Strategy #0000000103 · Crypto assets and multifactor models
Cryptocurrency cross-sectional factors
Enter four factor scores and weights, assumed long/short basket returns and costs to inspect the composite scenario.
Crypto-asset research tests cross-sectional market, size, momentum and investor-attention factors. Short token histories, delistings and survivorship bias, exchange quality, liquidity, token-supply changes and regime shifts can distort historical tests. This model combines user-entered standardised factor scores and applies assumed long/short basket returns.
Excludes token delistings, on-chain risks, exchange credit, funding rates, slippage and investor suitability.
Three ways in
Understand the story. Then inspect the risk.
Start with a familiar situation, check the payoff, then test how the numbers change.
The idea · in two minutes
How do market, size, momentum and attention factors combine in a hypothetical basket scenario?
Crypto-asset research tests cross-sectional market, size, momentum and investor-attention factors. Short token histories, delistings and survivorship bias, exchange quality, liquidity, token-supply changes and regime shifts can distort historical tests. This model combines user-entered standardised factor scores and applies assumed long/short basket returns.
Enter four factor scores and weights, assumed long/short basket returns and costs to inspect the composite scenario.
Excludes token delistings, on-chain risks, exchange credit, funding rates, slippage and investor suitability.
- Input assumptionsEnter four factor scores and weights, assumed long/short basket returns and costs to inspect the composite scenario.
- Model outputExcludes token delistings, on-chain risks, exchange credit, funding rates, slippage and investor suitability.
Illustrative research examples only. They are not live signals or a recommendation.
The mechanics · payoff and exposure
Score_i=\sum_k w_k z_{ik},\quad R_{scenario}=sign(Score_i)R_{side}-C
z is a manual factor score and w a manual weight; no token prices or exchange data are used.
Greeks: the directional intuition
- 訊號
- Measures sensitivity to implied volatility.
- 樣本
- Measures sensitivity to implied volatility.
- 執行
- Measures sensitivity to implied volatility.
Score_i=\sum_k w_k z_{ik},\quad R_{scenario}=sign(Score_i)R_{side}-C
Practical context · published observations
Cryptocurrency cross-sectional factors: read the record with its caveats.
The chart uses the published figures or explicitly labelled study inputs below. A historical index or model replay is not the same as an investor’s realised account return.
Excludes token delistings, on-chain risks, exchange credit, funding rates, slippage and investor suitability. Source ↗ · Methodology ↗
Change assumptions and inspect the scenario
Inputs illustrate the strategy mechanics; they are not live quotes, forecasts or investment advice.
Variants · same family, different risk levers
Data quality, sample selection and execution assumptions affect results.
Compare signal, sample and implementation choices.
| Related strategy | Relationship | What changes | New cost or risk |
|---|---|---|---|
| Base scenario | Manual inputs | Crypto-asset research tests cross-sectional market, size, momentum and investor-attention factors. Short token histories, delistings and survivorship bias, exchange quality, liquidity, token-supply changes and regime shifts can distort historical tests. This model combines user-entered standardised factor scores and applies assumed long/short basket returns. | Excludes token delistings, on-chain risks, exchange credit, funding rates, slippage and investor suitability. |
| Conservative version | Lower exposure | Reduce exposure and raise sample thresholds. | May narrow strategy coverage. |
| Validation version | Out-of-sample review | Freeze signal definitions before time-ordered evaluation. | Needs more clean data and governance. |
Excludes token delistings, on-chain risks, exchange credit, funding rates, slippage and investor suitability.
Read beyond the summary
References
Primary sources and research used to describe the strategy and its limits.