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Market data, decoded
Practical, no-fluff guides on real-time futures data, order-book microstructure, backtesting, options analytics and the plumbing behind trading systems — written by the team building the feed.
NEW · Research On the S&P, Buying the 2% Dip Is Just Owning the S&P
The rule made money on twelve and a half years of ES and still failed its own control: $345.50 a trade across 103 trades, 57.3% wins, t = 0.90, against a random-day placebo whose 95th percentile is $380.78. The dip-size ladder that made the Nasdaq version interesting is directionally visible here and never reaches significance. And the ten-day hold that averages $1,386 is collecting index drift — every other day held ten sessions pays $881.72.
Research ES Gaps Fill No More Often Than the Mirror Level Nobody Trades
We measured every opening gap on 3,642 ES regular sessions since 2014 against a control almost nobody runs: a mirror level the same distance from the open, on the other side, with no story attached. Gaps filled 52.6% of the time and the mirror was hit 51.0% — an edge of 1.6 percentage points at t = 1.38. On gaps of twenty points or more the two rates swap places, 29.3% against 30.9%, at t = −0.71 — a second null rather than a result in the other direction. What the famous fill rate tracks is how far the level sits from the open.
Research The EMA 9/20 Pullback Loses Money on ES, and Our First Two Runs Hid It
We re-ran the EMA 9/20 pullback on twelve and a half years of our own ES hourly data: 12,130 trades, 32.8% wins at a 2:1 target, −$37.90 per trade, −$459,730.54 in total, profit factor 0.878. Getting there took three runs. The first filled at the EMA inside the signal bar and printed +$2,290,997; the second scored same-bar stop-and-target as a win and printed −$301,387. The lookahead was worth $2,750,727 and the famous same-bar artifact only touched 1.4% of trades.
Research We Re-Ran Our Best Strategy on the S&P — and Found the Two Years the Nasdaq Test Never Saw
RSI-2 dip buying is the one rule that survived our entire mean-reversion sweep on NQ: 60% wins, profit factor 2.13, every calendar year green. We ran the identical rule on twelve years of our own ES tick archive. The edge replicates on the S&P almost exactly — and the five extra years show 2015 and 2018 in red. 'Positive every year' was a property of the window, not of the rule.
Research The Sunday Open "Free Money Glitch" Dies on 585 S&P Sundays. Our First Reading of the Drift Underneath It Was Wrong.
The viral Sunday-open mechanic loses $50.13 a trade across 543 ES trades at t = −3.35, and the 20:00 direction read agrees with the session on only 48.2% of 585 Sundays. We first measured the drift underneath it on the evening session alone — +$15.84 a night, t = 0.49 — and that was the wrong window, because the NQ study we compared it against held to Monday's cash open. Run that window on ES and the drift is +$163.62 a Sunday, +$95,717.50 across 585 sessions, t = 3.28. The glitch is dead either way, and the free ingredient underneath it is larger on the S&P than we found it on the Nasdaq.
Research Trading Yesterday's Winning Style Lost $294,894 on Twelve and a Half Years of ES
The regime filter promises that you can tell a trend day from a reversion day and trade the matching style. We tested it on 3,224 ES sessions back to 2014. Trend days repeat 30.0% of the time against a shuffled control of 33.3% — below its own placebo. And switching daily to whichever style paid yesterday lost $91.55 per session, worse than either style traded blindly.
Research 91% of Wickless ES Trades Hit Their Target. Only 16.5% Make Money.
We re-ran the viral wickless candle retest on twelve and a half years of our own ES archive: 868,567 five-minute bars, 68,726 wickless levels, three exit configurations. The famous win rate replicates — 91.1% of trades reach their target with a 0.25-ATR take-profit — and the same trades lose $34.63 each, $2,212,763 in total. Target-hit rate and win rate are not the same number once $29.50 of round trip comes out. And unlike NQ, the ordinary-wicked-low control loses too.
Research We Backtested the 'Cash Flow + Momentum' Indicator Ad. Both Halves Are Dead — and What Survives Isn't What's Being Sold.
Find the cash-flow wave, confirm momentum alignment, enter on the confirmation bar. We made the three-step picture mechanical and ran 144 parameter combinations over seven years of Nasdaq futures. 121 of 144 lose money. The best result sits exactly at the noise floor of its own search. Each component is dead on its own — and the one thing that does survive is a long-only drift timer that lost 66,000 dollars in the only bear year, and is strictly beaten by a two-line RSI rule.
Explainers Gamma Squeeze Explained — And What One Actually Looks Like in Dealer-Gamma Data
A gamma squeeze is dealer hedging turning into fuel: as price rises, the desks that sold the calls must buy more stock, which pushes price higher, which forces more buying. Most explainers stop at the mechanism. We kept seven years of our own dealer-gamma numbers, so this one shows a real episode day by day — SPY, March 2026, three weeks of deeply negative gamma, a 2.90% reversal, and the exact session where hedging flipped and the squeeze ended.
Guides CME Market-by-Order (Level 3) Explained — With a Real Book, Rebuilt
Level 3 market data is every individual order, not the level total. We rebuilt one real NQ book from our own MBO recording: 21,514,312 order events in a day against 501,736 trades, 320 MB against 2.2 MB for L1, and the reconstruction bug that crosses your book if you trust the deletes.
Comparisons Databento vs tickstream: An Honest Comparison of Two CME Data APIs
Databento bills by the gigabyte or from $199/month; we bill $29–$199 by use case. A side-by-side on coverage, pricing model and what each is actually built for — including the cases where Databento is the better buy.
Research Do Big Orders Predict Price? We Checked Every 25-Lot on 7 Years of Nasdaq Futures
Whale alerts, footprint charts, 'follow the institutional order flow' — the premise is that large trades reveal where price is going. We had the data to check it properly: 1,847 days of NQ with the exchange's own aggressor flag on every single print, so a 300-lot and three hundred 1-lots are never confused. Following the big orders lost $135,834 per contract. Fading them made nothing. Across three sessions, four horizons and four formulations of 'big', not one crossed the noise threshold. The one thing that did predict is worth a quarter of a tick.
Research We Ran 3,000 Combinations of an ICT Asian-Session Strategy. The Best One Is Exactly What Noise Looks Like.
Mark the 6-7pm range, wait for one side to get taken, then trade the reversal toward the other side. It is one of the most-taught setups in the ICT world. We tested it on seven years of Nasdaq futures — not once, but across 3,000 parameter combinations, a walk-forward over every year, and 120 null runs where the rule was deliberately made false. The best combination reached t = +2.29. Pure noise reaches that in 18% of runs, using a quarter of the search. The walk-forward lost $22,598.
Research The Earnings Calendar Spread Promises 90% a Year. We Tested 848 Earnings on Real Option Quotes
Sell the front expiry, buy 30 days out, hold one night through earnings and harvest the IV crush. The pitch claims $10,000 into $6 million over ten years at a 20% max drawdown. The IV crush is real — the front leg loses a median 28.9 vol points overnight while the back leg loses 6.3. But the round-trip bid/ask on those two legs is a median 50% of the capital at risk, and that is where the entire edge goes. At midpoints the strategy is flat; at any fill you can actually get, it is gone.
Research The 86% Win Rate That Still Loses Money: We Backtested the Negative-RR VWAP Absorption Strategy on 7 Years of NQ
A reader sent us a prop-firm strategy: fade the first VWAP touch of the RTH session, confirm with absorption, take $250, risk $2,000. It wins 86% of the time — and needs 89.3% to break even. We spent the whole study hunting those missing 3.4 points across 24 signal variants and 36 bracket combinations. Every one fell short by the same amount, and a random entry beat the strategy in 17 of 20 runs.
Research The Most Honest Strategy We've Backtested — and It Still Stopped Working in 2024
Matteo Conti, a former Nordea market maker, describes a fully mechanical VWAP drift-pullback system for NQ in a 44-minute interview: three coded trend conditions, first pullback candle, 80-point stop, 40–50-point target, 64% win rate, in-sample 2020–2023 and out-of-sample after. We rebuilt it from the interview and it reproduces his numbers within a few percent — which is rare. Then we looked at the out-of-sample years, and found the mechanism that killed it: the target is capped and the loss is not.
Research Robert Rother's VWAP Scalping Strategy, Backtested Tick by Tick — Including a Version Where We Cheat For It
An ex-hedge-fund manager describes his method in a 53-minute interview: limit orders at the VWAP, first touch only, 10-tick stop, 10–15-tick target, 80% win rate, trend days only — the trend call is discretionary. We mechanized every rule that can be written down, ran it on 7 years of NQ tick data, and then did something unusual: we deliberately gave the strategy lookahead bias — perfect knowledge of each day's regime — to stand in for his discretion. It loses at every layer, including that one.
Research We Built a Daily Breakout-vs-Mean-Reversion Score From Dealer Gamma — and It Grades Itself in Public
Can the morning gamma board tell you whether today will be a breakout day or mean-reversion chop? We tested it on 1,698 reconstructed daily option boards (2019→2026): direction is a coin flip, but EXPANSION is predictable — rank-IC −0.43, stronger out of sample. The score now runs live on our free GEX page, frozen at 09:35 ET and graded against the realized range every evening, misses included.
Guides The Rithmic API Problem: Why There's No Public REST Endpoint — and How the WebSocket Protocol Actually Works
Rithmic powers a huge share of retail futures trading, but there is no public REST API and no signup page for developer access. This is the honest map: what R|API+ and R|Protocol actually are, how the WebSocket plants work, the traps that cost us weeks (deployment pinning, silent trade-route rejects, plant eviction, an IP ban), and what you can query over plain HTTP today with one key.
Algos Counterflow: We Searched 990 Million Option Prints for an Edge. One Survived. It's Live Today.
We tested seven signals from 7.4 years of OPRA options tape against NQ. Six died in public — direction flow, sweeps, blocks, flow at gamma walls, intraday regime reads. The survivor is a two-sided positioning contrarian that was profitable every single year including 2022, with a working short side. It trades live as our 14th sleeve, paper record public from day one.
Research We Put 990 Million Option Prints Against Gamma Walls. The 'Defense Flow' Exists at Fake Levels Too.
Fourth and final test of the gamma-level thesis — this time measuring the options FLOW at wall touches instead of price reaction. 906 real wall touches vs 918 placebo levels: no extra volume, no sweep burst, and the strike-concentration everyone screenshots appears identically at fake levels. Bonus funeral: the strike with the biggest fresh OI build breaks MORE often than random.
Research Same Signal, Two Trades: Naked Future vs Defined-Risk 0DTE — Priced on Real Ask/Bid Quotes
We took our live contrarian sleeve's signals and priced BOTH expressions over 7.4 years: one NQ future held open-to-close, versus one ATM 0DTE option bought at the ask and sold at the bid. The option is the first options-BUYING strategy that survives real costs in our entire research program — because these specific days are the measured exception to the volatility risk premium. Full numbers, including the year it made nothing.
Research Three Things 7 Years of Options Data Refuses to Predict (and the One Thing It Nails)
We rebuilt the implied move through the trading day from millisecond options quotes, measured morning 0DTE flow, and computed the full IV term structure back to 2019 — hunting an intraday regime signal. All three ideas died honestly: trend-vs-reversion stays unpredictable, 'unconsumed' implied move knows nothing, and the term-structure slope is the IV level in a costume. What survives is amplitude.
Research The '10 a.m. Key Open' Strategy: We Tested Every Claim in the Video on 7 Years of Tick Data
A popular ICT-style educator teaches 'key opens' — the 10 a.m. and midnight open prices — combined with Fibonacci OTE entries: manipulation, displacement, limit at the open, 10–15 point stop, 1:4 to 1:6 targets. We mechanized it on 7 years of NQ tick data and measured every checkable claim in the video. The level is a placebo, the fib filter costs money, the midnight-open 'magnet' rule is backwards — and the one claim that's true is true of any candle ever printed.
Research We Tested Serge Hoffmann's Order-Book Scalping on 7 Years of NQ Ticks — It Loses, and the Order Flow Makes It Worse
Serge Hoffmann teaches order-book scalping: read the volume balance, the speed of the tape, the absorption at the edges, and fade the reversal back to the magnet. We mechanized exactly that on seven years of real NQ trades with honest fills and costs. It loses — 31% win rate, negative expectancy, t = −1.6. And the twist: the absorption-and-speed read that's supposed to be the whole edge makes it measurably worse than fading a random edge with no order flow at all.
Research "The Setup I Use Live Every Day": We Backtested the Decelerating Support Bounce on 7 Years of NQ
A popular stream setup: at support, wait for the down-candles' bodies to shrink, take the first green candle with a bottom wick, stop below the wick, take profit at 20 pips. It looks clean and it wins often. We mechanized it exactly and tested it across five timeframes on 7 years of NQ. It loses on every one — 1-min to 60-min — and the 61% win rate on the higher timeframes is the trap, not the edge. The specific pattern doesn't even beat buying any green candle after a down-move.
Research We Combined GEX, Volume Profile, Order Flow & ORB. The Backtest Made $500k. It Was Fake.
The dream stack: gamma levels + volume-profile nodes + order-flow confirmation + opening-range breakout, all confluencing into one strategy. We built it on 7 years of NQ tick data with real GEX levels back to 2019. The naive backtest printed half a million dollars per contract at t=8. Then we noticed both long AND short 'won' the same $400k — the signature of a fill artifact. With honest fills it collapses 90%. Here's the full autopsy: levels are base-rate, order-flow confirmation doesn't rescue them, and a shuffled fake GEX regime scores as high as the real one.
Market Data A Free GEX Tool Compared to GEXBOT: Honest Side-by-Side (2026)
GEXBOT is a well-regarded paid gamma-exposure product; tickstream ships a free, no-signup GEX tool on the same feed we sell as an API. An honest, factual side-by-side of what each focuses on — transparent methodology, OI vs volume, 0DTE, vanna/charm, single names, charting integrations — so you can pick the right one. Not affiliated with GEXBOT.
Market DataCME Data Feed Providers Compared (2026): Direct, Vendor APIs, Retail Platforms
An honest side-by-side of the realistic ways to get CME futures data in 2026: direct MDP 3.0, institutional vendors, usage-billed developer APIs, retail platform feeds like Rithmic/CQG, IQFeed-style desktop feeds, and flat-priced developer APIs — what each costs, what you actually get, and who each path is for. Including where our own product fits and where it doesn't.
Market DataLow-Latency CME Market Data: What's Physically Realistic (And What's Marketing)
A no-nonsense guide to CME market data latency in 2026: what colocation actually buys, what a direct MDP 3.0 feed costs, why 'ultra-low latency over the internet' is physics-denial, and how to reason about the latency budget of a WebSocket API — with our own measured pipeline numbers as a worked example.
Research We Got the Time Zone Wrong: Correcting Our Audit of the Viral 'Institutional Protocol' ORB Validation
We re-executed Fabio Valentini's IVB opening-range-breakout model on real NQ tick data and reported that $151k became $42k. That was our error: the report's parameters are Chicago time, not New York, so we tested a pre-open range the strategy never used. Corrected, the published logic gives 784 trades at 58.9% winners and +$121k over five years, against the report's 823 trades at 57.7%. The clock — not the entry rule and not the delta filter — carries the whole result.
Research A Reader Sent Us Their Camarilla Reversal Strategy. We Backtested It — Exactly As Written.
A community member submitted their full ruleset: Camarilla S3/S4/R3/R4 reversals on MNQ, daily 21-EMA filter, confirmation candles, stop under the candle, fixed 1:3 RRR, 9–11 ET, max 3 trades a day. We mechanized it word for word on 7 years of NQ tick data and ran it against placebo levels. The result is the cleanest zero we've ever measured — and a textbook lesson in why a fixed 1:3 can't create an edge.
Research We Backtested Every Setup From Two Best-Selling Volume Profile & Order Flow Books on 7 Years of NQ
Two popular trading books teach 13 concrete setups: S/R flips, open-drives, AB=CD, volume clusters, multiple nodes, stacked imbalances, unfinished business. Rare for trading books, they're specific enough to test. We mechanized every single one on 7 years of NQ tick data with honest fills, the authors' own risk rule, and placebo controls. Result: not one setup survives — and the one that looks positive is beaten by a two-day-old stale level.
Market Data CME Crypto Futures Data Is Live: Real-Time BTC & ETH Tick Streams (BTC, MBT, ETH, MET)
tickstream now streams CME Bitcoin and Ether futures in real time — BTC, Micro Bitcoin (MBT), ETH and Micro Ether (MET) as raw trade prints with size and aggressor side, over the same WebSocket and REST API as NQ and ES. What CME crypto futures data gives you that spot-exchange feeds can't, contract basics, code examples, and honest notes on what we don't have yet.
Research "Draw on Liquidity" Tested: Are Equal Highs and Unmitigated FVGs Really Magnets? 7 Years, Base-Rate Controlled
The viral concept: the market moves 'from liquidity to liquidity' — equal highs/lows and unmitigated higher-timeframe fair value gaps act as draws, and they tell you the daily bias. We measured it on 1,770 trading days of NQ with the control the videos never run: arbitrary levels at the same distance. Result: the 'magnet' touches at or below base rate everywhere — distant liquidity is reached significantly LESS often than random prices — and the daily-bias rule is a coin flip that costs you $283k against doing nothing. The reason is built into the concept itself.
Research "The Daily Sweep" — 14 Years to Master, 60 Seconds to Explain, One Backtest to Kill
The viral pitch: read who's in control on the daily chart, wait for a fakeout against the trend after the New York open, confirm with a fair value gap, enter the pullback, target the previous day's level. We ran it on seven years of real NQ tick data: the full mechanic loses in every session, the 'high probability entry' wins 34.6% of the time — and the multi-timeframe structure read that 'works on every system' is directionally backwards on NQ. Trading against it made +$126k; trading with it lost the same.
Research Do Our Strategies Work in Asia and London? We Audited Our Own Book — and Killed Two of Our Own Algos
A subscriber-grade question turned inward: every backtest we publish anchors to the New York open. So we rebuilt seven years of full 23-hour Globex bars from our own tick store and re-ran our validated sleeves on the Asia and London sessions — same rules, same honest fills, same costs. The NY edges do not travel. And the audit caught something worse: one of our own live strategies was standing on a gap-fill artifact. It's coming off the board.
Research "Sunday Open Is a Free Money Glitch" — We Tested the Viral Claim on 291 Sundays. The Glitch Is Real. His Rules Destroy It.
The viral pitch: wait for the Sunday Globex open, check the direction at 8 p.m., enter on the first 5-minute FVG inversion — 'fails never.' We ran it on seven years of real NQ tick data: the direction read is a coin flip (48.8%), the full mechanic loses money in every exit variant, and 'fails never' is a 46.6% win rate. The twist: doing nothing but being long Sunday evening made +$46,586 over the same window — the kernel of truth is the overnight drift, and every rule the guru adds subtracts from it.
Guides L1 vs L2 vs L3 Market Data: What Retail Algo Traders Actually Need (and Why L3 Is Wasted on You)
Level 1, Level 2, Level 3 — every data vendor sells the ladder, few explain who actually needs which rung. We run a market-data business AND publish tick-level research, so here's the self-inflicted honest version: exact definitions, real storage numbers from our own 7-year NQ store, the measured size of the only edge that's unique to the order book — and why order-by-order data is a storage bill, not an edge, for anyone trading through a broker API.
Research Is Market Entropy 'More Important Than the VIX'? We Tested Shannon Entropy on 98 Years of the S&P 500
A viral thesis says Shannon entropy measures whether the market is 'losing structure' — spiking in every crisis, telling you when to hedge, possibly beating the VIX. We computed it on 24,700 days of S&P data and asked the only questions that matter: does it replicate, is it different from volatility, and does it predict anything? One of those three answers is yes — and it's not the one the pitch needs.
Research Black-Scholes, Tested Against 7.5 Years of Real Option Chains: What the Famous Formula Gets Wrong — and Right
'The most powerful formula in finance' is making the rounds again. Instead of explaining it, we tested it: 1,872 daily QQQ option chains from our own recorded data. The 'constant volatility' assumption fails exactly as advertised (the smirk is visible in one chart), the formula's central number is a genuinely good forecast — better than history — and the one trade the story implies for retail loses after spreads. All three claims, measured.
Research Does CPI Above 4% Crash the Stock Market? We Tested the Claim on 98 Years — Right as It Fires Again
'The market will go down when year-over-year CPI goes above 4% — in the last 100 years that led the market down 4% in three months and 7% in six.' We rebuilt the test from raw CPI (1913–) and S&P 500 (1927–) data. The claim confuses a state with an event: months WITH high inflation are fine; the first CROSSING above 4% has a real but thin, borderline record — and it just fired in May 2026.
Research Do Price Gaps Get Filled? We Tested 1,748 NQ Opening Gaps — the Fill Rate Is a Distance Illusion
A gap is the simplest object in trading: today's open minus yesterday's close. Three simple questions follow — is direction predictable after a gap, are gaps predictable from prior action, and do gaps get filled? We answered all three on 7 years of NQ with a placebo control, then tested the wait-and-see strategy everyone actually trades. The famous fill rate turns out to be about distance, not memory.
Research Wickless Candle Strategy: We Backtested the '88% Win Rate' Claim on 7 Years of NQ
A viral entry model: find a candle with no bottom wick in an uptrend, mark it, buy the retest — claimed 88–90% win rate, 'changed my life'. We mechanized it exactly, on 7 years of NQ with conservative fills and real costs. The 88% win rate is real. It loses money. And the placebo test is brutal: ordinary candle lows WITH wicks beat the 'magic' wickless levels — the wick is the value.
Research ORB30 Strategy Backtest: 30-Minute Opening Range Breakout on NQ, 7 Years, Placebo-Controlled
A reader sent us a precise ORB30 spec: long-only breakout over the 30-minute opening range, stop at 2.25× the range, target at 0.75×, flat by 5pm, 2% risk, one trade a day. We ran it through the full discipline — conservative fills, real costs, train/holdout, two control groups and a parameter grid. It's one of the rare submissions that survives, with caveats worth reading.
Research "A 2% Drop Always Bounces" — We Tested Buy-the-Dip on 7 Years of NQ
Every trader has a friend with the same rule: when it falls 2%, it always comes back. We tested the literal rule and every variant of it on seven years of NQ daily data with real costs. The verdict is more interesting than a debunk: dip-buying on NQ is a real, statistically significant edge — but it peaks at MODERATE dips and fades exactly where the folk wisdom says it should be strongest. And 'always' is doing a lot of lying.
Research Does Post-Earnings-Announcement Drift Still Work? We Tested 50,000 Earnings Events
PEAD — buy the stocks that beat earnings, ride the drift for a quarter — is one of the oldest documented anomalies in finance, and it's being resold today in glossy PDFs with smooth green equity curves. We tested it on 50,152 real earnings events across the S&P 500, 2000–2026, with consensus-estimate surprises and real prices. The drift is real. About two-thirds of the marketed 'edge' is not — it's survivorship bias. Here's how to tell the difference.
Research The EMA 9/20 Pullback Strategy: 62% Win Rate Claimed, 31% Measured
The EMA 9/20 pullback is one of the most-taught entries on trading YouTube: trade with the fast-EMA trend, buy the pullback to the slow EMA, 2:1 reward-to-risk. A trader shared their 61.7% win-rate backtest with us. We ran the same rule on seven years of NQ hourly data with conservative fills and real costs: 31% win rate, negative expectancy. Here's the specific artifact that manufactures win rates like that — and how to check your own backtest for it.
Research Footprint Order-Flow Exhaustion: We Tested 187,018 Events — the Retest Claim Is Backwards
Footprint traders circle the '6 | 0' prints at a swing extreme and call it exhaustion: buyers are done, price reverses, and when price retests that level it rejects again. We built footprints from 7 years of real NQ trade prints (aggressor via quote rule against the prevailing bid/ask) and tested 187,018 events against a control group. The reversal is real — and worth less than the round-trip costs. And the retest claim isn't just unproven, it's inverted: exhaustion levels hold WORSE than ordinary swing levels.
Research Hidden Markov Model Trading: Regime Detection Only Works When It Sees the Future
HMM regime detection is the most convincing-looking strategy in quant trading: fit a hidden Markov model on daily returns, go long in the bull state, flat in the bear state — and the backtest prints Sharpe 1.84 while sitting out the entire 2022 bear. We rebuilt it honestly on 7 years of NQ: walk-forward, filtered states only, real switching costs. Sharpe drops to 0.59 — below buy-and-hold. The gap is pure lookahead, and it's hiding in one word: smoothed.
Guides How to Code a Trading Algorithm: The Roadmap That Survives an Honest Backtest
How to start algo trading without fooling yourself. Everyone's first AI-assisted trading algorithm backtests like a money machine — and it's almost always wrong. The complete roadmap: which market data you need (tick data vs OHLCV), how to backtest a trading strategy honestly (point-in-time, conservative fills, real costs, out-of-sample, placebo tests), how to use AI coding agents like Claude Code for strategy research, and why most of your ideas should die. Based on testing dozens of strategies on 7 years of real NQ tick data.
Research Higher-Timeframe Bias, Lower-Timeframe Entry: Does the Entry Actually Add Anything?
It's the most universally taught structure in trading: form your bias on the daily, execute on the hourly for a 'better price'. We separated the two components on seven years of NQ — the daily bias held alone versus the same bias traded through 1-hour pullback entries. The bias earned +$89k. Adding the entry turned it into −$48k. The precision entry didn't refine the edge; it deleted it.
Research A 78% Win-Rate First-Hour Strategy Went Viral. We Ran It on 7 Years of NQ.
The IB60 setup — first-hour initial balance, close outside the 15-minute opening range, dynamic pullback entry, two-leg exits — was posted with 33 trades, a 78.8% win rate and a 4.39 profit factor. We rebuilt the exact rules and ran them on seven years of NQ minute data with conservative fills and real costs: 38.6% win rate, profit factor 0.93, net negative. The interesting part is WHERE the edge leaks out — because the underlying signal is actually real.
Research A Viral Order-Flow Strategy Promised 50–100 Point Reactions. Random Levels Deliver the Same.
The strategy had everything: GEX and COT for the narrative, three-month composite-profile high-volume nodes with delta spikes for location, absorption-then-initiation on the footprint for the trigger — and one memorable promise: 'at least a 50–100 point reaction on Nasdaq' when price comes back to a level. We mechanized the whole stack on 7 years of NQ tick data and ran it against randomly placed levels. The 50-point reaction is real — at any price you pick. It's a base-rate illusion, and it's the most common trick in trading content.
Research The One Dip-Buying Rule That Was Positive Every Single Year: RSI-2 on NQ
We publish a lot of debunks, so here's the other kind of result. A reader asked for a 'many small wins' strategy, and we swept the whole mean-reversion family on seven years of NQ daily data. One classic rule survived everything we threw at it: buy the close when 2-period RSI drops below 10, exit the next close. 60% win rate, profit factor 2.13, positive every year from 2019 through 2026 — including the 2022 bear. Here's the full test, including the parts that DON'T work.
Research The Leveraged-ETF Rotation Backtest That Turns $100k Into Billions — And Why You Can't Trade It
Leveraged-ETF rotation 'symphonies' — daily RSI/SMA bots flipping between TQQQ, SOXL and volatility hedges — are everywhere on retail trading forums, and their backtests look unreal. We ported one to our engine and ran it on 13 years of real data with real costs. It turns $100k into $5.5 billion. Here's exactly why that's a red flag and not an edge, and what a tradable version would look like.
Research Do Gamma Walls Actually Work? Call Wall & Put Wall Tested on 7 Years of QQQ
The call wall and put wall are everywhere in options-flow trading — 'price gets pinned to the call wall', 'the put wall is support'. We rebuilt gamma-weighted walls from 7.5 years of real QQQ option chains and tested them. The walls are genuinely informative about which way price drifts — but trying to trade them loses money. What's real, what's a trap, and how much it's actually worth.
Research Order Flow Trading and Footprint Charts: What 7 Years of Data Show
Cumulative volume delta, footprint charts, order-book imbalance, 'follow the smart-money order flow' — it's the hottest thing in retail day-trading. We tested it on 7 years of real NQ trade prints (aggressor recovered tick-by-tick from the prevailing bid/ask), lookahead-free with real costs. Order flow turns out to be coincident, not predictive: it explains the move that's happening, not the next one. And used as a confirmation filter on strategies that already work, it makes 22 of 25 of them worse. The data, with a control.
Research Is Volume Really the Most Underrated Indicator? We Tested Volume Breakouts on 7 Years of NQ
‘Volume shows conviction.’ ‘A strong-volume breakout confirms the move.’ It's one of the most popular ideas in trading. We tested it properly on 7 years of NQ 1-minute data — 129,959 breakouts, placebo-controlled, on real trade volume. Volume is genuinely useful for one thing and useless for another, and most people have those two backwards.
Research Can You Tell If Today Is a Trend Day or a Reversion Day? We Tested It on 7 Years of NQ
Every trading course sells a 'regime filter' — know whether the market is trending or ranging, then trade breakout or mean-reversion accordingly. We tested it properly on 7 years of NQ futures: do breakout days come in streaks, and can any indicator tell you which style pays next? The regime is real but it's not forecastable. The data, with a placebo test.
Research Does Price 'Fill' the Prior-Day Value Area? We Tested the 80% Rule on 7 Years of NQ
Market Profile's famous '80% rule' says that when price returns to the prior day's value area, it trades all the way through it ~80% of the time. We measured it on 7 years of NQ futures: the real number is about 45–50% — a coin flip — and a random band of the same width fills just as often. The value area isn't special. The data, with a control.
Research Does the NY Opening-Range Breakout Actually Work? We Tested Every Version on 7 Years of NQ
Fade the opening range for an 81% win rate, or trade the breakout for easy money — the NY ORB is one of the most-sold day-trading strategies online. We tested every version on 7 years of NQ futures, lookahead-free with real costs and a train/holdout split. The result isn't a clean debunk: the popular versions are invalidated, but one version holds up as a thin, real edge. Here's the full data.
Research Does the 'Previous-Day Value Area' Strategy Work? We Tested Every Version on 7 Years of NQ
Open inside the prior day's value area → fade back to value; open outside → trade the trend. It's one of the most popular Market Profile day-trading frameworks. We tested every version mechanically on 7 years of NQ futures — lookahead-free, real costs, train/holdout. The premise is a coin flip and every rule loses. Here's the data, and why 'it's just my psychology' is the wrong diagnosis.
Research Order Block Trading and Fair Value Gaps, Tested on 7 Years of NQ
Order Blocks, Fair Value Gaps, Liquidity Sweeps, the Silver Bullet and OTE — we backtested the core ICT (Inner Circle Trader) concepts lookahead-free on 7 years of NQ futures, with real costs and daily-aggregated significance. Four of five fail outright, and the one that 'works' has nothing to do with Fibonacci. The data, in full.
Research Why PBD Is Failing: We Backtested the Market-Profile Model on 7 Years of NQ
The viral PBD (P / b / D) market-profile model promises a daily edge from value-area rejections and acceptance breakouts. We backtested it lookahead-free on 7 years of NQ futures — every variant and timeframe failed, and the intraday version loses with significance. Here's the data.
Market DataCME Market Data Pricing 2026: Exchange Fees, the NYMEX Fee Schedule, MDP Premium & $19/mo APIs
What CME market data actually costs in 2026, with numbers: non-professional vs professional exchange fees for CME, CBOT, NYMEX and COMEX, Level 2 depth surcharges, what a direct MDP 3.0 feed really involves, the per-message trap — and how to get a real-time CME futures feed from $19/month flat.
AI & AgentsConnecting AI Agents to Live Market Data with MCP (Claude, Cursor)
How to give Claude, Cursor and other AI agents real-time market data using the Model Context Protocol (MCP) — what MCP is, why it fits market data, and how to wire it up.
OptionsFutures Options Data via API: Greeks, Implied Volatility and Gamma Exposure
How to access futures and index options data over an API — option chains, the Greeks, implied volatility and gamma exposure (GEX) — and what each one is actually good for.
BacktestingHistorical Tick Data for Backtesting: The Complete Guide
How to source, clean and use historical tick data for backtesting futures strategies — resolution, survivorship, weekend gaps and the mistakes that make backtests lie.
Market DataLevel 2 Market Data Explained: Reading Order Book Depth in Futures
What Level 2 market data really shows, how to read order book depth and imbalance, and where the edge is — and isn't — for futures traders and quants.
Market DataReal-Time Futures Market Data API: How to Stream CME Ticks in 2026
A developer's guide to streaming real-time CME futures market data over a WebSocket API — latency, normalization, symbol rolls and the gotchas nobody warns you about.
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