pq_performance calculates performance metrics based on returns of market price or portfolio. The performance analysis functions are calling from PerformanceAnalytics package, which includes many widely used performance metrics.
pq_performance(dt, Ra, Rb = NULL, perf_fun, ...)a list/dataframe of time series datasets.
the column name of asset returns.
the column name of baseline returns, defaults to NULL.
performance function from PerformanceAnalytics package, see pq_perf_funs.
additional parameters, the arguments used in PerformanceAnalytics functions.
library(pedquant)
library(data.table)
# load data
data(dt_banks)
data(dt_ssec)
# calculate returns
datret1 = pq_return(dt_banks, 'close', freq = 'monthly', rcol_name = 'Ra')
datret2 = pq_return(dt_ssec, 'close', freq = 'monthly', rcol_name = 'Rb')
# merge returns of assets and baseline
datRaRb = merge(
rbindlist(datret1)[, .(date, symbol, Ra)],
rbindlist(datret2)[, .(date, Rb)],
by = 'date', all.x = TRUE
)
# claculate table.CAPM metrics
perf_capm = pq_performance(datRaRb, Ra = 'Ra', Rb = 'Rb', perf_fun = 'table.CAPM')
rbindlist(perf_capm, idcol = 'symbol')
#> symbol Alpha Beta Beta+ Beta- R-squared Annualized Alpha
#> 1: 601288.SH -0.0029 0.0724 0.0968 0.0964 0.0113 -0.0347
#> 2: 601328.SH -0.0001 0.1147 -0.0257 0.3716 0.0155 -0.0012
#> 3: 601398.SH -0.0047 0.2386 0.2711 0.4381 0.0802 -0.0545
#> 4: 601939.SH -0.0023 0.2817 0.1165 0.3164 0.0575 -0.0269
#> 5: 601988.SH -0.0009 0.0969 0.1387 -0.0737 0.0219 -0.0105
#> Correlation Correlation p-value Tracking Error Active Premium
#> 1: 0.1062 0.5436 0.1771 -0.0832
#> 2: 0.1245 0.4762 0.1963 -0.0520
#> 3: 0.2832 0.0993 0.1712 -0.0967
#> 4: 0.2398 0.1652 0.2078 -0.0741
#> 5: 0.1480 0.3962 0.1714 -0.0573
#> Information Ratio Treynor Ratio
#> 1: -0.4698 -0.4961
#> 2: -0.2647 -0.0406
#> 3: -0.5648 -0.2070
#> 4: -0.3566 -0.0952
#> 5: -0.3341 -0.1026