What's New
Product updates, improvements and fixes across the KlickAnalytics platform.
Build and Share Your Team’s Knowledge With Wiki

KlickAnalytics now includes a shared Team Wiki—a central place to create, organize, maintain, and share the knowledge that guides your team’s work.
Use Wiki to document:
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Trading rules and investment processes
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Portfolio and risk-management policies
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Research standards and review procedures
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Data definitions and analytical conventions
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Operational workflows and checklists
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Team onboarding and training material
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Market playbooks and strategy documentation
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Frequently used internal resources
With the KlickAnalytics Wiki, teams can:
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Create pages and organize them into folders
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Build a clear hierarchy for different desks, strategies, or functions
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Search across the complete Wiki
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Edit and update shared content
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See when a page was updated and by whom
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Track page revisions and review changes over time
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Use permanent page addresses for quick access
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View recently updated pages
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Share institutional knowledge across the team
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Keep important processes accessible inside the same platform used for market research
A portfolio manager can maintain an investment rule book. A risk team can publish exposure limits. A research desk can document its methodology. New team members can find onboarding material without searching through messages and disconnected files.
The Wiki turns knowledge that often lives in individuals, emails, and scattered documents into a structured resource for the entire organization.
Document the process. Share the knowledge. Build institutional memory.
To access: From the Meny > My > Wiki
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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