Does DCF modeling work? I did a backtest and the result is a clear yes!
u/Wooden_Fondant_703 ·
Reddit — r/ValueInvesting
· May 03, 2026 at 18:18
· ⬆ 17 pts
· 💬 5 comments
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Summary
The author backtested a DCF model using perfect hindsight of actual future earnings for ~100 large-cap U.S. stocks across multiple 5-year periods (2013–2016 start years). Results showed a strong negative correlation between market price premium (vs. DCF fair value) and subsequent 5-year returns.
The thesis is that DCF itself is a valid framework; the challenge is forecasting future earnings accurately. The real edge lies in being "less wrong" about earnings than the market, rather than abandoning the model.
Quality assessment: Well-researched backtest with clear methodology, statistical significance (p < 0.00001), and concrete examples (GE overvalued, Broadcom undervalued). Recognizes limitations (e.g., Netflix as outlier). This is solid quantitative DD.
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Everyone dunks on DCF. "Garbage in garbage out." "You can make it say anything."
But I kept wondering — is the model iintrinsically not practical in use or is it a solid framework to express the prediction power on the business? So I ran a simple experiment to test it.
Take \~100 large-cap US stocks in mid-2014. Build a basic DCF for each one. But instead of guessing future earnings, plug in the actual NOPAT they reported over the next 5 years. Perfect hindsight. Then compare what the model says each stock should have been worth vs what the market was actually charging.
I called that gap the "premium." Then checked: did stocks the market overpriced (vs perfect-information DCF) actually underperform over the next 5 years?
Yeah. Pretty cleanly.
Undervalued tercile: **+9.2%/yr** vs the S&P 500 Fair-valued tercile: **+5.1%/yr** Overvalued tercile: **-0.3%/yr**
Spearman correlation of -0.45 (p < 0.00001). Not a fluke. Ran it for 4 different starting years (2013-2016), same pattern every time.
The two cases that stuck with me:
GE in 2014. Market paying 14.2x operating earnings. Looks modest, right? But with actual future earnings plugged in, the "fair" multiple was only 5.3x. The market was paying a 165% premium over what GE's real future justified. We all know what happened next — the stock got cut in half while the S&P gained 50%.
Broadcom same year. Market paying 18.3x. DCF with perfect hindsight says fair value was 66.6x. The market was charging a 72% discount. NOPAT went from $590M to $4.4B in 5 years. Stock delivered +31.6%/yr vs the index.
The model wasn't wrong. The market just had no idea what earnings were going to do.
tbh this doesn't tell you how to actually use DCF better — you still don't have a crystal ball. But it does settle one thing imo: the framework isn't broken. The problem is always the inputs. Which means the real edge isn't finding a different model, it's being less wrong about future earnings than everyone else. Even slightly.
(NFLX was the fun exception — DCF said it was overpriced even with perfect 5-year hindsight, yet it crushed. Because the market was pricing a 10-year story, not a 5-year one. Outliers exist.)
Wrote up the full analysis with charts and the multi-cohort data in the lined post if you want to dig into more details.
Two biggest takeaway from me:
\- DCF is as good as your understanding of the company, reflected in your prediction on it's future cash flow
\- Don't ever buy over priced stocks regardless of how good they good now. Being expensive make your strongly against the odds!