Dashboard: Methodology and Sources

In depth16 min read · updated 5 November 2026 · 17 sources

The dashboard shows all markets at a glance at the daily close: stocks, bonds, currencies and commodities, plus yield curves, the rate moves priced in for the Fed and the ECB, the S&P 500 volatility surface, the economy and upcoming dates. This methodology explains how the code computes each tile, which assumptions it makes and where the numbers come from. Some sources require attribution under their terms of use; the full list is below.

Layout and timeliness

The dashboard groups its tiles by theme: an overview, stocks and risk, rates and bonds, and currencies, commodities and macro. You can create your own views, move tiles and resize them; larger tiles show more rows, columns or comparison lines, not just the same content bigger. All values are daily closes, not real-time quotes.

A daily snapshot is computed in the nightly run, or on the first request of the day if the run failed, and stays in the cache until the next run. If a price tile is missing the close of the last business day, for example because the price source returned nothing overnight, the code tries again after two hours. If a source fails, only its part stays empty; the rest still appears, with a note below the grid. The periods of the price tiles bundle the candles differently:

Where the price source provides no candles (always for currencies and yields), they are built from closing prices: the open is the previous close, and high and low are the larger and the smaller of the two. You can tap or hover over every line and every candle to see its date and value.

Prices via ETFs in local currency

Index levels require a license, so the dashboard measures each market through a broad exchange-traded fund (an ETF, an ETC for commodities, and a physically backed ETP for bitcoin) from general price data. Topix and Hang Seng come from their large index ETFs on the home exchange, in yen and Hong Kong dollars. The selection is a gauge for each market, not a recommendation. So that a euro-traded ETF on US stocks shows the return of the US market and not that of the dollar, the code converts every price into the market's currency with the ECB reference rates (ECB, reference rates 2026), day by day, using the last known rate on days without one.

The market table shows for each ETF the return over 1 day, 1 week (5 trading days), year to date (against the last price of the prior year) and 1 year, plus the position within the range of the last 52 weeks from 0 (low) to 100 (high). Each price tile shows the change over the selected period in large type and today's change in small type, and at the bottom the date range and the currency, the level for yields and the rate for currencies; yields change in basis points. Flat tiles in the overview show the same numbers more compactly. The article Currency risk explains how exchange rates change an investment.

The German edition quotes currencies against the euro (EUR/USD, EUR/JPY …). This English edition quotes them against the dollar, as is customary in the markets: EUR/USD, GBP/USD and AUD/USD in dollars per unit, the others as USD/JPY, USD/CHF, USD/CNY and USD/CAD in units per dollar. These are cross rates from the same ECB reference rates, for example with 165.00 yen and 1.0800 dollars per euro USD/JPY = 165.00 / 1.0800 = 152.78. The currency matrix then starts with the dollar, and the correlations are computed in dollars. Stocks, sectors and commodities stay in their local currency in both editions.

Volatility, trend, factors and correlations

• Historical volatility: standard deviation of daily log returns over the last 20 trading days, annualized with √252, plus its percentile rank among all values of the last 5 years and their median.
• Trend: distance of the last price from the moving average of the last 200 trading days in percent; above it counts as an uptrend.
• Sectors and commodities: return over the selected period (as on the price tiles) and over 1 day, world sectors in US dollars. The sector colors scale with the square root of the period length.
• Factors: excess return of momentum, value, quality, small caps, low volatility and dividend against the world ETF, both in euros, over the selected period and year to date.
• Correlations: correlation of daily returns of stocks (world), euro government bonds, gold, oil and the dollar over the last 60 common trading days, all computed in euros; in the English edition with US Treasuries and EUR/USD instead of euro government bonds and the dollar, all in dollars. With fewer than 10 common days the matrix stays empty.

More tiles on equities and risk

These tiles sit on the Equities and risk page and can be added to your own views. Like the others, they use ETF prices in local currency (total return), not index levels, and hold until the next nightly run.

• Distance from high: distance of the latest price from the high of the last 52 weeks and from the highest level since the series began (all-time), in percent, plus the calendar days since the 52-week high; for the markets of the price tiles and the world sectors. Because the series include distributions, an ETF's all-time high often comes later than that of the price index.
• Returns calendar: return per calendar month over the last twelve months, the current month up to the latest price (dashed).
• Sector rotation: relative strength and momentum of each sector against its market from weekly closes: world sectors against the world ETF, Stoxx Europe 600 sectors against the Stoxx Europe 600 ETF, US sectors against the S&P 500 ETF. The tile shows the path of the last 8 weeks.
• Market breadth: share of ETFs on countries, regions, sectors and factors whose price is above the moving average of the last 200 trading days, as a weekly history over one year.
• Stock-bond correlation: correlation of daily returns over 60 trading days, rolling over five years: world equities against euro government bonds in euros and the S&P 500 against US Treasuries in dollars, plus the median of the five years and the value one year ago.
• Seasonality: average return and share of positive years per calendar month, over full calendar years only, for the S&P 500, the DAX and gold through their oldest large ETFs. The current month is highlighted.

If an ETF's price jumps by a factor of 3 or more in one day, that is not a real market day for a broad fund. If it comes back within 5 trading days, the days in between drop out as data errors; otherwise the jump counts as an unadjusted stock split and the history before it is rescaled. This applies only to these tiles.

US insider buying and my watchlist

The US insider buying by sector tile counts the mandatory filings on trades by officers, directors and major shareholders in their own company's stock with the SEC (Form 4, more under insider trading). Only open-market purchases and sales (codes P and S) in the table of shares count, not grants, option exercises, gifts or tax withholdings. A filing counts as one buy if it contains at least one purchase and as one sale if it contains at least one sale, so a sale executed in many parts counts only once. What matters is the filing date, over the last 30 calendar days up to the latest daily index of the SEC.

The sector follows the company's SIC code at the SEC, mapped to our own scheme of eleven sectors as in the multiples calculator; funds and shell companies do not count. The tile shows a share only from 10 filings. The tick is the median of the monthly values over the last 12 full months from the SEC's quarterly data sets (Insider Transactions Data Sets); if the share is above it, the bar is green. Sales almost always dominate because officers receive a large part of their pay in stock and sell regularly. Research finds purchases more informative than sales (Lakonishok and Lee 2001), and routine trades carry little information (Cohen et al. 2012). What you can read is therefore mainly the deviation from the sector's own median, not the level.

My watchlist is your own list of up to 20 stocks, ETFs, funds or indices, added through the search and saved in your account. For each security the tile shows the latest closing price in local currency and the change from the previous day, over one month or over one year, plus the history (one month daily, one year with weekly closes). Asset classes only have monthly values and are not available in the list.

Yield curves, risk premiums and inflation expectations

The US yield curve consists of constant-maturity Treasury yields for 1, 2, 5, 10 and 30 years from the Treasury Department's daily yield curve (US Treasury, yield curves 2026). The Treasury publishes it on the evening of the trading day; the Fed adopts it one business day later in H.15 (Federal Reserve, H.15 2026), and the code falls back on H.15 if the Treasury is unavailable. The German curve comes from the Bundesbank's daily estimated term structure for the same maturities. Like the ECB, the Bundesbank estimates its curve with the method of Svensson (1994), an extension of Nelson and Siegel (1987). The tile shows today's curves and those of a year ago, plus the steepness, the difference between the 10-year and 2-year yields in basis points. Background in the article Yield curve.

Spreads from index providers require a license. The credit risk tile therefore shows no spread in basis points but a long-short of two bond ETFs in their fund currency: high yield against government bonds of similar maturity in the US and the euro area, and euro corporate bonds against euro government bonds. At the start of the period the price ratio is set to 100. If it rises, the riskier bonds have done better, which usually goes with tighter spreads.

US inflation expectations are the breakeven inflation for 5 and 10 years, the difference between the yields of nominal and inflation-protected Treasuries, plus the 10-year real yield, both from the Treasury Department's curves (US Treasury, yield curves 2026). Gürkaynak et al. (2010) show that this difference is not a pure expectation: an inflation risk premium and a liquidity premium distort it.

Recession signal and mortgage rates

The recession signal shows the spread between 10-year and 3-month yields as a monthly average since 1980. For the US this is the 10-year Treasury yield minus the 3-month T-bill yield, plus the probability of a recession within 12 months from the probit model of the Market expectations page (methodology) and the NBER recessions as gray areas. For Germany it is the 10-year Bund yield minus the 3-month money market rate from the OECD series, without a model. Below zero the curve is inverted; the tile says for how many months the spread has been above or below zero.

The mortgage rates are, for Germany, the effective rate on new housing loans to households with an initial rate fixation of over 10 years (MFI interest rate statistics, monthly) and, for the US, the 30-year fixed mortgage rate from Freddie Mac's weekly survey, as a monthly average. The tile shows ten years and the change from a year earlier in percentage points.

Futures positioning, liquidity, purchasing power parity and leading indicator

• Futures positioning: Williams COT index for the net position of speculators (hedge funds or managed money) in gold, WTI crude, the euro and the S&P 500 from the weekly CFTC reports: 0 is the shortest and 100 the longest position of the last 3 years, plus the change from the previous week. The values are the same as on the Sentiment page.
• Liquidity: total assets of the Fed (weekly, H.4.1) and of the Eurosystem (weekly financial statement) in trillions, change from the previous month and the history over ten years, plus the growth of US M2 and euro area M3 money supply from a year earlier.
• Purchasing power parity: for each country, the OECD publishes how many units of its own currency buy the same GDP goods as one US dollar in the United States. This gives an exchange rate by purchasing power, which is compared with today's ECB reference rate. Above zero the currency is more expensive than purchasing power implies. The German edition measures against the euro, the English edition against the dollar.
• OECD leading indicator: the OECD Composite Leading Indicator, amplitude adjusted, with the long-term trend at 100. The phase follows the OECD: above 100 and rising expansion, above 100 and falling cooling, below 100 and falling downturn, below 100 and rising recovery (each against the previous month). "Europe" combines Germany, France, Italy and the UK (the OECD's four big European economies).

Central bank rate expectations

The rate moves the market prices in for the next meetings are usually read from futures and interest rate swaps, whose prices are licensed. The dashboard uses public yields instead: for the Fed, the effective federal funds rate and Treasury bill yields for 1, 3, 6 and 12 months (Federal Reserve, H.15 2026); for the ECB, the €STR (ECB, €STR 2026) and the 1- to 12-month spot rates from the ECB yield curve for AAA-rated government bonds (ECB, yield curves 2026).

The idea: a yield with maturity T is roughly the average policy rate until T plus a spread (term premium, scarcity of the securities). Between two meetings the policy rate is constant. The code looks for one rate per meeting up to the longest maturity. Because there are more meetings than maturities, it solves a least-squares problem with light smoothing that penalizes large jumps from one meeting to the next.

The values are an approximation and can differ from futures by a few basis points. Piazzesi and Swanson (2004) show that fed funds futures, too, contain a time-varying risk premium that has to be separated from the path; Fama (1984) finds that expected returns on Treasury bills vary with maturity. A fixed spread captures both only roughly. The meeting dates come from the central banks' calendars and are extended once a year.

Volatility surface and VIX curve

The volatility surface shows the implied volatility of options on the S&P 500 ETF SPY by strike and maturity. It is built from the smiles that the Options tool fits every night for each expiry in SVI form (Gatheral and Jacquier 2014). The dashboard reads each curve at 80 to 120% of the forward in steps of 5%. Expiries with less than 14 days left are excluded because their steep wings distort the surface, as are expiries less than 10 days after the previous one; at least two are required.

Next to it are the at-the-money volatility by maturity and the smile of the nearest expiry. You can rotate the surface with the mouse or a finger, or with the arrow keys; a double click or Home resets the view. The VIX curve shows the volatility indexes for 9 days, 1, 3 and 6 months and 1 year, today and one month ago; if the 3-month value is above the 1-month value, the tile says contango. The calculation is described in the volatility methodology.

Economy, dates and context

The table Economy compared shows for each region real growth year over year, inflation, the unemployment rate and the policy rate, each as the latest published value. The euro area, Germany and the US come from the time series of the Macro page (Macro methodology). For the United Kingdom, Japan and China the code uses OECD growth and unemployment rates (OECD, GDP growth 2026; OECD, unemployment rates 2026) and BIS consumer prices and policy rates (BIS, consumer prices 2026; BIS, policy rates 2026); there is no unemployment rate for China there.

The dates show the rate decisions of the Fed, the ECB, the Bank of England and the Bank of Japan, and the releases of US consumer prices, the employment report and GDP over the next 75 days, each with the latest value from our own time series. The dashboard shows no forecasts or consensus estimates. If a central bank's list reaches less than 60 days into the future, the code flags it.

The Context strip takes one number each from other tools, with a link to them:

The My portfolios tile computes the portfolios from the backtest with fixed weights, rebalanced to the target weights daily, in the base currency: return over 1 day, year to date and distance from the high of the last 52 weeks. Asset classes with monthly data only and holdings without prices are left out; the remaining weights are scaled up to 100%. The Ships at chokepoints tile (not part of the default layout, available under Add tiles) counts tankers and cargo ships at five straits and canals (Ships methodology).

Sources and terms of use

Prices of ETFs and ETCs and the options data come from general price data, the volatility indexes from the index provider. For the following public data the terms require attribution, which appears here and in the tiles:

• OECD: real GDP growth (OECD, GDP growth 2026) and unemployment rates (OECD, unemployment rates 2026), license CC BY 4.0. The values are used unchanged, only rounded.
• BIS (Bank for International Settlements): consumer prices (BIS, consumer prices 2026) and policy rates (BIS, policy rates 2026). The German and English labels in the dashboard are not an official BIS translation.
• European Central Bank: reference rates (ECB, reference rates 2026), €STR (ECB, €STR 2026) and yield curves (ECB, yield curves 2026).
• US Treasury Department and Federal Reserve: daily yield curves for nominal and inflation-protected Treasuries from the Treasury (US Treasury, yield curves 2026); the effective federal funds rate, Treasury bill yields and, as a fallback, the curves from the Fed's H.15 (Federal Reserve, H.15 2026).
• Deutsche Bundesbank: term structure of interest rates for the German yield curve.
• CFTC: Commitments of Traders (weekly, public domain). OECD: purchasing power parities for GDP and Composite Leading Indicators (CC BY 4.0). Federal Reserve: total assets (H.4.1) and M2 money supply. ECB: weekly financial statement of the Eurosystem and M3 money supply.
• Freddie Mac: Primary Mortgage Market Survey for the US mortgage rates; the data may be used with attribution, which the tile shows.
• SEC: Form 4 filings from EDGAR and the Insider Transactions Data Sets (public domain, retrieved under the SEC's rules for automated access).
• ECB, MFI interest rate statistics: rates on housing loans in Germany; OECD: long-term interest rates and the 3-month money market rate for Germany (CC BY 4.0); NBER: dating of US recessions.

None of these institutions has reviewed or endorses the dashboard. The central bank dates come from their published calendars; the server retrieves the US release dates automatically.

Limitations

• Daily close: all values refer to the last trading day; markets in other time zones close at different times, which blurs correlations of daily returns.
• ETFs instead of indexes: costs, dividends and tracking differences are part of the returns; single days can differ from the index.
• Credit risk as a price ratio: besides the spread, the ratio also reflects differences in maturity and interest rate risk between the two funds, and it is not a spread in basis points.
• Rate expectations as an approximation: the spread between yields and the policy rate fluctuates; the path depends on the smoothing and differs from futures.
• Lagging macro data: growth and inflation appear weeks to months after the period they describe and are often revised later.
• Insider filings: Form 4 must be filed within two business days after the trade, so the tile lags slightly. Amendments (4/A) do not count, and large sectors with many companies dominate the value for all sectors.
• Not investment advice: the dashboard describes the situation; it does not tell you whether or how to react.

This page describes how Portfolio Lab calculates; past results are not a forecast. All terms in the glossary.