2020 Economy with COVID Pandemic

General trends

University of Michigan Consumer Sentiment UMCSENT

senti <- 
  "UMCSENT" %>% 
  tq_get(get = "economic.data", from = "2019-06-01") %>%
  rename(count = price) 

  senti %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "firebrick4",size=.8) + 
    labs(
      x = "",
      y = "",
      title = "Consumer Sentiment Index per University of Michigan",
      subtitle = str_glue("Weekly from {min(senti$date)} through {max(senti$date)}")
    ) +
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

General trends

Effective Federal Funds Rate (FEDFUNDS)

fedrate <- 
  "FEDFUNDS" %>% 
  tq_get(get = "economic.data", from = "2010-06-01") %>%
  rename(count = price) 

  fedrate %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "dodgerblue4",size=.8) + 
    labs(
      x = "",
      y = "",
      title = "Effective Federal Funds Rate (FEDFUNDS)",
      subtitle = str_glue("Monthly from {min(fedrate$date)} through {max(fedrate$date)}")
    ) +
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

General trends

All Employees: Total Nonfarm in California (CANAN)

labor <- 
  "CANAN" %>% 
  tq_get(get = "economic.data", from = "2018-06-01") %>%
  rename(count = price) 

  labor %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "goldenrod4",size=.8) + 
    labs(
      x = "",
      y = "",
      title = "All Employees: Total Nonfarm in California (CANAN)",
      subtitle = str_glue("Monthly from {min(labor$date)} through {max(labor$date)}")
    ) +
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

Total Vehicle Sales (TOTALSA)

car <- 
  "TOTALSA" %>% 
  tq_get(get = "economic.data", from = "2019-06-01") %>%
  rename(count = price) 

  car %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "deeppink1",size=.8) + 
    labs(
      x = "",
      y = "",
      title = "Total Vehicle Sales",
      subtitle = str_glue("Monthly from {min(car$date)} through {max(car$date)}")
    ) +
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

Consumer Automobile Loans (CARACBW027SBOG)

carloan <- 
  "CARACBW027SBOG" %>% 
  tq_get(get = "economic.data", from = "2019-06-01") %>%
  rename(count = price) 

  carloan %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "dodgerblue1",size=.8) + 
    labs(
      x = "",
      y = "",
      title = "Consumer Loans _ Car Loans",
      subtitle = str_glue("Monthly from {min(carloan$date)} through {max(carloan$date)}")
    ) +
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

Crude Oil Prices: West Texas Intermediate (WTI) - Cushing, Oklahoma (DCOILWTICO)

oil <- 
  "DCOILWTICO" %>% 
  tq_get(get = "economic.data", from = "2019-06-01") %>%
  rename(count = price) 

  oil %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "dodgerblue4",size=.8) + 
    labs(
      x = "",
      y = "",
      title = " Crude Oil Prices: West Texas Intermediate (WTI)",
      subtitle = str_glue("Monthly from {min(oil$date)} through {max(oil$date)}")
    ) +
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

New Single Family Residence Sold: United States = HSN1F

housing <- 
  "HSN1F" %>% 
  tq_get(get = "economic.data", from = "2018-06-01") %>%
  rename(count = price) 

  housing %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "blue2",size=.8) + 
    labs(
      x = "",
      y = "",
      title = "Sales of New Single Family Residence units",
      subtitle = str_glue("From {min(housing$date)} through {max(housing$date)}")
    ) +
    theme_minimal() +
    scale_y_continuous(labels = scales::comma)+
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

New Private Housing Units Authorized by Building Permits (PERMIT)

Indicator for builders’ sentiment.

permit <- 
  "PERMIT" %>% 
  tq_get(get = "economic.data", from = "2018-06-01") %>%
  rename(count = price) 

  permit %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "blue4",size=.8) + 
    labs(
      x = "",
      y = "",
      title = "Building permits for residential units",
      subtitle = str_glue("From {min(permit$date)} through {max(permit$date)}")
    ) +
    theme_minimal() +
    scale_y_continuous(labels = scales::comma)+
    theme(plot.title = element_text(color="blue", size=14, face="bold"))

Existing Home Sales (EXHOSLUSM495S)

sfr <- 
  "EXHOSLUSM495S" %>% 
  tq_get(get = "economic.data", from = "2019-06-01") %>%
  rename(count = price) 

  sfr %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "003366",size=.8) + 
    labs(
      x = "",
      y = "",
      title = "Existing Home Sales _ Nationwide",
      subtitle = str_glue("From {min(sfr$date)} through {max(sfr$date)}")
    ) +
  
     theme(plot.title = element_text(color="blue", size=14, face="bold"))

## Construction commodity : Lumber ## Producer Price Index by Commodity for Lumber and Wood Products: Plywood (WPU083)

lumber <- 
  "WPU083" %>% 
  tq_get(get = "economic.data", from = "2010-06-01") %>%
  rename(count = price) 

  lumber %>% 
    ggplot(aes(x = date, y = count)) +
    geom_line(color = "maroon",size=.8) + 
    labs(
      x = "",
      y = "",
      title = "Producer Price Index for Plywood",
      subtitle = str_glue("From {min(lumber$date)} through {max(lumber$date)}")
    ) +
  
     theme(plot.title = element_text(color="blue", size=14, face="bold"))