Signal Desk

Harmonic patterns are five-point price shapes (X, A, B, C, D) whose swings match set Fibonacci ratios. When price reaches the D zone (the "potential reversal zone"), harmonic traders expect a turn: buy in a bullish pattern, sell in a bearish one. Here, swings are found automatically (a swing must be at least 5% or 2.5 times the average daily range), each pattern's standard ratios are checked, and a swing only counts once price has moved away from it, so nothing uses information from the future. The harmonic average is +1 for each bullish and −1 for each bearish pattern completed in the last 10 days and not stopped out, averaged. Independent research has found harmonics alone don't beat simply holding, which is why every pattern is tested and the average is also shown using only the ones that passed.

Each style is detected automatically from daily candles using its usual textbook rules, and only from information available at that day's close. The average is +1 for each style whose latest signal in the last 10 days was a buy and −1 for a sell. Every style is then tested across all coins' history: does price actually move the signal's way more often than its normal trend would suggest? Styles that rely on a trader's judgement (Elliott Wave, Wyckoff) aren't included, because any automatic version would really be a guess at how someone would draw them.

The numbers a fund's risk team checks before allocating. Sharpe and Sortino measure return per unit of risk (above 1 is good); Value at Risk is the loss you'd expect to exceed on only 1 day in 20; beta shows how hard the coin swings when Bitcoin moves. Risk-free rate assumed 0%.

How the selected coin did in every month of every year. The bottom rows show each month's average and how often it finished up, which reveals seasonal patterns. The current month uses the live price and is still moving.

How it works: for each horizon, a logistic regression model learns from about 7 months of this coin's hourly candles, plus extra data with real history where your network can reach it: funding rates, Fear & Greed, the daily trend and, for altcoins, Bitcoin's own moves. Each horizon is trained with and without the extra data and keeps whichever tested better. It's trained on the older 70%, tested on the most recent 30% it never saw, and its percentages are recalibrated on that test so they reflect how often it was actually right. A model with no edge is pulled back toward 50/50. The 3-day and 7-day odds come from a separate model trained on years of daily candles (momentum over days to months, distance from the 20, 50 and 200-day averages, volatility, volume, Fear & Greed and, for altcoins, Bitcoin's week), tested the same way. Probabilities, not promises; short-term crypto moves are mostly noise.

Every hour, the direction odds' predictions for each coin you view (and every coin in the scanner) are saved in this browser. Once the hour, 4 hours, 12 hours, day, 3 days or week has passed, each prediction is checked against what price actually did. Unlike the backtests, nothing here uses past data: these are real predictions made in real time, so it's the most honest test there is. It builds up the more you use the page.

Watches for the conditions behind sharp turning points: panic selling into a capitulation low, or euphoria into a blow-off top. When pressure is stretched and price then reverses, a setup fires. Every past setup is backtested below so you can judge how much to trust it.

How it works: a setup arms when the pressure score reaches 50 (minor) or 65 (major), then fires on the first day within 5 days that price closes beyond the previous day's high (bottoms) or low (tops), confirming a reversal. Setups that fire during an open 20-day hold count as re-fires, not new trades. Use this as historical context, not instructions; even the best setups fail regularly.

Funds run this as a "cash and carry" or "basis" trade: buy the coin and sell the same amount of perpetual futures, so price moves cancel out and the position earns the funding that leveraged buyers pay. The figures are today's funding rate turned into a yearly rate, plus the average over the last 30 days and the last year. Funding changes every few hours, so the yield isn't locked in.

Options prices tell you how far traders are paying to protect against or bet on moves. The ranges and odds here come from the whole "smile" of option prices for each expiry, not just one number. They are "risk-neutral": they include what traders pay for insurance, so they tend to overstate the chance of falls and assume no expected gain. Research and the live test above both point the same way: options are much better at predicting how big moves will be than which way they'll go. Sources: Bitcoin implied-volatility forecasting study, why option-implied odds differ from real-world odds.

How each indicator is tested: the "favourable" direction is fixed in advance from the usual claim (for example, a falling dollar is good for Bitcoin). For every day since 2012, the test compares Bitcoin's next-30-day return when the indicator was favourable versus when it wasn't, and checks the result separately in the retail era (to 2019) and the institutional era (2020+). Because 30-day windows overlap, only about one day in 30 counts as independent. Each value is used only after it was published (daily data the next day, weekly Fed data two days later, monthly money supply about 8 weeks later), so nothing uses information that wasn't available yet. Data: Federal Reserve Bank of St. Louis (FRED).

MVRV compares Bitcoin's market value with its "realised" value, which prices every coin at the price it last moved, roughly what holders paid on average. Below 1, the average holder is at a loss, which has happened near major lows. Above about 3.5, holders are sitting on big gains, which has happened near major tops. Bitcoin has only had a handful of full cycles, so these zones rest on few examples. Hash ribbons compare miners' 30-day and 60-day average computing power: when the 30-day drops below, weaker miners are shutting down (stress); when it climbs back above, the stress is over, which has often been near lows. Data: Coin Metrics community data (CC BY-NC 4.0), Blockchain.com.

The ETFs launched in January 2024, so there's too little history to test them properly. They're shown as context: steady inflows mean new buyers (often advisers and institutions) are absorbing supply. Figures are in US dollars, millions.

Each cycle is rescaled to start at 1× so they can be compared directly (log scale). Hover or tap the chart to compare cycles at the same point. Past performance doesn't guarantee future results.

Targets assume this cycle repeats patterns from past cycles. Bitcoin's uses its gain from the cycle low; Ethereum's and Solana's use where their price against Bitcoin peaked in past cycles. Progress is measured on a log scale, the way cycle gains compound.

Past Bitcoin cycles

Every cycle so far has followed the same rhythm: a low roughly 1–1.5 years before a halving, a peak 1–1.5 years after it, then a crash of 75–85%.

Performance across timeframes

Returns over each period, using the live price. Strength across every column is what traders call momentum; a coin that's green short term but red long term is bouncing inside a downtrend.

How the coins move together

Correlation of daily returns over the last 90 days. 1.00 means they move in lockstep; near 0 means unrelated. High correlation means holding several of them gives less diversification than it looks.

Scroll to zoom, drag to pan, hover for details. The history uses only ingredients with real history, and each day only uses data available by that day's close. Live-only data (funding, options, order book) counts in today's signal counters but can't be in the history line.

Rules: each strategy starts with $10,000 and decides from each day's close whether to hold Bitcoin or cash for the next day, so it never trades on information it couldn't have had. Every switch costs 0.1% in fees. Cash earns nothing. To avoid flip-flopping, "avoid the caution zone" sells at 30 and only buys back at 40, "above 50" uses 45/55, and the 200-day rule needs a 2% move through the average. "No hindsight" builds the index with equal weights on every ingredient; "Evidence-weighted" uses the weights from the full history, which knows the future and will flatter itself. Past results don't guarantee future ones.

Each rule below has research behind it for Bitcoin. Each one is tested here on Bitcoin's full daily history with fees, and then put through two tougher tests: did it still beat holding in both eras (the retail years to 2019 and the institutional years since 2020), and does it still work if you nudge its settings? A rule that only works with one exact setting was probably fitted to luck. Click a row to see its buys and sells on the chart.

All rules decide from Bitcoin's daily close (midnight UTC) and hold Bitcoin or cash for the next day, so none of them uses information it couldn't have had. Every buy or sell costs 0.1%. Cash earns nothing. During the day the panel shows what would happen if the day closed at the current price; it only becomes a signal at the close. Research: trend rules on moving averages and channel breakouts were found to predict Bitcoin's returns (Hudson & Urquhart, 2019), though that study also found many rules failed on later data, which is why the era and settings tests are here. Price momentum over 1 to 4 weeks predicting the following weeks was documented by Liu & Tsyvinski (2021). Past results don't guarantee future ones, and this isn't financial advice.

The rule: every Monday at the daily close, rank the coins by how much they rose over the last 4 weeks, and hold the top 3 in equal amounts until the next Monday. Each change of coin costs 0.1%. The trend-filter version moves to cash whenever Bitcoin closes below its 200-day average. "Nudged versions" rerun it with 2 or 8-week lookbacks and 2 or 4 coins, to check it isn't a lucky setting. Research: momentum across coins was documented by Liu, Tsyvinski & Wu (2022, Journal of Finance).

Log every trade and the stats below show whether your approach actually makes money. Most traders who keep a journal discover their losses come from a few repeat mistakes. Saved in this browser.

Important numbers are fetched from more than one place: one source is used and the other checks it, and if the main one is blocked on your network the backup takes over automatically. Small differences between sources are normal (they measure slightly differently); large ones are flagged.

The macro data, ETF flows, shared track record and alerts come through a small Cloudflare Worker on your own account. On tradingmaxpayne.com it's found automatically at api.tradingmaxpayne.com. Elsewhere, paste its address here.