Balance Sheet _ Federal Reserve

Velocity of M1 Money Stock (M1V)

• M1 is the money supply of currency in circulation (notes and coins, traveler’s checks [non-bank issuers], demand deposits, and checkable deposits).
• A decreasing velocity of M1 might indicate fewer short- term consumption transactions are taking place

Calculated as the ratio of quarterly nominal GDP (https://fred.stlouisfed.org/series/GDP) to the quarterly average of M1 money stock (https://fred.stlouisfed.org/series/M1SL).

• The velocity of money is the frequency at which one unit of currency is used to purchase domestically- produced goods and services within a given time period. In other words, it is the number of times one dollar is spent to buy goods and services per unit of time. If the velocity of money is increasing, then more transactions are occurring between individuals in an economy.

• The frequency of currency exchange can be used to determine the velocity of a given component of the money supply, providing some insight into whether consumers and businesses are saving or spending their money. There are several components of the money supply,: M1, M2, and MZM (M3 is no longer tracked by the Federal Reserve); these components are arranged on a spectrum of narrowest to broadest. Consider M1, the narrowest component. M1 is the money supply of currency in circulation (notes and coins, traveler’s checks [non-bank issuers], demand deposits, and checkable deposits). A decreasing velocity of M1 might indicate fewer short- term consumption transactions are taking place. We can think of shorter- term transactions as consumption we might make on an everyday basis.

• The broader M2 component includes M1 in addition to saving deposits, certificates of deposit (less than $100,000), and money market deposits for individuals. Comparing the velocities of M1 and M2 provides some insight into how quickly the economy is spending and how quickly it is saving. MZM (money with zero maturity) is the broadest component and consists of the supply of financial assets redeemable at par on demand: notes and coins in circulation, traveler’s checks (non-bank issuers), demand deposits, other checkable deposits, savings deposits, and all money market funds. The velocity of MZM helps determine how often financial assets are switching hands within the economy.

indicator <-fredr_series_observations(series_id = "M1V",
        observation_start = as.Date("2010-01-01")) 

# plotting data
indicator %>% ggplot() + geom_line(mapping = aes(x=date,y=value), 
                              color = "blue4",size=1) +
  labs(title = "Velocity of M1 Money Stock (M1V)", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
       x="Quarterly", y="Ratio",
       caption = "Data source: FRED St. Louis Federal Reserve\nIllustration by @JoeLongSanDiego")+
    theme_economist()

indicator%>%
    hchart( type = "column",hcaes(x = date, y = value)) %>% hc_colors("steelblue") %>%
    hc_subtitle(text=str_glue("from {min(indicator$date)} through {max(indicator$date)}"), align = "center") %>%
     hc_title(text = "Velocity of M1 Money Stock (M1V)",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Source: FRED Federal Reserve (CALEIH) _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Ratio")) %>%
   hc_add_theme(hc_theme_economist())

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Velocity of M2 Money Stock (M2V)

• The broader M2 component includes M1 in addition to saving deposits, certificates of deposit (less than $100,000), and money market deposits for individuals.
• Comparing the velocities of M1 and M2 provides some insight into how quickly the economy is spending and how quickly it is saving.

indicator <-fredr_series_observations(series_id = "M2V",
        observation_start = as.Date("2010-01-01")) 

# plotting data
indicator %>% ggplot() + geom_line(mapping = aes(x=date,y=value), 
                              color = "red4",size=1) +
  labs(title = "Velocity of M2 Money Stock (M2V)", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
       x="Quarterly", y="Ration",
       caption = "Data source: FRED St. Louis Federal Reserve\nIllustration by @JoeLongSanDiego")+
    theme_economist()

indicator%>%
    hchart( type = "column",hcaes(x = date, y = value)) %>% hc_colors("steelblue") %>%
    hc_subtitle(text=str_glue("from {min(indicator$date)} through {max(indicator$date)}"), align = "center") %>%
     hc_title(text = "Velocity of M2 Money Stock (M2V)",
             style = list(fontWeight = "bold", fontSize = "20px"),
             align = "center")  %>%
  hc_credits(enabled = TRUE,text = "Source: FRED Federal Reserve (CALEIH) _ Illustration by @JoeLongSanDiego") %>%
   hc_yAxis(title = list(text = "Ratio")) %>%
   hc_add_theme(hc_theme_economist())

Total Assets (Less Eliminations from Consolidation): Wednesday Level (WALCL)

indicator <-fredr_series_observations(series_id = "WALCL",
        observation_start = as.Date("2000-01-01")) 

# plotting data
indicator %>% ggplot() + geom_line(mapping = aes(x=date,y=value), 
                              color = "red3",size=.8) +
  labs(title = "Total Assets (Less Eliminations from Consolidation)", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
       x="Quarterly", y="Ratio",
       caption = "Data source: FRED Federal Reserve. Illustration by @JoeLongSanDiego")+
    theme_economist()

Assets: U.S. Treasury Securities: (WSHOBL)

indicator <-fredr_series_observations(series_id = "WSHOBL",
        observation_start = as.Date("2000-01-01")) 

# plotting data
indicator %>% ggplot() + geom_line(mapping = aes(x=date,y=value), 
                              color = "red3",size=.8) +
  labs(title = "U.S. Treasury Securities held by Federal Reserve", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
       x="Weekly", y="Millions of dollars",
       caption = "Data source: FRED Federal Reserve. Illustration by @JoeLongSanDiego")+
    theme_economist()

Assets: Securities Held Outright: Mortgage-Backed Securities: Week Average (WMBSEC)

indicator <-fredr_series_observations(series_id = "WMBSEC",
        observation_start = as.Date("2000-01-01")) 

# plotting data
indicator %>% ggplot() + geom_line(mapping = aes(x=date,y=value), 
                              color = "red3",size=.8) +
  labs(title = "Mortgage-Backed Securities held by Federal Reserve", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
       x="Weekly", y="Millions of dollars",
       caption = "Data source: FRED Federal Reserve. Illustration by @JoeLongSanDiego")+
    theme_economist()

University of Michigan: Consumer Sentiment (UMCSENT)

indicator <-fredr_series_observations(series_id = "UMCSENT",
        observation_start = as.Date("2000-01-01")) 

# plotting data
indicator %>% ggplot() + geom_line(mapping = aes(x=date,y=value), 
                              color = "blue3",size=.8) +
  labs(title = "University of Michigan: Consumer Sentiment (UMCSENT)", 
       subtitle = str_glue("from {min(indicator$date)} through {max(indicator$date)}"),
       x="Weekly", y="Millions of dollars",
       caption = "Data source: FRED Federal Reserve\nIllustration by @JoeLongSanDiego")+
    theme_economist()