MBAlib百科对动量策略和反转策略作了很好的解释：
动量/反向策略是指买入赢家/输家组合，同时卖空输家/赢家组合的交易策略。其主要步骤为：
①确定目标证券市场作为交易对象的范围。
②选定一个时间长度作为证券业绩评价期，通常称为投资组合的形成期或排名期。
④根据形成期各样本证券的收益率的大小，对目标市场所有样本证券进行升序、降序排列，然后等分成若干组，其中收益率最大的一组称为赢家组合，收益率最小的一组称为输家组合。
⑤形成期之后或间隔一段时间后，再选一个时间长度，作为卖买赢家组合和输家组合后的持有期限。
⑥连续或间隔一段时期，不断重复 ②一⑤行为。
⑦业绩评价。计算动量/反向策略各持有期的回报率均值及t统计值，如果t统计值表明动量/反转策略的收益率显著大少0，实业界则称动量/反向策略成功，学术界称存在动量/反转现象，反之亦反。
本人尝试着用sas一步一步完成上述操作：股票范围为国内整个A股，形成期用P周来表示，组合持有期用Q周表示，这里将P,Q都简单的取1，2，3。后续的T检验待继续完善。
这里test数据系包含2000多只A股的日线数据。
* test系多只股票的日线数据，选取2009-2012年度日线数据;
data test1;
set test;
year=year(date);
month=month(date);
week=week(date);
keep id date year month week close ;
if 2009<=year<=2012 then output;
run;
*计算两年期间股票的日线数据长度，剔除较短数据;
proc freq data=test1 noprint ;
table id /out=test2(keep=id count) ;
run;
data test3;
merge test1 test2;
by id;
if count<360 then delete ;
if id eq lag(id) then do;
ret_1=log(close)-log(lag(close));
end;
run;
proc sort data=test3;by id;run;
*计算每支股票的周累计收益;
proc sql;
create table test4 as
select *,
sum(ret_1) as sum_ret
from test3
group by id,year,month,week;
quit;
*计算日均收益率，对其进行排序，进而对2000多只股票进行分组;
proc sql;
create table test5 as
select distinct id,year,month,week,sum_ret
from test4;
quit;
*选定一个测试时点,例如以2011年1月第一周开始，找到该时点前p周到数据，
进而按照前P周到累计收益率进行排序，这里p取1，2，3;
data test6;
set test5;
if id eq lag(id) then do;
ret_lag1=lag(sum_ret);
ret_lag2=lag(sum_ret)+lag2(sum_ret);
ret_lag3=ret_lag2+lag3(sum_ret);
end;
run;
*考虑lag函数产生缺失值的问题，我们选取观测时间点位2011年1月第一周;
data test7;
set test6;
if year=2011 & month=1 & week=1 then output;
run;
*对观测时间点进行前P周到累计收益进行排序：升序：轮转策略；降序：动量策略;
%macro rank(num);
%do i=1 %to #
proc rank data=test7 out=test7_&i group=14;
var ret_lag&i;
ranks group;
run;
data test_dong&i test_fan&i;
set test7_&i;
if group=0 then output test_fan&i;
if group=13 then output test_dong&i;
run;
*从待选股票中选出动量组合股票，从观测日开始，计算持有组合内股票Q周的累计收益;
data new;
set test6;
if year<2011 then delete;
run;
*计算动量策略形成期为1周，持有期为1，2，3周到收益，同理可以计算
形成期为2/3周到动量策略;
data merge_d&i;
merge test_dong&i(in=a) new(in=b);
by id;
if a=1 & b=1 then output;
run;
proc expand data=merge_d&i out=d_&i;
convert ret_lag1=ret1 / transform=(lead 2);
convert ret_lag2=ret2 / transform=(lead 3);
convert ret_lag3=ret3 / transform=(lead 4);
run;
data d_&i;
set d_&i;
if year=2011 & month=1 & week=1 then output;
run;
%end;
%mend;
%rank(3);
试图将上面代码得到的组合和沪深300指数进行比对，考察其收益率情况。下面需要计算相应时间段的沪深300指数收益率，进而进行差值比对。沪深300指数数据需要首先下载。
*沪深300指数收益率的计算;
data sz399300_1;
set sz399300;
year=year(var1);
month=month(var1);
week=week(var1);
ret=dif(log(var5));
drop var: ;
run;
proc sql;
create table sz399300_2 as
select distinct year,month,week,
sum(ret) as sum_ret
from sz399300_1
group by year,month,week ;
quit;
data sz399300_3;
set sz399300_2;
ret_lag1=lag(sum_ret);
ret_lag2=lag(sum_ret)+lag2(sum_ret);
ret_lag3=ret_lag2+lag3(sum_ret);
run;
proc expand data=sz399300_3 out=sz399300_4;
convert ret_lag1=ret1 / transform=(lead 2);
convert ret_lag2=ret2 / transform=(lead 3);
convert ret_lag3=ret3 / transform=(lead 4);
run;
data sz399300_4;
set sz399300_4;
if year=2011 & month=1 & week=1 then output;
run;
*沪深300与组合收益率比较;
%macro diff_hs(num);
%do i= 1 %to #
proc sql;
create table d&i_need as
select distinct a.year,a.month,a.week,
mean(a.ret1-b.ret1) as ret1,
mean(a.ret2-b.ret2) as ret2,
mean(a.ret3-b.ret3) as ret3
from d_&i as a
join sz399300_4 as b
on a.year=b.year;
quit;
proc sql;
create table f&i_need as
select distinct a.year,a.month,a.week,
mean(a.ret1-b.ret1) as ret1,
mean(a.ret2-b.ret2) as ret2,
mean(a.ret3-b.ret3) as ret3
from f_&i as a
join sz399300_4 as b
on a.year=b.year;
quit;
%end;
%mend;
%diff_hs(3);
下面系组合形成期和持有期（p,q）都用月来表示的代码：
libname yu "E:\TMP";
* test系多只股票的日线数据，选取2009-2012年度日线数据;
data test1;
set YU.test;
year=year(date);
month=month(date);
keep id date year month close ;
if 2009<=year<=2012 then output;
run;
*计算两年期间股票的日线数据长度，剔除较短数据;
proc freq data=test1 noprint ;
table id /out=test2(keep=id count) ;
run;
data test3;
merge test1 test2;
by id;
if count<360 then delete ;
if id eq lag(id) then do;
ret_1=log(close)-log(lag(close));
end;
run;
proc sort data=test3;by id;run;
*计算每支股票的月累计收益;
proc sql;
create table test4 as
select distinct id,year,month,
sum(ret_1) as sum_ret
from test3
group by id,year,month;
quit;
*选定一个测试时点,例如以2011年1月1日开始，找到该时点前p月到数据，
进而按照前P月到累计收益率进行排序，这里p取1，2，3，4，5，6;
data test5;
set test4;
if id eq lag(id) then do;
ret_lag1=lag(sum_ret);
ret_lag2=lag(sum_ret)+lag2(sum_ret);
ret_lag3=ret_lag2+lag3(sum_ret);
ret_lag4=ret_lag3+lag4(sum_ret);
ret_lag5=ret_lag4+lag5(sum_ret);
ret_lag6=ret_lag5+lag6(sum_ret);
end;
run;
*考虑lag函数产生缺失值的问题，我们选取观测时间点位2011年1月第一周;
data test6;
set test5;
if year=2011 & month=10 then output;
run;
*对观测时间点进行前P周到累计收益进行排序：升序：轮转策略；降序：动量策略;
%macro rank(num);
%do i=1 %to #
proc rank data=test6 out=test6_&i group=14;
var ret_lag&i;
ranks group;
run;
data test_dong&i test_fan&i;
set test6_&i;
if group=0 then output test_fan&i;
if group=13 then output test_dong&i;
run;
*从待选股票中选出动量组合股票，从观测日开始，计算持有组合内股票Q周的累计收益;
data new;
set test6;
if year<2011 then delete;
run;
*计算动量策略形成期为1周，持有期为1，2，3周到收益，同理可以计算
形成期为2/3周到动量策略;
data merge_d&i;
merge test_dong&i(in=a) new(in=b);
by id;
if a=1 & b=1 then output;
run;
proc expand data=merge_d&i out=d_&i;
convert ret_lag1=ret1 / transform=(lead 2);
convert ret_lag2=ret2 / transform=(lead 3);
convert ret_lag3=ret3 / transform=(lead 4);
convert ret_lag4=ret4 / transform=(lead 5);
convert ret_lag5=ret5 / transform=(lead 6);
convert ret_lag6=ret6 / transform=(lead 7);
run;
data d_&i;
set d_&i;
if year=2011 & month=10 then output;
run;
data merge_f&i;
merge test_fan&i(in=a) new(in=b);
by id;
if a=1 & b=1 then output;
run;
proc expand data=merge_f&i out=f_&i;
convert ret_lag1=ret1 / transform=(lead 2);
convert ret_lag2=ret2 / transform=(lead 3);
convert ret_lag3=ret3 / transform=(lead 4);
convert ret_lag4=ret4 / transform=(lead 5);
convert ret_lag5=ret5 / transform=(lead 6);
convert ret_lag6=ret6 / transform=(lead 7);
run;
data f_&i;
set f_&i;
if year=2011 & month=10 then output;
run;
%end;
%mend;
%rank(6);
*沪深300指数收益率的计算;
data sz399300_1;
set YU.sz399300;
year=year(var1);
month=month(var1);
ret=dif(log(var5));
drop var: ;
run;
proc sql;
create table sz399300_2 as
select distinct year,month,
sum(ret) as sum_ret
from sz399300_1
group by year,month ;
quit;
data sz399300_3;
set sz399300_2;
ret_lag1=lag(sum_ret);
ret_lag2=lag(sum_ret)+lag2(sum_ret);
ret_lag3=ret_lag2+lag3(sum_ret);
ret_lag4=ret_lag3+lag4(sum_ret);
ret_lag5=ret_lag4+lag5(sum_ret);
ret_lag6=ret_lag5+lag6(sum_ret);
run;
proc expand data=sz399300_3 out=sz399300_4;
convert ret_lag1=ret1 / transform=(lead 2);
convert ret_lag2=ret2 / transform=(lead 3);
convert ret_lag3=ret3 / transform=(lead 4);
convert ret_lag4=ret4 / transform=(lead 5);
convert ret_lag5=ret5 / transform=(lead 6);
convert ret_lag6=ret6 / transform=(lead 7);
run;
data sz399300_4;
set sz399300_4;
if year=2011 & month=10 then output;
run;
%macro diff_hs(num);
%do i= 1 %to #
proc sql;
create table d_need&i as
select distinct a.year,a.month,
mean(a.ret1-b.ret1) as ret1,
mean(a.ret2-b.ret2) as ret2,
mean(a.ret3-b.ret3) as ret3,
mean(a.ret4-b.ret4) as ret4,
mean(a.ret5-b.ret5) as ret5,
mean(a.ret6-b.ret6) as ret6
from d_&i as a
join sz399300_4 as b
on a.year=b.year;
quit;
proc sql;
create table f_need&i as
select distinct a.year,a.month,
mean(a.ret1-b.ret1) as ret1,
mean(a.ret2-b.ret2) as ret2,
mean(a.ret3-b.ret3) as ret3,
mean(a.ret4-b.ret4) as ret4,
mean(a.ret5-b.ret5) as ret5,
mean(a.ret6-b.ret6) as ret6
from f_&i as a
join sz399300_4 as b
on a.year=b.year;
quit;
%end;
%mend;
%diff_hs(6);
data final_d9;
set d_need:;
run;
data final_f9;
set f_need:;
run;
proc datasets library=work;
delete d_: f_: merge_: Sz399300: test: new;
run;
quit;
如果以日为单位进行测试，可以稍微变化下：
*e:\temp\test系国内A股数据，sz399300系沪深300指数数据;
libname gao "e:\tmp";
data test1;
set gao.test;
if id eq lag(id) then do;
ret=dif(close)/lag(close);
end;
if year(date)<2009 then delete;
keep id date ret close;
run;
*计算两年期间股票的日线数据长度，剔除较短数据;
proc freq data=test1 noprint ;
table id /out=test2(keep=id count) ;
run;
data test3;
merge test1 test2;
by id;
if count<360 then delete ;
run;
*选定一个测试时点,例如以2011年1月5日，计算前P日累计收益率并进行排序，
这里p取21，42;
proc expand data=test3 out=test4 method=none;
by id;
convert ret =ret_lag1 / transformout=(movsum 21);
convert ret =ret_lag2 / transformout=(movsum 42);
run;
*选定测试日;
data test5;
set test4;
if date="05jan2012"d then output;
run;
*以05jan2011日前21/42日累计收益率进行排序，生产动量组合和反转组合;
%macro rank(num);
%do i=1 %to #
proc rank data=test5 out=test5_&i group=10;
var ret_lag&i;
ranks group;
run;
data test_dong&i test_fan&i;
set test5_&i;
if group=0 then output test_fan&i;
if group=9 then output test_dong&i;
run;
*从待选股票中选出动量组合股票，从观测日开始，计算持有组合内股票Q日的累
计收益;
data new;
set test4;
if date<"05jan2012"d then delete;
run;
*计算动量策略形成期为1，持有期为1，2，3收益，同理可以计算
形成期为2/3到动量策略;
data merge_d&i;
merge test_dong&i(in=a) new(in=b);
by id;
if a=1 & b=1 then output;
run;
proc expand data=merge_d&i out=d_&i;
convert ret_lag1=ret1 / transform=(lead 21);
convert close=close21 / transform=(lead 21);
convert ret_lag2=ret2 / transform=(lead 42);
convert close=close42 / transform=(lead 42);
run;
data d_&i;
set d_&i;
if date="05jan2012"d then output;
run;
data merge_f&i;
merge test_fan&i(in=a) new(in=b);
by id;
if a=1 & b=1 then output;
run;
proc expand data=merge_f&i out=f_&i;
convert ret_lag1=ret1 / transform=(lead 21);
convert close=close21 / transform=(lead 21);
convert ret_lag2=ret2 / transform=(lead 42);
convert close=close42 / transform=(lead 42);
run;
data f_&i;
set f_&i;
if date="05jan2012"d then output;
run;
%end;
%mend;
%rank(2);
*沪深300指数收益率的计算;
data sz399300_1;
set gao.sz399300(rename=(var1=date var5=close));
ret=dif(close)/lag(close);
drop var: ;
run;
proc expand data=sz399300_1 out=sz399300_2 method=none;
convert ret =ret_lag1 / transformout=(sum 21);
convert ret =ret_lag2 / transformout=(sum 42);
run;
proc expand data=sz399300_2 out=sz399300_3;
convert ret_lag1=ret1 / transform=(lead 21);
convert close=close21 / transform=(lead 21);
convert ret_lag2=ret2 / transform=(lead 42);
convert close=close42 / transform=(lead 42);
run;
data sz399300_4;
set sz399300_3;
c0=close*300;
c21=close21*300;
C42=close42*300;
if date="05jan2012"d then output;
run;
%macro diff_hs(num);
%do i= 1 %to #
proc sql;
create table d_need&i as
select distinct a.date,
mean(a.ret1-b.ret1) as ret1,
mean(a.ret2-b.ret2) as ret2,
(sum((ceil(b.c0/193)/a.close)*a.close21) -c21)/c0 as r21,
(sum((ceil(b.c0/193)/a.close)*a.close42) -c42)/c0 as r42
from d_&i as a
join sz399300_4 as b
on a.date=b.date;
quit;
proc sql;
create table f_need&i as
select distinct a.date,
mean(a.ret1-b.ret1) as ret1,
mean(a.ret2-b.ret2) as ret2,
(sum((ceil(b.c0/193)/a.close)*a.close21) -c21)/c0 as r21,
(sum((ceil(b.c0/193)/a.close)*a.close42) -c42)/c0 as r42
from f_&i as a
join sz399300_4 as b
on a.date=b.date;
quit;
%end;
%mend;
%diff_hs(2);
data final_d1;
set d_need:;
run;
data final_f1;
set f_need:;
run;