R, the DJIA, and M1 Money Multiplier (MULT)

Description:

My explorations with the FRED (St Louis Financial Reserve Database) in R have yielded some interesting plots, charts and graphs. And some questions…

Charts with Explanations:

DJIxMULT-20090101-20110211
Yes, I know, the axes are a mess, and the site’s style sheet doesn’t play well with the chart image. I’ll look into that “pretty-ing up” stuff later. Also note that I have not set x-limits or y-limits on these graphs. Showing each time series to matching scale doesn’t show their correlation as well.
The blue line is the DJIA. The red line is the result of multiplying the M1 MULT ratio by the DJIA. Feel free to comment why this would be wrong, or bad finance theory, but I thought it would be an interesting investigative study to see what kind of information the dollar multiplier can add to a financial market time series.
Something odd’s going on… The DJI*MULT appears to be loosely correlative to the market until the “crash” of 2008. Afterwards, peaks are followed, but there’s a definite de-coupling. I look back in history:
DJIxMULT-20010101-20110101
Now this is from 20010101-20110101. See how the DJIA*MULT is above the DJIA before the 2009 crash? What’s going on there? Also note the effects of Quantitative Easing in late 2008, and QE2, and so on.
It appears we’re not improving as well as we thought. Historically, the DJIA * MULT provided a timeline above the DJIA (even when using the same y-scale). Now, all of a sudden, the M1 Multiplier has inverted to DJIA to show that while, yes, the DJIA is rising, the M1 Multiplier value is adjusting the DJIA’s “real” value in dollars, essentially showing that we’re improving, but nowhere near where it should be.

Summary:

I’m at a loss as to what the M1 Money Multiplier is doing to the market, but there’s clearly some funny business going on here. Would DJIA*MULT actually constitute as a health indicator for the DJIA? Could this be some sort of “real” indicator for how the market is truly doing?

Source Code in R:


   1: # DJI weighted against M1 dollar multiplier (MULT)
   2: # 
   3: # Author: Jerold Haas
   4: ###############################################################################
   5:  
   6: library("quantmod")
   7:  
   8: Range <- list(
   9:                 Start    = '2001-01-01',
  10:                 End        = '2011-01-01'
  11: )
  12:  
  13: # Get DJIA, SPY, and USD Multiplier (MULT)
  14: getSymbols(
  15:         c('SPY', '^DJI'),
  16:         from    = Range$Start,
  17:         to        = Range$End,
  18:         src        = 'yahoo'
  19: )
  20:  
  21: getSymbols(
  22:         c('MULT'),
  23:         from    = Range$Start,
  24:         to        = Range$End,
  25:         src        = 'FRED'
  26: )
  27:  
  28:  
  29: ###############################################################################
  30: # Calculations
  31: ###############################################################################
  32:  
  33: DJIxMULT <- reclass(DJI$DJI.Adjusted * MULT$MULT)
  34: names(DJIxMULT) <- c("Adjusted")
  35: Plot <- list(
  36:         Max    = max(DJIxMULT),
  37:         Min    = min(DJIxMULT)
  38: )
  39:  
  40:  
  41: ###############################################################################
  42: # Charting
  43: ###############################################################################
  44:  
  45: par(
  46:     bg            = "darkgrey",
  47:     col.axis    = "lightgrey",
  48:     col.lab        = "lightgrey",
  49:     col.main    = "lightgrey",
  50:     cex.axis    = "lightgrey",
  51:     fg            = "lightgrey"
  52:     )
  53:  
  54: plot(
  55:     DJIxMULT,
  56:     col            = "red",
  57:     main        = "",
  58:     xlab        = "",
  59:     ylab        = "",
  60:     xlim        = c(
  61:                     as.POSIXct(Range$Start),
  62:                     as.POSIXct(Range$End)
  63:                     ),
  64:     ylim        = c(
  65:                     Plot$Min,
  66:                     Plot$Max
  67:                     ),
  68:     major.ticks    = F,
  69:     minor.ticks    = F,
  70:     
  71: )
  72:  
  73: par( new=T ) #plot over last plot
  74:  
  75: plot.xts(
  76:     DJI$DJI.Adjusted,
  77:     auto.grid    = F,
  78:     col            = "blue",
  79:     main        = "DJI (Adjusted) & DJI (Adjusted) * MULT)",
  80:     xlab        = "",
  81:     ylab        = "",
  82:     xlim        = c(
  83:                     as.POSIXct(Range$Start),
  84:                     as.POSIXct(Range$End)
  85:                 ),
  86:     ylim        = c(
  87:                     Plot$Min,
  88:                     Plot$Max
  89:                 ),
  90:     major.ticks    = F,
  91:     minor.ticks    = F,
  92:     axes        = F
  93: )
  94:  
  95: #layout(1:6)
Code above is an R script relevant to article. Run in your favourite flavour of R.

Comments

Scott Yannitell said…
A decrease in the money multiplier should mean a decrease in "check book money" also known as bank credit. Money as we know it today all originates from debt, promises to repay a loan. This loan is usually a treasury bond. Since reserve requirements of banks have all but completely been done away with there are other forces at work that are causing money to increase in amounts. If you have more money in the the world today than yesterday it has to chase after the same resources. This will lead to price increases and one of these prices happens to be the stock market. More money == higher stock prices. Also conversely, and very importantly, less money == a stock market priced lower. When you understand that debt is money you can understand the real force of deflation which is the defaulting in mass of loans. The deflation of the 30s was a result of people taking out margins in the stock market that could not be paid in case of a small tremor in prices. The tremor became an avalanche because creditors, feeling less confident in the stock market began calling in margins. This meant that stocks had to be liquidated in mass which drove down prices leading to a death spiral that ended destroying over 70% of the value of the market in just a few weeks. The debts being defaulted on was what extinguished the money supply. No debt == no money. I wonder if someday people will wake up to the fact that the national debt can never be repaid. If it was, there would be no more money at all.
18 February 2011 at 21:50:00 GMT
Scott Yannitell said…
So something other than the multiplier is causing an increase in the supply of money. Just what exactly is quantitative easing really doing? "Printing money" is too simple. I don't think the answer will be complicated but in reality the fed does not print money, they furnish bank credit in check book money. The federal bureau of minting and engraving is who actually makes the cash. But the cannot do it without bank credit which is provided by the federal reserve a non governmental cartel of banks.
18 February 2011 at 21:55:00 GMT
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