An Investigation into the Causes of Stock Market Return Deviations from Real Earnings Yields
Austin Murphy (Oakland University), et al.
December 2024
This research demonstrates that the simple difference between the current earnings yield on the S&P500 and the long-term real TIPS yield has significant forecasting power for excess returns on that stock market index over both short-term and long-term investment horizons. For all time frames, deviations from that theoretical identity for the equity premium are positively related to current economic slack in the economy. Over annual horizons, those excess stock return deviations are negatively (positively) associated with recent inflation rates (money growth). Inflation is found to be positively (negatively) related to monetary policy restrictiveness (long-term real profit growth) in the future.

Taylor Rule Monetary Policy and Equity Market Risk Premia
Hui Guo (University of Cincinnati), et al.
October 2024
The Fed mainly uses the federal funds rate (FFR) to achieve its dual mandate of price stability and maximum employment. Recent asset pricing models argue that changes in FFR affect equity market risk premia. Consistent with this financial condition channel of monetary transmission, the Fed’s macroeconomic needs estimated using the Taylor (1993) rule negatively predict stock market returns. They are also identified as a crucial equity premium determinant along with the scaled market price and conditional market variance via variable selection analyses. The linear multifactor equity premium model has remarkably stable predictive power, outperforming machine learning and other prediction techniques.

Risk Factor, Risk Premium and Black-Litterman Model
Natasha Abou Rjaily (University Paris-Saclay, Amundi Asset Management), et al.
October 2024
Risk factor models are now widely used by fund managers to construct portfolios and assess both return and risk based on the behavior of common risk factors to which the portfolios are exposed. However, fund managers often have subjective views on these risk factors that they may wish to incorporate into their asset allocation strategies. This study introduces an extension of the Black-Litterman model that allows views to be applied to risk factors rather than individual assets, greatly simplifying the process since the number of factors is typically much smaller than the number of assets in a portfolio. The concept of risk premia is central to portfolio allocation, but is typically assessed at the asset level. In our framework, risk premia are formulated and analyzed at the factor level. This theoretical advance allows the manager to calculate factor risk premia, formulate views based on these premia, and incorporate them into the portfolio optimization process to create an adjusted portfolio that is consistent with the manager’s expectations. This new framework has many applications. It allows fund managers to analyze the market’s implied risk premia and identify the key drivers of market returns. In addition, the model facilitates comparisons between an actively managed portfolio and its benchmark by calculating how both are priced and identifying the factors that differentiate them.

US Equity Announcement Risk Premia
Lukas Petrasek and Jiri Kukack (Charles University)
October 2024
We analyze the announcement risk premia on the US market between September 1987 and March 2023 and find that the market index exhibits average excess returns of 8.3 bps for macroeconomic announcement days. This strongly contrasts with 1.4 bps returns for non-announcement days. We further measure the individual stocks’ sensitivities to macroeconomic data announcements over various lookback periods and show that stocks in the high-sensitivity portfolios offer investors significantly higher returns than stocks in the low-sensitivity portfolios. The average returns on the difference portfolios amount to 18 bps per month for the 60-month sensitivities. The Fama-MacBeth regression coefficients for the announcement sensitivity are positive and statistically significant across all lookback periods.

Risk Premiums in the Cryptocurrency Market
Guilda Akbari and Adelphe Ekponon (University of Ottawa)
December 2024
We examine the relationship between cryptocurrencies and the stock market to find out whether risk premiums exist in the cryptocurrency market. A double-sorted portfolio strategy that buys cryptocurrencies with the highest exposure to the stock market – high exposure to the market returns and low exposure to the market return volatility – and shorts cryptocurrencies with the lowest exposure to the stock market – low exposure to the market return and high exposure to the market return volatility – generates an excess return of 50% annually after surviving borrowing and trading costs. Exposure to the stock market using the principal component analysis of equity market returns and volatility produces monotonic returns and a long-short strategy return of more than 85% annually. We propose a reduced-form model that considers cryptocurrencies as levered assets on the equity market and provides evidence that investors have since 2018 employed coins in portfolio strategies which in turn have created a connection between the two markets.

A Historical Perspective on US Treasuries Risk Premia
Olivier Davanne (Risk Premium Invest)
July 2024
The uncontrolled growth of US public debt is causing some anxiety among investors in US Treasuries. It is therefore useful to estimate the current risk premia embedded in the US yield curve and assess the extent to which investors are pricing in potential future financing difficulties for the US government. In this paper, we provide both a theoretical and empirical explanation of the factors driving the US Treasuries yield curve and how it is possible to extract what market participants are currently pricing in. It is widely acknowledged that expectations about future US monetary policy play a crucial role in this market. However, there is a notable underestimation-even within academic literature-of the symmetrical role played by expectations regarding future risk premia. Through our original modeling of the US Treasuries yield curve, we document the history of these expected risk premia. Our findings indicate that from 2000 to 2022, investors consistently underestimated the strength of demand for US Treasuries, which may explain the somewhat unusual behavior of this key market during that period. Since 2022, however, a new paradigm has emerged. Demand for long-term US treasuries has declined due to the resurgence of inflation, while debt issuance has surged, driven by substantial deficits and the Federal Reserve’s Quantitative Tightening policies. Consequently, risk premia have increased sharply. The future remains highly uncertain as lower inflation could once again bolster demand for US Treasuries while public debt is expected to continue its rapid expansion. In this volatile environment, our model will help investors manage their positions by enabling real-time comparisons between their own expectations and the actual market pricing.

Long-Run Asset Returns
David Chambers (University of Cambridge), et al.
October 2024
The literature on long-run asset returns has continued to grow steadily, particularly since the start of the new millennium. We survey this expanding body of evidence on historical return premia across the major asset classes-stocks, bonds, and real assets-over the very long run. In addition, we discuss the benefits and pitfalls of these long-run data sets and make suggestions on best practice in compiling and using such data. We report the magnitude of these risk premia over the current and previous two centuries, and we compare estimates from alternative data compilers. We conclude by proposing some promising directions for future research.

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