modelReturn skips the first day of returns

### Description

modelReturn does not include in its math the first day of returns.
In modelReturn, the calculation of 'daily returns' is incorrect.

### Expected behavior

modelReturn must include in its math the 'first day of returns.'

### Minimal, reproducible example

When I run the code, the following occurs.

```r

library(quantmod)

getSymbols("IBM", from = "2017-01-01", to = "2018-10-20")

m <- specifyModel(Next(OpCl(IBM)) ~ Lag(OpHi(IBM)))
m.built <- buildModel(m,method='rpart',training.per=c("2017-01-01","2017-04-01"))
tm <- tradeModel(m.built,leverage=2)
tm
```
In modelReturn, the following happens.

```r
# our model data in modelReturns
model.data <- modelData(tR.results$model, trade.dates, exclude.training = exclude.training)

Browse[3]> head(model.data)
Next.OpCl.IBM Lag.OpHi.IBM
2017-04-03 0.0057630243 0.005575359 - (NOT INVESTED): DETERMINING WHAT TO INVEST NEXT
2017-04-04 -0.0104178136 0.006040663
2017-04-05 -0.0058800023 0.008298772
2017-04-06 0.0003486576 0.009330309
2017-04-07 -0.0077088159 0.000000000
2017-04-10 -0.0004101494 0.004939511

# daily return and our morning signal
Browse[3]> head(trade.signal)
Next.OpCl.IBM signal.zoo
2017-04-04 0.0057630243 1 - MORNING OF THE 4TH ( RETURN OF INVESTED ALL DAY TODAY )
2017-04-05 -0.0104178136 1
2017-04-06 -0.0058800023 1
2017-04-07 0.0003486576 1
2017-04-10 -0.0077088159 1
2017-04-11 -0.0004101494 1

# profit that day (4TH)
model.results <- trade.signal[, 1] * leverage * trade.signal[, 2]
model.results[which(is.na(model.results))] <- 0

Browse[3]> head(model.results)
Next.OpCl.IBM
2017-04-04 0.0115260486 0.005763024 * 2 = 0.01152605 (correct) - (4TH PROFIT)
2017-04-05 -0.0208356271
2017-04-06 -0.0117600045
2017-04-07 0.0006973152
2017-04-10 -0.0154176318
2017-04-11 -0.0008202989

# total returns
model.cumret <- cumprod(1 + model.results)

Browse[3]> head(model.cumret)
Next.OpCl.IBM
2017-04-04 1.0115260 - EVE OF THE 4TH CUMULATIVE RETURN (I WAS INVESTED ALL DAY)
2017-04-05 0.9904503
2017-04-06 0.9788026
2017-04-07 0.9794851
2017-04-10 0.9643838
2017-04-11 0.9635927

# every days return
returnsBy <- allReturns(model.cumret)

Browse[3]> head(returnsBy)
daily weekly monthly quarterly yearly
2017-04-04 NA NA NA NA NA - returns of the 4th are SKIPPED
2017-04-05 -0.0208356271 NA NA NA NA
2017-04-06 -0.0117600045 NA NA NA NA
2017-04-07 0.0006973152 -0.03167585 NA NA NA
2017-04-10 -0.0154176318 NA NA NA NA
2017-04-11 -0.0008202989 NA NA NA NA

# that is actually

Browse[3]> head(dailyReturn(model.cumret))
daily.returns
2017-04-04 0.0000000000 - NOT CORRECT, I WAS INVESTED ALL DAY ON THE 4TH
2017-04-05 -0.0208356271
2017-04-06 -0.0117600045
2017-04-07 0.0006973152
2017-04-10 -0.0154176318
2017-04-11 -0.0008202989

# Perhaps, One may need to include the 'night of the previous day'
# where the Price == 1.0
Browse[3]> head( rbind( model.cumret, xts(1.0, head(index(model.data),1)) ) )
Next.OpCl.IBM
2017-04-03 1.0000000
2017-04-04 1.0115260 - ON THE 4TH, I WAS INVESTED ALL DAY
2017-04-05 0.9904503
2017-04-06 0.9788026
2017-04-07 0.9794851
2017-04-10 0.9643838

# So,now that looks right
Browse[3]> head(dailyReturn( rbind( model.cumret, xts(1.0, head(index(model.data),1)) ) ))
daily.returns
2017-04-03 0.0000000000
2017-04-04 0.0115260486 - ON THE 4TH, I WAS INVESTED ALL DAY
2017-04-05 -0.0208356271
2017-04-06 -0.0117600045
2017-04-07 0.0006973152
2017-04-10 -0.0154176318
```
### Session Info
```r
Browse[2]> devtools::session_info()
- Session info ---------------------------------------------------------------
setting value
version R version 3.5.1 Patched (2018-10-09 r75424)
os Windows 10 x64
system x86_64, mingw32
ui RTerm
language (EN)
collate English_United States.1252
ctype English_United States.1252
tz America/Chicago
date 2018-10-25

- Packages -------------------------------------------------------------------
package * version date lib source
curl 3.2 2018-03-28 [1] CRAN (R 3.5.1)
devtools 2.0.0 2018-10-19 [1] CRAN (R 3.5.1)
quantmod * 0.4-13 2018-04-13 [1] CRAN (R 3.5.1)
TTR * 0.23-4 2018-09-20 [1] CRAN (R 3.5.1)
xts * 0.11-1 2018-09-12 [1] CRAN (R 3.5.1)
zoo * 1.8-4 2018-09-19 [1] CRAN (R 3.5.1)
```

Reproduce the example with modelReturn, modelData, tradeModel, and dailyReturn, then trace how the cumulative return series is built from the first trading date. Check the daily and allReturns outputs against the reported 2017-04-04 case. Done means the first invested day is included rather than reported as zero, skipped, or NA.

Written by the indexing model from the issue text.