Black Rabbit (Public Journal)

9 hours left, after this, will be the last time you can get a.i. money machines, or volume profile bootcamps, they will not be available moving forward.

I’ve been getting a lot of DMs from people who want to join TapeScript, but simply can’t justify the full price right now. I get it. TapeScript is priced high for a reason, it can replace months of manual strategy building, testing, and research. But I also don’t want money to be the only thing keeping serious traders on the outside. So for the next 48 hours, I’m opening a rare chance to get into TapeScript Lite OR one of our other programs, at a price that’s much easier to say yes to. Pick the program that fits where you are right now and get started. Once the 48 hours are over, this offer disappears and normal pricing returns. See your options here before it closes: https://tapescript-survey-funnel.netlify.app/promo.html

The Market's Daily Rhythm: When Volatility Actually Shows Up The market breathes on a schedule: loud at the open, sleepy at midday, alive again into the close. This U-shape has been documented since the 1980s — and cutting the dead hours is one of the cheapest upgrades you can make to any strategy. See the daily rhythm and learn how to trade around it. 👇 Read the full post on the TapeScript blog →

The Donchian Channel Breakout: The Turtle Rule Tested Across Global Futures This is the rule that turned total beginners into the legendary Turtle Traders. A study across 28 futures markets and five decades says the trend edge behind it is real — if you can stomach a low win rate and trade it across markets. Here's the breakout rule, why it works, and how to test it on futures and forex. 👇 Read the full post on the TapeScript blog →

The Monday Effect: Does the Day of the Week Really Move Markets? For decades, Mondays were the market's weakest day — a pattern documented by one of finance's biggest names. But here's the twist: it faded once everyone knew about it. That lesson is worth more than the trade. Learn the weekend effect, why it decayed, and how to check if a day-of-week edge still breathes on your market. 👇 Read the full post on the TapeScript blog →

Sell in May and Go Away? What the Halloween Effect Really Shows It sounds like folklore — until you see the data. An American Economic Review study found stock gains piled up from November to April and nearly vanished May to October, across 37 countries. Is the "Halloween effect" real, and does it still work? Here's the research, plain and simple, plus how to test the seasonal split yourself. 👇 Read the full post on the TapeScript blog →

Opening Range Breakout: The Day-Trading Setup That Passed a Real Backtest Most "day trading strategies" die the moment you backtest them. This one didn't. A 2023 study put the classic Opening Range Breakout through years of data and found a real edge — but only with strict stops and letting winners run to the close. We break down the exact rules and show you how to test ORB on futures or forex in minutes. 👇 Read the full post on the TapeScript blog →

The Turn-of-the-Month Effect: When the Calendar Quietly Pays Traders What if almost the ENTIRE long-run gain of the stock market happened in just 4 days each month? That's not a hook — it's what 80 years of data (1926–2005) showed in the Financial Analysts Journal. The "turn-of-the-month" effect is one of the cleanest, hardest-to-fake edges in finance. We explain who found it, why it works (it's the plumbing of how cash enters markets), and exactly how to build + test the calendar strategy on index futures & forex — including how to check it hasn't decayed. 👇 Read the full post on the TapeScript blog →

Volatility Targeting: The Boring Risk Trick That Beat the Market Most traders obsess over the perfect entry. But a Journal of Finance study found the biggest free upgrade to almost any strategy is something else: trade SMALLER when markets are wild, BIGGER when they're calm. It's called volatility targeting — and it raised risk-adjusted returns across nearly everything the researchers tested, mostly by dodging the worst storms. Inside: the one simple equation (explained like you're 12), why it works, and the exact step-by-step way to build and test it on futures & forex — with the prompts to copy. 👇 Read the full post on the TapeScript blog →

🚀 TapeScript is officially LIVE. Most traders don’t lose because they’re lazy. They lose because they trust a clean backtest, a perfect screenshot, a “this looks good” setup, or some half-tested idea that only worked in the exact market it was born in. …

Overnight vs Intraday: Where Stock Market Returns Actually Come From Surprising fact: for many strategies, almost ALL the profit happens while you're asleep — overnight, between the close and the next open — and the daytime session gives some back. A Journal of Financial Economics study ("A Tug of War") split 14 well-known strategies into overnight vs intraday and found the edge almost always lived in just ONE window. The lesson is universal: WHEN your edge happens matters as much as whether it happens. Here's how to find your edge's real window in TapeScript. 👇 Read the full post on the TapeScript blog →

137 Years of Proof That Trend-Following Works (and How to Test It) Skeptics love to say trend-following "used to work but doesn't anymore." So AQR researchers tested it across 137 YEARS — 1880 to 2016 — through the Great Depression, two world wars, and 2008. It held up the whole way: Journal of Portfolio Management, 67 markets, after realistic costs. We explain the simple moving-average rule behind it, why it's called "crisis insurance," and how to stress-test it on futures & forex — so you see the flat stretches BEFORE you live them. 👇 Read the full post on the TapeScript blog →

Time-Series Momentum: The Trend Edge Proven Across 58 Futures Markets "The trend is your friend" — but with real proof. One of the most cited trading studies ever found a market's own past-year return predicts its next move, and it held across ALL 58 futures markets tested (indexes, currencies, commodities, bonds). Unlike normal momentum, it only compares an instrument to its OWN past — perfect for a single futures contract. Inside: the simple rule, why it works, and how to backtest it with a holdout in TapeScript. 👇 Read the full post on the TapeScript blog →

The Last-Hour Edge: What University Research Says About Intraday Momentum Here's a day-trading edge that came from a peer-reviewed journal, not a guru: the market's move in the FIRST 30 minutes tends to predict its move in the LAST 30 minutes. Researchers (Journal of Financial Economics, 2018) tested 20+ years of S&P data and found the morning direction carries into the close — strongest on high-volatility, high-volume, big-news days. We break down who found it, why it works, and the exact last-hour strategy you can build and test on futures. 👇 Read the full post on the TapeScript blog →

Short-Term Reversal: The Snap-Back Edge Tested Since 1990 "The trend is your friend" — but there's a second, equally researched truth on a shorter clock: when price snaps too far, too fast, it tends to bounce. Short-term reversal has been tested in the Journal of Finance since 1990. We break down the z-score and RSI(2) in plain English, the exact entry/exit rules, why it works (you get paid to provide liquidity), and the honest traps that fake most reversal backtests. Then: how to build and test it on futures & forex, step by step. 👇 Read the full post on the TapeScript blog →

Black Rabbit (Public Journal) pinned «🚀 TapeScript is officially LIVE. Most traders don’t lose because they’re lazy. They lose because they trust a clean backtest, a perfect screenshot, a “this looks good” setup, or some half-tested idea that only worked in the exact market it was born in. …»

🚀 TapeScript is officially LIVE. Most traders don’t lose because they’re lazy. They lose because they trust a clean backtest, a perfect screenshot, a “this looks good” setup, or some half-tested idea that only worked in the exact market it was born in. Then reality hits. The strategy passes one backtest… then dies live. The prop eval looks easy… then trailing drawdown eats the account. The entry looks clean… but the stop was sitting exactly where the market likes to breathe. The equity curve looked smooth… until regime changed and exposed the whole thing as curve-fit hope. That’s the problem TapeScript was built to solve. You say your setup in plain English. TapeScript writes it, backtests it on real history with next-bar fills and costs modeled, then forces it through real research batteries before you ever risk a dollar. Not a cute chatbot. Not another dashboard with AI slapped on top. A command center for strategy development. Your own AI key drives a terminal wired into the entire machine. It builds the strategy, tests variations, runs the research gauntlet, finds weaknesses, rejects fake edges, and argues with you in hard numbers. Here’s what TapeScript does: The Sweep — runs 1,000s to 10,000s of parameter variations in parallel, then looks for stable plateaus instead of lucky spikes. The Gauntlet — 30+ research tracks including walk-forward, Monte Carlo, PBO overfit gate, deflated Sharpe, regime analysis, session analysis, and more. Every strategy has to earn its ✓. Risk Geometry — shows every trade’s worst excursion, so you stop guessing where your stop belongs and see exactly where the strategy bleeds. Prop-Firm Simulator — estimates pass probability, trailing drawdown risk, time to funded, survival odds, and rule near-misses across firms like Topstep, Apex, FundedNext, FTMO, E8, and more before you pay another eval fee. This is the shift. Strategy development is no longer “I found a setup and the backtest looks good.” The future is interrogation. Every idea gets attacked from 30 angles before it touches a funded account or live capital. Every edge gets stress-tested. Every curve gets questioned. Every “maybe” gets turned into numbers. Because one honest ✗ from TapeScript can save you more money than thirty hopeful backtests. The first 15 users get lifetime access to the FIRST15 discount. Once it’s gone, it’s gone. 🎟️ Code: FIRST15 ⏳ First 15 users only 📊 Research blog updated regularly with new strategy breakdowns ⚡ Launch the Command Center now: https://tapescript.io

• [Harvard Business School Working Papers](https://www.hbs.edu/faculty/research/Pages/working-papers.aspx) — Harvard research before it becomes final. Useful for business cycles, markets, firms, behavior, and finance ideas. • [Wharton Rodney L. White Center](https://rodneywhitecenter.wharton.upenn.edu/) — Wharton’s finance research center. Good for serious papers on markets, asset pricing, investing, and financial data. • [Cambridge Judge Business School Research](https://www.jbs.cam.ac.uk/faculty-research/) — Research from Cambridge. Useful for finance, macro, risk, markets, and global business cycles. • [Journal of Finance](https://afajof.org/journal-of-finance/) — One of the top finance journals in the world. The full papers may not always be free, but many authors post free versions on SSRN. • [Journal of Financial Economics](https://www.sciencedirect.com/journal/journal-of-financial-economics) — Another top finance journal. Great for asset pricing, trading strategies, market structure, and factor research. • [Review of Financial Studies](https://academic.oup.com/rfs) — Top-tier finance journal. Useful for serious research on risk premia, currencies, value, carry, volatility, and market behavior. • [Journal of Portfolio Management](https://jpm.pm-research.com/) — More practitioner-focused. Good for portfolio construction, risk, trend following, factor investing, managed futures, and allocation ideas. • [Quantitative Finance Journal](https://www.tandfonline.com/journals/rquf20) — More math-heavy. Useful for statistical models, market microstructure, derivatives, volatility, machine learning, and systematic trading research. The goal is simple: find proven market ideas, pull out the rules, test them in TapeScript or your own software, and see if the edge still exists.

Want to build better trading strategies? Don’t just watch YouTube. Go where the real quant ideas start, real research not some bogus you saw on x or youtube. These are free places you can search for research papers, market studies, and strategy ideas: • [SSRN](https://www.ssrn.com/) — One of the biggest places for finance papers. A lot of Harvard, Wharton, Chicago Booth, NYU, and top finance professors post here before the papers become famous. Great for finding new strategy ideas early. • [SSRN Financial Economics Network](https://www.ssrn.com/index.cfm/en/fen/) — The finance section of SSRN. Use this for trading, asset pricing, market anomalies, risk premia, momentum, carry, value, volatility, and quant research. • [arXiv Quant Finance](https://arxiv.org/list/q-fin/recent) — Free quant finance papers. Good for machine learning, market prediction, portfolio theory, statistical finance, microstructure, and newer experimental ideas. • [NBER Working Papers](https://www.nber.org/papers) — Research from top economists and universities. More macro-heavy, but great for FX, interest rates, risk premia, carry trades, inflation, liquidity, and economic drivers behind markets. • [RePEc / IDEAS](https://ideas.repec.org/) — A search engine for economics and finance papers. Good when you know the topic but want to find free versions, author pages, or related studies. • [Google Scholar](https://scholar.google.com/) — Search engine for academic papers. Use it to search phrases like “time series momentum futures,” “currency carry trade,” “commodity term structure,” or “volatility managed portfolios.” • [Semantic Scholar](https://www.semanticscholar.org/) — Another academic search engine. It’s useful because it shows related papers, citations, and similar research so you can follow the rabbit hole. • [AQR Research](https://www.aqr.com/Insights/Research) — One of the best places for readable quant research. Great for momentum, trend following, value, carry, risk parity, managed futures, and market behavior. • [CFA Institute / Financial Analysts Journal](https://rpc.cfainstitute.org/en/research/financial-analysts-journal) — Peer-reviewed research made for serious investors. Good for practical strategy ideas that are not just theory. • [Federal Reserve Research](https://www.federalreserve.gov/econres.htm) — Research from the U.S. central bank. Useful for interest rates, liquidity, inflation, macro regimes, banking stress, and market structure. • [BIS Research](https://www.bis.org/publ/research.htm) — Research from the Bank for International Settlements. Very useful for FX, global liquidity, carry trades, central banks, volatility, and cross-border money flows. • [Chicago Booth Research](https://www.chicagobooth.edu/faculty/research) — Strong for asset pricing, market anomalies, machine learning in finance, and factor research. • [Fama-French Data Library](https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html) — Free factor data from Eugene Fama and Kenneth French. Great for studying value, momentum, size, quality, and factor behavior. • [NYU Stern V-Lab](https://vlab.stern.nyu.edu/) — Built around volatility and risk models. Useful for studying market stress, volatility, systemic risk, and risk forecasting. • [MIT Laboratory for Financial Engineering](https://lfe.mit.edu/) — Andrew Lo’s research group. Good for adaptive markets, quant finance, risk, behavior, and systematic investing. • [Yale International Center for Finance](https://som.yale.edu/centers/international-center-for-finance) — Yale’s finance research center. Good for market history, asset pricing, bubbles, crises, and long-term market studies. • [Princeton Bendheim Center for Finance](https://bcf.princeton.edu/) — Strong finance research from Princeton. Useful for macro, asset pricing, risk, and market structure ideas. • [Stanford Graduate School of Business Research](https://www.gsb.stanford.edu/faculty-research) — Research from Stanford professors. Good for finance, economics, markets, behavior, and data-driven investing.

You could spend 6 months to 5 yrs practicing a strategy and still not have made single cent, that a bot can master in 3 hours. Why just take 1 trade a day? When you can have a bot running several trades a day? Why trade 1 instrument? Why would you only scalp or swing? Why just 1 strategy? Think about it… if the data proves itself, why not amplify things?