(a)

the institution documents, as part of its internal policies, any methodology used to fill in time series with missing data points, and whether such documentation contains sound analysis showing that those methodologies do not affect the risk factors’ volatilities and correlations;

(b)

the institution has established objective criteria setting out which methodology to fill in time series is used, where more than one methodology is available, and has documented those criteria in its internal policies;

(c)

the institution has established, as part of its internal policies, the process to be followed whenever the values in a time series are changed, and whether such process includes the documentation of the performed changes;

(d)

the institution does not perform filtering of data, including flooring, capping and exclusions of outliers, unless the institution is able to demonstrate that the excluded data point relates to erroneous or stale data, and the institution documents such an exclusion;

(e)

the institution performs periodic quality checks on the time series used for the computation of the expected shortfall risk measure, and documents those checks and the corresponding results are documented;

(f)

the institution analyses, as part of the checks referred to in point (e), the effect that missing or replaced data and the methodology used to obtain the time series have on the risk factors’ volatilities and correlations;

(g)

the data quality of the time series used by the institution is appropriate.

(a)

the number of days for which data points were initially missing and were then filled in using a particular methodology;

(b)

the number of days for which data points were initially available and have been replaced using a particular methodology;

(c)

the number of days with no daily changes;

(d)

the maximum number of consecutive days with no daily change.

(a)

(b)

based on the overview referred to in point (a), identify those times series used for risk factors that may be affected by low data quality;

(c)

based on the overview referred to in point (a), select a sample of time series that are characterised by a high number of data points initially missing, and apply the following steps in the following order:

(d)

based on the overview referred to in point (b), select a sample of time series characterised by a high number of data points that were initially available but have been substituted by other data points, and apply the following steps in the following order:

(a)

time series with less than 10 % of initially available data points;

(b)

time series with 20 consecutive business days without any daily change;

(c)

time series with more than 20 % of days with no changes;

(d)

time series for which more than 50 % of the initially available data have been changed.