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 ⇕|
|HD||The Home Depot, Inc||$320.09||$181.84||1.66|
|JPM||JPMorgan Chase & Co||$151.39||$103.04||1.49|
|KO||The Coca-Cola Company||$53.11||$39.21||1.34|
|BAC||Bank of America Corporation||$39.96||$27.92||1.18|
|UNH||UnitedHealth Group Incorporated||$376.85||$375.14||0.99|
|VZ||Verizon Communications Inc||$57.69||$65.21||0.89|
|GM||General Motors Company||$58.61||$64.21||0.87|
|COST||Costco Wholesale Corporation||$363.17||$472.90||0.74|
|CVS||CVS Health Corporation||$75.10||$163.02||0.46|
|F||Ford Motor Company||$12.26||$28.44||0.43|
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 9 dimensions, including earnings, revenue, operating income, cash, 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.
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