The "Fundamental Fitted Estimate Ratio" (FFER) is the ratio between the actual market price and the "Fundamental Fitted Estimate" (FFE) price. The FFE is the estimate generated by the machine learning model and is conceptually represented by the green line in the diagram above.
|Ticker ⇕||Name ⇕||Price ⇕||FFE Price ⇕||FFER ⇕|
|PYPLPayPal Holdings||PayPal Holdings||$247.25||$58.59||4.220|
|CHTRCharter Communications||Charter Communications||$633.27||$175.80||3.602|
|AMTAmerican Tower Corporation (REIT)||American Tower Corporation (REIT)||$216.88||$105.53||2.055|
|DISThe Walt Disney Company||The Walt Disney Company||$172.26||$95.89||1.796|
|SPGIS&P Global||S&P Global||$313.14||$175.91||1.780|
|JNJJohnson & Johnson||Johnson & Johnson||$162.78||$91.69||1.775|
|UNHUnitedHealth Group||UnitedHealth Group||$352.19||$201.87||1.745|
|LLYEli Lilly and Company||Eli Lilly and Company||$198.48||$116.18||1.708|
|NEENextEra Energy||NextEra Energy||$82.81||$55.71||1.486|
|LOWLowe's Companies||Lowe's Companies||$170.76||$115.44||1.479|
|PGThe Procter & Gamble Company||The Procter & Gamble Company||$133.60||$101.24||1.320|
|MSMorgan Stanley||Morgan Stanley||$74.99||$60.35||1.243|
|ABTAbbott Laboratories||Abbott Laboratories||$112.57||$92.37||1.219|
|KOThe Coca-Cola Company||The Coca-Cola Company||$48.51||$41.08||1.181|
|TMOThermo Fisher Scientific||Thermo Fisher Scientific||$507.38||$442.18||1.147|
|BAThe Boeing Company||The Boeing Company||$210.71||$187.80||1.122|
|FISFidelity National Information Services||Fidelity National Information Services||$128.06||$115.51||1.109|
|XOMExxon Mobil||Exxon Mobil||$48.84||$45.87||1.065|
|COSTCostco Wholesale||Costco Wholesale||$354.47||$335.73||1.056|
|MRKMerck & Co.||Merck & Co.||$83.19||$79.62||1.045|
|UPSUnited Parcel Service||United Parcel Service||$156.28||$152.77||1.023|
|UNPUnion Pacific||Union Pacific||$215.28||$210.85||1.021|
|HONHoneywell International||Honeywell International||$206.76||$213.16||0.970|
|LMTLockheed Martin||Lockheed Martin||$341.50||$424.40||0.805|
|VZVerizon Communications||Verizon Communications||$57.05||$73.06||0.781|
|CSCOCisco Systems||Cisco Systems||$45.19||$57.95||0.780|
|MMM3M Company||3M Company||$169.12||$217.31||0.778|
|TXNTexas Instruments||Texas Instruments||$174.19||$267.54||0.651|
|BACBank of America||Bank of America||$32.77||$50.71||0.646|
|BMYBristol-Myers Squibb Company||Bristol-Myers Squibb Company||$66.74||$113.44||0.588|
|IBMInternational Business Machines||International Business Machines||$129.02||$270.80||0.476|
|CVSCVS Health||CVS Health||$75.40||$162.94||0.463|
|GILDGilead Sciences||Gilead Sciences||$67.07||$248.26||0.270|
You can use the FFER as a valuation metric similar to the Price/Earnings, Price/Book, or EV/EBITDA ratios. The difference is that the FFER is comprehensive. Each FFER is calculated using 16 dimensions, including income, revenue, assets, liabilities, and dividends.
Like other valuation metrics, the FFER tells us the intrinsic value of the stock and whether it is cheap or expensive. If the actual price is lower than the fundamental price, it implies that it is cheap relative to the market. Likewise, if the actual price is higher than the fundamental price, it implies that it is expensive relative to the market.
The FFER is the ratio between the actual price and the fundamental price. The fundamental price is the output of a machine learning model trained with 16 fundamental dimensions as independent (X) variables and the actual price as the dependent (Y) variable. For those unfamiliar with machine learning, you can think of it as "curve fitting." So for FFER, we are "fitting" an equation to predict any stock price given the fundamentals of a public company.
Since real-world data tends to be messy, even the best machine learning models are subject to error. Few points actually fall on the curve. For most machine learning applications, this error is treated as regrettable. For the FFER, retrieving the magnitude of the error is the goal.
The "fitted curve" represents the best-guess valuation function of the market. If the actual price is significantly above or below the curve, either the stock is incorrectly valued, or there is some other significant information impacting the price.
A more detailed technical explanation is available here.
Not exactly. Because the FFER is derived from only basic financial statements, it is missing a lot of information. It does not capture consumer sentiment, economic conditions, price momentum, etc. Indeed, stocks with high or low FFERs tend to have justifications for their ratios. This might be an exciting product, a bankruptcy proceeding, or some recent economic trend. Additionally, because the model is trained daily with EOD prices, it only signals the stock's value relative to the market on a single day. It cannot predict broader market movements.
Given that the FFER is just a better valuation metric, you can substitute it wherever you would use the P/E or any other metric. If you are a value investor, you can utilize the FFER as a stock screener to find cheap stocks worthy of closer investigation. If you do algorithmic trading, you can use the FFER as an input to your model.
Yes. Being derived from the same data, the FFER is correlated with other valuation metrics.
The FFER model is re-built and prices are updated on trading days one hour after US markets close (5:30PM Eastern Time). The 100 largest stocks by market cap will remain free on this page indefinitely.
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