MarketLens
Tuesday, 25 August 2026
what the news does to markets

How it works

Financial news tells you an event happened. It rarely tells you the thing that matters: who else is affected, and how? The obvious effect is priced within minutes of the headline. The interesting one is two or three steps down the chain, hitting a company nobody has mentioned, or a currency, or a fund forced to sell something unrelated.

MarketLens traces those chains, every weekday morning, in the same three stages.

The three stages

StageQuestion it answers
1. What happenedThe event in plain English, and whether the market had already expected it.
2. How it spreadsEach consequence, link by link, with each link caused by the one before it.
3. What it meansThe effect on each market, with a direction, a size, a timeframe and a confidence score.

Picking the stories

Every morning before the London open, the system reads headlines from 23 sources: central banks and statistical agencies, wire services and financial newsrooms, and specialist feeds for each asset class. Around 257 articles come in on a normal day.

Near-identical headlines are grouped, so a story carried by eight outlets counts as one event with eight sources rather than eight events. Each group is then scored out of 100:

What is measuredMaxWhy it counts
How many outlets ran it30The best available signal that something is genuinely important
How authoritative the source is20A central bank announcement outranks an aggregator
How many markets it touches20Breadth is what makes a story worth a full analysis
How market-relevant the language is20Weighted vocabulary, so "tariff" counts for more than "quarterly"
How fresh it is10Decays over a 36-hour window

This step is deliberately mechanical and cheap. It cuts several hundred headlines down to about 25 before any expensive analysis begins. The score for each published story is shown on its own page, so you can check the working.

Tracing the chain

Every knock-on effect has to travel through one of eight named routes. That constraint is the whole design. Without it, this kind of analysis drifts into saying markets might be volatile, which is true every day and useful never.

RouteWhat it means
What central banks do nextChanges how likely it is that central banks cut or raise interest rates, and how quickly.
The cost of moneyMoves government bond yields, which set the baseline return every other investment is judged against. When that baseline moves, everything reprices.
Company profitsChanges revenue, costs or pricing power somewhere in a supply chain, including for companies not mentioned in the story.
Borrowing costsChanges how expensive or how easy it is for companies to borrow, which matters most for those already carrying a lot of debt.
Currencies and tradeMoves an exchange rate, which changes what importers pay and what exporters earn.
Who is forced to tradeInteracts with bets investors already hold. When a crowded position goes wrong, forced selling pushes the move further than the news alone justifies.
How assets move togetherChanges whether assets that normally offset each other still do. When those relationships break, hedges stop working and leveraged funds are forced to cut risk.
Knock-on to similar assetsRead-across to competitors, suppliers, customers and assets that investors treat as alternatives.

Two versions of everything

Each claim is written twice. The plain version explains what it means to someone who reads the news but does not work in markets. Underneath sits the same point in the language a trading desk would use, with the exact mechanism. Neither reader has to put up with the other's version.

Being marked

Whenever the analysis makes a confident directional call, it is logged with the market price at that moment and scored against what actually happened once its timeframe is up. The scorecard shows the record, including every miss, broken down by market and by how confident the call was. If the confident calls are not more accurate than the hedged ones, the confidence scale is meaningless, and that will be visible on the page rather than hidden.

What it cannot do

  • The analysis is generated by a language model. It reasons well about how things connect and badly about precise numbers, which is why every size is a range and no figure is presented as a data point.
  • It reads only freely available sources. Paywalled reporting and real-time wire services are not included.
  • Market data is delayed. It is used for context and for scoring, never for trading.
  • It runs once a day. This is a way of thinking about how news travels, not a live trading signal.

Who built it

Jonathan Savill. MarketLens is an independent project, built to develop and demonstrate a structured way of reading cross-asset news. The whole pipeline, from reading the feeds to scoring the calls to rendering this page, is custom-built with no third-party code.