Store output object to a data frame from different variables in R

Below is my script for a stock back testing project. I wrote to test the return of 2 SMA cross over for a buy/sell strategy. Now, I want to automate the input value of x and y and generate a table for different result. With X value changing from (1:30) as well as Y value changing from (1:30) and output to an Excel like dataframe file which row against column from 1 to 30. I had tried different ways but still cannot make the final data frame in R

library(quantmod)
library(lubridate)
library(xlsx)
stock0<-getSymbols("^HSI",src="yahoo",from="1988-01-01",auto.assign=F)
stock0 <- to.weekly(stock0)


x<-1
y<-30


stock1<-na.locf(stock0)
stock1$SMA1<-SMA(Cl(stock1),n=x)
stock1$SMA30<-SMA(Cl(stock1),n=y)

stock1$SMACheck<-ifelse(stock1$SMA1>stock1$SMA30,1,0)
stock1$SMA_CrossOverUp<-ifelse(diff(stock1$SMACheck)==1,1,0)
stock1$SMA_CrossOverDown<-ifelse(diff(stock1$SMACheck)==-1,-1,0)


stock1<-stock1[index(stock1)>="1998-01-01",]

stock1_df<-data.frame(index(stock1),coredata(stock1))

colnames(stock1_df)<-c("Date","Open","High","Low","Close","Volume","Adj","SMA1","SMA30","SMACheck","SMACheck_up","SMACheck_down")




sum(stock1_df$SMACheck_up==1 & index(stock1)>="2010-01-01",na.rm=T)

stock1_df$Date[stock1_df$SMACheck_up==1 & index(stock1)>="2010-01-01"]

sum(stock1_df$SMACheck_down==-1 & index(stock1)>="2010-01-01",na.rm=T)

stock1_df$Date[stock1_df$SMACheck_down==-1 & index(stock1)>="2010-01-01"]


#To generate the transcation according to the strategy

transaction_dates<-function(stock2,Buy,Sell)
{
Date_buy<-c()
Date_sell<-c()
hold<-F
stock2[["Hold"]]<-hold
for(i in 1:nrow(stock2)) {
  if(hold == T) {
    stock2[["Hold"]][i]<-T
    if(stock2[[Sell]][i] == -1) {
      #stock2[["Hold"]][i]<-T
      hold<-F
    }
  } else {
    if(stock2[[Buy]][i] == 1) {
      hold<-T
      stock2[["Hold"]][i]<-T
    }
  }
}


stock2[["Enter"]]<-c(0,ifelse(diff(stock2[["Hold"]])==1,1,0))
stock2[["Exit"]]<-c(ifelse(diff(stock2[["Hold"]])==-1,-1,0),0)

Buy_date <- stock2[["Date"]][stock2[["Enter"]] == 1]
Sell_date <- stock2[["Date"]][stock2[["Exit"]] == -1]

if (length(Sell_date)<length(Buy_date)){
  #Sell_date[length(Sell_date)+1]<-tail(stock2[["Date"]],n=2)[1]
  Buy_date<-Buy_date[1:length(Buy_date)-1]

}

return(list(DatesBuy=Buy_date,DatesSell=Sell_date))
}

#transaction dates generate:
stock1_df <- na.locf(stock1_df)

transactionDates<-transaction_dates(stock1_df,"SMACheck_up","SMACheck_down")


num_transaction1<-length(transactionDates[[1]])

Open_price<-function(df,x) {
  df[which(df[["Date"]]==x)+1,][["Open"]]
}

transactions_date<-function(df,x) {
  df[which(df[["Date"]]==x)+1,][["Date"]]
}

transactions_generate<-function(df,num_transaction)
{
price_buy<-sapply(1:num_transaction,function(x) {Open_price(df,transactionDates[[1]][x])})
price_sell<-sapply(1:num_transaction,function(x) {Open_price(df,transactionDates[[2]][x])})
Dates_buy<-as.Date(sapply(1:num_transaction,function(x) {transactions_date(df,transactionDates[[1]][x])}))
Dates_sell<-as.Date(sapply(1:num_transaction,function(x) {transactions_date(df,transactionDates[[2]][x])}))


transactions_df<-data.frame(DatesBuy=Dates_buy,DatesSell=Dates_sell,pricesBuy=price_buy,pricesSell=price_sell)
#transactions_df$return<-100*(transactions_df$pricesSell-transactions_df$pricesBuy)/transactions_df$pricesBuy
transactions_df$Stop_loss<-NA
return(transactions_df)
}

transaction_summary<-transactions_generate(stock1_df,num_transaction1)
transaction_summary$Return<-100*(transaction_summary$pricesSell-transaction_summary$pricesBuy)/transaction_summary$pricesBuy

result<-sum(transaction_summary$Return,na.rm=T)
result