AlgoEdge Research is live. 33 strategies scored every trading day, a regime detector, a full volatility suite, options flow, institutional data, and Python notebooks for every model — all in one browser tab. This is a complete walkthrough.

If you've been reading AlgoEdge Insights for any length of time, you know the format. We pick a strategy — TICA regime detection, lead-lag stat arb, Kelly criterion, whatever is interesting that week — we write the Python, run the backtest, and publish every line of code alongside the math. No hand-waving. No vague charts without methodology.

That model works well for education. But over the past year, a different question kept arriving in replies and DMs, worded slightly differently each time but always asking the same thing:

That question is what became AlgoEdge Research. Not a continuation of the newsletter — a separate platform that runs every model we've ever written (and many new ones) on real end-of-day data, every single trading day, and surfaces the results as clean, actionable signals alongside the tools you need to make sense of them.

Today I want to walk you through the whole thing. Not as a sales pitch — as a genuine tour of what's inside, how each part works, and how it pairs with what you already read here every week.

The first thing you see when you open AlgoEdge Research is the Live Signals dashboard. This is the operational center of the platform — every strategy, its current position, its real-time holdings, Sharpe ratio, annualized return, and max drawdown, all on one screen.

A few things worth pointing out in this view. At the top you get the macro snapshot instantly: SPY at $728.99, QQQ at $706.52, VIX at 22.6, and the current regime — Bull, Day 44. That last number matters. The system doesn't just tell you the regime; it tells you how long we've been in it. Day 44 of a bull run is a very different risk environment than Day 4.

The strategy table shows every model with its signal (Long / Watch / Cash), its live holdings, and its risk metrics side by side. You can filter to just Long signals, just Cash, just Watch — whatever slice of the book you want. On the right rail, a live signal activity feed shows intraday moves: AAPL up 3.1%, GOOGL down 1.8%, which strategies are holding what.

Every signal updates automatically at 4:30 PM ET. You don't need to run any code, check any terminal, or interpret any chart. You open the page after market close and the book is already computed.

If there's one feature that separates AlgoEdge Research from a simple signal service, it's the regime detector. Most platforms will tell you whether a strategy is long or short. Very few tell you whether you should trust that signal given current market structure.

The regime detector runs three independent models simultaneously and combines their readings:

These three signals combine into a position sizing table that tells you exactly how to scale each strategy family. Bull regime: trend strategies at 100%, mean-reversion at 50%. Bear regime: trend at 0% (cash), mean-reversion at 25%. This is the discipline that protects capital — and it's baked into every signal automatically.

If you've read our articles on Hidden Markov Models or the Hurst Exponent, you'll recognize this machinery. This is exactly that research, running live, every day.

The vault is where the newsletter and the platform connect most directly. Every strategy that appears here has a documented Python notebook — the same kind of deep-dive you read in AlgoEdge Insights every week — attached to it.

Each card in the vault shows the strategy's live Sharpe, max drawdown, and annualized return. You can filter by family, by signal (Long/Short/Cash), or by difficulty level. A new strategy is added every Friday, published alongside the week's newsletter deep-dive.

The free tier gives you full access to the first three notebooks. Analyst unlocks all 30 remaining ones. Here's what a notebook actually looks like:

Every notebook contains the full Python source, a plain-English explanation of the mathematical logic, parameter sensitivity analysis, walk-forward backtest results, and clear discussion of edge cases and failure modes. You can download them, fork them, and run them directly on your own data. The code was written to be reused — not locked away behind a paywall and never touched again.

Most retail platforms tell you whether you're up or down. AlgoEdge Research tells you your Value at Risk, Expected Shortfall, Cornish-Fisher tail-adjusted VaR, skew, kurtosis, fat-tail days, and how your book would have performed in the 2008 financial crisis. This is the Risk Monitor.

The top row gives you the key risk metrics at a glance. At the time of this screenshot: 1-day VaR at 95% confidence is 0.86% (meaning there's a 5% chance of losing more than $86 on a $10,000 book on any given day). Expected Shortfall of 1.5% captures what you'd expect to lose on the bad days that blow through that threshold. A Sharpe of 1.40 with a Beta of just 0.49 means the book is generating returns with roughly half the market's directional exposure.

The stress test section is where this gets genuinely useful. The platform runs your current book against the six most significant market crises of the past 20 years: the 2008 Global Financial Crisis, COVID-19 crash, 2022 rate-shock bear market, Volmageddon, the 2018 Q4 selloff, and the August 2015 flash crash. For each crisis it shows you the beta-adjusted P&L impact on your current portfolio — not historical returns, but what your actual current positions would have experienced.

The correlation matrix below the stress tests shows the full cross-asset picture in realized daily-return terms. Dark red means highly correlated (SPY and QQQ at 0.96 — essentially the same exposure twice). Dark green means diversifying — GLD, USO, and UUP all show low or negative correlations with equities. The position risk breakdown shows exactly which holdings are driving portfolio VaR, so you know where to cut first if you want to reduce risk.

Every Friday, AlgoEdge Research generates a full written market briefing — not a template, not a set of bullet points, but a narrative explanation of exactly what the models are reading and why every active strategy is positioned the way it is.

This week's briefing headline: "Bull regime, day 44 — 12 of 33 strategies positioned long." What follows is a plain-English account of the quantitative state of the market. The HMM regime model remains in Bull mode. Hurst at 0.586 confirms a trending market — momentum strategies have a statistical edge. VIX at 16.4 (33rd percentile) is within normal range — no volatility overlay adjustment needed. The 10Y–3M yield curve is positive (+0.71%), supporting the growth outlook.

Then, for every active long position, the briefing documents exactly why the model is positioned the way it is. For Momentum Rotation: "Top momentum leaders (63d): GOOGL=20.0%, AAPL=17.7%. RF leadership scores: GOOGL=80%, AAPL=80%. Weekly rebalance active." For Dual Momentum: "SPY 12-month return=10.0% leads vs EFA/SPY. Absolute momentum positive. 3-month=15.4%. LR confidence=55%. Long SPY."

This is the briefing you'd pay a quant analyst to produce. It arrives automatically, every Friday, in your inbox.

Options data is where institutional intent shows up before price moves. The Options Flow section of AlgoEdge Research gives you four views into this data: a live screener, full chains, per-ticker flow, and OI changes.

The screener is the fastest way to see where institutional premium is flowing. The default filter — OTM call buyers, minimum $250K premium — surfaces the trades that matter. Right now: MU is seeing enormous call flow at deep OTM strikes ($1,200 with spot at $1,132), SPY 0DTE calls at $733–735 are printing tens of millions in premium, TSLA calls at $380 with $11.67M premium. This is the market telling you something before it moves.

The Ticker Flow view gives you the aggregate picture for any ticker: total call vs put volume, the put/call ratio, and the dollar premium on each side. SPY today: 1.06M call contracts vs 1.54M puts, P/C ratio of 1.45 — institutions are buying protection. Net premium is -$16.77M, meaning put buyers are spending more than call buyers. Combined with the Bull regime read from the regime detector, this creates an interesting tension worth watching.

The Vol Lab is probably the most data-dense section of the platform, and the one that will feel most immediately useful if you trade options or size positions based on volatility regime.

The ticker view gives you everything in one place for any US ticker or ETF: IV rank, IV percentile (both 1-year), the current IV 30d, the Variance Risk Premium (VRP = IV30 minus RV30 — negative means realized vol is running above implied, which is unusual and worth paying attention to), and the 200-day MA Z-score. Then below that, the volatility cone, the term structure, option volume breakdown by expiration, and the full skew curve.

The Vol Scanner deserves special mention. It shows fixed-tenor ATM implied volatility across every maturity (7d through 365d) for the full ETF universe, normalized to the 60d as a base. A ratio above 100 means the front end is more expensive than the 60d anchor (backwardation — fear front-loaded). Below 100 means the curve is in contango. The EFA 90d tenor at 993.6 is a striking outlier — that kind of term structure dislocation in an international equity ETF is exactly the kind of vol signal that generates edge.

The Dashboard view maps every ETF by its IV percentile (x-axis) against term structure steepness (y-axis), color-coded by sector. At a glance you can see which sectors have cheap vol with steep curves (long vol candidates) vs expensive vol with flat curves (short vol candidates). The Real Vol table gives you RV10, RV20, RV30, RV60, RV90, the Parkinson estimator, IV30, and VRP for every ETF in the universe — this is the data that drives the AI Volatility Agent's answers.

Three more sections round out the platform, each one useful in a different part of a trader's workflow.

Press ⌘K anywhere in the platform and you can search any US ticker. The stock research view gives you everything: price and fundamentals, a full interactive chart with SMA/EMA/VWAP overlays across 1D to Max timeframes, options volume and implied volatility, open interest, volume profile, and the analyst consensus. For AAPL right now: the average analyst price target is $315.09, with 6 Strong Buy, 22 Buy, 16 Hold, 1 Sell, 2 Strong Sell. The insider activity chart shows net selling of $199M — useful context alongside the bullish analyst consensus.

The Markets view is a real-time sector heatmap for 80+ ETFs, organized by sector family: Benchmark, Technology, Software, Semiconductors, Healthcare, Financials, Energy, Clean Energy, Consumer, Industrials, Materials, Real Estate, Utilities, Fixed Income, Metals, Commodities, FX, and Foreign. Each cell shows today's return and the 1-month return, color-coded red/green. The breadth bar at the top (53% advancing today) gives you the market-wide picture instantly.

The Institutions tab pulls 13F filings and shows you the top institutional holders for any ticker — shares held, percent of float, dollar value, and the change since last filing. For AAPL: Vanguard increased its position by 100% last quarter (that's a massive addition), while Blackrock trimmed by 0.86% and State Street reduced by 0.28%. Below the top holders, the top fund holders show which ETFs and index funds are most exposed. This is the data that explains why certain stocks move the way they do on index rebalance dates.

The free tier is not a 7-day trial. It's a permanent tier that gives you live signals for all 33 strategies, the regime detector, the full ETF market dashboard, stock research, all calendars, and the first three strategy notebooks. No credit card. No expiry date.

Analyst unlocks the rest: all 30 remaining notebooks, the AI volatility agent, the complete Vol Lab (skew, scanner, real vol, term structure, market movers), options flow, Market Intel, the risk monitor, 12-month signal history, and the weekly briefing email.

The newsletter and the platform are designed to reinforce each other. Each Friday, AlgoEdge Insights publishes a deep-dive on a strategy — the math, the Python, the backtest, the edge cases. That same strategy is added to the platform's vault as a new notebook that Friday, and its signal goes live the same day.

So if you read the newsletter article about Pairs Trading, you can immediately open the Pairs Trading notebook in the vault, download it, run it on your own data, and then watch its live signal on the signals dashboard every day going forward. The education and the live application are the same thing — just at different stages of the same pipeline.

The platform doesn't replace the newsletter. It's the answer to "what does all of this research say about the market right now?" — which is a different question, and one that requires live data, daily computation, and the kind of persistent infrastructure that a newsletter format can't provide.

If you've been reading AlgoEdge Insights and finding the research useful, AlgoEdge Research is built for you. Start with the free tier — you'll have live signals in under a minute. And if the Analyst plan looks right, the founding member rate won't be available for much longer.

See you on the other side. 🤝

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