I backtested share buybacks from 2006 to 2026.

I’ve been digging into share buybacks recently, and I wanted to test something simple: >Do companies that buy back shares actually perform better, or are buybacks mostly financial tricks? More specifically: **Which type of buyback works best?** Because “the company is buying back stock” is not enough. A buyback can be great, neutral, or actively stupid depending on the context. A good buyback should probably do a few things: 1. Actually reduce the share count. 2. Be funded by real cash flow, not desperation leverage. 3. Happen at a reasonable valuation. 4. Not exist purely to offset stock-based compensation. 5. Not just make EPS look better while shareholders own the same percentage of the business. So I ran a step-by-step backtest to see whether historical data supports that idea. >This is not an academic paper, and I’m not claiming causality. It is more of a practical signal test: can buyback-related variables rank stocks by future returns? # Setup I used Portfolio123 with FactSet data. * Universe: **Easy To Trade USA**, basically US stocks with some liquidity and quality-of-data filters. * Period: **2006 to 2026** * Method: Every 4 weeks, rank the universe into 10 equal-weight deciles based on different buyback-related factors. Then compare future performance by decile. Returns include dividends, use point-in-time data, include delisted stocks, and are before taxes, transaction costs, and slippage. Important: this is signal research, not a production-ready strategy! # Test 1: Net buyback yield First, I tested the obvious metric: > The idea is simple. If a company is buying back a lot of stock relative to its size, maybe that contains useful information. Result: |Factor|Top 20% CAGR|Bottom 20% CAGR|Spread|Best decile| |:-|:-|:-|:-|:-| |Net buyback yield|10.35%|1.51%|\+8.84 pp|Decile 9| So yes, there is signal. The high buyback-yield companies did much better than the low buyback-yield companies. But the result was messy. The best decile was not decile 10, it was decile 9. The middle deciles were also not especially clean. That suggests that simply buying the companies with the most aggressive buybacks is not enough. And that makes sense. A company can spend a lot on buybacks but still fail to reduce the diluted share count because of stock-based compensation, acquisitions paid with shares, options, RSUs, convertibles, or other forms of dilution. So net buyback yield is useful, but noisy. >**Finding 1:** Buyback yield contains signal, but “buying back a lot” is not the same as “buying back well.” # Test 2: Add real diluted share count reduction Next, I added a measure of whether the buyback actually reduced the fully diluted share count over three years. The logic: If a company buys back stock but diluted shares do not go down, the buyback may be more narrative than economics. Metric: > Why diluted shares? Because diluted shares better capture options, RSUs, convertibles, and other instruments that can dilute shareholders. Result: |Ranking|Top 20% CAGR|Bottom 20% CAGR|Spread|Best decile| |:-|:-|:-|:-|:-| |Net buyback yield|10.35%|1.51%|\+8.84 pp|9| |Buyback yield + diluted share reduction|10.93%|0.54%|\+10.40 pp|10| This improved the signal. The top decile became the best decile, and the spread between the best and worst groups widened. This is probably the most intuitive result of the whole test: **Buybacks work better as a signal when they actually reduce the number of diluted shares.** That sounds obvious, but a lot of companies announce buybacks that do not meaningfully change shareholder ownership. >**Finding 2:** The market seems to reward “real” buybacks more than cosmetic buybacks. A real buyback is not just cash spent. It is a buyback that leaves remaining shareholders owning a larger percentage of the business. # Test 3: Add free cash flow yield Then I added free cash flow yield. Why? Because FCF yield helps with two things at once: 1. It tells us whether the company generates enough cash to plausibly fund buybacks. 2. It adds a valuation component. Buying back stock with abundant FCF is not the same as buying back stock with weak FCF. Buying back stock at a low valuation is not the same as buying back stock at a crazy valuation. Result: |Ranking|Top 20% CAGR|Bottom 20% CAGR|Spread|Best decile| |:-|:-|:-|:-|:-| |Net buyback yield|10.35%|1.51%|\+8.84 pp|9| |Buyback yield + diluted share reduction|10.93%|0.54%|\+10.40 pp|10| |Buyback yield + diluted share reduction + FCF yield|11.66%|\-1.47%|\+13.13 pp|10| This was the biggest improvement. The top 20% improved, but the bottom 20% got much worse. That is useful because a good factor should not only help identify winners, it should also help avoid disasters. The interpretation: A buyback is more attractive when it is backed by actual cash generation and reasonable valuation. >**Finding 3:** The best buyback signal was not “high buyback yield.” It was high buyback yield plus real share reduction plus FCF yield. Look for companies that are buying back shares, actually reducing diluted share count, and generating enough cash to justify it. # Test 4: Add debt control Finally, I added a balance sheet guardrail: > If a company is already highly levered, spending cash on buybacks may be a bad capital allocation decision. Buybacks are great when the company has excess capital. They are less great when management is borrowing heavily just to shrink the share count or support EPS. Result: |Ranking|Top 20% CAGR|Bottom 20% CAGR|Spread|Best decile| |:-|:-|:-|:-|:-| |Net buyback yield|10.35%|1.51%|\+8.84 pp|9| |Buyback yield + diluted share reduction|10.93%|0.54%|\+10.40 pp|10| |Buyback yield + diluted share reduction + FCF yield|11.66%|\-1.47%|\+13.13 pp|10| |Buyback yield + diluted share reduction + FCF yield + debt|11.59%|\-1.80%|\+13.39 pp|10| This was interesting. Adding debt control did not improve the top deciles much. In fact, the top 20% CAGR was slightly lower than the previous version. But it did improve the separation at the bottom. So debt was not really a return engine. It was more of a mistake filter. >**Finding 4:** Debt control helps identify bad buybacks more than it helps identify great buybacks. This makes sense. A strong company with high FCF and real buybacks can still have some debt. But companies buying back stock while financially stretched are often playing a more dangerous game. # Main takeaway The simple version: **Don’t look for companies that buy back a lot. Look for companies that buy back well.** The full version: Buybacks become more interesting when: 1. The company has positive net buyback activity. 2. Diluted shares are actually going down. 3. The company generates strong free cash flow. 4. The stock is not obviously expensive, proxied here by FCF yield. 5. The balance sheet is not being abused to fund buybacks. # What each variable corrected |Added signal|What it fixes|Result| |:-|:-|:-| |Net buyback yield|Measures buyback flow|Has signal, but noisy| |Diluted share reduction|Filters cosmetic buybacks|Improves ranking quality| |FCF yield|Adds cash generation and valuation|Stronger separation between good and bad deciles| |Net debt / FCF|Avoids stretched balance sheets|Helps identify the bottom| # Important! This is not a complete investment strategy. The best deciles beat SPY, but not by enough to declare victory and call it done. There are still many things to test: * transaction costs * slippage * taxes * turnover * volatility * drawdowns * sector exposure * and waaaay more So the conclusion is not “here is a strategy, go buy decile 10.” but something more like "**buybacks contain useful information, but only when interpreted properly."** ps: for more details and visuals (no images allowed here) you can go to the original blog post at [https://www.jeravalue.com/en/blog/buybacks-performance](https://www.jeravalue.com/en/blog/buybacks-performance)