Bloomberg Query Language (BQL) Function Notes

abs(): Returns the absolute value of a number.
ceil(): Rounds up to the nearest whole number.
exp(): Returns e raised to a specified value.
floor(): Rounds down to the nearest whole number.
ln(): Calculates the natural logarithm of a number.
log(): Computes the base 10 logarithm.
round(): Rounds a number to a specified precision.
sign(): Returns the sign of an integer (-1 for negative, 0 for zero, +1 for positive).
sqrt(): Calculates the square root of a number.
square(): Computes the square of a number.
mod(): Returns the modulus (remainder) of a division between two numbers.
negation(): Returns the negative value.
pow(): Raises a number to the nth power.
normal_dist(): Calculates the normal (cumulative) distribution.
normal_inv(): Calculates the inverse of the normal (cumulative) distribution.

sum(): Computes the sum of all values in a dataset.
count(): Counts all non-null values in a dataset.
avg(): Calculates the average (mean) of values.
wAvg(): Calculates the weighted average of values.
min(): Returns the lowest value in a dataset.
max(): Returns the highest value in a dataset.
median(): Returns the median value in a dataset.
product(): Calculates the product of all values.
corr(): Computes the correlation coefficient between two dataset variables.
rsq(): Calculates the r-squared value of a regression model.
std(): Computes the standard deviation of values in a dataset.
var(): Calculates the variance of values.
skew(): Returns the skewness of a distribution.
kurt(): Calculates the kurtosis of a distribution.
zScore(): Computes the z-score for a data point in relation to its dataset.
winsorize(): Limits outlying data under specific thresholds.
compoundGrowthRate(): Calculates the geometric average growth rate of a value.
cut(): Calculates quantile boundaries in a dataset.
rank(): Ranks values in a dataset either in descending or ascending order.

group(): Groups data for statistical analysis across defined security boundaries.
ungroup(): Projects grouped data back onto the original security count.
groupAvg(): Returns the average across group categories.
groupCount(): Counts non-null entries across groups.
groupMax(): Returns the maximum value across groups.
groupMedian(): Returns the median value across groups.
groupMin(): Provides the minimum value of group entries.
groupRank(): Ranks values dynamically within groups.
groupStd(): Computes standard deviation across groupings.
groupSum(): Sums values for specified groups.
groupWAvg(): Computes weighted average for groups.
groupZscore(): Calculates z-scores in the grouped context.
groupcut(): Segments data into quantiles within groups.
groupwinsorize(): Winsorizes data to mitigate the impact of outliers by groups.

cumAvg(): Computes cumulative average of values over time.
cumMax(): Tracks the cumulative maximum across a series.
cumMin(): Maintains a record of cumulative minimum values within a timeframe.
cumProd(): Calculates cumulative product of a series of values.
cumSum(): Accounts for cumulative sum across values over time.
diff(): Computes the difference between current and previous values in a series.
net_chg(): Determines the net change in values over time.
pct_chg(): Computes percentage change between current and previous instances.
pct_diff(): Measures percentage difference between two distinct values.
rolling(): Evaluates expressions on a rolling date range basis.