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Standard applications of the consumption-based asset pricing model assume that goods and services within the nondurable consumption bundle are substitutes. We estimate substitution elasticities between different consumption bundles and show that households cannot substitute energy consumption by consumption of other nondurables. As a consequence, energy consumption affects the pricing function as a separate factor. Variation in energy consumption betas explains a large part of the premia related to value, investment, and operating profitability. For example, value stocks are typically more energy-intensive than growth stocks and thus riskier, since they suffer more from the oil supply shocks that also affect households.
We study the design features of disclosure regulations that seek to trigger the green transition of the global economy and ask whether such regulatory interventions are likely to bring about sufficient market discipline to achieve socially optimal climate targets.
We categorize the transparency obligations stipulated in green finance regulation as either compelling the standardized disclosure of raw data, or providing quality labels that signal desirable green characteristics of investment products based on a uniform methodology. Both categories of transparency requirements can be imposed at activity, issuer, and portfolio level.
Finance theory and empirical evidence suggest that investors may prefer “green” over “dirty” assets for both financial and non-financial reasons and may thus demand higher returns from environmentally-harmful investment opportunities. However, the market discipline that this negative cost of capital effect exerts on “dirty” issuers is potentially attenuated by countervailing investor interests and does not automatically lead to socially optimal outcomes.
Mandatory disclosure obligations and their (public) enforcement can play an important role in green finance strategies. They prevent an underproduction of the standardized high-quality information that investors need in order to allocate capital according to their preferences. However, the rationale behind regulatory intervention is not equally strong for all categories and all levels of “green” disclosure obligations. Corporate governance problems and other agency conflicts in intermediated investment chains do not represent a categorical impediment for green finance strategies.
However, the many forces that may prevent markets from achieving socially optimal equilibria render disclosure-centered green finance legislation a second best to more direct forms of regulatory intervention like global carbon taxation and emissions trading schemes. Inherently transnational market-based green finance concepts can play a supporting role in sustainable transition, which is particularly important as long as first-best solutions remain politically unavailable.
Using the pandemic as a laboratory, we show that asset markets assign a time- varying price to firms' disaster risk exposure. In 2020 the cross-section of realized and expected stock returns reflected firms' different exposure to the pandemic, as measured by their vulnerability to social distancing. Realized and expected return differentials initially widened and then narrowed, but disaster exposure still commanded a risk premium in December 2020. When inferred from market outcomes, resilience correlates not only with social distancing, but also with cash and environmental ratings. However, vulnerability to social distancing is the only characteristic that identifies persistently scarred firms.
We introduce Implied Volatility Duration (IVD) as a new measure for the timing of uncertainty resolution, with a high IVD corresponding to late resolution. Portfolio sorts on a large cross-section of stocks indicate that investors demand on average about seven percent return per year as a compensation for a late resolution of uncertainty. In a general equilibrium model, we show that `late' stocks can only have higher expected returns than `early' stocks if the investor exhibits a preference for early resolution of uncertainty. Our empirical analysis thus provides a purely market-based assessment of the timing preferences of the marginal investor.
The long-run consumption risk model provides a theoretically appealing explanation for prominent asset pricing puzzles, but its intricate structure presents a challenge for econometric analysis. This paper proposes a two-step indirect inference approach that disentangles the estimation of the model's macro-economic dynamics and the investor's preference parameters. A Monte Carlo study explores the feasibility and efficiency of the estimation strategy. We apply the method to recent U.S.\data and provide a critical re-assessment of the long-run risk model's ability to reconcile the real economy and financial markets. This two-step indirect inference approach is potentially useful for the econometric analysis of other prominent consumption-based asset pricing models that are equally difficult to estimate.
The long-run consumption risk model provides a theoretically appealing explanation for prominent asset pricing puzzles, but its intricate structure presents a challenge for econometric analysis. This paper proposes a two-step indirect inference approach that disentangles the estimation of the model's macroeconomic dynamics and the investor's preference parameters. A Monte Carlo study explores the feasibility and efficiency of the estimation strategy. We apply the method to recent U.S. data and provide a critical re-assessment of the long-run risk model's ability to reconcile the real economy and financial markets. This two-step indirect inference approach is potentially useful for the econometric analysis of other prominent consumption-based asset pricing models that are equally difficult to estimate.
After the Lehman-Brothers collapse, the stock index has exceeded its pre-Lehman-Brothers peak by 36% in real terms. Seemingly, markets have been demanding more stocks instead of bonds. Yet, instead of observing higher bond rates, paradoxically, bond rates have been persistently negative after the Lehman-Brothers collapse. To explain this paradox, we suggest that, in the post-Lehman-Brothers period, investors changed their perceptions on disasters, thinking that disasters occur once every 30 years on average, instead of disasters occurring once every 60 years. In our asset-pricing calibration exercise, this rise in perceived market fragility alone can explain the drop in both bond rates and price-dividend ratios observed after the Lehman-Brothers collapse, which indicates that markets mostly demanded bonds instead of stocks.
Financial market interactions can lead to large and persistent booms and recessions. Instability is an inherent threat to economies with speculative financial markets. A central bank’s interest rate setting can amplify the expectation feedback in the financial market and this can lead to unstable dynamics and excess volatility. The paper suggests that policy institutions may be well-advised to handle tools like asset price targeting with care since such instruments might add a structural link between asset prices and macroeconomic aggregates. Neither stock prices nor indices are a good indicator to base decisions on.
We propose a 2-country asset-pricing model where agents' preferences change endogenously as a function of the popularity of internationally traded goods. We determine the effect of the time-variation of preferences on equity markets, consumption and portfolio choices. When agents are more sensitive to the popularity of domestic consumption goods, the local stock market reacts more strongly to the preferences of local agents than to the preferences of foreign agents. Therefore, home bias arises because home-country stock represents a better investment opportunity for hedging against future fluctuations in preferences. We test our model and find that preference evolution is a plausible driver of key macroeconomic variables and stock returns.
Demographic change belongs to the mega-trends of the 20th and the 21st century. The ongoing aging process in major industrialized countries gives rise to the relative scarcity of raw labor and the relative abundance of physical capital. Standard macroeconomic models suggest that this depresses asset returns and increases wages which, in turn, provides incentives for more human capital accumulation. This thesis quantifies the macroeconomic effects of demographic change and reveals the importance of human capital adjustments for price and welfare effects within and across generations. Chapter 1 investigates the distributions of income, skills, and welfare in the German economy along the inter- and the intra-generational dimension. It shows that demographic change leads to a more capital- and skill-intensive economy and that high-school households loose compared to college households in terms of welfare. Chapter 2 disentangles the effect of demographic change on returns to risk-free and risky assets in the U.S. and measures the net effect on the equity premium. It shows that both returns decline while the equity premium increases slightly. Endogenous human capital adjustments are crucial for relatively small effects. Chapter 3 develops a method for computing transitional dynamics in heterogeneous agent models with aggregate risk if these transitions are induced by exogenous deterministic dynamics such as demographic change. The application of the method to a simple illustrative example shows a large reduction in total computing time while approximation errors are small.
We study consumption-portfolio and asset pricing frameworks with recursive preferences and unspanned risk. We show that in both cases, portfolio choice and asset pricing, the value function of the investor/ representative agent can be characterized by a specific semilinear partial differential equation. To date, the solution to this equation has mostly been approximated by Campbell-Shiller techniques, without addressing general issues of existence and uniqueness. We develop a novel approach that rigorously constructs the solution by a fixed point argument. We prove that under regularity conditions a solution exists and establish a fast and accurate numerical method to solve consumption-portfolio and asset pricing problems with recursive preferences and unspanned risk. Our setting is not restricted to affine asset price dynamics. Numerical examples illustrate our approach.
Consumption-based asset pricing with rare disaster risk : a simulated method of moments approach
(2014)
The rare disaster hypothesis suggests that the extraordinarily high postwar U.S. equity premium resulted because investors ex ante demanded compensation for unlikely but calamitous risks that they happened not to incur. Although convincing in theory, empirical tests of the rare disaster explanation are scarce. We estimate a disaster-including consumption-based asset pricing model (CBM) using a combination of the simulated method of moments and bootstrapping. We consider several methodological alternatives that differ in the moment matches and the way to account for disasters in the simulated consumption growth and return series. Whichever specification is used, the estimated preference parameters are of an economically plausible size, and the estimation precision is much higher than in previous studies that use the canonical CBM. Our results thus provide empirical support for the rare disaster hypothesis, and help reconcile the nexus between real economy and financial markets implied by the consumption-based asset pricing paradigm.
The long-run consumption risk (LRR) model is a promising approach to resolve prominent asset pricing puzzles. The simulated method of moments (SMM) provides a natural framework to estimate its deep parameters, but caveats concern model solubility and weak identification. We propose a two-step estimation strategy that combines GMM and SMM, and for which we elicit informative macroeconomic and financial moment matches from the LRR model structure. In particular, we exploit the persistent serial correlation of consumption and dividend growth and the equilibrium conditions for market return and risk-free rate, as well as the model-implied predictability of the risk-free rate. We match analytical moments when possible and simulated moments when necessary and determine the crucial factors required for both identification and reasonable estimation precision. A simulation study – the first in the context of long-run risk modeling – delineates the pitfalls associated with SMM estimation of a non-linear dynamic asset pricing model. Our study provides a blueprint for successful estimation of the LRR model.
We study consumption-portfolio and asset pricing frameworks with recursive preferences and unspanned risk. We show that in both cases, portfolio choice and asset pricing, the value function of the investor/representative agent can be characterized by a specific semilinear partial differential equation. To date, the solution to this equation has mostly been approximated by Campbell-Shiller techniques, without addressing general issues of existence and uniqueness. We develop a novel approach that rigorously constructs the solution by a fixed point argument. We prove that under regularity conditions a solution exists and establish a fast and accurate numerical method to solve consumption-portfolio and asset pricing problems with recursive preferences and unspanned risk. Our setting is not restricted to affine asset price dynamics. Numerical examples illustrate our approach.
A large literature over several decades reveals both extensive concern with the question of time-varying betas and an emerging consensus that betas are in fact time-varying, leading to the prominence of the conditional CAPM. Set against that background, we assess the dynamics in realized betas, vis-à-vis the dynamics in the underlying realized market variance and individual equity covariances with the market. Working in the recently-popularized framework of realized volatility, we are led to a framework of nonlinear fractional cointegration: although realized variances and covariances are very highly persistent and well approximated as fractionally-integrated, realized betas, which are simple nonlinear functions of those realized variances and covariances, are less persistent and arguably best modeled as stationary I(0) processes. We conclude by drawing implications for asset pricing and portfolio management. JEL Klassifikation: C1, G1
Recent empirical work shows that a better legal environment leads to lower expected rates of return in an international cross-section of countries. This paper investigates whether differences in firm-specific corporate governance also help to explain expected returns in a cross-section of firms within a single jurisdiction. Constructing a corporate governance rating (CGR) for German firms, we document a positive relationship between the CGR and firm value. In addition, there is strong evidence that expected returns are negatively correlated with the CGR, if dividend yields and price-earnings ratios are used as proxies for the cost of capital. Most results are robust for endogeneity, with causation running from corporate governance practices to firm fundamentals. Finally, an investment strategy that bought high-CGR firms and shorted low-CGR firms would have earned abnormal returns of around 12 percent on an annual basis during the sample period. We rationalize the empirical evidence with lower agency costs and/or the removal of certain governance malfunctions for the high-CGR firms.