What's New
Product updates, improvements and fixes across the KlickAnalytics platform.
Historical Seasonality by Years/Months
To enhance your experience and make data analysis more intuitive, we’re introducing several exciting product updates based on the historical returns table. First, we’re transforming the returns table into an interactive heatmap. This new feature will allow you to visually assess performance trends at a glance. By simply hovering over any month, you’ll gain immediate access to exact return values and year-on-year comparisons for that period, providing deeper insights without navigating through multiple screens.
Additionally, we’re introducing a new comparison tool where you can highlight or pin specific years, such as 2021, 2022, or 2023, for direct side-by-side analysis. This will make it easier for you to identify seasonal trends or significant performance shifts between years, helping you focus on the data that matters most to you. These updates are designed to make your workflow smoother and more efficient, empowering you to make well-informed decisions based on historical data trends.
To access: Search for any symbol say TSLA, from the top menu, select Analysis > Seasonality
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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