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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.
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
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.
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.
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.
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 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.
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 (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.
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.