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Cognitive Quant

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Additional Price Data

Dividend Yield
Earnings Yield

Agilent Technologies Inc

Checklist Summary: 


average rating is 3 out of 5


Company Description

Last Price

Market Cap

Dividend Yield

Earnings Yield




Company Description overflow

-Quality score is based on historical performance across business cycle of the firm's ROA, ROIC, CFOA, and Piotroski Score among other metrics mostly derived from Quantitative Value.

-Exercise judgement on likelihood and continuity of historical performance and be mindful of risks as highlighted by checklist items

-Relative Valuation score based on percentile score of Earnings Yield (EBIT/EV)

-EBIT / EV is largely considered the overall best performing relative valuation metric

-However, be cautious of inflated yield of cyclical firms in course of long business cycle expansion

Note: Relative valuation is not a protection against overpaying; Use it as starting point of analysis

average rating is 3 out of 5


-If firm has positive cashflow from operations

-Is that resulting in positive free cash flow

-If firm's entire CFO is consumed in Capex

-Is firm underinvesting to show positive FCF


-If revenues are growing/declining

-If the firm is profitable on an accrual basis

-Are those profits resulting in cash generation

-Or is the firm pursuing unprofitable growth

-Likely future trend & business cycle impacts


-If firm is increasing its debt and/or liabilities

-Strength of balance sheet & its liquid assets

-If the firm is taking on excessive leverage
(ie debt in relation to equity)


-Financial strength trend (via Piotroski Score)

-Multiple return metrics to give perspective on

  • Asset efficiency (ROA)

  • Shareholder returns (ROE)

  • Capital allocation efficiency (ROIC)


Shows most important items (greys out rest)

Highlights items to be cautious about

Highlights items that are best avoided

   Shows all checklist items


​-Checklists help overcome our brain's inability to (concurrently) hold more than 7 pieces of information

-Cognitive Quant uses NLP & machine learning to provide differentiated quantitative & qualitative insights

-Very few firms will likely pass all checklist items, but checklists will help you more methodically and efficiently assess risks to enable better & timely decisions

Financial Statements

Data in US$ Thousands, except per share data

Cognitive Insights

Summary of risks extracted from SEC filings

Legal proceedings extracted from SEC filings


-As a species we are wired to take shortcuts(ie be lazy) - in investing, this often leads to ignoring hidden risks

-CQ uses Natural Language Processing and AI to extract key nuggets from SEC filings to surface important risks

-We are continually improving our algos to help you more efficiently conduct a thorough due-diligence

Most relevant negative sentiment texts extracted and contextualized by Cognitive Quant algorithms


Select checkbox and then click a word in any sentiment cloud below to see how its narrative has evolved over time

Cognitive Insights
Please use default settings of the models as starting points for analysis and use judgement to adjust the parameters to arrive at valuation
Display Scenarios/Sensitivity Params

Valuation is not an exact science. Given the inherent uncertainties in a business, consider the likely range of intrinsic value taking into account the firm's performance across the business cycle. Multiple valuation models have been provided along with heuristically selected parameters as starting points for conducting analysis.


Data in US$ Thousands, except per share data

News & Filings
News & Filings

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Fundamental Data sourced from Quandl & Sharadar and from SEC Filings. Company profiles & Price data sourced from IEX Cloud. Discount rates informed by Prof. Damodaran's data

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