Research
Each desk brings several published topics together to examine one economic question: how the series move together, which moves first, and which readings warrant attention. Every figure is cited to an approved snapshot.
A topic covers one dataset with its charts and sources. A research desk combines several topics, for example monetary policy, credit and the rupee, and adds a correlation matrix, lead–lag checks and screens with stated thresholds.
9 desks read 18 published topics. Each card lists the topics behind it.
The RBI policy rate and liquidity alongside credit, inflation, the rupee and the reserves the RBI bought or sold, compared fiscal year by fiscal year with the sample size shown, and this week's conditions from RBI's weekly statistics.
Brent, the petroleum import bill, the goods and services balances, foreign portfolio money, RBI's dollar sales and the rupee, month by month: how fast an oil shock reaches the import bill, what moves with what, and who covered the gap.
Compare market and sector returns, mutual fund flows, foreign buying and fund results across five topics, alongside inflation, the rupee, rates and money growth.
India's ten largest banks set beside the whole banking system, the repo rate, inflation, the stock market and the money flowing into it: their share of all lending, which measures move with them, how closely, and over how many matched periods.
UPI payments set against household spending, GST and consumer prices, to separate three explanations for rising payments: more payments, larger payments or higher prices.
What is keeping India's CPI away from 4%, and whether household fuel is moving with Brent at a lead chosen in advance.
The latest fiscal year's budget gap beside the current account, and which capital flow financed the external gap.
CPI contributions by category, compared with oil, jobs, wages and the effective Fed rate for timing, with risk screens and a back-tested one-month baseline.
Japan policy, dollar funding and Treasury-market pressure, with an explicit bond-sale scenario.
Every pair of series on the desk, with the number of matched periods behind each cell. For example, a reading of +0.6 across 40 matched months means the two series tended to rise and fall together; a reading near zero means no consistent pattern.
Whether one series tends to move before another. A lead is a timing pattern in past data, not proof that one caused the other.
Each screen names its watch line and its basis, so a flagged reading can be checked against the published rows and the source.
Share the question, the data sources and the method you would use. We can turn it into a research desk with published evidence and clear source notes.