---
title: "Dashboard Lab"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    social: menu
    source: embed
    html_document:
    df_print: paged
    pdf_document: default
---

# Table of Contents {.sidebar}

* Introduction
  
* Background Information                          
  
* Stock Performance Analysis

* Summary and Conclusion

# **Introduction**

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-------------------------------------
    
### **Introduction in Dashboarding** 
In today's fast-paced world, decision-makers are expected to analyze a massive amount of data on a daily basis. The sheer volume of information can be overwhelming, making it challenging to find the key insights necessary to make informed decisions. That's where information dashboards come in.

An information dashboard is an essential tool used by businesses, organizations, and individuals to gather, visualize, and analyze key data in a centralized location. The dashboard acts as a hub, providing users with an at-a-glance view of critical metrics and KPIs, allowing them to quickly identify trends, patterns, and anomalies. This enables faster decision-making, reduces the risk of errors and misinterpretation, and ultimately increases efficiency and productivity.

Dashboards can be customized to meet the specific needs of an organization or individual, providing a tailor-made solution that addresses specific concerns and challenges. Furthermore, dashboards can be configured to pull data from various sources, including spreadsheets, databases, and web applications, providing users with a comprehensive view of their data.

Another crucial benefit of information dashboards is that they enable collaboration and communication across teams and departments. By providing a centralized platform for data analysis, stakeholders can quickly and easily share insights and discuss findings, fostering a more collaborative work environment.

Information dashboards are a critical tool for businesses, organizations, and individuals seeking to manage data effectively, make informed decisions, and improve efficiency and productivity. By providing a centralized platform for data analysis, dashboards simplify the process of data gathering and analysis, allowing users to focus on the insights that matter most.

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### **Aims and Purposes** 

The purpose of this laboratory is to equip with the skills necessary to plan, design, and create an information dashboard that can be used to support quantitative decision-making. In order to achieve this objective, there is a need to work through a series of steps, including defining the necessary decision, identifying relevant information, collecting and summarizing data, designing effective visualizations, and organizing those visualizations in a way that conforms to dashboarding theory. Ultimately, the goal of the laboratory is to prepare to effectively communicate complex data to decision-makers in a clear, concise, and impactful manner.

### **Selected Companies**

In this lab, the objective is to analyze investment opportunities for an organization by strategically purchasing securities or commodities to maximize short-term profits. I will be considering investments in four well-known companies: HCA Healthcare, Inc (HCA), AmerisourceBergen Corporation (ABC), Humana Inc. (HUM),UnitedHealth Group Incorporated (UNH). My aim is to determine which one of these four financial instruments will yield the most substantial short-term gains, using my research and analytical skills to assess their potential performance in the market.

# **Background Information**

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-------------------------

### **Variables**

+ `r kableExtra::text_spec("**Market Cap**", color = "#5c5c5c")` - represents the total value of a company's outstanding shares in the stock market. It is calculated by multiplying the company's current stock price by the total number of its outstanding shares, providing investors with an essential measure to evaluate a company's size and growth potential.
+ `r kableExtra::text_spec("**D/Y Ratio**", color = "#5c5c5c")` - The dividend yield ratio is a financial metric that indicates the percentage of a company's annual dividend payments relative to its stock price. This ratio helps investors assess the income generated from their investments, as a higher dividend yield ratio typically signifies a more attractive investment opportunity for income-seeking investors.
+ `r kableExtra::text_spec("**P/E Ratio**", color = "#5c5c5c")` - The price-to-earnings ratio, is a valuation metric that compares a company's current share price to its earnings per share (EPS). It serves as an indicator of how much investors are willing to pay for each dollar of earnings, and it is commonly used to assess whether a stock is overvalued or undervalued relative to its peers or historical averages.
+ `r kableExtra::text_spec("**EPS**", color = "#5c5c5c")` - Earnings Per Share is a financial metric that measures the portion of a company's profit allocated to each outstanding share of its common stock. It is an essential indicator of a company's financial health, as it helps investors evaluate the profitability of a company and its potential for future growth.


### **Data Collected**

```{r}
library(plyr)
library(dplyr)
library(xts)
library(zoo)
library(quantmod)
library(tidyquant)
library(DT)
library(broom)
library(ggplot2)
library(viridisLite)
library(highcharter)
what_metrics <- yahooQF(c("Price/Sales", 
                          "P/E Ratio",
                          "Price/EPS Estimate Next Year",
                          "PEG Ratio",
                          "Dividend Yield", 
                          "Market Capitalization"))
tickers <- c("HCA", "ABC", "HUM", "UNH")
metrics <- getQuote(paste(tickers, sep = ",", collapse = ";"), what = what_metrics)
metrics <- data.frame(Symbol = tickers, metrics[,2:length(metrics)])
colnames(metrics) <- c("Symbol", "P/E Ratio", "EPS", "D/Y Ratio", "Market Cap")
DT::datatable(metrics)

```

## Column {data-height=650 .tabset .tabset-fade}

### Daily Trend of Stock Prices {data-width=500}

```{r}
start <- as.Date("2022-01-01") 
end <- as.Date("2022-12-31")

getSymbols(tickers, src = "yahoo", from = start, to = end)
stocks = as.xts(data.frame(A = HCA[, "HCA.Adjusted"], 
B = ABC[, "ABC.Adjusted"], C = HUM[, "HUM.Adjusted"], 
E = UNH[,"UNH.Adjusted"]))
```


``` {r}
names(stocks) <- c("HCA", "ABC", "HUM", "UNH")
index(stocks) <- as.Date(index(stocks))

stocks_series <- tidy(stocks) %>% 
  
  ggplot(aes(x=index,y=value, color=series)) +
  labs(title = "Daily Stock Adjusted Prices Comparison for 2022 year",
       
       subtitle = "HCA Healthcare, AmerisourceBergen Corporation, Humana ,UnitedHealth Group Incorporated",
       caption = " Source: Yahoo Finance",
       color = "Stock",
       x = "Date",
       y = "End of day Adjusted Price ($)") +
  scale_color_manual(values = c("Red", "Green", "DarkBlue","Orange"))+
  geom_line()

stocks_series
```

### Facet Charts {data-width=500}

```{r}
stocks_series2 = tidy(stocks) %>% 
  
  ggplot(aes(x=index,y=value, color=series)) + 
  geom_line() +
  facet_grid(series~.,scales = "free") + 
  labs(title = "Daily Stock Adjusted Prices Comparison for 2022 year",
       
       subtitle = "HCA Healthcare, AmerisourceBergen Corporation, Humana ,UnitedHealth Group Incorporated",
       caption = " Source: Yahoo Finance",
       color = "Stock",
       x = "Date",
       y = "End of day Adjusted Price ($)") +
  scale_color_manual(values = c("Red", "Green", "DarkBlue","Orange"))
stocks_series2
```

# **Stock Performance Analysis**

## Column {data-height=1200 .tabset .tabset-fade}

``` {r}
library(tidyverse)
library(tidyquant)
library(dygraphs)
library(xts)
options("getSymbols.yahoo.warning"=FALSE)
options("getSymbols.warning4.0"=FALSE)
```

### HCA {data-width=1200}

``` {r}
stocks1 = as.xts(data.frame(A = HCA[, "HCA.Open"], 
B = HCA[, "HCA.High"], C = HCA[, "HCA.Low"], 
E = HCA[,"HCA.Close"]))
data(stocks1)
m <- tail(stocks1, n = 365)
dygraph(m) %>%
  dyCandlestick()
```

### ABC {data-width=1200}

``` {r}
stocks2 = as.xts(data.frame(A = ABC[, "ABC.Open"], 
B = ABC[, "ABC.High"], C = ABC[, "ABC.Low"], 
E = ABC[,"ABC.Close"]))
data(stocks2)
m <- tail(stocks2, n = 365)
dygraph(m) %>%
  dyCandlestick()
```

### HUM {data-width=1200}

``` {r}
stocks3 = as.xts(data.frame(A = HUM[, "HUM.Open"], 
B = HUM[, "HUM.High"], C = HUM[, "HUM.Low"], 
E = HUM[,"HUM.Close"]))
data(stocks3)
m <- tail(stocks3, n = 365)
dygraph(m) %>%
  dyCandlestick()
```

### UNH {data-width=1200}

``` {r}
stocks4 = as.xts(data.frame(A = UNH[, "UNH.Open"], 
B = UNH[, "UNH.High"], C = UNH[, "UNH.Low"], 
E = UNH[,"UNH.Close"]))
data(stocks4)
m <- tail(stocks4, n = 365)
dygraph(m) %>%
  dyCandlestick()
```

# **Summary and Conclusion**

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-------------------------

### **Data Analysis**
The analysis of the key selected indicators for the four stocks analyzed yield the following results:

+ `r kableExtra::text_spec("**Market Cap**", color = "#5c5c5c")` - The highest market cap is demonstrated by UNH, followed by HCA, HUM and, finally, ABC. This mean that based on the market capitalization, UNH is the best choice to invest. 
+ `r kableExtra::text_spec("**D/Y Ratio**", color = "#5c5c5c")` - The highest D/Y ratio is in UNH, followed by ABC, HCA, and HUM. Therefore, high dividend yield of UNH makes it good for investors to collect dividend payments. 
+ `r kableExtra::text_spec("**P/E Ratio**", color = "#5c5c5c")` - The highest P/E ratio is again in UNH, followed by HUM, ABC, and HCA. From the perspective of this ratio, the investors may expect higher earnings growth if invest in UNH.
+ `r kableExtra::text_spec("**EPS**", color = "#5c5c5c")` - The highest EPS is in UNH, followed by HUM, HCA, and ABC. From this perspective, the company makes the highest amount for each share.

Summing the above, it seems that United Health Group Incorporated is the best choice to invest based on the key financial indicators.


### **Analysis of Trends**
The analysis of stock price trends during 2022 year indicates the following:

+ `r kableExtra::text_spec("**HCA**", color = "#5c5c5c")` stock exhibits a growing trend, since the middle of the summer. However ,there were two considerable decreases in autumn, but the price quickly grew after each fall.

+ `r kableExtra::text_spec("**ABC**", color = "#5c5c5c")` stock price is growing since October, where the price found its local minimum.

+ `r kableExtra::text_spec("**HUM**", color = "#5c5c5c")` stock reached its peak in November, after that the price has fallen to the level of the end of October. However, the trend is still positive.

+ `r kableExtra::text_spec("**UNH**", color = "#5c5c5c")` stock has grown considerably in the beginning of the summer, and then started to decline in autumn, falling to its minimum in the end of October. Still, the stock demonstrates the upward trend.

Together with the mentioned analysis of key indicators, it is suggested to invest in UNH.