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NTU Management Review Vol. 35 No. 2 Oct. 2025

6.3 Frequency of Forecast Revision
In this subsection, we examine whether the 2005 change in accounting standards also
leads to changes in forecast frequency. Analysts revise their forecasts (increasing forecast
frequency) upon receiving new information that is sufficiently important to prompt

a revision to an existing forecast through the pursuit of additional information about
future earnings. In line with Holden and Stuerke (2008), we estimate the determinants of
analysts’ forecast frequency, presenting the results in Table 6. FREQ is the average number
of revisions made by an individual analyst, measured as the total number of revisions made

to existing forecasts between earnings announcements scaled by the number of analysts
following. AVG_VOL is the average daily trading volume over the year prior to the date
of the annual earnings announcement. ABS_PRICECHANGE is the average daily price
change over the year prior to the date of the annual earnings announcement, measured as

the average of the absolute difference between daily high and low stock prices scaled by
the closing price. SKEW is the skewness of daily trading volume over the year prior to the
date of the annual earnings announcement. All other variables are as previously defined.
We find that the frequency of forecast revisions decreases in the post-IFRS period,

as reflected in the negative coefficient on UK×POST in Column (1) and the negative
coefficients on all interaction terms between UK and the time-period indicators in Column
(2). The frequency of forecast revisions is lower among UK firms reporting under the
full fair value model (IFRS) than it is among UK firms reporting under the partial fair

value model (domestic standards). The results are consistent with the view that improved
consistency between income statements and balance sheets under the full fair value model
can help analysts to more effectively assess future outcomes.

6.4 Assessing Parallel Trend Assumptions
One potential concern with our main argument is that the results are driven by
coincidental changes in market conditions that are unrelated to IFRS. To address
this concern, we conduct an analysis aimed specifically at validating parallel trend
assumptions. This analysis includes PRE, an indicator variable that equals one if the

observation comes from two or more years prior to IFRS adoption and zero otherwise. A
significant UK×PRE coefficient raises concerns that parallel trend assumptions may not
hold. Table 7 presents the results of the analysis. In Column (1), UK×PRE is insignificant,

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