The trend of closing price is always regarded as one of the most straightforward indications of a stock’s demand and performance, so the time series price plot is supposed to be a key component in a dashboard for investment guidance.
The graph shows the stock price performance for Apple over the last 3 years.
Up and down closing prices over previous day is shown through green and red colored ribbon beneath the stock price performance chart.
Date range selector is enabled.
The stock price to index performance shows how the stock price has been performing relative to its peer companies and the composite index in general over a span of time.
The graph displays the current valuation and return on invetment of the stock vs. the NASDAQ index if $100 were invested in each of them on the same day for any period of time chosen through the date range selector.
A Bollinger Band, developed by famous technical trader John Bollinger, is plotted two standard deviations away from a simple moving average.
The price of the stock is bracketed by an upper and lower band along with a 21-day simple moving average.
The graph shows candlestick chart with Bollinger Bands with an additional date range selector.
The up, mavg and down symbols show the Bollinger Bands.
Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of prices.
The MACD is calculated by subtracting the 26-day exponential moving average (EMA) from the 12-day EMA.
A nine-day EMA of the MACD, called the “signal line”, is then plotted on top of the MACD, functioning as a trigger for buy and sell signals.
Traders can look for signal line crossovers, centerline crossovers and divergences to generate signals.
---
title: "Stock Recommendation Dashboard"
output:
flexdashboard::flex_dashboard:
storyboard: true
orientation: rows
vertical_layout: fill
source_code: embed
social: menu
---
```{r setup, include=FALSE}
library(flexdashboard)
library(quantmod)
library(dygraphs)
library(TTR)
options(getSymbols.warning4.0 = FALSE,
getSymbols.yahoo.warning = FALSE)
```
```{r Technical_Analysis, include = FALSE}
invisible(getSymbols("AAPL", from = "2015-01-01", auto.assign=TRUE))
AAPL <- as.data.frame(AAPL)
# Simple Moving Averages (SMA)
# 20-day SMA
sma20 <- SMA(AAPL$AAPL.Close, n=20)
# 50-day SMA
sma50 <- SMA(AAPL$AAPL.Close, n=50)
# 200-day SMA
sma200 <- SMA(AAPL$AAPL.Close, n=200)
# Exponential Moving Average (EMA)
# 14-day EMA
ema14 <- EMA(AAPL$AAPL.Close, n=14)
# Bollinger Bands
bb20 <- BBands(AAPL$AAPL.Close, sd=2.0, n=14, maType=EMA)
# Overall data frame
AAPLplusBB <- data.frame(AAPL,bb20)
# Relative Strength Indicator
rsi14 <- RSI(AAPLplusBB$AAPL.Close, n=14)
#MACD
macd <- MACD(AAPLplusBB$AAPL.Close, nFast = 12, nSlow = 26,
nSig = 9, maType = SMA)
# allData
allData <- data.frame(AAPL,sma20,sma50,sma200,ema14,bb20,rsi14,macd)
```
###Stock Price Performance
```{r Stock_Price}
invisible(getSymbols("AAPL", from = "2015-01-01", auto.assign=TRUE))
difference <- AAPL[, "AAPL.Open"] - AAPL[, "AAPL.Close"]
decreasing <- which(difference < 0)
increasing <- which(difference > 0)
dyData <- AAPL[, "AAPL.Close"]
ribbonData <- rep(0, nrow(dyData))
ribbonData[decreasing] <- 0.5
ribbonData[increasing] <- 1
dygraph(dyData, main = "Stock Price Movement") %>%
dyRibbon(data = ribbonData, top = 0.1, bottom = 0.02) %>%
dyRangeSelector(height = 50)
```
***
- The trend of closing price is always regarded as one of the most straightforward indications of a stock's demand and performance, so the time series price plot is supposed to be a key component in a dashboard for investment guidance.
- The graph shows the stock price performance for Apple over the last 3 years.
- Up and down closing prices over previous day is shown through green and red colored ribbon beneath the stock price performance chart.
- Date range selector is enabled.
###Relative Rebase: Stock Price vs. Nasdaq
```{r Relative_Rebase}
tickers <- c("AAPL", "NDAQ")
invisible(getSymbols(tickers))
closePrices <- do.call(merge, lapply(tickers, function(x) Cl(get(x))))
dateWindow <- c("2015-01-01", "2017-10-31")
dygraph(closePrices, main = "Prcie-to-Index Performance", group = "stock") %>%
dyRebase(value = 100) %>%
dyRangeSelector(dateWindow = dateWindow, height = 50) %>%
dyAxis("y", label = "Price Indexed over a period")
```
***
- The stock price to index performance shows how the stock price has been performing relative to its peer companies and the composite index in general over a span of time.
- The graph displays the current valuation and return on invetment of the stock vs. the NASDAQ index if $100 were invested in each of them on the same day for any period of time chosen through the date range selector.
###Technical Analysis: Candlestick Chart with Bollinger Bands
```{r Bollinger_Bands}
m <- cbind(allData[,1:4], allData[,11], allData[,12], allData[,13])
colnames(m)[5] <- "dn"
colnames(m)[6] <- "mavg"
colnames(m)[7] <- "up"
dygraph(m, main = "Bollinger Bands" ) %>%
dyCandlestick() %>%
dyRangeSelector(height = 50)
```
***
- A Bollinger Band, developed by famous technical trader John Bollinger, is plotted two standard deviations away from a simple moving average.
- The price of the stock is bracketed by an upper and lower band along with a 21-day simple moving average.
- The graph shows candlestick chart with Bollinger Bands with an additional date range selector.
- The **up**, **mavg** and **down** symbols show the Bollinger Bands.
###Technical Analysis: Moving Average Convergence Divergence (MACD)
```{r MACD}
m <- cbind(allData[,1:4], allData[,16], allData[,17])
colnames(m)[5] <- "MACD"
colnames(m)[6] <- "MACD Signal Line"
dygraph(m, main = 'MACD') %>%
dyAxis("y", valueRange = c(-8, 8), label = "Rate of Convergence/ Divergence")%>%
dyRangeSelector(height = 50)
```
***
- Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of prices.
- The MACD is calculated by subtracting the 26-day exponential moving average (EMA) from the 12-day EMA.
- A nine-day EMA of the MACD, called the "signal line", is then plotted on top of the MACD, functioning as a trigger for buy and sell signals.
- Traders can look for signal line crossovers, centerline crossovers and divergences to generate signals.