Blockcircle @Blockcircle

@Romynft There’s a free plan and 7 day free trial to experiment with the Valuation Engine and everything else. You can try everything first, we are confident you’ll love it

If you want to quickly determine whether or not a publicly traded company is overvalued / undervalued / fairly valued using 6 different valuation methods… Then you should try the Company Valuation Engine! You can see the scoring for every listed name on fundamentals, technicals, and sentiment, then showing one composite verdict per company. The whole board sorts and filters by index, country, and sector.

A 10% owner at Goosehead Insurance spent the week selling. Several Form 4 filings across two days, the largest cutting the stake by nearly 96%, more than three million dollars of stock at around 41 to 42 a share. Insider Alpha caught each one the moment it hit EDGAR and grouped them under the same owner, so the pattern reads as one move instead of four scattered lines.

Seven separate recession models, and right now not one of them is flagging elevated risk. The combined score sits at 33 out of 100, which reads as low, with zero of the seven above the 60 line. The interesting part is the disagreement underneath. Growth and jobs are still expanding while consumer sentiment is down at 49.8 and reading pessimistic. The scorecard shows both at once instead of picking a side.

Bernie Moreno's eToro sale hit the feed at an 85 signal score, $100K to $250K, filed 16 days after the trade. Two of the company's own insiders were selling the same stock in the same window. That overlap, an elected official and corporate insiders moving the same direction, is the kind of thing Political Alpha is built to put side by side. Public filings, scored and sorted the moment they post.

A wallet opens a position. Twelve seconds later it is on your screen, tagged by cohort, ranked against 516 others, with a route button right next to it. That window between the move happening on-chain and you knowing about it is where most edge gets lost. Whale Alpha is built to keep it short. 22,616 signals came through in the last 24 hours, and $3.7M of it routed.

A market can sit at 100% yes and still be mispriced. Prediction Alpha flagged exactly that on a Russia and Ukraine ceasefire contract, trading at full confidence while the engine read it as a strong buy no, an 88% gap against where the crowd had it. Running six venues at once is what surfaces this. The same event gets listed in more than one place, priced differently, and the spread between them is the part worth looking at.

You can lay net liquidity against the S&P 500 and gold on the same chart and watch how they track each other over time. The data runs straight from the Federal Reserve and FRED. There is also a 12-week forward projection on M2, so you are not only looking backward. The whole view covers the Fed balance sheet, money supply, RRP and the Treasury account together. Seeing liquidity and price on the same axis makes the relationship a lot harder to ignore.

x.com/i/article/2056…

Insiders dumping $1.3B+ of stock across 124 sells with zero buys is only one view. The same tickers pulled through the Company Valuation Engine tell a more useful story. A subset of those names is flagged as overvalued by 30% or more on the composite score, where the insider selling lines up with the model. Others sit close to fair value, where the same insider activity is harder to read as a directional call, still very useful, but more difficult to gauge. Insider behavior and valuation context are two layers of the same picture.

We just shipped an update to something we've wanted for a long time. It's in the Asset Outperformer Engine. Now you can construct your own benchmark that you care about (e.g. BTC, ETH, SOL, Gold, or the S&P 500) and it surfaces every asset consistently beating it across short, medium, and long timeframes. Scans 3,000+ cryptos, 4,000+ stocks, ETFs, commodities, and metals throughout the day. Free to try at blockcircle.com/aoe/

Conversational, structured, and grounded in observable data rather than random speculations. The same kind of breakdown a hedge fund analyst would put together by stitching seven separate tools manually, regenerated on demand for any supported asset.

His Market Analysis covers three layers: macro write-ups on regime, rates, and liquidity; sector research on tech and energy; financials; and the rest, plus single-asset deep dives on specific names that fit a thesis worth holding.

The Market Analysis output by @BaselIsmail reads like an analyst who has been watching the market all day, walking through what they are seeing.

The Global Liquidity Scorecard uses 27 currencies as denominators. USD is the default starting point. EUR, GBP, JPY, CAD, CHF, AUD, CNY for the majors. Then 20 more across Asia Pacific, the Middle East, and Latin America. KRW, INR, BRL, MXN, SAR, AED, TRY, IDR, and others. The same liquidity composite reads differently in different currencies, and a trader operating in Brazil or Saudi Arabia benefits from the local currency view rather than the default USD one. The world is GLOBAL, and as such, it is critical to track liquidity across the major markets, and not just with a US-centric mindset.

The combined Model 7 (M7 Combined) score is the single number to watch. It is a 0 to 100 composite recession risk reading built on the agreement or disagreement of the 7 underlying models. A score where all 7 models agree on elevated risk reads very differently from a score driven by one or two models firing while the rest stay quiet. The number is informative on its own, just a simple way to summarize the macro picture empirically. The breakdown panel below explains exactly where the score came from, preventing the user from overreacting to any single model.

The Alt Season Index inside the Altcoin Market Scorecard (AMS) tracks the percentage of the top 50 altcoins outperforming Bitcoin over a rolling window. When more than 75% of the top 50 outperform BTC, the market is in alt season. When fewer than 25% do, it is BTC season. Anything in between is a transition. The reading sits at a specific percentage on the dashboard right now, with the historical chart showing exactly where similar past readings landed in the cycle.

@Bambardini Yes, absolutely a key consideration

The cross-match arbitrage view on Prediction Alpha is probably the most underused feature on the platform. It scans every market across six venues for the same event listed at different prices. Polymarket pricing an election outcome at fifty-three percent while Kalshi/PredictIt/Manifold has the same event at forty-eight percent is a five-point spread you can lock in by taking opposite sides on the two venues. These spreads are usually under three points and close fast. The dashboard surfaces them as they open, ranked by spread size and liquidity. Most retail prediction market traders never see them because they only check one venue.

Here is one fast moving market: blockcircle.com/market/0xa93b2…