Tails, Fears, and Risk Premia BOLLERSLEV, TIM; TODOROV, VIKTOR
The Journal of finance (New York),
December 2011, Letnik:
66, Številka:
6
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We show that the compensation for rare events accounts for a large fraction of the average equity and variance risk premia. Exploiting the special structure of the jump tails and the pricing thereof, ...we identify and estimate a new Investor Fears index. The index reveals large time-varying compensation for fears of disasters. Our empirical investigations involve new extreme value theory approximations and high-frequency intraday data for estimating the expected jump tails under the statistical probability measure, and short maturity out-of-the-money options and new model-free implied variation measures for estimating the corresponding risk-neutral expectations.
Over the years, many asset pricing studies have employed the sample cross-sectional regression (CSR) R² as a measure of model performance. We derive the asymptotic distribution of this statistic and ...develop associated model comparison tests, taking into account the impact of model misspecification on the variability of the CSR estimates. We encounter several examples of large R² differences that are not statistically significant. A version of the intertemporal capital asset pricing model (CAPM) exhibits the best overall performance, followed by the Fama-French three-factor model. Interestingly, the performance of prominent consumption CAPMs is sensitive to variations in experimental design.
This paper examines the time and frequency dynamics of connectedness among stock prices of U.S. clean energy companies, crude oil prices and a number of key financial variables using the methodology ...developed by Barunik and Krehlik (2018). This approach allows measuring the dynamics of return and volatility connectedness over time and across frequencies simultaneously. The empirical results show that most of return and volatility connectedness is generated in the very short-term, i.e. movements up to five days, while the long-term plays a minor role. Our analysis further reveals a greater degree of interconnectedness across crude oil and financial markets since the onset of the U.S. subprime mortgage crisis in summer of 2007, consistent with the view of a global re-pricing of risk triggered by the recent worldwide financial crisis. Crude oil prices do not appear as a key driver of the stock market performance of renewable energy companies in the short-term or the long-term, which suggests a decoupling of the alternative energy industry from the traditional energy market. Moreover, crude oil prices are a net receiver of financial shocks, supporting the financialization of the commodity markets since the early 2000s. In addition, a significant pairwise connectedness is found, mainly in the short-term, between clean energy and technology stock prices, indicating that these two types of stocks are perceived by investors as similar assets. These results can have important practical implications for investors and policy makers with different time horizons.
•Connectedness among stock prices of U.S. clean energy companies, crude oil prices•Dynamics of return and volatility connectedness over time and across frequencies•Most of return and volatility connectedness is found in the short-term•Crude oil prices are not the key driver of renewable energy companies' performance•Clean energy and technology stock prices co-move in short-run
We propose a Fundamental Theorem of Asset Pricing and a Super‐Replication Theorem in a model‐independent framework. We prove these theorems in the setting of finite, discrete time and a market ...consisting of a risky asset S as well as options written on this risky asset. As a technical condition, we assume the existence of a traded option with a superlinearly growing payoff‐function, e.g., a power option. This condition is not needed when sufficiently many vanilla options maturing at the horizon T are traded in the market.
Firms increasingly deploy algorithmic pricing approaches to determine what to charge for their goods and services. Algorithmic pricing can discriminate prices both dynamically over time and ...personally depending on individual consumer information. Although legal, the ethicality of such approaches needs to be examined as often they trigger moral concerns and sometimes outrage. In this research paper, we provide an overview and discussion of the ethical challenges germane to algorithmic pricing. As a basis for our discussion, we perform a systematic interpretative review of 315 related articles on dynamic and personalized pricing as well as pricing algorithms in general. We then use this review to define the term algorithmic pricing and map its key elements at the micro-, meso-, and macro levels from a business and marketing ethics perspective. Thus, we can identify morally ambivalent topics that call for deeper exploration by future research.
The Pre-FOMC Announcement Drift LUCCA, DAVID O.; MOENCH, EMANUEL
The Journal of finance (New York),
February 2015, Letnik:
70, Številka:
1
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We document large average excess returns on U.S. equities in anticipation of monetary policy decisions made at scheduled meetings of the Federal Open Market Committee (FOMC) in the past few decades. ...These pre-FOMC returns have increased over time and account for sizable fractions of total annual realized stock returns. While other major international equity indices experienced similar pre-FOMC returns, we find no such effect in U.S. Treasury securities and money market futures. Other major U.S. macroeconomic news announcements also do not give rise to preannouncement excess equity returns. We discuss challenges in explaining these returns with standard asset pricing theory.
We propose a spatial capital asset pricing model and a spatial arbitrage pricing theory (S-APT) that extend the classical asset pricing models by incorporating spatial interaction. We then apply the ...S-APT to study the comovements of eurozone stock indices (by extending the Fama–French factor model to regional stock indices) and the futures contracts on S&P/Case–Shiller Home Price Indices; in both cases, spatial interaction is significant and plays an important role in explaining cross-sectional correlation.
The e-companion is available at
https://doi.org/10.1287/mnsc.2016.2627
.
This paper was accepted by Neng Wang, finance.
In a model with heterogeneous-risk-aversion agents facing margin constraints, we show how securities' required returns increase in both their betas and their margin requirements. Negative shocks to ...fundamentals make margin constraints bind, lowering risk-free rates and raising Sharpe ratios of risky securities, especially for high-margin securities. Such a funding-liquidity crisis gives rise to "bases," that is, price gaps between securities with identical cash-flows but different margins. In the time series, bases depend on the shadow cost of capital, which can be captured through the interest-rate spread between collateralized and uncollateralized loans and, in the cross-section, they depend on relative margins. We test the model empirically using the credit default swap—bond bases and other deviations from the Law of One Price, and use it to evaluate central banks' lending facilities.
When a product of uncertain quality is first introduced, consumers may choose to strategically delay their purchasing decisions in anticipation of the product reviews of their peers. This paper ...investigates how the presence of social learning affects the strategic interaction between a dynamic-pricing monopolist and a forward-looking consumer population, within a simple two-period model. Our analysis yields three main insights. First, we find that the presence of social learning has significant structural implications for optimal pricing policies: In the absence of social learning, decreasing price plans are always preferred by the firm; by contrast, in the presence of social learning we find that (i) if the firm commits to a price path ex ante (preannounced pricing), an increasing price plan is typically announced, whereas (ii) if the firm adjusts price dynamically (responsive pricing), prices are initially low and may either rise or decline over time. Second, we establish that under both preannounced and responsive pricing, even though the social learning process exacerbates strategic consumer behavior (i.e., increases strategic purchasing delays), its presence results in an increase in expected firm profit. Third, we illustrate that, contrary to results reported in existing literature on strategic consumer behavior, in settings where social learning is significantly influential, preannounced pricing policies are generally not beneficial for the firm.
This paper was accepted by Yossi Aviv, operations management
.
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