리서치 의제
가설, 기간, 확인하거나 반박할 근거를 정리합니다.
02리서치
투자 전략
리서치 먼저, 투자 노출은 그 다음.
리서치 중심으로 디지털 자산, 시장 구조, 포트폴리오 구성을 평가합니다.
NORA / CAPITAL FRAMEWORK01 / 03
리서치 의제
가설, 기간, 확인하거나 반박할 근거를 정리합니다.
리서치 / THE FRAMEWORK
리서치 먼저, 투자 노출은 그 다음.
비중, 집중도, 상관관계, 유동성, 비용, 하방 시나리오를 비교합니다.
포트폴리오 구성
비중, 집중도, 상관관계, 유동성, 비용, 하방 시나리오를 비교합니다.
지속적 검토
모니터링, 리밸런싱, 가설 변경, 매도 기준을 정합니다.
EXPLORE / 06
Six capabilities. A clearer investment process.
Choose a route to explore its mechanics, operating priorities and trade-offs.
Trend and multi-factor research
AI quantitative trading
Convert an investment thesis into entry, sizing, and exit rules.
01Research inputs
02Evaluate mechanics
03Execute & review
How it works
Define the market universe, validate signals after costs, then review position limits before execution.
Key consideration
Discuss this routeRegime changes can invalidate historical patterns.
YOUR JOURNEY
A clear next step. At every stage.
01
Define objectives
Document your horizon, withdrawals, loss tolerance and involvement. Establish suitability before choosing a route.
DECISION CHECKLIST
Look beyond returns. Understand your way out.
| Route | Source of value | Execution & exit priorities |
|---|---|---|
| AI quantitative trading | Trend and multi-factor research | Regime changes can invalidate historical patterns. |
| Prediction markets | Event-driven opportunities | Resolution disputes and thin liquidity can affect exits. |
| On-chain copy trading | Address and transaction research | Your fill price and timing can differ from the source wallet. |
| Exchange copy trading | Trader and portfolio selection | A trader’s historical record does not predict future results. |
| AI Quant Lab | Hypothesis to validation | Overfitting can make a backtest look stronger than live trading. |
| TradingView signals | Signal validation and routing | Alerts can be delayed or repeated; execution requires safeguards. |
위험 고지
과거 성과는 미래 결과를 보장하지 않습니다. 가격, 유동성, 기술, 규제 위험이 있습니다.
10자주 묻는 질문
구조를 이해한 뒤 다음 단계로.
Terms, access, and product availability depend on your jurisdiction and account eligibility.
When in doubt, verify the governing terms.
Start with the problem: strategy research belongs in AI Quant or the Lab; event probabilities in prediction markets; following existing activity in copy trading; external alerts in TradingView integration. Then compare your time commitment, data access and execution constraints.
A useful report identifies the dataset, period, benchmark, fees, slippage and drawdown. It separates training from out-of-sample evaluation and explains sensitivity to changing parameters. Assess these together rather than comparing return figures alone.
Not necessarily. The workflow should validate the signal, check permissions and available exposure, and reject duplicates or expired instructions before execution. Monitoring must distinguish an alert from an accepted order and an actual fill.
Yes, as a portfolio design question. Review shared assets, correlated exposures, leverage and total loss limits before combining approaches. Two different strategy names can still create the same underlying risk.
11CONTACT NORA
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