每月收费的再平衡策略

Question

I have a question regarding PerformanceAnalytics and Quantstrat packages. I want to test a monthly rebalancing portfolio strategy, but I want to incorporate the effect of annual fees and buy&sell fees for rebalancing.

Is there any practical way of doing this? In PerformanceAnalytics, I can easily test the monthly rebalancing strategy, but fees are problematic. In Quantstrat, I can easily incorporate fees, but is there a way to construct a monthly rebalance structure?

Thank you very much,

Kind regards.

Answer 1

In case an alternative package is also acceptable: here is how it could be done with the PMwR package.

Start with example data: 30 industry series from Kenneth French's website.

library("NMOF")
library("PMwR")
library("datetimeutils")
library("zoo")
P <- French(tempdir(),
            "30_Industry_Portfolios_daily_CSV.zip",
            price.series = TRUE, na.rm = TRUE)
P <- zoo(P, as.Date(row.names(P)))
P <- window(P, start = as.Date("2000-1-1"))

Now we compute the dates at which transactions take place.

eoy <- nth_day(index(P), period = "year", n = "last")
## [1] "2000-12-29" "2001-12-31" "2002-12-31" "2003-12-31"
## [5] "2004-12-31" "2005-12-30" "2006-12-29" "2007-12-31"
## [9] "2008-12-31" "2009-12-31" "2010-12-31" "2011-12-30"
## ....

eom <- nth_day(index(P), period = "month", n = "last")
## [1] "2000-01-31" "2000-02-29" "2000-03-31" "2000-04-28"
## [5] "2000-05-31" "2000-06-30" "2000-07-31" "2000-08-31"
## [9] "2000-09-29" "2000-10-31" "2000-11-30" "2000-12-29"
## ....

For the backtest, I'll use function btest in the PMwR package. It takes as input a function signal which evaluates to the target portfolio. Suppose we wanted an equal-weights portfolio; then signal could look as follows:

signal <- function() {
    k <- ncol(Close())
    rep(1/k, k)
}

btest also accepts an argument cashflow that can be used to add/subtract arbitrary amounts to the cash balance. The following function deducts 10% of the total wealth at every end of year (it's just an example).

cf <- function() {
    if (Timestamp(0) %in% eoy)
        -Wealth()*0.1
    else
        0
}

This would take care of the annual fee. The easiest way to include trading fees proportional to the amount traded is via the separate argument tc . It remains to run the backtest:

bt <- btest(list(coredata(P)),
            timestamp = index(P),
            signal = signal,
            do.signal = eom,
            cashflow = cf,
            tc = 0.0025,  ## 0.25% transaction fees 
            convert.weights = TRUE,
            initial.cash = 100)
summary(bt)
plot(bt)

## ---------------------------------------------------------
## 03 Jan 2000 ==> 30 Oct 2020   (5242 data points, 0 NAs)
##         100         55.2453
## ---------------------------------------------------------
## High                 110.97  (28 Dec 2000)
## Low                   35.32  (09 Mar 2009)
## ---------------------------------------------------------
## Return (%)             -2.8  (annualised)
## ---------------------------------------------------------
## Max. drawdown (%)      68.2
## _ peak               110.97  (28 Dec 2000)
## _ trough              35.32  (09 Mar 2009)
## _ recovery                   (NA)
## _ underwater now (%)   50.2
## ---------------------------------------------------------
## Volatility (%)         19.1  (annualised)
## _ upside               12.1
## _ downside             14.7
## ---------------------------------------------------------
## 
## Monthly returns  ▁▁▃▇█▂▁ 
## 
##        Jan   Feb   Mar  Apr  May  Jun   Jul  Aug   Sep   Oct  Nov   Dec   YTD
## 2000   0.0  -3.6   8.0 -0.2 -0.8  0.0   0.3  6.0  -2.3   1.4 -3.8  -4.7  -0.7
## 2001   2.8  -3.5  -4.8  7.5  1.8 -3.1  -1.3 -3.0 -11.1   3.6  6.6  -7.1 -12.5

(Disclosure: I am the maintainer of packages PMwR , NMOF and datetimeutils .)