Daily Market Report

About & Resources

What this is, who built it, where the data comes from, and the methodology behind every number.

01About

Daily Market Report (dailymarket.report) is a free, public, single-page macro and crypto market dashboard. It aggregates US equity benchmarks, mega-cap tech quotes, Treasury yields, commodity prices, crypto market data, ETF flows, sentiment indicators, and a daily Howard Marks cycle position assessment into one dark-themed page, refreshed twice a day (05:00 and 17:00 UTC).

The site is built and maintained by Vladislav (Vlad) Dramaliev, an independent operator. It is not affiliated with Bloomberg, Reuters, or any data vendor. The dashboard is a personal project shared publicly because the author wanted a single-page morning scan and discovered no free version existed. It is a work in progress - new sections, indicators, and frameworks are added over time based on the author's preferences and reader feedback. Dashboard utility scales directly with data coverage, so if you know a quality, free-tier API or feed that would round out an area not yet covered, please share it via the feedback widget - most expansions start that way.

Vlad has been in crypto since 2013, when he was among the first in Bulgaria to publicly explain Bitcoin, and is considered one of the founders of the Bulgarian crypto community. His core conviction: the primary use case for public blockchains is money and finance, and the tokenization of financial markets will be predominantly onchain - which is also why this dashboard bridges traditional macro and crypto on the same page. After years across multiple crypto teams in marketing and community-building roles, he's currently shifting focus toward finance, AI, and quant/product work.

The selection of indicators, frameworks, and signals on the dashboard is shaped by his experience as a participant in the crypto markets, plus heuristics that have come up repeatedly in trader communities he reads - including the Market Wizards (by Hristo Ahtardziev) Discord and the broader macro/crypto commentariat. The Howard Marks cycle framework, in particular, is a foundational lens: where we sit on the cycle today matters more than predicting where prices will be tomorrow.

Educational by design - built for both professionals and newcomers. The dashboard is constructed to serve readers across the experience spectrum. Practitioners receive a dense, single-page macro-and-crypto scan suitable for a morning routine. Readers earlier in their market education receive the same data layered with progressive disclosure: every technical term, indicator name, and acronym is linked to an inline tooltip with a plain-English definition, and a comprehensive Glossary on this page provides longer-form explanations with curated further-reading links to canonical primary or pedagogical sources (FRED, BLS, the Federal Reserve, Investopedia, StockCharts, CBOE, the original academic papers where applicable). Per-section Sources ⓘ tooltips on the dashboard surface the exact data provider and endpoint behind every number. The intent is to make the report educational without making it remedial - concise where the audience is sophisticated, clarifying where the audience is learning.

Daily Market Report is informational only. Nothing on this site is a recommendation to buy, sell, or hold any security or cryptocurrency. Always do your own research and consult a licensed financial advisor before making investment decisions.

02Methodology & Data Sources

Data providers

All hard data is pulled from primary, authoritative sources. Per-section attribution is shown in the small Sources ⓘ tooltip next to each section header on the dashboard.

Financial Modeling Prep (FMP) is the dashboard's primary data provider and its single largest paid dependency. Equity quotes, indices, sector snapshots, commodity prices, crypto symbol quotes, mega-cap fundamentals (trailing and forward P/E), ETF AUM, and the economic and earnings calendars all come from FMP, accessed under the Starter tier. FMP delivers real-time and historical market data sourced directly from global exchanges:

Real-time quotes and over 30 years of financial data: historical prices, fundamentals, insider transactions, and more, via API.
Trusted by Trading 212, Franklin Templeton, Deloitte, Societe Generale, Royal Bank of Canada, and Perplexity.
70,000+ securities, 4,500+ cryptocurrencies, 1,500+ forex pairs, and 40 commodities.
100+ API endpoints, AI-ready data formats, MCP available, and free API tiers.
SOC 2 Type 2 compliant, FISD member, with data sourced directly from global exchanges.

Macro & Treasury yields: FRED (Federal Reserve Economic Data) - CPI, Core CPI, NFP, Unemployment, Retail Sales, Industrial Production, Fed Funds Target Band (DFEDTARU/L), 2Y/10Y/30Y constant-maturity Treasury yields, plus DXY (DTWEXAFEGS).
Equities & indices: FMP Stable API - quotes, daily ranges, market cap, trailing P/E (key-metrics-ttm), forward P/E (analyst-estimates), 50-DMA, 200-DMA, RSI(14), 52-week ATH, YTD%.
Crypto market data: CoinGecko for asset metrics, global market cap, BTC dominance, derivatives volume; DefiLlama for global DeFi TVL by category, stablecoin total, DEX volume, ETH staking yield; Hyperliquid public info for 24h notional volume; Binance USD-M Futures for BTC + ETH funding rates and BTC large-trader long/short ratio.
Spot ETF flows: Farside Investors (BTC, ETH, SOL daily and 7-day cumulative). Per-fund AUM from FMP.
DeFi reference rates: IPOR for the USDC, USDT, DAI, and WETH market rate suite (the DeFi equivalent of SOFR / LIBOR; published as both spot and rolling DAY / WEEK / MONTH / YEAR averages). Sits in Section 04.5's Macro Indicators block alongside SOFR for direct TradFi-vs-DeFi short-end comparison.
Market-driven sentiment (Section 02): alternative.me for the Crypto Fear & Greed Index; CNN dataviz for the equity Fear & Greed Index. Both are computed from market-data inputs (price, volume, breadth, volatility) and surface side-by-side in Section 02 alongside a daily News Sentiment row from JungleTrade (see next item) for at-a-glance comparison between market-driven and news-driven sentiment.
News Sentiment (Section 03): JungleTrade by J.Labs — an LLM analyzer that reads recent crypto and macro news from 41 publishers (Bloomberg Economics, Reuters, AP, AFP, Coindesk, Cointelegraph, Coinjournal, Cryptoslate, Decrypt, Beincrypto, NewsBTC, Nasdaq News, BBC Business, NY Times Economy and others) and produces a signed score from −100 (very bearish news narrative) through 0 (balanced) to +100 (very bullish). Three JT data feeds combine to power the dedicated Section 03: an aggregate realtime read for the headline score plus the direction and coverage breakdown bars; a historical time-series for the 7-day chart, plotted as an exponentially-weighted smoothed line at founder Dragomir Dikov's recommendation to eliminate intraday noise; and a per-article realtime feed for the featured article plus seven compact driver rows, sorted by absolute impact so the most influential bullish AND bearish stories surface together regardless of sign.
Calendars: FMP economic-calendar (high-impact macro releases) + earnings-calendar (next 7 days, watchlist tickers).
Hyperliquid HIP-3 perp DEXs (Ventuals, trade.xyz): public /info endpoint serving onchain perpetual-futures market data for Ventuals' pre-IPO names and trade.xyz's listed-equity perps. All data is public and free.
Ventuals oracle (Notice): Ventuals' oracle price for pre-IPO names is anchored to Notice, which aggregates secondary-market transactions and bids/offers, latest funding-round announcements, mutual fund marks, 409A valuations, and a relevant public-company basket. Polled at least once per minute and pushed onchain every few seconds.
trade.xyz: DEX deployer of the xyz HIP-3 perpetual venue on Hyperliquid. Carries listed-equity perpetuals (CRCL, COIN, MSTR) and a per-share SPCX listing used as a cross-venue check on the SPACEX card.

AI commentary

Three sections of the dashboard are generated by language models, with deterministic infrastructure to prevent hallucinated numbers:

Macro implications (Section 02 commentary column): Grok 4.3 via NanoGPT. Given the FRED-verified values as ground truth, it writes one sentence of context per indicator. Web search is OFF - the model cannot fetch any number; it can only narrate the values it was handed.
Howard Marks cycle assessment (Section 07 / howard-marks-market-cycle.html): Claude Sonnet 4.6 via NanoGPT, with web search ON. Assesses 9 indicators with primary-source citations. Every cited URL is HEAD-checked post-generation; unreachable citations are dropped and orphan footnotes are stripped from the rationale text. A 27-domain trusted-source allowlist (Federal Reserve, BLS, BEA, SEC, IMF, OECD, ECB, BoE, ISM, FactSet, S&P, Moody's, Fitch, MSCI, FTSE, plus major financial press) skips the network check for primary sources.
Closing take + Executive snapshot (Sections 01 and 08): Claude Sonnet 4.6 via NanoGPT, with web search OFF. Pure synthesis from the dashboard's already-verified data - no external lookups, no citations. The snapshot returns a regime label (Risk-On / Mixed Signals / Risk-Off); the closing take returns an entry-conviction label (Add / Add Selectively / Hold / Trim / Wait); each carries a one-paragraph narrative and structured bullets / a 6-item bias row.

All LLM calls go through NanoGPT, which routes to Anthropic (for Claude) and xAI (for Grok) under a single API and billing surface.

Refresh cadence & archives

The dashboard refreshes twice a day, at 05:00 and 17:00 UTC. The 05:00 fire lands 9 hours after the US close (so all end-of-day prints, ETF flow updates, and FRED EOD series have settled) and early in the European morning. The 17:00 fire is a pre-close, intraday read: it lands after the US morning data window (CPI, PPI, ISM, payrolls) and a few hours into the US session, so a European-evening reader gets the day's releases and intraday action without waiting for the next morning. Every fire writes an immutable archived snapshot to /archive/{date}.html (and /archive/cycle/{date}.html); the 17:00 fire updates that date's snapshot with the intraday read, and the next 05:00 fire carries the settled close. Browse via Menu → Daily Report - by date.

Time zone display

All timestamps on the dashboard are shown in two time zones simultaneously - the canonical UTC reading alongside Central European Summer Time (CEST, UTC+2) in summer, which automatically switches to Central European Time (CET, UTC+1) when daylight saving ends in late October. The header refresh pill, the footer "Generated" stamp, and every macro-release event in Section 06's calendar all carry this dual format (e.g. 14:00 UTC · 16:00 CEST). UTC is retained as the primary reference because it is the international standard for financial-data timestamps and removes ambiguity for a global readership; the secondary CEST/CET display covers the bulk of European market hours (Germany, France, Italy, Spain, Netherlands, Poland) without forcing readers to do mental arithmetic. Readers in Eastern European time zones (EEST/EET) can add one hour to the CEST/CET reading; readers in U.S. Eastern Time can subtract four hours from UTC during DST (five hours outside DST).

Forward P/E methodology

Forward P/E is computed as current price ÷ consensus next-fiscal-year EPS, sourced from FMP's /analyst-estimates endpoint. The picker prefers fiscal-year-end dates at least 6 months out - when a stock's next FY end is just a few months away (e.g. Microsoft's June 30 fiscal year viewed in May), the "soonest future" estimate is essentially current TTM, not genuinely forward-looking. The 6-month cutoff pushes the read to FY+1, which is the convention Bloomberg and Yahoo Finance use.

Sharpe ratio methodology

Sharpe ratios shown on each index, equity, and crypto card use the standard industry formula: Sharpe = mean(excess returns) ÷ std(excess returns) × √N, where excess return is the asset's daily return minus the daily-equivalent risk-free rate (FRED 3-month Treasury yield DGS3MO) and N is 252 for stocks/ETFs and 365 for crypto (annualization factor). The lookback window is 1 year of daily closes. Crypto Sharpe is famously high in bull runs and brutally negative in drawdowns - read it as a historical risk-adjusted return measure, not a forecast.

Cross-checking and verification

The site is intentionally architected to make hallucinated data structurally difficult: hard data comes from primary sources (FRED / FMP / CoinGecko etc.), LLMs are restricted to commentary, and any URL the cycle assessment cites is HEAD-checked before render. A dormant verifier/tiebreaker pipeline (Opus 4.6 + GPT-5.5 cross-check) is preserved in the codebase for future use on narrative LLM sections where a third opinion would help.

03Frequently Asked Questions

What is Daily Market Report?

Daily Market Report (dailymarket.report) is a free, public, single-page macro and crypto market dashboard. It aggregates US equity benchmarks, mega-cap tech quotes, Treasury yields, commodity prices, crypto market data, ETF flows, sentiment indicators, and a daily Howard Marks cycle position assessment into one dark-themed page, refreshed twice a day at 05:00 and 17:00 UTC. The dashboard is a continually-evolving work in progress - new sections, indicators, and frameworks are added over time based on the author's preferences and reader feedback.

Is this investment advice?

No. Daily Market Report is informational only. Nothing on this site is a recommendation to buy, sell, or hold any security or cryptocurrency. Always do your own research and consult a licensed financial advisor before making investment decisions.

Who built Daily Market Report?

Daily Market Report is built and maintained by Vladislav (Vlad) Dramaliev, an independent operator. Vlad has been in crypto since 2013, when he was among the first in Bulgaria to publicly explain Bitcoin, and is considered one of the founders of the Bulgarian crypto community. His core conviction: the primary use case for public blockchains is finance - which is also why this dashboard bridges traditional macro and crypto on the same page. After years across multiple crypto teams in marketing and community-building roles, he's currently shifting focus toward finance, AI, and quant/product work. The site is not affiliated with Bloomberg, Reuters, or any data vendor.

Where does the data come from?

All hard data is pulled from primary, authoritative sources: FRED (Federal Reserve Economic Data) for macro indicators and Treasury yields; Financial Modeling Prep (FMP) for equity and ETF quotes; CoinGecko and DefiLlama for crypto market data and DeFi TVL; Hyperliquid and Binance for derivatives volumes and funding rates; Farside Investors for spot ETF flows; alternative.me for Crypto Fear & Greed; CNN dataviz for the equity Fear & Greed Index. Per-section attribution is shown in the Sources tooltip next to each section header.

How often is the data refreshed?

Twice a day. The generator fires at 05:00 UTC (a settled overnight and end-of-day recap, 9 hours after the US close) and at 17:00 UTC (a pre-close intraday read, after the US morning data window). All times are UTC.

What is the Howard Marks cycle position?

The Howard Marks cycle position is a daily reading of where the current market environment sits on the framework Marks lays out in Mastering the Market Cycle (2018). It is generated by Claude Sonnet 4.6 with web search enabled, assessing 9 indicators (valuations, sentiment, credit spreads, IPO/M&A activity, leverage, fund flows, etc.) against primary-source citations. The framework is intentionally counterintuitive: green means fear and attractive entry conditions; red means euphoria and poor entry conditions. The full assessment lives on /howard-marks-market-cycle.html.

How is the Daily Alpha (Section 07) verdict built?

Section 07 (Daily Alpha) is the dashboard's contrarian voice. Instead of reporting the day's tape (the Executive Snapshot at the top does that), it answers one question: 'is this a good time to add risk, and where?'. The verdict is synthesized by Claude Sonnet 4.6 from this dashboard's already-verified data only, with web search disabled and no external claims. Reasoning anchors on three signals. First, Howard Marks's cycle position from Section 06: Late-cycle pushes the model toward Trim or Wait, Early-cycle toward Add or Add Selectively, Mid-cycle toward Hold or stance-with-asymmetric-risk. Second, sentiment extremes: Crypto and Equity Fear & Greed scores below 25 or above 75 trigger contrarian discipline (Greed at all-time highs leans defensive, Fear with stable fundamentals leans constructive). Third, pre-flagged outlier moves computed in Python before the prompt fires (equity index 1d ≥2%, BTC 24h ≥5%, HY OAS 1d ≥10 bp, sector rotation ≥3% best-vs-worst, and similar thresholds across mag-7 movers, commodities, ETF flows, and funding rates) so the model leads with what is most striking instead of reciting the whole tape. The verdict also incorporates a daily news-sentiment read from <b>JungleTrade</b> (score, classification, time horizon, plus the headline articles that drove it), so material headline shifts are visible to the model when forming the take. <b>This is calibrated contrarianism, not reflexive.</b> When sentiment is in the normal zone (F&G between 25 and 75) and fundamentals support the trend, the model can lean with the tape. The contrarian push only fires at sentiment extremes or at Late-cycle readings; it does not fight a healthy trend for the sake of it. Output: an entry-conviction label (Add / Add Selectively / Hold / Trim / Wait), a one-sentence verdict, a short narrative defending it, and a 6-item entry-decision bias row covering 24h direction, equities, bonds, commodities, crypto, and volatility hedges.

What is the difference between Trailing P/E and Forward P/E?

Trailing P/E divides current share price by the last 12 months of reported earnings - a backward-looking valuation. Forward P/E divides current share price by the consensus next-fiscal-year earnings estimate - a forward-looking valuation. When Forward P/E is lower than Trailing P/E, analysts expect earnings to grow; when higher, they expect earnings to decline. The Mega-cap Tech section shows both for each of the 9 names.

What is the Crypto Fear & Greed Index?

The Crypto Fear & Greed Index is a composite sentiment score from 0 to 100 published daily by alternative.me. Scores below 25 indicate Extreme Fear; scores above 75 indicate Extreme Greed. Inputs include crypto market volatility, momentum, social-media activity, surveys, BTC dominance, and Google search trends. The dashboard also displays a separate equity-market Fear & Greed Index from CNN that uses different components calibrated to the US stock market.

Is the data free to use?

Yes. Daily Market Report is free to read, free to share, and the underlying data shown on the page is licensed under Creative Commons Attribution 4.0 (CC BY 4.0). If you reference or republish, please cite Daily Market Report (dailymarket.report) and link back to the original page. The third-party data providers we aggregate from each have their own terms - please consult them directly if you plan to use the underlying data outside this site.

How can I provide feedback?

There is a feedback widget in the lower-right corner of every page. Three sentiment options (something I like, something I dislike, an idea) and a short comment field. Submissions are delivered directly to the author. For longer correspondence, the secondary channel is a LinkedIn DM to Vladislav (Vlad) Dramaliev - both channels are read.

Do you collect personal data? Are you GDPR-compliant?

The dashboard takes a privacy-first posture: no cookies, no fingerprinting, no advertising trackers, no consent banner needed. The only browser-side telemetry is Cloudflare Web Analytics - a cookieless aggregate pageview counter with no individual-user profiling and no cross-site tracking. The only voluntarily-submitted data we process is what you type into the feedback widget (sentiment choice, optional name, comment, and the page URL you submitted from). Your raw IP address is never stored - only a SHA-256 hash with a daily-rotating salt, used solely for rate-limiting and structurally non-recoverable across days. Under GDPR you have the right to access, rectify, erase, restrict, port, and object to any data we hold about you. Message the author via the feedback widget or LinkedIn to exercise any of these rights - manual deletion is performed within 30 days. The full privacy statement lives in the About page's Privacy section.

04Glossary

Definitions of the technical indicators, valuation metrics, and frameworks the dashboard uses, with further-reading links pointing at canonical primary or pedagogical sources.

RSI(14) - Relative Strength Index

A momentum oscillator scaled 0–100 that measures the speed and magnitude of recent price changes over a 14-period window (daily by default on this dashboard). Above 70 is conventionally read as overbought (price has run hot - risk of mean reversion); below 30 as oversold. Useful for spotting exhaustion in trends, but on its own RSI is a notoriously poor timing tool - strong trends routinely keep RSI pinned above 70 (or below 30) for weeks. Pair it with trend confirmation (50-DMA / 200-DMA) before acting on extremes.

Further reading: Investopedia - RSI · StockCharts ChartSchool - RSI

50-DMA / 200-DMA - Daily Moving Averages

Simple averages of the asset's closing price over the last 50 or 200 trading days. The 50-DMA is a short-to-medium-term trend gauge; the 200-DMA is the canonical long-term trend line. Price above its 200-DMA is usually read as a constructive bias; below as defensive. A 50-DMA crossing above the 200-DMA is the golden cross (bullish); below is the death cross. Moving averages lag price by construction - they confirm trends, they don't predict them.

Further reading: Investopedia - Moving Averages

200-Week Moving Average

The average weekly closing price over the last 200 weeks (roughly four years). On this dashboard it is computed and displayed only for assets with enough price history: Bitcoin, Ethereum, and Solana. For Bitcoin specifically, the 200-week moving average has historically tracked the long-term cycle floor: since 2011 price has rarely closed a calendar week below it for more than a short window, and prior instances have marked multi-year accumulation zones. The row shows the current level of the 200W MA and how far today's price sits above or below it as a percentage. Moving averages lag price by construction - they describe where the trend has been, not where it is going.

Further reading: Investopedia - Moving Averages

EMA - Exponential Moving Average

A weighted moving average that gives more weight to recent prices, so it responds faster to new information than a simple moving average of the same length. The 20-period EMA is a common short-term trend filter - when daily closes hold above their 20-EMA, the asset is trending up; persistent closes below signal weakening. EMA reacts to noise more readily than SMA, so it's better for active traders and worse for slow-moving long-term frameworks.

Further reading: Investopedia - EMA

P/E TTM - Trailing Twelve-Months Price-to-Earnings

Share price divided by the last 12 months of reported earnings per share, summed across the four most recent fiscal quarters. Roughly: how many years of current earnings buy the stock at today's price. Higher = more expensive. Compare within a sector (tech vs. utilities have different normal ranges) and to the asset's own historical average. Shows 'n/a' on the dashboard when TTM earnings are negative - a negative P/E is mathematically meaningless, so we hide it.

Further reading: Investopedia - P/E Ratio

Forward P/E

Share price divided by the consensus next-fiscal-year earnings per share estimate (collected from sell-side analysts). Forward P/E captures what the stock is being priced at on expected earnings, not past ones. If Forward P/E is lower than Trailing P/E, analysts expect earnings to grow; if higher, they expect earnings to decline. The dashboard uses FMP's analyst-estimates endpoint and prefers fiscal-year-ends ≥6 months in the future, matching the Bloomberg/Yahoo Finance FY+1 convention.

Further reading: Investopedia - Forward P/E

Sharpe Ratio (1Y)

Risk-adjusted return - average daily excess return (asset return minus risk-free rate) divided by the standard deviation of those excess returns, then annualized. Formula: mean(excess) ÷ std(excess) × √N, with N=252 for stocks/ETFs/indices and N=365 for crypto (which trades every day). Above 1 is good, above 2 is excellent. Negative means the asset under-performed cash on a risk-adjusted basis. Crypto Sharpe is famously regime-dependent - bull-market readings can exceed +3, drawdown years routinely push −2 or worse. Read it as historical, not predictive.

Further reading: Investopedia - Sharpe Ratio · Original Sharpe paper (1966)

VIX - CBOE Volatility Index

Real-time index of expected 30-day S&P 500 volatility, derived from S&P 500 options pricing. Often called the fear gauge. Below 15 is complacency / low vol; 15–25 is normal; above 25 is elevated stress; above 35 is panic. VIX is mean-reverting - extremes don't last long. A rising VIX while equities are falling confirms genuine risk-off; a rising VIX with equities flat is unusual and worth investigating.

Further reading: CBOE - About VIX · Investopedia - VIX

RSP - S&P 500 Equal Weight (Market Breadth)

RSP is the Invesco S&P 500 Equal Weight ETF: same 500 constituents as the cap-weighted S&P 500 (SPX), but each company gets a fixed ~0.2% weight instead of being weighted by market cap. That structural difference turns RSP into a de-Mag7 read on the index. When SPX is being carried by a handful of mega-caps (Apple, Microsoft, Nvidia, Amazon, Alphabet, Meta, Tesla together ~33% of SPX), RSP shows what the other 493 names are actually doing. SPX vs RSP YTD divergence is the headline breadth signal: a wide gap (SPX leading RSP by several percentage points) means the rally is narrow and concentration risk is high; a closing gap means breadth is broadening and the rally is healthier. Marks reads breadth as an input to risk attitudes: narrow leadership at high valuations is a classic late-cycle pattern.

Further reading: Invesco - RSP product page · S&P Dow Jones - Equal Weight methodology

CAPE 10 - Shiller Cyclically-Adjusted P/E

CAPE 10 is the S&P 500 index level divided by the 10-year inflation-adjusted average of S&P real earnings. Developed by Yale economist Robert Shiller and detailed in his book Irrational Exuberance. The 10-year denominator filters out the earnings noise (booms, busts, one-off charges, GFC-style collapses) that trips up a plain trailing P/E at cycle inflection points. Readings above 30 have historically clustered around late-cycle phases: the all-time high was 44.19 in December 1999, the last month of the dotcom peak. Current readings comparable to that mark are not a timing signal, but they shift the burden of proof against broad-based buying. Howard Marks cites CAPE explicitly in The Most Important Thing and Mastering the Market Cycle as one of the most legible long-horizon valuation reads. The dashboard renders CAPE in the Indices section as one of two S&P 500 valuation cards, alongside trailing P/E. Reading the two together gives a denominator-robust view of where multiples sit in their historical distribution.

Further reading: multpl.com - Shiller PE chart · Robert Shiller - Online data (Yale) · Wikipedia - Cyclically adjusted price-to-earnings ratio

Trailing P/E (TTM) - S&P 500

The classical equity valuation multiple: index price divided by trailing-twelve-months reported S&P 500 earnings. Read literally, it answers how many years of past earnings buy the index at today's price. The long-run median is around 15, the long-run mean around 16, and readings above 25 have historically clustered around late-cycle phases (the 1999 dotcom peak, the 2021 post-pandemic reach for equities). The all-time high (123.73 in May 2009) is a denominator artifact: GFC earnings collapsed to near zero while the index was already recovering. That outlier illustrates the structural weakness of trailing P/E at cycle turns and why CAPE's 10-year smoothing matters. Trailing P/E is most useful as a quick anchor against its own long-run distribution; CAPE 10 is the better read at cycle turns. The dashboard renders trailing P/E in the Indices section as the second S&P 500 valuation card, complementing CAPE 10.

Further reading: multpl.com - S&P 500 P/E Ratio (TTM) · S&P Dow Jones - S&P 500 data · Investopedia - P/E Ratio explained

Buffett Indicator - Corporate Equities to GDP

Total US corporate equity value divided by US Gross Domestic Product, expressed as a percentage. Warren Buffett described this measure as probably the best single measure of where valuations stand at any given moment in his December 2001 Fortune piece. The intuition is simple: equity markets are a claim on the underlying economy, so the ratio shows whether the stock-market wrapper is running ahead of the real economy it sits on top of. Reference points across the historical record: dotcom peak (Q1 2000) ~163%, pre-GFC high (Q3 2007) ~121%, GFC trough (Q1 2009) ~69% (close to the long-run median), COVID trough (Q1 2020) ~129% (a shallow dip, not a full reset), post-COVID peak (Q4 2021) ~219%. Long-run mean since 1945 is ~86%, median ~72%. Current readings have moved well above every prior peak in the data, which is one of the reasons valuation-sensitive observers (Buffett himself, Howard Marks, John Hussman, and others) have been writing more cautiously about US equities. Methodology used here: Federal Reserve Z.1 Financial Accounts series for Nonfinancial Corporate Business Corporate Equities Outstanding (FRED NCBEILQ027S) divided by Nominal GDP (FRED GDP). FRED removed the Wilshire 5000 series in 2025 when FT/Wilshire pulled licensing, so the dashboard uses the Z.1 form that Yardeni Research and several other respected publishers adopted post-Wilshire. The Z.1 form excludes financial-sector equities, which makes the absolute level read ~80% of the Wilshire-based version (e.g. ~190% Wilshire ↔ ~150% Z.1). The cycle-position signal is preserved exactly: above mean is above mean either way. Update cadence: quarterly, tracking the Fed's Z.1 release schedule. Each new GDP print triggers a fresh value; between releases the figure carries forward. Note that GDP is revised multiple times per quarter (advance, second, third estimate plus annual revisions), so the displayed value for a given historical quarter may shift slightly over time as the underlying data is restated. The dashboard always uses the latest-available print. Marks framing: like CAPE 10 and Trailing P/E, this is one valuation input among several. Marks treats valuation metrics as evidence to be weighed, not standalone cycle calls. Read alongside the other two valuation cards and the broader cycle indicators rather than as a single verdict.

Further reading: Warren Buffett - Fortune (December 2001) - the original piece naming the indicator · FRED - Nonfinancial Corporate Equities (NCBEILQ027S) · FRED - Gross Domestic Product (GDP) · Federal Reserve - Z.1 Financial Accounts release

DXY - Trade-Weighted U.S. Dollar Index

Weighted average of the U.S. dollar's value against a basket of major foreign currencies. The dashboard uses FRED's DTWEXAFEGS (USD vs. advanced foreign economies) - same conceptual basket as the popular ICE DXY but with current trade weights, not the frozen 1973 weights ICE uses. A rising DXY tightens global dollar liquidity (bad for risk assets, bad for emerging markets); a falling DXY loosens it. Watch DXY trend alongside Fed policy expectations - they usually co-move.

Further reading: FRED - Trade-Weighted USD Index (DTWEXAFEGS) · Investopedia - U.S. Dollar Index

US 10Y2Y Spread (yield curve)

Difference between the 10-year and 2-year U.S. Treasury yields, in basis points. Positive (normal) curve: long-dated debt yields more than short-dated, reflecting expected growth + inflation. Negative (inverted) curve: short rates exceed long rates, historically a recession warning that leads downturns by 12–18 months. The 2s10s inversion of 2022–24 is the longest in modern history. The dashboard tracks this as a daily-frequency row in Section 02.

Further reading: FRED - 10Y–2Y Spread (T10Y2Y) · New York Fed - Yield Curve and Recession Probabilities

CPI / Core CPI

Consumer Price Index - average price change of a basket of consumer goods and services vs. 12 months ago. Headline CPI includes everything (food, energy); Core CPI excludes food and energy because they're volatile. The Fed watches Core CPI and Core PCE more closely than Headline when judging underlying inflation pressure. Core falling toward 2% (the Fed's target) is the disinflation signal markets price rate cuts on.

Further reading: BLS - CPI overview · FRED - All-Items CPI (CPIAUCNS, Not Seasonally Adjusted)

PPI / Core PPI

Producer Price Index - average price change for goods and services sold by U.S. producers vs. 12 months ago. We display the BLS Final Demand methodology (series PPIFIS for headline, PPIFES for core), which is the version Wall Street and Bloomberg currently report under the name 'PPI'. Older legacy series like PPI All Commodities (PPIACO) run hotter and more volatile and don't match the BLS-published headline number.

PPI is watched as a leading inflation read: producer prices typically flow into consumer prices (CPI) with a 1-3 month lag. A widening PPI-over-CPI gap suggests margin compression at the producer level (firms can't fully pass costs through) and tends to precede CPI re-acceleration. The reverse spread (CPI above PPI) tends to precede CPI cooling.

Methodology note on Core PPI. The label 'core PPI' is informal industry shorthand, not a BLS-published term, and has drifted in meaning. Older Reuters / Yahoo Finance copy used 'core PPI' to mean PPI ex food and energy (parallel to Core CPI's exclusion list). Bloomberg's current usage and the BLS PPIFES series we display use a broader exclusion: foods, energy, AND trade services. The trade-services component captures distribution and retail margins, which can swing on short-term inventory and margin dynamics rather than underlying producer-price pressure; stripping it out gives a cleaner read on persistent upstream inflation. The Fed cites this broader-exclusion version when discussing core PPI in FOMC commentary.

Further reading: BLS - PPI Final Demand overview · FRED - PPI Final Demand (PPIFIS, Not Seasonally Adjusted) · FRED - Core PPI (PPIFES, less foods, energy, trade services, NSA)

NFP - Nonfarm Payrolls

Monthly change in U.S. employment, excluding farm workers, private household employees, and non-profit organization employees. Released the first Friday of each month at 08:30 ET by the Bureau of Labor Statistics. Historically the most market-moving single macro release of any given month - consensus beats / misses by ±50k jobs routinely move equities, Treasuries, and the dollar within seconds. Pair with the unemployment rate (released the same day) for a fuller read.

Further reading: BLS - Employment Situation release · FRED - Nonfarm Payrolls (PAYEMS)

JOLTS - Job Openings and Labor Turnover Survey

Monthly U.S. Bureau of Labor Statistics release covering job openings, hires, separations, quits, and layoffs across the economy. Two series are watched most closely: the job-openings count as a labor-demand proxy (falling openings indicate a cooling labor market and create room for the Fed to ease policy), and the quits rate as a leading indicator for wage pressure - workers only quit when they are confident they can secure a higher-paying role, so a rising quits rate typically precedes wage growth and, in turn, services inflation. The Federal Reserve cites JOLTS directly in FOMC minutes. Released roughly six weeks after the reference month, so it is a lagged indicator - but its labor-market signal often moves rates and equities on the print.

Further reading: BLS - JOLTS overview · FRED - Job Openings: Total Nonfarm (JTSJOL)

ISM PMI - Manufacturing & Services Purchasing Managers' Indexes

Monthly diffusion indexes published by the Institute for Supply Management, built from surveys of supply executives across the U.S. economy. The Manufacturing PMI tracks factory activity; the Services PMI (formerly Non-Manufacturing PMI) covers the services sector, which represents roughly two-thirds of U.S. economic output. Readings above 50 indicate expansion versus the prior month; below 50 indicate contraction. Both releases include a Prices Paid sub-index that markets watch as a forward-looking inflation gauge - a rising Prices Paid reading frequently precedes a CPI surprise on the upside. The Services PMI release is typically more market-moving than the Manufacturing PMI given the services sector's larger share of GDP. This dashboard surfaces both readings (Manufacturing and Services PMI) directly from ISM's published Report on Business, alongside FRED's Industrial Production index (INDPRO) as a complementary actual-output signal.

Further reading: ISM - Report on Business · Investopedia - Purchasing Managers' Index

SOFR - Secured Overnight Financing Rate

The post-LIBOR U.S. benchmark rate for short-term USD funding, published every business day at approximately 08:00 ET by the New York Federal Reserve. SOFR measures the cost of borrowing cash overnight collateralised by U.S. Treasury securities, i.e. the actual market-clearing rate at which financial institutions lend cash against the safest available collateral. After LIBOR's manipulation scandals and discontinuation, SOFR became the official successor benchmark in 2022; trillions of dollars of derivatives, floating-rate notes, syndicated loans, and adjustable-rate mortgages now reset against it. SOFR sits structurally between the Fed Funds Target Band (policy lever) and the Treasury curve (market expectations of where rates go from here). The crypto-native equivalent is the suite of IPOR rates covered in the Crypto Macro Indicators block of Section 03.5. Comparing SOFR to USDC IPOR / USDT IPOR provides a direct read on the spread between TradFi and DeFi short-end funding markets.

Further reading: NY Fed - SOFR overview · FRED - SOFR series · Investopedia - SOFR

IPOR - Inter-Protocol Offered Rate

The first crypto-native, onchain DeFi market rate infrastructure in the industry, the DeFi equivalent of SOFR / LIBOR. A daily reference rate suite for the cost of borrowing major assets onchain, computed from the lending protocols that dominate each asset's borrow market (Aave, Compound, Lido, etc.) and published as both a spot reading and rolling DAY / WEEK / MONTH / YEAR averages. The dashboard surfaces four of the five published rates: USDC, USDT, and DAI (the three dominant stablecoins, directly comparable to SOFR as 'the cost of dollars onchain'), plus WETH, the cost of borrowing wrapped ETH. The fifth, stETH, is shown via the ETH Staking APR cell instead. IPOR rates anchor the dashboard's TradFi-vs-DeFi rate comparison: a USDC IPOR materially above SOFR signals onchain leverage demand running hot relative to the policy-anchored TradFi short end; a tight or inverted spread suggests DeFi is deleveraging. Disclosure: Vlad served as Marketing Director at IPOR Labs. Including this rate suite is both a data-quality choice (best-in-class DeFi rate methodology, no comparable alternative exists) and a personal endorsement of work he was close to.

Further reading: IPOR Fusion · IPOR Docs · IPOR Rates

Treasury bills, notes & bonds (instrument types)

U.S. Treasury debt is issued in three instrument types, distinguished by maturity and coupon structure. Treasury bills (T-bills) mature in one year or less (4-, 8-, 13-, 17-, 26-, and 52-week maturities are auctioned weekly). They pay no coupon and are sold at a discount to face value - the yield is the difference between purchase price and the par received at maturity. Treasury notes (T-notes) mature in 2, 3, 5, 7, or 10 years and pay a fixed semi-annual coupon. The 10Y note is the global benchmark risk-free rate; mortgages, corporate borrowing costs, and equity discount rates all hinge on it. Treasury bonds (T-bonds) mature in 20 or 30 years and also pay a semi-annual coupon - long-end debt that reflects long-horizon inflation and growth expectations plus QT/QE flow effects. The dashboard's bonds row tracks the 2Y, 10Y, and 30Y constant-maturity yields (FRED DGS2, DGS10, DGS30) - see the Treasury yields entry below for what each maturity signals about Fed policy, growth, and risk.

Further reading: U.S. Treasury - Securities Issued · Investopedia - Treasury Bills, Notes & Bonds

Treasury yields (2Y / 10Y / 30Y)

Yield on U.S. government debt at three benchmark maturities. 2Y is most sensitive to Fed policy expectations - rises when markets price more hikes, falls when they price cuts. 10Y is the global benchmark risk-free rate; mortgages, corporate borrowing costs, and equity valuations all hinge on it. 30Y reflects long-term inflation and growth expectations, plus QT/QE flow effects. The shape and slope of the curve (2s10s, 2s30s) matters as much as any individual level - see the yield-curve glossary entry above.

Further reading: FRED - Treasury yields by maturity · U.S. Treasury - daily yield curve rates

TIPS, Real Yields & Breakeven Inflation

Treasury Inflation-Protected Securities (TIPS) are U.S. Treasuries whose principal adjusts daily with CPI. The yield on a TIPS bond is therefore a real yield - the return an investor earns above realized inflation. The dashboard tracks the 10Y TIPS real yield (FRED DFII10) because it is the single most important number for gold, silver, BTC, and growth-stock multiples. When the real yield rises, the opportunity cost of holding non-yielding assets goes up and they get cheaper; when the real yield falls (especially into negative territory), those same assets rip. The 10Y breakeven inflation rate (FRED T10YIE) is the difference between the nominal 10Y Treasury yield and the 10Y TIPS yield - that is, the inflation rate at which the two bonds would deliver the same return. It is the bond market's best real-time read on long-term CPI expectations and is closely watched by the Fed to gauge whether inflation expectations remain anchored near the 2% target. Together, the pair lets readers decompose any 10Y nominal yield move into a 'real growth repricing' component (TIPS) and an 'inflation repricing' component (breakeven).

Further reading: FRED - 10Y TIPS Yield (DFII10) · FRED - 10Y Breakeven Inflation Rate (T10YIE) · U.S. Treasury - TIPS overview

Credit Spreads (HY OAS & IG OAS)

Option-Adjusted Spread (OAS) is the extra yield an investor demands to lend to a corporate borrower over a duration-matched U.S. Treasury, after stripping out the value of any embedded options (callable bonds, etc.). Quoted in basis points. The dashboard tracks two ICE BofA index OAS series from FRED: HY OAS (BAMLH0A0HYM2, junk-rated US issuers) and IG OAS (BAMLC0A0CM, investment-grade US issuers). Credit spreads are the credit market's risk thermometer: tight spreads = lenders are sanguine, risk appetite is high, often a late-cycle signal of complacency. Wide spreads = lenders are demanding more premium for default risk, often a cycle-turn signal that precedes an equity decline. Howard Marks's framework (Section 06) cites credit spreads as one of the key cycle indicators for exactly this reason. Historical regime markers for HY OAS: <250 bp = late-cycle tight (2007, 2021). ~300-400 bp = normal expansion. >500 bp = stressed (recession-adjacent). >1000 bp = panic (2008 GFC, March 2020 COVID). For IG OAS, the equivalent markers are roughly <80 bp tight, ~100-130 bp normal, >200 bp stressed.

Further reading: FRED - ICE BofA US High Yield OAS · FRED - ICE BofA US Corporate Index OAS

Major central banks (Fed · ECB · BoE · BoJ · RBA · PBoC)

Macro narrative on this dashboard frequently references foreign central-bank decisions alongside the U.S. Federal Reserve. The five most market-relevant non-U.S. central banks for global investors are: the European Central Bank (ECB), which sets monetary policy for the 20 eurozone economies via its Deposit Facility Rate and Main Refinancing Operations Rate; the Bank of England (BoE), which sets the U.K. Bank Rate via its Monetary Policy Committee; the Bank of Japan (BoJ), historically the most accommodative major central bank, which sets the Policy Rate and conducts Yield Curve Control; the Reserve Bank of Australia (RBA), which sets the Cash Rate Target and is closely watched as a commodity-currency bellwether; and the People's Bank of China (PBoC), which manages China's Loan Prime Rate (LPR), Reserve Requirement Ratio (RRR), and the offshore yuan reference rate. Foreign central-bank decisions move U.S. assets primarily through three channels - the U.S. dollar (DXY), cross-asset risk sentiment, and global liquidity conditions. Per editorial convention on this dashboard, any rate-decision reference is prefixed with the central-bank acronym (e.g. Fed rate decision, RBA Cash Rate, ECB deposit rate) so the country is never ambiguous.

Further reading: Federal Reserve - Monetary Policy · ECB - Key interest rates · Bank of England - Monetary Policy · Bank of Japan - Monetary Policy · Reserve Bank of Australia - Cash Rate

Spot ETF Flows

Net daily inflows (or outflows) of capital across the spot exchange-traded funds for an asset - for crypto, the BTC, ETH, and SOL spot ETF complexes. Positive flows mean creation units are being struck (new shares issued, AUM expanding); negative flows mean redemptions (shares retired, AUM shrinking). Treated as a proxy for institutional/RIA capital allocation since most professionals access crypto via these vehicles rather than spot exchanges. The dashboard sources daily flows from Farside Investors with T+1 settlement.

Further reading: Farside Investors - daily ETF flows

Perp Funding Rate

Periodic payment between long and short holders of a perpetual futures contract, used to keep the perp's price tethered to the underlying spot price. Positive funding: longs pay shorts (market positioned bullish, paying a premium to hold leverage). Negative: shorts pay longs (market positioned bearish). The dashboard shows BTC and ETH funding from Binance USD-M as an annualized APR. Extreme positive funding (>30% APR) often warns of a crowded long; extreme negative often marks short-squeeze fuel.

Further reading: Binance - perp funding rates explained

Fear & Greed Index (Crypto + Equity)

Composite sentiment scores (0–100) summarizing crowd psychology. The dashboard tracks two separately: alternative.me's Crypto F&G (inputs: crypto volatility, momentum, social media, surveys, BTC dominance, Google trends) and CNN's Equity F&G (inputs: market momentum vs. 125-DMA, stock-price strength, breadth, put/call ratio, junk-bond demand, VIX, safe-haven demand). Convention: <25 = Extreme Fear, >75 = Extreme Greed. Famously useful as a contrarian signal at extremes - though always with caveats. The dashboard reads it directionally (Greed = green) rather than contrarian, leaving the contrarian read to the Howard Marks cycle assessment.

Further reading: alternative.me - Crypto Fear & Greed · CNN - Fear & Greed Index

News Sentiment (JungleTrade)

JungleTrade's general-news-sentiment model is an LLM analyzer that reads a continuously-updated window of crypto and macro news articles (Decrypt, CoinDesk, Nasdaq News, NewsBTC, others) and grades each one for directional sentiment. The aggregate is a single signed score from -100 to +100. The dashboard cell maps that score to a five-tier label using the same Fear/Greed vocabulary as the two market-driven Fear & Greed rows alongside it: |score| < 5 = Neutral, 5 to 50 = Fear or Greed (clear directional bias), ≥ 50 = Extreme Fear or Extreme Greed (strongly one-sided news flow). Different signal from the two F&G indices around it: those are built from market-data inputs (CNN's equity index from price/volume momentum, alternative.me's crypto index from market cap, volatility, social media volume, dominance). This one tracks how crypto is being talked about, which can lead, lag, or contradict what the market is doing.

Further reading: JungleTrade

GICS - Global Industry Classification Standard

Industry classification taxonomy jointly maintained by MSCI and S&P Global, used as the canonical sector framework across the indexing industry. GICS organises the global equity universe into 11 sectors (Energy, Materials, Industrials, Consumer Discretionary, Consumer Staples, Health Care, Financials, Information Technology, Communication Services, Utilities, Real Estate), 25 industry groups, 74 industries, and 163 sub-industries. Most ETFs (the Select Sector SPDRs, iShares, Vanguard, etc.) and most professional sector-rotation analysis use GICS as the unit of analysis. The dashboard's Section 03.2 sector-rotation strip shows today's % change across all 11 GICS sectors, sorted best-to-worst, so you can read leadership at a glance.

Further reading: MSCI - GICS overview · S&P Global - GICS

US Federal Debt & Servicing Cost

Four related indicators shown in the US Rates section's 'US Debt & Servicing' and 'Rate & Rollover Risk' rows, all sourced from the U.S. Treasury Fiscal Data API (fiscaldata.treasury.gov, public domain). Total federal debt (Debt to the Penny, daily): all debt held by the public plus intragovernmental holdings. The pill shows the 1-day change; the sub-line shows the year-over-year change. Annual gross interest cost: computed as the weighted-average interest rate on all interest-bearing debt multiplied by total debt outstanding. This is the gross servicing figure, not the smaller 'net interest' number commonly cited by the CBO (which nets out intragovernmental interest received back to the Treasury). The gross figure represents the full all-in annual cost of carrying the debt stock. Monthly data; lags by up to one month. Weighted-average interest rate (Average Interest Rates on Treasury Securities, monthly): the blended rate the Treasury pays across all interest-bearing debt. Rises slowly as maturing low-coupon debt is rolled over at current market rates, so it structurally lags spot market yields. Debt maturing within 12 months (Monthly Statement of the Public Debt): marketable debt coming due within the next 12 months, expressed as a percent of total debt outstanding. The primary refinancing-risk gauge: that marketable portion gets refinanced at prevailing market rates within the year.

Further reading: U.S. Treasury Fiscal Data - Debt to the Penny · U.S. Treasury - Average Interest Rates on Treasury Securities · U.S. Treasury - Monthly Statement of the Public Debt (MSPD)

Howard Marks Market Cycle

Framework laid out in Howard Marks's Mastering the Market Cycle (2018) for reading where the current investment environment sits - by interpreting investor psychology, not by forecasting prices. The dashboard's daily assessment (/howard-marks-market-cycle.html) scores 9 indicators (valuations, sentiment, credit spreads, IPO/M&A, leverage, fund flows, etc.) green (cold/fear/attractive entry) or red (warm/euphoria/poor entry). The framework is intentionally counterintuitive: green means the conditions look bad - which historically means future returns are higher. Red means conditions look great - which historically means future returns are lower.

Further reading: Oaktree Capital - Howard Marks memos

Pre-IPO & Onchain Equity Perps

Pre-IPO and listed-equity perpetual-futures markets running on Hyperliquid's permissionless HIP-3 rails. Three venues are involved: Hyperliquid is the trading L1 and API, Ventuals deploys the pre-IPO DEX, trade.xyz deploys the listed-equity DEX. The dashboard's pre-IPO section reads them all via Hyperliquid's public /info endpoint. The distinctive signal is the mark-vs-oracle premium on the pre-IPO names: the spread between where perp traders are pricing each company and the externally anchored valuation from Notice.

Further reading: Hyperliquid docs - HIP-3 · Ventuals · trade.xyz

Mark-vs-oracle premium

Each perpetual contract on Ventuals has two prices that matter. The oracle is Notice's externally anchored valuation, combining secondary-market transactions, funding-round announcements, mutual fund marks, 409A valuations, and a public-company basket. The mark is the venue's smoothed perp price, where traders are actually paying. The premium is mark relative to oracle, in percent. Positive premium means perp traders are pricing the company above its externally anchored fundamental valuation; negative premium means a discount. The reading sits alongside the rest of the dashboard's signals for the reader to weigh, not as a standalone cycle call. On listed equities the oracle tracks the public-market quote so the premium collapses to roughly zero and we omit the pill.

Further reading: Ventuals docs

HIP-3 (Hyperliquid Improvement Proposal 3)

The mechanism that lets builders deploy their own perpetual-futures DEXs on Hyperliquid's L1, with custom markets, oracles, and fee recipients. The Ventuals (vntl) and trade.xyz (xyz) DEXs we read from are HIP-3 deployments. Each carries its own asset universe but shares Hyperliquid's order book, settlement, and public API.

Further reading: Hyperliquid docs - HIP-3

05Privacy & GDPR

What we collect (and what we don't)

The dashboard takes a privacy-first posture: no cookies, no fingerprinting, no advertising trackers, no consent banner needed. The only browser-side telemetry on the live site is Cloudflare Web Analytics - a cookieless aggregate pageview counter delivered automatically by the Cloudflare proxy (no individual-user profiling, no cross-site tracking, no data shared beyond Cloudflare; see Cloudflare's privacy posture). Server-side, the only log is the nginx access log, which auto-rotates and is not analyzed.

The feedback widget, when used, collects only what you voluntarily type - your sentiment choice (like / dislike / idea), an optional name or alias, your comment, an optional contact field (LinkedIn URL, email address, or Telegram handle - provided only if you'd like a reply), and the URL of the page you submitted from (for context). The contact field is stored alongside the submission solely so the author can reply to you; it is never used for any other purpose, never shared with third parties, and never added to any mailing list. If you do not provide contact details, your submission is treated as one-way input and reviewed without a reply.

Your raw IP address is never stored. Submissions are rate-limited (3/hour per IP), but the IP is one-way hashed with SHA-256 using a salt that rotates every 24 hours - so the same IP produces a different hash on different days, and the hash cannot be reversed back to the IP. The hash exists solely to enforce the rate limit.

What we do with feedback data

Feedback submissions are written to a local CSV file on the droplet hosting this site, and a notification is sent to the author via Telegram. The data is not shared with third parties, not used for advertising, not used to build user profiles, and not used to train models. The CSV is never published.

Your rights under GDPR

If you're in the EU/EEA, you have the rights to access, rectify, erase (right to be forgotten), restrict processing of, receive a copy of (portability), and object to processing of any data we hold about you, plus the right to lodge a complaint with your local data protection authority. To exercise any of these rights, message the author via the feedback widget itself (note which submission you want acted on) or via LinkedIn DM. Manual deletion is performed within 30 days of a request.

Third-party data sources

The dashboard fetches market data from third-party providers (FRED, FMP, CoinGecko, DefiLlama, Hyperliquid, Farside Investors, Binance, alternative.me, CNN's dataviz endpoint). These calls happen server-side, on a schedule - when you load the dashboard, your browser only fetches static HTML/CSS/JS from dailymarket.report itself. No user data is transmitted to those providers.

Data controller

The data controller for this site is Vladislav (Vlad) Dramaliev in his individual capacity. Contact via the feedback widget or LinkedIn DM.

Updates to this policy

This policy may evolve as the dashboard adds new features. Material changes will be noted in the dashboard's update history; the canonical version always lives at this URL.

06Contact & Feedback

The best way to reach the author is the feedback widget in the lower-right corner of every page on the site - three sentiment options (something I like, something I dislike, an idea), a short comment field, and an optional contact field for those who would like a reply (LinkedIn URL, email address, or Telegram handle accepted). Submissions are delivered directly to the author and the success state confirms when the message landed.

For longer correspondence, the secondary channel is a LinkedIn DM to Vladislav (Vlad) Dramaliev. Data-source suggestions, methodology critiques, bug reports, and partnership inquiries are all welcome on either channel - both are read.