使用行值作为 R 函数中的变量在数据框中创建新列 [英] Creating a new column in dataframe using row values as variables in a function in R

问题描述

我有一个数据框:

df <- structure(list(LAST = c(3.4, 2.52, 1.82, 1.16, 0.69, 0.36, 4, 
3.21, 2.54, 1.93), CURRENTPRICE = c(464.16, 464.16, 464.16, 464.16, 
464.16, 464.16, 464.16, 464.16, 464.16, 464.16), STRIKEPRICE = c(461, 
462, 463, 464, 465, 466, 461, 462, 463, 464), YEARSTOEXPIRATION = c(0.00273972602739726, 
0.00273972602739726, 0.00273972602739726, 0.00273972602739726, 
0.00273972602739726, 0.00273972602739726, 0.010958904109589, 
0.010958904109589, 0.010958904109589, 0.010958904109589)), row.names = c(NA, 
-10L), class = c("data.table", "data.frame"))

我正在尝试使用来自每一行的数据并使用 RQuantLib 包中的 AmericanOptionImpliedVolatility 函数创建一个新列，计算每一行的隐含波动率:

I am trying to create a new column calculating implied volatility for each row using data from each row and using the AmericanOptionImpliedVolatility function from the RQuantLib package:

df$IMPLIEDVOLATILITY <- AmericanOptionImpliedVolatility(type="call", value=df$LAST, underlying=df$CURRENTPRICE, strike=df$STRIKEPRICE, dividendYield=0.00, riskFreeRate=.03, maturity=df$YEARSTOEXPIRATION, volatility=0.2)

我知道代码是错误的，因此我收到一条错误消息:

I know that the code is wrong and I accordingly get an error message:

在 americanOptionImpliedVolatilityEngine 中出错(类型，值，底层，:期望一个值:[extent=10]."

"Error in americanOptionImpliedVolatilityEngine(type, value, underlying, : Expecting a single value: [extent=10]."

我如何正确使用AmericanOptionImpliedVolatility"?以行值作为变量的函数，以创建具有该结果值的新列?

How do I correctly use the "AmericanOptionImpliedVolatility" function with the row values as variables to create a new column with that resulting value?

推荐答案

df %>%
  rowwise() %>%
  mutate(IMPLIEDVOLATILITY = 
           RQuantLib::AmericanOptionImpliedVolatility(type="call", 
                  value = LAST, 
                  underlying = CURRENTPRICE, 
                  strike = STRIKEPRICE, 
                  dividendYield = 0.00, 
                  riskFreeRate =.03,
                  maturity = YEARSTOEXPIRATION,
                  volatility=0.2))



LAST CURRENTPRICE STRIKEPRICE YEARSTOEXPIRATI~ IMPLIEDVOLATILI~
   <dbl>        <dbl>       <dbl>            <dbl> <AmrcnOIV>      
 1  3.4          464.         461          0.00274 0.12058321      
 2  2.52         464.         462          0.00274 0.11218994      
 3  1.82         464.         463          0.00274 0.11577334      
 4  1.16         464.         464          0.00274 0.10918985      
 5  0.69         464.         465          0.00274 0.10744424      
 6  0.36         464.         466          0.00274 0.10472401      
 7  4            464.         461          0.0110  0.09853768      
 8  3.21         464.         462          0.0110  0.09443249      
 9  2.54         464.         463          0.0110  0.09343687      
10  1.93         464.         464          0.0110  0.09130677  

使用基础 R，您可以:

With base R, you could do:

transform(df, IMPLIEDVOLATILITY = 
           Vectorize(RQuantLib::AmericanOptionImpliedVolatility)(type="call", 
                  value = LAST, 
                  underlying = CURRENTPRICE, 
                  strike = STRIKEPRICE, 
                  dividendYield = 0.00, 
                  riskFreeRate =.03,
                  maturity = YEARSTOEXPIRATION,
                  volatility=0.2))

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