Interest Rates

Introduction

In this chapter we discuss a fundamental area of macroeconomics: interest rates. In particular, we want to explore the relationship between interest rates and economic and market conditions. We also introduce a few key skills which are quite handy for macroeconomic data: creating, exploring and analyzing different time series based features like lags and rolling calculations.

Exploring, investigating and identifying the lag or rolling effects of macroeconomic features goes beyond interest rates and the workflows we establish in this chapter have broad applicability,in economics and in general financial analytics.

The structure of this chapter is as follows: We start with a brief summary of interest rates and Treasury debt instruments (or Treasuries) and their importance for markets and the economy. We then import and visualize data on Treasuries. Next we create different time-based features based on our imported Treasury data and explore relationships with the economy and market returns.

On Interest Rates

The one line explanation of interest rates is that they are the price of money. The longer explanation is that interest rates are the price that borrowers (or debtors) must pay lenders (or creditors) for access to capital today in exchange for a promise to repay that capital in the future. Interest rates are a function of supply and demand from creditors and debtors, overall economic conditions, future expectations, inflation and central bank actions. Interest rates have been called both the price of money and the price of time, and also the most important price in the world.1

Ray Dalio, the founder of Bridgewater Capital, ascribes the following causal connection between interest rates (the cost of credit) and recessions:

“Recessions occur when central banks raise the cost of credit… recessions end when central banks lower interest rates.”2

Mr. Dalio’s statement might be too absolute for some of us, but at the least we believe there is consensus that interest rates are a crucial factor in determining the strength of the economy. Another of our favorite market thinkers Howard Marks ascribes much of the stupendous performance of the stock market between 1980 and 2021 to the fact that this period was marked by low and declining interest rates. In one of his investment letters titled “Sea Change”, he listed some of the effects of low interest rates way.3

  1. Accelerate the growth of the economy by making it cheaper for consumers to buy on credit and for companies to invest
  2. Provide a subsidy to borrowers (at the expense of lenders and savers)
  3. Increase the fair value of assets…as interest rates fall, valuation parameters such as p/e ratios and enterprise values rise, and cap rates on real estate decline
  4. Create a “wealth effect” that makes people feel richer and thus more willing to spend
  5. Produce a bonanza for those who buy assets using leverage

Mr. Marks further foresees a “Sea Change” that started in 2022 and will characterize a different interest rate and inflation environment. He opines, “Inflation and interest rates are highly likely to remain the dominant considerations influencing the investment environment for the next several years.”4

We could continue quoting others on the importance of interest rates, but suffice it to say they are very important to the economy and financial markets.

A salient feature of interest rates is that there is not one interest rate but rather many. There are different types of credit according to the type of borrower and thus we can categorize interest rates according to the type of borrower:

  • Treasury rates, sometimes called the risk-free rate, when the Federal Government is the borrower.
  • Corporate bond rates or commercial bank loan rates when businesses are the borrowers.
  • Credit card interest rates, mortgage rates and auto loan rates when consumers are the borrowers.

The largest borrower in the U.S. is the federal government, which pays interest on its debt in the form of interest on Treasury securities, called as such because they are issued by the U.S. Department of the Treasury.

Federal debt has grown significantly in recent years outpacing corporate and consumer debt. Let’s pull these three types of debt from FRED and examine them. We can use the get_data_fred() function to pull multiple series at the same time by passing a list with the mnemonics we need, the result from such a request is a wide dataframe where each series is in a different column.

debt_table = (
    pdr.get_data_fred(["GFDEBTN", "TBSDODNS", "HCCSDODNS"],
                     start = '1979-01-01')
        .reset_index()
        .rename(columns = {'DATE': 'date',
                          'GFDEBTN': 'Federal', 
                          'TBSDODNS': 'Corporate',
                          'HCCSDODNS': 'Consumer'})
)
        date   Federal  Corporate  Consumer
0 1979-01-01  796792.0   1224.876   322.611
1 1979-04-01  804913.0   1269.922   333.789
2 1979-07-01  826519.0   1312.240   345.271
3 1979-10-01  845116.0   1346.999   354.616
4 1980-01-01  863451.0   1386.800   359.093

How are interest rates set?

Treasury Instruments

Data Import and Visualization

Monthly Rates and Returns

Interest Rates and Market Returns

Adding Lags

Rolling Features

Putting GDP, Market Data and Treasury Rates Together

Exploring relationships

Rolling correlation

Interest Rate Use Case

Yield curve and recessions

Term spread and market returns

Dr. Copper

The CAPE and Interest Rates

Conclusion

Footnotes

  1. See The Price of Time, by Edward Chancellor for more background on interest rates in general throughout history.↩︎

  2. https://media.economist.com/sites/default/files/pdfs/A_Template_for_Understanding_-_Ray_Dalio__Bridgewater.pdf↩︎

  3. https://www.oaktreecapital.com/insights/memo/sea-change↩︎

  4. https://www.oaktreecapital.com/insights/memo/sea-change↩︎