[R] Adjusting OHCL data via quantmod

[Joe O]

Hello,

I'm trying to do two things:
-1. Ensure that I understand how quantmod adjust's OHLC data
-2. Determine how I ought to adjust my data.

My overarching-goal is to adjust my OHLC data appropriately to minimize the
difference between my backtest returns, and the returns I would get if I
was trading for real (which I'll be doing shortly).

Background:
-1. I'm using Alpha Vantage's data, and quantmod's data adjustment tools.
-2: I used Joshua Ulrich's DataCamp guidance (
https://campus.datacamp.com/courses/importing-and-managing-financial-data-in-r/importing-text-data-and-adjusting-for-corporate-actions?ex=10)
(and quantmod documentation) to determine how Alpha Vantage's data is
adjusted.

Here are my findings:

-It seems that Alpha Vantage's OHLC data are unadjusted, and the adjusted
close column provided is adjusted for splits, and split-adjusted dividends.
-If I use AV's adjusted close column to adjust my OHCL data, my data will
be adjusted for splits, and split-adjusted dividends. (So, I can use
adjustOHLC(), with argument use.Adjusted = TRUE to adjust for splits, and
split-adjusted dividends)

Evidence:

###
library(quantmod)

#AV data
getSymbols("AAPL",src = "av" ,api.key = my_api_key
           , adjusted = TRUE, output.size = "full") #supply your own api key

#Manual adjustments for splits, and split-adjusted dividends
close_av <- Cl(AAPL)
splits <- getSplits("AAPL")
dividends <- getDividends("AAPL", split.adjust = TRUE)
ratios_av <- adjRatios(splits = splits, dividends = dividends, close =
close_av)
close_av_adj <- close_av * ratios_av[,"Div"] * ratios_av[,"Split"]
head(merge(close_av, close_av_adj, Ad(AAPL)))

#The leftmost column is the raw close data from Alpha Vantage,
#the middle column is the raw Alpha Vantage close column manually adjusted
#for splits and split-adjusted dividends, and the last column is the
adjusted close column returned by Alpha Vantage

#Adjust all data for splits, and split-adjusted dividends (I think)
AAPL_a <- adjustOHLC(AAPL, use.Adjusted = TRUE)
head(AAPL_a)
###

Two questions:
-1. Am I interpreting these adjustments correctly?
-2. What adjustment method minimizes the difference between backtesting and
live-trading?

p.s., I expect there is no "correct" method for adjusting data. I'm curious
if there is a "best-practice" or norm that is used. I'm curious if there is
a method which minimizes the difference between backtesting and
live-trading. Thanks you, -Joe

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