Markets
USDT pairs from Binance, refreshed every few seconds.
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The law of cycles
Markets move through four seasons, each tied to a phase of capital flow.
Life flows through birth, aging, sickness and death; markets flow through the same structural exhaustion. We don’t trade emotions, we trade the inevitable exhaustion of liquidity. Price is the result. Flow is the cause.
Portfolio framework
Risk first, return second. Core-satellite construction, inverse-volatility weights, volatility targeting and cycle-aware overlays, computed live from Binance data. Illustrative allocation only, not investment advice.
Crypto index portfolioLoading data…
LiveIndex universe
The most liquid coins the portfolio may hold
Risk profile
How capital is allocated within the chosen universe
Capital
Defaults to $100,000. Enter any amount to convert weights into USD
Your portfolio
Enter a weight (% of total capital) for each coin; the remainder is cash. Saved in this browser.
Portfolio composition
Each slice is one coin; the grey slice is USDT cash. The bar below separates cash, core and satellite.
Top 20 most liquid coins
USDT pairs on Binance with at least 180 days of history, refreshed every 60 seconds. Risk contribution shows how much of portfolio volatility each coin accounts for.
Return and drawdown projection
Simulates 1,500 price paths for the current portfolio. Amounts use the capital you entered.
BTC halving cycle: next peak and trough
A timing model based on three historical cycles (2013, 2017, 2021). The sample is very small; treat as reference only.
Precedent: peaks came 385, 526 and 548 days after the halving; troughs followed about 393, 363 and 376 days after each peak. Drawdowns are getting shallower and each peak rises less than the last (roughly 17×, 3.5× and 1.8× the prior peak), so the 1.0× to 1.5× multiple for the next peak is our own assumption. ETF flows and macro conditions can break this pattern.
8 phases of the market cycle
Each phase gets a fit score against live BTC price data and the Fear & Greed index, totalling 100%. The outlined card is the highest. These are normalised fuzzy-rule scores, not calibrated statistical probabilities.
Methodology
Every step on this page has a reason, and the limits are stated plainly.
1. The process, in order
On each load the page works like a portfolio desk:
- Source: the 60 largest USDT pairs on Binance, excluding stablecoins and wrapped tokens.
- Filter: keep coins with at least 180 days of history, ranked by volume, trade count, open interest, or a blend.
- Structure: BTC and ETH form the core; everything else is satellite.
- Weight by risk, not by equal dollars, then scale total volatility to the profile target. The reduction becomes cash.
- Trend filter: add cash when BTC trades below its 200-day average.
- Measure and project: volatility, VaR, risk contribution, simulated returns and drawdowns.
The key point: risk control comes first and return is the result.
2. Why risk comes before return
Losses are asymmetric. A 50% loss needs a 100% gain to recover; an 80% loss needs 400%.
Funds answer to investors. LPs redeem when drawdowns pass their tolerance, and forced selling at the bottom is the most common way a good strategy still loses.
Risk is easier to estimate than return. Volatility clusters, so recent volatility is a reasonable guide to near-term volatility.
3. Core–satellite construction
Core (BTC, ETH) takes market risk cheaply: deepest liquidity, ETFs and derivatives, and the longest history. Satellites take higher risk in search of excess return.
Core share of the invested portion: Conservative 75%, Balanced 60%, Growth 45%, Aggressive 30%.
If the satellites are wrong, the core keeps the portfolio standing, and each layer can carry its own limits.
4. Liquidity, history and open interest
Liquidity is a fund's first constraint. Satellite weights scale with 24h volume (power 0.25, light enough not to dominate).
Open interest (OI) is the value of open futures positions. Volume measures activity; OI measures capital actually at stake. High OI also means high leverage, so it measures market depth, not safety.
180 days of history are needed to estimate volatility and correlation reliably. Stablecoins and wrapped tokens are excluded to avoid counting the same risk twice.
5. Weights, correlation and volatility targeting
Inverse-volatility weighting gives each position a comparable stand-alone risk, a simple form of risk parity:
Portfolio risk depends on correlation:
Σ is an EWMA covariance (λ = 0.97) over 180 daily returns, with correlations shrunk 20% toward their mean. Each profile has a volatility target; anything above it is converted to cash. When BTC is below its 200-day average, risk is cut by up to a further 15%. VaR and ES use filtered historical simulation, but 180 days is a short sample, so tail risk may be understated. Suggested practice: rebalance monthly, or when a position drifts more than 20% from target.
Illustrative allocation only, not investment advice.
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