I have 1 year time series data of 300 constituents of the Australian All Ordinaries index (which is composed of 491 firms). The missing firms are mostly smaller firms.
I run the market model $R_{it} = a_i + b_i R_{mt} + e_t$ for $i \in \{1,...,300\}$. Then I take $\textrm{mean}(\hat{b}_i)$ and it's equal to $0.60$.
Is it a problem that it isn't approximately $1.0$? $0.6$ seems a bit low. Is a potential explanation that the AORD is market capitalization weighted, but I'm taking the unweighted mean of $\hat{b}_i$.
Concern is heightened when reading "Stock market crashes, firm characteristics, and stock returns" which took a similar mean over NASDAQ and got 1.20 average market model slope estimate (however they use CRSP).
All data is from Datastream.