The Factor Multiverse: The Role of Interest Rates in Factor Discovery
Jules H. van Binsbergen (University of Pennsylvania), et al.
We study the importance of the decline in interest rates in the discovery of asset pricing anomalies. We investigate 153 discovered anomalies as well as 1,395 potential undiscovered anomalies and find that absent the decline in interest rates, the asset pricing literature would likely entertain a different set of anomalies today. As the decline in interest rates is not continuing, a reevaluation of relevant anomalies going forward is warranted. To this end, we use a duration-based interest rate adjustment procedure to classify anomalies into false positives, false negatives, and those robust to the effect of interest rates. Our analysis highlights the sensitivity of the factor discovery process to this specific observed economic time period.
Can the Fed Control Inflation? Stock Market Implications
Daniel Andrei (McGill U.) and Michael Hasler (U. of Texas at Dallas)
This paper investigates how the stock market reacts to the Federal Reserve’s ability to tame inflation through rate hikes. Since investors do not directly observe the speed at which rate hikes reduce inflation, they need to learn about it by observing inflation prints. When investors realize that the Federal Reserve loses control of inflation, the market risk premium and volatility spike. Furthermore when the Federal Reserve hikes interest rates following high inflation prints, the stock market crashes, and both the market risk premium and volatility surge. We test these theoretical predictions and show that they find strong empirical support.
The Term Structure of Interest Rates as Predictor of Stock Market Volatility
Anastasios Megaritis (Keele Business School), et al.
We examine the forecasting power of the volatility of the slope of the US-Treasury yield curve on US stock-market volatility. Consistent with theoretical asset pricing models, we find that the volatility of the slope of the term structure of interest rates has significant forecasting power on stock market volatility for forecasting horizon ranging from one up to twelve months. Moreover, the term structure volatility has significant forecasting power when used for volatility predictions of the intra-day returns of S&P500 constituents, with the predictive power being higher for stocks belonging to the telecommunications and financial sector. Our forecasting models show that the forecasting power of yield curve volatility is higher to and absorbs that of Economic Policy Uncertainty and Monetary Policy Uncertainty, showing that the main channel through which the yield curve volatility affects the stock market is not only related with uncertainty about monetary policy actions or policy rates, but also with uncertainty regarding the future cash flows and dividend payments of US equities. Lastly, we show that the forecasting power of term structure volatility significantly increases during the post-2007 Great recession period which coincides with the Fed adopting unconventional monetary policies to stimulate the economy.
Inflation, Market Failures, and Algorithms
Rory Van Loo (Boston University)
Inflation is a problem of tremendous scale. But inflation itself is unlikely to cause the greatest economic harm during inflationary periods. Instead, a more likely source of devastation will be policymakers’ response to inflation. Their main anti-inflation tools, most notably increasing interest rates, increase unemployment and the risk of recessions. This Article argues that there is a better approach. Rather than defaulting to interest rate hikes that harm markets, policy makers should prioritize laws that lower prices while improving markets. For decades, businesses have raised prices by manipulating consumers, exercising monopoly power, and lobbying for laws that block competition. Automated pricing algorithms have further enhanced businesses’ ability to charge higher prices. Although those past market failures did not cause the currently high levels of inflation, they create new challenges and opportunities. Most importantly, they now provide an inflation-fighting tool that would not otherwise exist—like a piggy bank of market improvements that the law can break open to offset some portion of inflation. Interest rate hikes would surely still be needed, but to a lesser extent. Many of these market improvement opportunities lie in existing administrative agency authority, while more could be done through new legislation, such as a universal price transparency statute. Moreover, these legal reforms are desirable independent of inflation because they would improve efficiency, expand total wealth, and reduce inequality. Thus, policymakers should resist the urge to rely too extensively on interest rate hikes that bring impoverishment and should instead pursue legal rules that promote prosperity. Doing so could transform a grave crisis into a tremendous economic opportunity.
The Fear Economy: A Theory of Output, Interest, and Safe Assets
Ruchir Agarwal (International Monetary Fund)
This paper presents a fear theory of the economy, based on the interplay between fear of rare disasters and the interest rate on safe assets. To do this, I study the macroeconomic consequences of government-administered interest rates in the neoclassical real business cycle model. When the government has the power to fix the safe real interest rate, the gap between the `sticky real safe rate’ and the `neutral rate’ can generate far-reaching aggregate distortions. When fear exogenously rises, the demand for safe assets rise and the neutral rate falls. If the central bank does not lower the safe rate by the same amount, savings rise leading to a decline in consumption and aggregate demand. The same mechanism works in reverse, when fear falls. Quantitatively, I show that a single fear factor can simultaneously (i) generate cross-correlations in output, labor, consumption, and investment consistent with the postwar US economy; and (ii) generates variation in equity prices, bond prices, and a large risk premium in line with the asset pricing data. Six novel insights emerge from the model: (1) actively regulating the safe interest rate (in both directions) can mitigate the fluctuations generated by fear cycles; (2) recessions will be deeper and longer when central banks accept the zero lower bound and are unwilling to use negative rates; (3) a commitment to use negative rates in recessions—even if never implemented—raises both the short- and long-run real neutral rates, and moderates the business cycle; (4) counter-cyclical fiscal policy can act as disaster insurance and be expansionary by reducing fear; (5) quantitative easing can be narrowly effective only when fear is high at the lower bound; and (6) when fear is high, especially at the lower bound, policies that boost productivity also help fight recessions.
Learn To Use R For Portfolio Analysis
Quantitative Investment Portfolio Analytics In R:
An Introduction To R For Modeling Portfolio Risk and Return
By James Picerno