwhile, flat balances in strategies without fresh trades showed limited participation rather than a proven improvement. Existing rules were retained throughout. The next research priority is to compare fresh entries, remaining exposure and matched-period holding benchmarks, while distinguishing quick recovery after an exit from lasting recovery. Read the full English paper for the evidence, protection tradeoffs and specific next-review measurements.

METHODQuantitative analysis
Published2026-11-02
CR-R-2026-W43
Research report · English full text

This edition reviews live strategy behavior across crypto rotation, crypto active trading and stock swing systems. The clearest finding is that trade quality cannot be judged from a single number. Some rotation strategies accumulated more asset units, while cash portfolio value still weakened during the market pullback. Some BUY and SELL systems produced respectable realized trade records, yet open exposure or larger losses reduced portfolio capture. The most important refinements therefore focused on entry quality, loss magnitude and stop-loss behavior rather than chasing more trades. Several strategies now need fresh post-change evidence before success can be claimed. In the next review, the key questions are whether protective exits stop firing into recoverable lows, whether average losses fall relative to average wins, and whether results improve versus simply holding the same assets.

METHODQuantitative analysis
Published2026-10-26
CR-R-2026-W42
Research report · English full text

This edition reviews six public CoinRobot strategies across rotation, crypto BUY/SELL and stock swing styles. The main finding is that trade quality must be judged against portfolio capture and Buy & Hold, not only against win rate or profit factor. The stock swing strategy showed the strongest realized trade quality, but its exit evidence still suggested premature selling and protective exits, so the rules were refined. The two main CONVERT strategies continued to show useful unit accumulation, yet cash-value performance remained under pressure during a weak crypto week. The trusted-asset recovery strategy improved to modest positive performance, but entry and exit quality still needed attention. The weakest current strategy was the regime-adaptive trend capture model, where entries and loss exits both required tightening. The next review will focus on benchmark excess, loss size and whether refinements reduce avoidable exits.

METHODQuantitative analysis
Published2026-10-25
CoinRobot.AI

One token.
Across ecosystems.

COINROBOT is the project token, originally issued on BNB Smart Chain. Wormhole-wrapped versions are now available on Arbitrum and Solana, with liquidity on all three networks.

BSC — ORIGINAL CONTRACT0x3fd230b77ad19aaf6330da7854ec76d5aeb49ead

Community Intelligence Edition · Whitepaper PDF ↗

Start experimenting

Your strategy.
Your robot. Your next move.

Join the project, create a strategy and connect it to the market environment you choose.

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