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I am working on a research project that requires me to run a CAPM regression on all intra-day stock quotes in NSDAQ, NYSE and all other U.S. exchanges since 1993.

The precision of the quote data is at second-level. We calculated the second by second stock returns, market returns, risk free rate, and ran a CAPM regression on the data. We used SPY return as the market benchmark.

However, an interesting problem that occurred was - there are some stocks with really small beta (very close to 0). That is, the stock barely moves with the market.

While pondering about the reasons behind this, we think it might be caused by different minimum stock movements. Some stocks might be trading at \$1, but a market movement of, say, \$10, will overshoot the price movement of such stocks.

However, we are still not exactly sure about the reasons and how to adjust the data properly.

The follow screenshot is an example of how small the beta can be (estimate is the beta value).

Does anyone have an idea on this?

enter image description here

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    $\begingroup$ Just by looking over your list of symbols, I can tell you that a few of these are short term bond funds and a few others are closed-end funds that don't hold equities. It is not surprising that they have no beta. They shouldn't. When simply using every listed equity, you are going to run into such problems. I don't think adjusting data is your answer; I think adjusting your test universe would be more appropriate, FWIW. $\endgroup$
    – amdopt
    Commented Jun 13, 2017 at 15:29
  • $\begingroup$ I think it'd be best if you would add how you calculated the beta. BACWSA is Bank of America, which shouldn't have a beta close to zero. $\endgroup$
    – Richard
    Commented Jun 14, 2017 at 14:37

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