My RcppBDT package has a function for this.
RcppBDT wraps parts of the Boost Date_Time library, and Boost Date_Time happens to have a number of functions like that.  So here is a quick loop for years 2008 to 2011, getting each year's fourth Wednesday in November:
R> library(RcppBDT)
Loading required package: Rcpp
Creating a generic function for ‘print’ from package ‘base’ in package ‘RcppBDT’
Creating a generic function for ‘format’ from package ‘base’ in package ‘RcppBDT’
R> for (y in 2008:2011) print(getNthDayOfWeek(fourth, Wed, Nov, y))
[1] "2008-11-26"
[1] "2009-11-25"
[1] "2010-11-24"
[1] "2011-11-23"
R> 
Here fourth, Wed and Nov are constants in the package namespace, modeled after corresponding enum types in the underlying C++ library. Makes for pretty easy use.
Edit: Here is a complete example for all 4th-Wed-in-Nov since 2000. I ensure that both the GSPC and the vector Wed of Wednesdays agree on the same Date type.  Then it is just a matter of sticking Wed into GSPC:
R> library(quantmod)
Loading required package: Defaults
Loading required package: TTR
R> getSymbols("^GSPC", from="1900-01-01")  
R> Wed <- sapply(2000:2011, function(y) getNthDayOfWeek(fourth, Wed, Nov, y))
R> index(GSPC) <- as.Date(index(GSPC))
R> GSPC[as.Date(Wed)]
           GSPC.Open GSPC.High GSPC.Low GSPC.Close GSPC.Volume GSPC.Adjusted
2000-11-22   1347.35   1347.35  1321.89    1322.36   963200000       1322.36
2001-11-28   1149.50   1149.50  1128.29    1128.52  1423700000       1128.52
2002-11-27    913.31    940.41   913.31     938.87  1350300000        938.87
2003-11-26   1053.89   1058.45  1048.28    1058.45  1097700000       1058.45
2004-11-24   1176.94   1182.46  1176.94    1181.76  1149600000       1181.76
2005-11-23   1261.23   1270.64  1259.51    1265.61  1985400000       1265.61
2006-11-22   1402.69   1407.89  1402.26    1406.09  2237710000       1406.09
2007-11-28   1432.95   1471.62  1432.95    1469.02  4508020000       1469.02
2008-11-26    852.90    887.68   841.37     887.68  5793260000        887.68
2009-11-25   1106.49   1111.18  1104.75    1110.63  3036350000       1110.63
2010-11-24   1183.70   1198.62  1183.70    1198.35  3384250000       1198.35
2011-11-23   1187.48   1187.48  1161.79    1161.79  3798940000       1161.79
R> 
Edit 2  As a Public Servive Announcement, here is where Jeff's answer fails:
R> ind <- .indexmon(GSPC)==10 & .indexmday(GSPC) > 22 & .indexmday(GSPC) < 29 
+         & .indexwday(GSPC) == 3
R> index(GSPC)[ind]
 [1] "1951-11-28" "1952-11-26" "1953-11-25" "1954-11-24" "1955-11-23"
 [6] "1956-11-28" "1957-11-27" "1958-11-26" "1959-11-25" "1960-11-23"
[11] "1962-11-28" "1963-11-27" "1964-11-25" "1965-11-24" "1966-11-23"
[16] "1968-11-27" "1969-11-26" "1970-11-25" "1971-11-24" "1973-11-28"
[21] "1974-11-27" "1975-11-26" "1976-11-24" "1977-11-23" "1979-11-28"
[26] "1980-11-26" "1981-11-25" "1982-11-24" "1983-11-23" "1984-11-28"
[31] "1985-11-27" "1986-11-26" "1987-11-25" "1988-11-23" "1990-11-28"
[36] "1991-11-27" "1992-11-25" "1993-11-24" "1994-11-23" "1996-11-27"
[41] "1997-11-26" "1998-11-25" "1999-11-24" "2001-11-28" "2002-11-27"
[46] "2003-11-26" "2004-11-24" "2005-11-23" "2007-11-28" "2008-11-26"
[51] "2009-11-25" "2010-11-24" "2011-11-23"
and
R> S <- 1951:2011
R> S[!S %in% as.numeric(format(index(GSPC)[ind], "%Y")) ]
[1] 1961 1967 1972 1978 1989 1995 2000 2006
R> 
So there are eight years missing in the sample of sixty when you use his approach.