---
title: "Indexes in the 21st Century"
author: "Joseph Connolly"
output: 
  flexdashboard::flex_dashboard:
    theme: readable
    orientation: rows
    social: menu
    source_code: embed
---


```{r setup, include = FALSE}
library(ggplot2)
library(plotly)
library(plyr)
library(flexdashboard)
library(quantmod)
library(TTR)
library(shiny)
library(htmltools)
library(purrr)
library(rsconnect)

setwd("C:/Users/jmcon/OneDrive/D608_FP")

markets <- read.csv("https://raw.githubusercontent.com/jconno/R-data/master/indexProcessed.csv")

markets$macd <- MACD(markets$Close, nFast = 12, nSlow = 26, nSig = 9)
markets$sma <- SMA(markets$Close, n=12)

#tibble::view(markets)


# Factor Index column
factorize <- c("Index")
markets[factorize] <- lapply(markets[factorize], factor)

# As.Date
markets$Date <- as.Date(markets$Date)
markets <- markets %>% filter(Date > "1999-12-31")

# Subsetting Indexes

sz.399001 <- markets %>% filter(Index == "399001.SZ")
ss.000001 <- markets %>% filter(Index == "000001.SS")
gdaxi <- markets %>% filter(Index == "GDAXI")
gsptse <- markets %>% filter(Index == "GSPTSE")
hsi <- markets %>% filter(Index == "HSI")
ixic <- markets %>% filter(Index == "IXIC")
J203.JO <- markets %>% filter(Index == "J203.JO")
n100 <- markets %>% filter(Index == "N100")
n225 <- markets %>% filter(Index == "N225")
nsei <- markets %>% filter(Index == "NSEI")
nya <- markets %>% filter(Index == "NYA")
ssmi <- markets %>% filter(Index == "SSMI")
twii <- markets %>% filter(Index == "TWII")

```


Intro
=======================================================================


Global Index Performance in the 21st Century

By Joseph Connolly

Professor Charley Ferrari
 
CUNY SPS, MSDS: Data 608

Spring, 2022





  This final project for Data 608, Knowledge and Visual Analytics, at the CUNY School of Professional Studies, entails a Flexdashboard to visualize and display the performance of global indexes in the 21st Century. From Kaggle.com, I downloaded and imported a global index dataset that contains stock information ranging from 1965-2021. This was cleaned and sub-setted to only include data onward from December 31st, 1999


  Included in this application is a simple Shiny app that shows the summaries of all indexes from the dataset. You may access it via the link embedded in   ShinySummaries


 Data Source:  kaggle.com


This application is for academic purposes only



Price and Volume
=======================================================================


Closing Prices and Volume

Instructions


Click on the icons within the "Index" key to customize which indexes are displayed on the graph


Draw a box to zoom in and see a shorter time frame

Row 
------------------------------------------------------------------------



```{r}
p1 <- ggplot(markets, aes(x = Date, y = CloseUSD, fill = Index)) +
  geom_bar(stat = "identity") + ggtitle("Closing Prices") +theme_classic() 

p1 <- ggplotly(p1)

p1_build <- plotly_build(p1)
p1_build$layout$height = 350
p1_build$layout$width = 350

p1_build
```

```{r}
# Volume 

p2 <- ggplot(markets, aes(x = Date, y = Volume, fill = Index)) +
  geom_bar(stat = "identity") + ggtitle("Volume") +theme_classic() 

p2 <- ggplotly(p2)

p2_build <- plotly_build(p2)
p2_build$layout$height = 350
p2_build$layout$width = 350

p2_build
```

Indexes
=======================================================================

The time frame is adjustable by dragging the "time window" from the left and right towards the center. This renders a closer view of each indexes' performance.



```{r}
# Swiss Market Index

# Candle colors
up <- list(line = list(color = "limegreen"))
down <- list(line = list(color = "red2"))

fig.ssmi <- ssmi %>% plot_ly(x = ~Date, type = "candlestick",
                             open = ~Open, close = ~ Adj.Close,
                             high = ~High, low = ~Low,
                             increasing = up, decreasing = down)
fig.ssmi <- fig.ssmi %>% layout(title = "Swiss Market Index, CHF Fr. (Zurich, Switzerland)")
fig.ssmi
```



Row 
------------------------------------------------------------------------


```{r}
# NASDAQ
up <- list(line = list(color = "limegreen"))
down <- list(line = list(color = "magenta"))

fig.ixic <- ixic %>% plot_ly(x = ~Date, type = "candlestick",
                             open = ~Open, close = ~ Adj.Close,
                             high = ~High, low = ~Low,
                             increasing = up, decreasing = down)
fig.ixic <- fig.ixic %>% layout(title = "NASDAQ Composite, USD (New York, USA)")
fig.ixic
``` 




Row 
------------------------------------------------------------------------


```{r}
# Shanghai
up <- list(line = list(color = "limegreen"))
down <- list(line = list(color = "red2"))

fig.ss <- ss.000001 %>% plot_ly(x = ~Date, type = "candlestick",
                             open = ~Open, close = ~ Adj.Close,
                             high = ~High, low = ~Low,
                             increasing = up, decreasing = down)
fig.ss <- fig.ss %>% layout(title = "Shanghai Component Index, CNY (Shanghai, China)")
fig.ss
```




Row 
------------------------------------------------------------------------


```{r}
# South Africa
up <- list(line = list(color = "limegreen"))
down <- list(line = list(color = "hotpink"))

fig.J203.JO <- J203.JO %>% plot_ly(x = ~Date, type = "candlestick",
                             open = ~Open, close = ~ Adj.Close,
                             high = ~High, low = ~Low,
                             increasing = up, decreasing = down)
fig.J203.JO <- fig.J203.JO %>% layout(title = "All Share Index, ZAR (Johanessburg, South Africa)")
fig.J203.JO
```




Row 
------------------------------------------------------------------------


```{r}
# India
up <- list(line = list(color = "limegreen"))
down <- list(line = list(color = "red"))

fig.nsei <- nsei %>% plot_ly(x = ~Date, type = "candlestick",
                             open = ~Open, close = ~ Adj.Close,
                             high = ~High, low = ~Low,
                             increasing = up, decreasing = down)
fig.nsei <- fig.nsei %>% layout(title = "Nifty 50 Index, INR (Mumbai, India)")
fig.nsei
```




Row 
------------------------------------------------------------------------


```{r}
# Europe (Paris)
up <- list(line = list(color = "limegreen"))
down <- list(line = list(color = "hotpink"))

fig.n100 <- n100 %>% plot_ly(x = ~Date, type = "candlestick",
                             open = ~Open, close = ~ Adj.Close,
                             high = ~High, low = ~Low,
                             increasing = up, decreasing = down)
fig.n100 <- fig.n100 %>% layout(title = "Euronext Index, EUR (Paris, France)")
fig.n100
```




Row 
------------------------------------------------------------------------


```{r}
# Hong Kong
up <- list(line = list(color = "limegreen"))
down <- list(line = list(color = "red2"))

fig.hsi <- hsi %>% plot_ly(x = ~Date, type = "candlestick",
                             open = ~Open, close = ~ Adj.Close,
                             high = ~High, low = ~Low,
                             increasing = up, decreasing = down)
fig.hsi <- fig.hsi %>% layout(title = "Hang Seng Index, HKD (Hong Kong)")
fig.hsi
```