Bitcoin Automated Alert Mock-up (SatRday 2018)

Readme.md

Hi!

This gist contains all of the necessary files to set up an automated alert on the price of Bitcoin, as covered in my talk at SatRday 2018.

You should be able to pop these files into a folder, fill out the necessary config at the top of 'Analysis_template.R' and have a working Rscript and Rmarkdown pair. In order to get this running on a schedule, you will need to hook 'BitcoinAlert_template.bat' to a task in Windows Task Scheduler. And that's it! If you experience any issues, please feel free to ask questions at vishalin.pillay@outlook.com.

Analysis_template.R

library(jsonlite)
library(dplyr)
library(tidyr)
library(ggplot2)
library(RcppRoll)
library(mailR)
library(knitr)

setwd("directory/of/your/Rscript")

#---------------------------------Define Parameters----------------------------------------------
currentDate    <- Sys.Date()
anchorDate     <- as.Date('2016-01-01')
currency       <- 'ZAR'
retro          <- 1 #how far back to compare the price in days

#Email Config
sender         <- 'example@example.com'
recipients     <- c('abc@example.com','def@example.com')
smtp.hostname  <- 'smtp.gmail.com'
smtp.port      <- 465
smtp.username  <- 'example@example.com'
emailpass      <- 'you may want to put this elsewhere'

#---------------------------------Define Parameters----------------------------------------------

coindeskURL <- paste('https://api.coindesk.com/v1/bpi/historical/close.json', 
                     '?currency=', currency, 
                     '&start=', anchorDate, 
                     '&end=', currentDate, sep='')

coindesk <- fromJSON(coindeskURL)

bpi <- as.data.frame(coindesk[1]) %>% 
  gather('Day', 'Price') %>%
  mutate(Day = as.Date(gsub('bpi.', '', Day), format='%Y.%m.%d'), Price = as.numeric(Price)) %>%
  arrange(Day) %>%
  mutate(Index = seq.int(nrow(.)))

#12, 26, 50, 200 ema

emamult <- function(period)
{
  2/(period + 1)
}

EmafromSma <- function(data)
{
  data <- as.matrix(data)
  
  for(i in 2:nrow(data))
  {
    if(!is.na(data[i-1, 'EMA12']))
    {
      data[i, 'EMA12'] <- (as.numeric(data[i, 'Price']) - as.numeric(data[i-1, 'EMA12'])) * emamult(12) + as.numeric(data[i-1, 'EMA12'])
    }
    
    if(!is.na(data[i-1, 'EMA26']))
    {
      data[i, 'EMA26'] <- (as.numeric(data[i, 'Price']) - as.numeric(data[i-1, 'EMA26'])) * emamult(26) + as.numeric(data[i-1, 'EMA26'])
    }
    
    if(!is.na(data[i-1, 'EMA50']))
    {
      data[i, 'EMA50'] <- (as.numeric(data[i, 'Price']) - as.numeric(data[i-1, 'EMA50'])) * emamult(50) + as.numeric(data[i-1, 'EMA50'])
    }
    
    if(!is.na(data[i-1, 'EMA200']))
    {
      data[i, 'EMA200'] <- (as.numeric(data[i, 'Price']) - as.numeric(data[i-1, 'EMA200'])) * emamult(200) + as.numeric(data[i-1, 'EMA200'])
    }
  }
  
  data
}

bpitechnical <- 
  mutate(bpi, 
         SMA12 = roll_mean(Price, 12, align='right', fill=NA),
         SMA26 = roll_mean(Price, 26, align='right', fill=NA),
         SMA50 = roll_mean(Price, 50, align='right', fill=NA),
         SMA200 = roll_mean(Price, 200, align='right', fill=NA)
         ) %>%
  mutate(EMA12 = ifelse(Index == 12, SMA12, NA),
         EMA26 = ifelse(Index == 26, SMA26, NA),
         EMA50 = ifelse(Index == 50, SMA50, NA),
         EMA200 = ifelse(Index == 200, SMA200, NA),
         )

bpitechnical <- as.data.frame(EmafromSma(bpitechnical)) %>% mutate(Day = as.Date(as.character(Day)))

numericcolumns <- 2:11
bpitechnical[,numericcolumns] <- apply(bpitechnical[,numericcolumns], 2, function(x) {as.numeric(as.character(x))})

saveRDS(bpitechnical, 'bpitechnical.rda')

emastatus <- function(data, ema, lag)
{
  yesterdayabove <- ifelse(data[nrow(data)-lag, 'Price'] > data[nrow(data)-lag, ema], T, F)
  todayabove <- ifelse(data[nrow(data), 'Price'] > data[nrow(data), ema], T, F)
  
  if(yesterdayabove != todayabove)
  {
    ifelse(yesterdayabove, 'FALL', 'RISE')
  }else
  {
    'UNCHANGED'
  }
}

ema12status <- emastatus(bpitechnical, 'EMA12', retro)
ema26status <- emastatus(bpitechnical, 'EMA26', retro)
ema50status <- emastatus(bpitechnical, 'EMA50', retro)
ema200status <- emastatus(bpitechnical, 'EMA200', retro)

if(ema12status != 'UNCHANGED' || ema26status != 'UNCHANGED' || ema50status != 'UNCHANGED' || ema200status != 'UNCHANGED')
{
  markdown <- paste(readLines('BitcoinAlert_template.Rmd', warn = FALSE), collapse = "\n")
  
  message <- knitr::knit2html(text=markdown, options=c("use_xhtml", "smartypants","mathjax","highlight_code"))
  
  send.mail(from = sender,
            to = recipients,
            subject = "Bitcoin Alert",
            body = message,
            html = TRUE,
            inline = TRUE,
            smtp = list(host.name = smtp.hostname, port = smtp.port, user.name = smtp.port, passwd = emailpass, ssl = TRUE),
            authenticate = TRUE,
            send = TRUE)
}

BitcoinAlert_template.bat

Rscript path\to\your\script\Analysis_template.R
pause

BitcoinAlert_template.Rmd

```{r setup, include=FALSE}
knitr::opts_chunk$set(
  echo = FALSE,
  message = FALSE,
  warning = FALSE,
  fig.width = 12,
  fig.height = 6
)
```

## Bitcoin Price Alert

The bitcoin price has broken through one or more resistance levels. Please see below for details:

</br>

```{r}
library(ggplot2)
library(dplyr)

bpitechnical <- readRDS('bpitechnical.rda')

emastatus <- function(data, ema, lag)
{
  yesterdayabove <- ifelse(data[nrow(data)-lag, 'Price'] > data[nrow(data)-lag, ema], T, F)
  todayabove <- ifelse(data[nrow(data), 'Price'] > data[nrow(data), ema], T, F)
  
  if(yesterdayabove != todayabove)
  {
    ifelse(yesterdayabove, 'FALL', 'RISE')
  }else
  {
    'UNCHANGED'
  }
}

ema12status <- emastatus(bpitechnical, 'EMA12', 3)
ema26status <- emastatus(bpitechnical, 'EMA26', 3)
ema50status <- emastatus(bpitechnical, 'EMA50', 3)
ema200status <- emastatus(bpitechnical, 'EMA200', 3)

ema12colour <- ifelse(ema12status == 'RISE', 'green', 'red')
ema26colour <- ifelse(ema26status == 'RISE', 'green', 'red')
ema50colour <- ifelse(ema50status == 'RISE', 'green', 'red')
ema200colour <- ifelse(ema200status == 'RISE', 'green', 'red')

ema12message <- ifelse(ema12status == 
                       'RISE', 'The price has risen through the 12 day resistance level.',
                       ifelse(ema12status == 
                              'FALL', 'The price has fallen through the 12 day resistance level.\n', '')
                       )

ema26message <- ifelse(ema26status == 
                       'RISE', 'The price has risen through the 26 day resistance level.',
                       ifelse(ema26status == 
                              'FALL', 'The price has fallen through the 26 day resistance level.\n', '')
                       )

ema50message <- ifelse(ema50status == 
                       'RISE', 'The price has risen through the 50 day resistance level.',
                       ifelse(ema50status == 
                              'FALL', 'The price has fallen through the 50 day resistance level.\n', '')
                       )

ema200message <- ifelse(ema200status == 
                       'RISE', 'The price has risen through the 200 day resistance level.',
                       ifelse(ema200status == 
                              'FALL', 'CRITICAL: The price has fallen through the 200 day resistance level.\n', '')
                       )

risesig <- ifelse(ema200status=='RISE', 4, ifelse(ema50status=='RISE', 3, ifelse(ema26status=='RISE', 2, ifelse(ema12status=='RISE', 1, 0))))

fallsig <- ifelse(ema200status=='FALL', 4, ifelse(ema50status=='FALL', 3, ifelse(ema26status=='FALL', 2, ifelse(ema12status=='FALL', 1, 0))))

positivenews <- ifelse(risesig > fallsig, T, F)

```

<span style="color:`r ema12colour `"> `r ema12message `</span>  
<span style="color:`r ema26colour `"> `r ema26message `</span>  
<span style="color:`r ema50colour `"> `r ema50message `</span>  
<span style="color:`r ema200colour `"> `r ema200message `</span>  

### Historical Views

```{r}
ggplot(bpitechnical, aes(x=Day)) +
  geom_line(aes(y=Price), colour='black') +
  geom_line(aes(y=EMA12), colour='green', size=1.3, alpha=0.3) +
  geom_line(aes(y=EMA26), colour='yellow', size=1.3, alpha=0.3) +
  geom_line(aes(y=EMA50), colour='orange', size=1.3, alpha=0.3) +
  geom_line(aes(y=EMA200), colour='red', size=1.3, alpha=0.3) +
  ylab('ZAR') +
  theme(axis.title.x = element_blank()) +
  ggtitle('All Time')

ggplot(filter(bpitechnical, Index > nrow(bpitechnical) - 365), aes(x=Day)) +
  geom_line(aes(y=Price), colour='black') +
  geom_line(aes(y=EMA12), colour='green', size=1.3, alpha=0.3) +
  geom_line(aes(y=EMA26), colour='yellow', size=1.3, alpha=0.3) +
  geom_line(aes(y=EMA50), colour='orange', size=1.3, alpha=0.3) +
  geom_line(aes(y=EMA200), colour='red', size=1.3, alpha=0.3) +
  ylab('ZAR') +
  theme(axis.title.x = element_blank()) +
  ggtitle('1 Year')

ggplot(filter(bpitechnical, Index > nrow(bpitechnical) - 92), aes(x=Day)) +
  geom_line(aes(y=Price), colour='black') +
  geom_line(aes(y=EMA12), colour='green', size=1.3, alpha=0.3) +
  geom_line(aes(y=EMA26), colour='yellow', size=1.3, alpha=0.3) +
  geom_line(aes(y=EMA50), colour='orange', size=1.3, alpha=0.3) +
  geom_line(aes(y=EMA200), colour='red', size=1.3, alpha=0.3) +
  ylab('ZAR') +
  theme(axis.title.x = element_blank()) +
  ggtitle('3 Months')

ggplot(filter(bpitechnical, Index > nrow(bpitechnical) - 31), aes(x=Day)) +
  geom_line(aes(y=Price), colour='black') +
  geom_line(aes(y=EMA12), colour='green', size=1.3, alpha=0.3) +
  geom_line(aes(y=EMA26), colour='yellow', size=1.3, alpha=0.3) +
  geom_line(aes(y=EMA50), colour='orange', size=1.3, alpha=0.3) +
  geom_line(aes(y=EMA200), colour='red', size=1.3, alpha=0.3) +
  ylab('ZAR') +
  theme(axis.title.x = element_blank()) +
  ggtitle('1 Month')
```
  
</br>  
  
`r if(positivenews){'[comment]: # '}` EVERYTHING WILL BE FINE, JUST <span style="color:green"> HODL </span>  

</br>  

Trading in cryptocurrencies is a high risk venture. Consult with a financial advisor before making investment decisions. This should not be treated as expert financial advice.  

</br>  
  

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