Foundational Factors
Market-Neutral
Survivorship-Bias Free
Multi-Factor
Top 20 Market Cap
Tier 1
This portfolio integrates three orthogonal factors: momentum, mean reversion and enhanced carry. The momentum component captures assets with strong, persistent price trends, while the mean reversion component captures assets with medium-term mean reversion effects, and the carry strategy seeks to profit from funding rates and related statistical price distortions. All have been inspired by the academic literature, with proprietary enhancements.
Together, these factors create a diversified return stream designed to outperform in a range of market conditions.
Its universe consists of the most liquid and actively traded assets, identified on rolling basis - various techniques employed to keep it both stable and relevant, as well as survivorship-bias free.
To balance each asset's risk contribution, positions are scaled according to the inverse of their rolling volatility.
The portfolio is rebalanced daily, with hourly updates provided, 5 minutes past the hour (UTC).
| Benchmark (BTC) | Portfolio | |
|---|---|---|
0.93 | 1.92 | |
45.4% | 62.8% | |
0.00 | 0.51 | |
1.00 | 0.03 | |
-76.6% | -33.1% | |
60.5% | 27.4% | |
0% | 53% | |
100% | 6.7% | |
100% | 140% |
Sharpe Ratio
Rolling 12 MonthsBeta
Rolling 12 Months - Benchmark: BTCNet Exposure of Portfolio
Portfolio Variants
Foundational Factors - Top 30 Market Cap
Tier 1
Combines cross-sectional momentum and carry factors, optimizing for market-neutral risk-adjusted performance.
Foundational Factors - Top 40 Market Cap
Tier 3
Combines cross-sectional momentum and carry factors, optimizing for market-neutral risk-adjusted performance.
Current Weights
5/16/2026, 11:03:14 PM (UTC)
The portfolio is designed to be market-neutral on a volatilty-adjusted basis, therefore it may have net directional exposure on any given day. The weighting mechanism ensures that volatility-weighted directional exposure is negligible on the portfolio level.
| Ticker | Name | Arrival Price | Weight | Date |
|---|---|---|---|---|
| BTC | Bitcoin | 78172.606 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| ETH | Ethereum | 2180.105 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| SOL | Solana | 86.53 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| XRP | Ripple | 1.414 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| DOGE | Dogecoin | 0.109 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| SUI | Sui | 1.063 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| BNB | Binance Coin | 656.524 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| ADA | Cardano | 0.255 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| LTC | Litecoin | 56.08 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| LINK | Chainlink | 9.723 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| AVAX | Avalanche | 9.297 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| BCH | Bitcoin Cash | 415.824 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| HBAR | Hedera | 0.09127924223100048 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| TRX | TRON | 0.355 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| TAO | Bittensor | 273.452 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| XLM | Stellar | 0.152 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| SHIB | SHIB | 0.000005865031602698 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| HYPE | HYPE | 41.925 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| XMR | Monero | 386.306 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| ZEC | ZEC | 513.766 USD | 0.00% | 2026-05-16T23:03:14.789152+00:00 |
| 0.00% | ||||
Properties
Frequently Asked Questions
What is the construction methodology of the model portfolio on display? How do I replicate it?
The portfolio is constructed by applying cross-sectional binning - quantiles. This ensures that the weights are calculated in proportion to the strength of the factor. The assets are then weighted according to the inverse of their rolling volatility, to mitigate the impact of widely different volatilities of digital assets. We provide a replication notebook in the "Resources" section that will produce a very similar portfolio than what's shown on the site.
Is the raw factor data available?
Yes, we serve the raw factor data via the "portfolio/factors" endpoint, please see the API Docs for more information.
What is smoothing? Some factors have by default setting (eg. 10 Day Moving Average) applied. Why is that?
Some of the cross-sectional factors have very high turnover, and despite being highly predictive, the alpha does not survive transaction costs. Smoothing (applying a simple moving average) is a way to reduce the turnover and the impact of transaction costs.
What is the universe of assets? How is it determined? Is it survivorship-bias free?
The universe of assets (there are multiple variants, for example, top 20, 30, 40 market cap digital assets) is the most liquid and actively traded assets, identified on rolling basis - various techniques (volume, open interest, volatility filters) are employed to keep it both stable and relevant. The universe is survivorship-bias free.
What is the rebalancing frequency?
The portfolio is rebalanced daily, with hourly updates, 5 minutes past the hour (UTC), and available point-in-time.
What are the transaction cost / slippage assumptions?
There are 0.05% transaction costs applied on each position adjustment. This is a parameter that can be adjusted in the backtest settings. Slippage, spread is not considered in the simplistic backtest that's on our site. We encourage using an independent backtesting infrastructure to validate performance.
When have been the factors developed? Is there an out-of-sample period?
Our cutoff date for our research process is 2024-01-01, we consider any data onwards as out-of-sample. Many factors have been traded live in some form from 2025-01-01.
Some of the factors look great! Should I pick an individual factor and start trading it?
We recommend using a portfolio of factors to maximize risk-adjusted returns. Alpha from individual factors is simply not consistent enough, and even running a simple arithmetic average of 3-5 relatively orthogonal factors will produce superior results.
Replication & API
Live Weights
Get live weights with the code provided below.
from unravel_client import get_live_weights
UNRAVEL_API_KEY = "null"
portfolio = "foundational.20"
live_weights = get_live_weights(
id=portfolio, api_key=UNRAVEL_API_KEY, smoothing=None, exchange=None
)
print(live_weights)