Blog
Guides, product news and research from KlickAnalytics — practical workflows for market data, analytics and investment teams.
Set up KlickAnalytics in Slack for your desk, step by step
Add the app to your workspace, connect everyone on the desk, and build a daily routine of commands — from the morning check to sharing a chart with the channel.
Introducing KlickAnalytics for Slack: every CLI command, where your team already talks
Type /ka and any KlickAnalytics CLI command in Slack. Answers are private until you share them, charts come back as images, and /ka help teaches the commands as you go.
Build a cross-asset correlation dashboard and review it with your team
One data pull, an eight-asset correlation matrix and a chart — then share it, see where colleagues are working, and settle questions in comments on the cell.
Run your desk rule book and company handbook in Wiki
Set up a trading desk manual from a template, make the numbers yours, protect the pages that are policy, and share one company handbook with every team.
Introducing Wiki: one place your teams write down how they work
A wiki for every team — folders, pages and a notebook-style editor, version history on every page, sharing with other teams, and notifications when something changes.
Ask the market a question. Get a calculated answer.
The AI is not a chatbot bolted onto a document store. It calls the same analytics engine that powers every screen on this platform — so what comes back is a number it computed from raw history, with the command that produced it.
86,000+ instruments
Global equities, ETFs, funds, options, FX, commodities, crypto, economics, filings, transcripts and news — one normalised symbol universe with adjusted history.
A real analytics engine
Screening, backtesting, technicals, options analytics, correlations, seasonality and factor models — computed on demand from raw prices, never a stale cache.
It shows its working
Answers arrive with the charts, tables and tool calls behind them, so you can check the number instead of trusting a paraphrase.
Your own documents
Upload filings, decks and research. Ask across them and the answer cites the page it came from.
Agents and workflows
Multi-step research that runs the platform's tools for you — screen, pull the history, compute, compare, then write it up.
MCP, CLI and API
The same command catalogue from Claude, your own agent, a shell or your pipeline. The answer on screen is the answer your job gets at 4am.
You ask
“How does NVDA usually trade through earnings?”
It calls
→ ka.options_expected_move(NVDA)
It answers
NVDA has averaged a 9.2% absolute move on the day after earnings and closed higher 67% of the time. Two in three reactions land between −4.2% and +16.3% — the distribution is skewed right, not symmetric.
Every figure computed live from our own history — not scraped, not summarised.
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