What's New
Product updates, improvements and fixes across the KlickAnalytics platform.
142 updates · clear
Explore seasonality patterns
Access seasonality patterns like average returns for daily, weekly, monthly and yearly along with key stats like standard deviations, variance and more.
Access now at https://klickanalytics.com/symbol_seasonality_patterns?s=TSLA
Quickly access intraday market movers and companies information side by side
We've added a new app, which will allow our users to quickly view intraday market movers and companies information side by side.
To access, take a look at klickanalytics.com/now
You can even filter movers by sectors, price and volume range too. Now you can quickly access markets movers and also see the companies key information side-by-side with single click!
Historical Discount Cash Flows
Discounted cash flow (DCF) is a valuation method used to estimate the value of an investment based on its expected future cash flows. DCF analysis attempts to figure out the value of an investment today, based on projections of how much money it will generate in the future. This applies to the decisions of investors in companies or securities, such as acquiring a company or buying a stock, and for business owners and managers looking to make capital budgeting or operating expenditures decisions.
We've added a new app called 'DCF' which will allow our users to view;
DCF for any listed company
View Daily, Quarterly and Annual DCF values
View Historical DCF values displayed on a chart to see historical trends and more.

To view: Search for a symbol like AAPL, and then from to dropdown click Fundamentals > DCF
Compare open price to vs previous day
We've added a new view to all our data tables called 'Open to Previous Day' which will provide the following columns:
Open price to previous high price (%)
Open price to previous low price (%)
Open price to previous close price (%)

This update is available on all data tables.
This will allow you to view if the stocks are opening higher or lower than the previous day and more.
To access: Click on Menu > Movers > Click on drop down 'Main' and then select 'Open to Previous Day'
Compare close price to previous day
We've added a new view to all our data tables called 'Close to Previous Day' which will provide the following columns:
Close price to previous open price (%)
Close price to previous high price (%)
Close price to previous low price (%)

This update is available on all data tables.
This will allow you to view if the stocks are opening higher or lower than the previous day and more.
To access: Click on Menu > Movers > Click on drop down 'Main' and then select 'Close to Previous Day'
Movers > View stocks opening higher or lower
Our users can view stocks in our movers app that are opening i.e.;
Higher than their previous day close price
Lower than their previous day close price

To access: Click on Menu > Movers > and select Open > Previous Close or Open < Previous Close
View pivot points for global symbols
We've added a new view called 'Pivot Points' which is available for all data tables. The view will give the following information;
Pivot Points
Support level 1 (S1)
Support level 2 (S2)
Support level 3 (S3)
Resistance level 1 (R1)
Resistance level 2 (R2)
Resistance level 3 (R3)

With the above, you can see price trends and related pivots support and resistance levels and more.
To access: From any of the data tables, click on views drop down called 'Main' and then select 'Pivot Points'
Movers > Added Top ETFs Stocks
We've added a new filter to view all Top performing ETFs in our movers app.

To access: Click on Menu > Movers > Top Performing ETFs
Movers > View breakout stocks
We've added a new filter in out movers app, that will allow you to look at stocks that are in the breakout formation. We will have two ways to look at breakout stocks;
Breakout - positive
Where stocks price moving above its 20-Days simple moving averages
Breakout - negative
Where stocks price moving below its 20-Days simple moving averages

In addition, we also display a column with values for % Change from Close price to 20-Day simple moving averages.
To access: Click on Menu > Movers, and then select from the drop down for either 'Breakout - positive or Breakout - Negative option'
View Dividend reports for Units and Close End Funds
We've added the following two new reports in our 'Dividend Reports' app;
Dividend Report - Units
Dividend Report - Close End Funds

This report will display all the dividend related information as per companies selected as either REIT, Units or Close End Funds.
To access: Click on Menu > Dividends > Dividends Reports
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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