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We analyse the responses of the monetary policy of five (Brazil, Chile, Mexico, India, and South Africa) emerging market economies (EME) to domestic and external (U.S.) shocks. We argue that the domestic policy rate is sensitive to risk premiums, financial markets, and the world economy, showing that Taylor's Rule can benefit from the inclusion of these variables to understand the behaviour of the monetary authority. Therefore, our results suggest the following: i) policy rates are affected by risk premiums, ii) domestic monetary policy is affected by exchange rates, stock markets, and the U.S. and iii) there is heterogeneity in the factors explaining the behaviour of central banks. [ABSTRACT FROM AUTHOR]

Earnings announcement (EA) poses a non‐diversifiable risk to investors. This study examines whether investors demand higher returns for stocks with high systematic EA risk. We find evidence that systematic EA risk is priced, however, the premium is realized only during periods with intensified cash‐flow news. Specifically, we construct an ex‐ante measure of expected information intensity (EII) and find that in the subsample of high‐EII firms, those with high systematic EA risk earn significantly higher future returns. Controlling for known risk factors, stocks with high systematic EA risk outperform those with low systematic EA risk by 0.43% in monthly Fama–French five‐factor alpha. We also confirm the well‐documented announcement premium, i.e., high‐EII firms outperform low‐EII firms and show that the EA risk premium is distinct from the announcement premium. To exploit both premiums, a feasible strategy of long stocks with both high‐EII and high systematic EA risk and short stocks with low‐EII yields monthly 0.81% five‐factor alpha. [ABSTRACT FROM AUTHOR]

Based on the typical positions of S&P 500 option market makers, we derive a funding illiquidity measure from quoted prices of S&P 500 derivatives. Our measure significantly affects the returns of leveraged managed portfolios; hedge funds with negative exposure to changes in funding illiquidity earn high returns in normal times and low returns in crisis periods when funding liquidity deteriorates. The results are not driven by existing measures of funding illiquidity, market illiquidity, and proxies for tail risk. Our funding illiquidity measure also affects leveraged closed-end mutual funds and, to an extent, asset classes where leveraged investors are marginal investors. [ABSTRACT FROM AUTHOR]

This study examines how inline XBRL (iXBRL) mandatory adoption impacts audit fees. Although iXBRL can make financial reporting information accessible to a wide range of external stakeholders, the presentation format change should have no impact on audit pricing. However, audit firms note that presenting nonaudited XBRL metadata on top of audited financial statements could lead to an expectation gap where external stakeholders believe that the inline tags have been audited despite no procedures being required. We find that iXBRL adoption is associated with higher audit fees. Upon further examination, we find that the increase in audit fees reflects more of a risk premium being placed on iXBRL clients rather than increased audit effort, as audit quality does not necessarily improve following adoption. We provide timely information on how auditors respond to iXBRL adoption. JEL Classifications: M41; M42; O33. [ABSTRACT FROM AUTHOR]

This paper documents that the ratio of residential-to-nonresidential investment is a strong in-sample and out-of-sample predictor for the dollar up to 12 quarters. The predictability is robust to a battery of additional checks and holds for other G10 currencies. We explain the predictability in an analytical model with time-varying housing preference, productivity, and volatility. In the model, the U.S. housing investment share is higher during periods with higher growth and lower uncertainty, corresponding to lower future nontradable prices, dollar index, and excess returns. We find strong empirical support for the channel. Alternative explanations, including the business and financial cycle, find less empirical support. This paper was accepted by David Sraer, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4932. [ABSTRACT FROM AUTHOR]

To assess outright and relative value opportunities in stocks and benchmark their performance against an index with global relevance, it is important to achieve and measure risk-adjusted excess returns. Academic and corporate research has focused quite extensively on analyzing stock returns and comparing the outperformance of specific investment strategies, with value investing being one of the most prominent and longest-known factor strategies. In this event study, to test for the existence of risk-adjusted excess returns, or alpha, a novel two-step approach is proposed to assess Enhanced Value in single stocks for three different investment approaches: plain value investing, investing in spin-offs, and investing in turnaround companies. While the first step of the two-step approach screens companies for a combination of financial company characteristics, the second step ranks and sorts them by either their price-earnings ratio or by their price-book ratio, thus “enhancing” the value assessment. Their short- and mid-term stock performance is investigated for an investment horizon of one year, three years, and five years. Stocks of value companies, spin-offs, and turnaround companies outperform the S&P 500 benchmark on average and on a risk-adjusted basis for all three investment horizons when tested for Enhanced Value with the novel two-step approach. The analysis results provide deeper insights into how the value factor in its different characteristics needs to be understood in the context of investment strategies and how it potentially can be applied to stock selection and portfolio construction, resulting in investment strategies showing a risk-adjusted outperformance.

In this article, a new method is introduced under the Bayesian framework to derive the credibility estimator of risk premiums based on the Esscher premium principle. This new estimator offers desirable statistical properties, making it more useful and practical compared to existing estimators. Additionally, Bayesian models for policy portfolios are established, and empirical Bayes methods are employed to estimate the structural parameters. The empirical Bayesian estimation of risk premiums is also discussed in detail. The convergence rate and goodness of the proposed estimators are verified through simulations. The results demonstrate the effectiveness and accuracy of the new estimator and its superior performance compared to other existing methods. Finally, an empirical analysis is conducted using real insurance data, which further confirms the applicability and reliability of the proposed credibility estimator and its superiority in practical insurance applications. [ABSTRACT FROM AUTHOR]

For ESG-oriented investors, the inquiry into whether companies with high-ESG scores can achieve excess returns holds significant significance. Existing research has generated some controversy regarding the existence of an ESG premium. In this study, we attempt to reconcile conflicting empirical findings by introducing a dimension of investment time horizons. We examine the impact of ESG scores (representing long-term values) and $\Delta $ Δ ESG (short-term changes) on subsequent stock returns. Our results indicate that high-ESG stocks tend to achieve higher expected returns, while high $\Delta $ Δ ESG has the opposite effect. One plausible explanation is that high-ESG firms tend to exhibit superior governance practices, making them more likely to create long-term value, while efforts to improve ESG may increase short-term costs, impacting profitability and exerting a negative influence on stock prices temporarily. The results based on financial data also support this conjecture. [ABSTRACT FROM AUTHOR]

Using stochastic spanning tests without any distributional assumptions on returns, we show that the two classes of GDP-linked bonds, floaters and linkers, are not spanned by a broad benchmark set of stocks, bonds, and cash for a wide range of design specifications. Thus, they provide a new asset class with significant diversification benefits for investors, with proportional investments to these novel instruments estimated in the double digits and an increase in Sharpe ratios by up to 0.37 over the benchmark. The benefits depend on the market risk premium, but they persist for a wide range of premia estimates from existing literature and are robust to a randomized test. Using the generalized method of moments regressions, we document the finance and macro determinants of GDP-linked bond returns. [ABSTRACT FROM AUTHOR]

Climate change and environmental issues have received increasing attention across the world. China's governmental targets for carbon peak and carbon neutralization show the ambition and efforts necessary in challenging these problems. The transportation industry will be crucial in reducing carbon emissions. Based on the green patent application data in China's new energy vehicle (NEV) industry from 2006 to 2021, this article focuses on risk premium of green technology innovation. In particular, the premium effects of the green technology innovation and the cooperative network are empirically examined. Furthermore, two channels that play a role in generating the premium are investigated, i.e., attracting market attention and reducing financing constraints. The empirical results show that the stock returns are positively correlated to the green technology innovation and the company's central position in the cooperative network, i.e., there exist the premium effects of green technology innovation in China's NEV industry. The positional advantage in the cooperative innovation network can further increase analyst following and reduce financing constraints. The research can provide evidence and policy implications for the government, companies and investors. [ABSTRACT FROM AUTHOR]

This paper examines the uncovered interest parity puzzle in Central and Eastern European countries. Apart from investigating baseline UIP regressions, we check for structural breaks in this relationship, scrutinize deviations from the UIP, and employ different estimation methods and models augmented with various risk measures. Moreover, we offer several extensions to the common UIP testing that account for foreign-exchange interventions, the implied volatility of exchange rates, and the limited availability of data on direct measures of market expectations. The study shows that the choice of the reference currency matters for the outcome of the interest parity tests in the CEE economies. In particular, we demonstrate that inconsistencies between the results of the UIP tests vis-à-vis the euro and the US dollar that appear in CEE economies may be accounted for by the movements of the euro-dollar risk premium. This regularity has not been documented in previous studies. Additionally, we show that (a) the FX interventions in Czechia distorted the UIP, (b) the directly measured exchange rate expectations (granular survey data) in Poland do not seem to be informed by the UIP relationship, (c) the limited resilience of CEE economies to rare disasters may plausibly explain deviations from the UIP. [ABSTRACT FROM AUTHOR]

Market risk premium and market volatility are essential in investment decisions. Volatility is a vital variable in derivative securities that measures changes in stock returns. The research focuses on stock return volatility, research that points to a risk premium in emerging markets. This study aims to explain the relationship between market equity premium and volatility using GARCH (1.1) on the Indonesia Stock Exchange. This research uses daily closing price data of the Indonesia Stock Exchange Composite Index (JCI). The result of this study is that there is a relationship between risk premium and volatility in the Indonesian stock market. This study's conclusion is to test whether there is a relationship between the volatility of return and risk premium in the Indonesian stock market. Using the daily trend of the Indonesian stock market (IDX) from January 2010 to September 2023. [ABSTRACT FROM AUTHOR]

When evaluating the value of a particular firm or asset, to calculate the final result objectively and consider the critical variables of the market conjuncture, it is necessary to select the optimal discount rate, which will be used to assess the riskiness of cash flows. The discount rate should reflect all possible premiums impacting the financial and non-financial riskiness of the evaluated asset. In particular, for calculating the value of the loan obligation, the discount rate must reflect the default premium, which implies the risk that the borrower will not be able to repay the obligation in the predetermined volume and term stipulated by the agreement. On the other hand, when investing with equity, the discount rate should reflect the equity risk premium. Therefore, a logical question arises: how do we measure the riskiness of default and investor's equity? It is rational to share the opinion that assessing the risk from the investors' point of view and subsequently converting it into a numerical indicator is a rather complex task, especially when it comes to developing countries, where the sources of market risk, measurability, are even more obscure and require additional observation and study. Therefore, the selection of the optimal model, which is as close as possible to reality and, at the same time, can quickly reflect all the risk factors that affect the investment, is critically important. This task is complex for an investor, but based on theoretical and practical knowledge, experience, and logic, it is possible to cope with this challenge. Financial and economic representatives unanimously agree that selecting an effective numerical model for calculating the cost of equity and reflecting relevant risk factors in it is beneficial both for local and global investors and for a developing country's stable economic growth. Improving the cost of capital methodology can transmit positive results to the economy and its agents through several channels. Within the framework of the article, a comparative analysis of numerical models for measuring investment cost was carried out. In the first part of the article, the theoretical and practical numerical models in the financial and economic literature were reviewed in detail. After that, an analysis of the capital asset pricing model, arbitrage pricing model, multifactor, and alternative models was carried out, the shortcomings and advantages of each model were reviewed, as well as a discussion was made about how realistic the assumptions behind these models are and how materially damaging the existence of these assumptions can be to the numerical results, of the model as a predictor of expected returns. The next part of the article analyzed which numerical model should be used and what changes are needed so that the standard financial models for calculating the cost of equity would reflect the systemic risk environment of the developing country relevantly. The literature review shows several main directions to choose from when selecting a measurement model for expected returns. Within the article, the decision to choose a model for calculating the cost of capital in developing countries is based on theoretical and pragmatic considerations. During the selection of the methodology, further questions were asked: to what extent is it possible to obtain information about the variables required to use the numerical model, how simple and intuitive the essence of the model, and what the interpretation of the results derived from it will be for the reader, which model, as a determinant of future expected returns, is inclined to use in the empirical studies carried out in the financial field. After analyzing and evaluating the questions arising from all the factors mentioned earlier, a modified version of the capital asset pricing model was selected. Modifying the capital asset pricing model allows for a change in the standard approach and reflects all the additional risk factors that may characterize the economy of a developing country. The essence of the modification lies in including an additional premium in the numerical model, which will reflect and try to reflect local financial and non-financial riskiness in numerical indicators. Aswat Damodaran notes that the modified CAPM's main advantage is its simplicity and intuitiveness in assessing the relationship between risk and opportunities. Also, Damodaran emphasizes that more sophisticated and complex numerical models, such as arbitrage pricing, Fama and French 3-factor, and other models, despite being better explainers of historical trends, empirical research shows that they cannot offer Significantly improved forecasts of expected rates of return compared to CAPM, it is therefore not surprising that the capital asset pricing model is still the most popular and applicable to investors today. Calculating the cost of equity is a rather complex and time-consuming process, which in turn requires a reliable information resource, in-depth knowledge of the field, and a detailed analysis of the features of the potential investment proposal. When an investment decision is made in the market of a developing country, all the circumstances mentioned above are associated with additional risk factors, such as access to historical databases, reliable information resources, the existence of political risks, low level of development of the country's financial infrastructure, low transparency of the market, increased signs of corruption and others. Hence, directly selecting and transferring the numerical model that is used in developed markets to the market of a developing country could be materially damaging and not lead to optimal financial decision-making for the investor. Based on this fact, within the framework of the article, a traditional, wellknown capital asset pricing model was selected and recommended, which should be modified and include a premium relevant to a developing country's systemic risk. On the other hand, as mentioned at the beginning of the article, the numerical model for calculating the investment discount rate, which is consistent with economic and financial logic, is beneficial for the economy of a developing country in many ways, including effective allocation of resources among economic agents, support for the development of financial infrastructure, increasing the transparency of financial markets, and others. [ABSTRACT FROM AUTHOR]

To construct a stochastic version of [R. J. Barro, J. Polit. Econ. 87, 940-971 (1979)] normative model of tax rates and debt/GDP dynamics, we add risks and markets for trading them along lines suggested by [K. J. Arrow, Rev. Econ. Stud. 31, 91-96 (1964)] and [R. J. Shiller, Creating Institutions for Managing Society's Largest Economic Risks (OUP, Oxford, 1994)]. These modifications preserve Barro's prescriptions that a government should keep its debt-gross domestic product (GDP) ratio and tax rate constant over time and also prescribe that the government insure its primary surplus risk by selling or buying the same number of shares of a Shiller macro security each period. [ABSTRACT FROM AUTHOR]

Levels of government debt-to-GDP have been rising substantially for over a decade in emerging market economies such as South Africa, which has led to much debate around the implementation of large-scale debt-financed fiscal stimulus programs in response to the economic fallout of the global covid-19 pandemic. Debt-financed fiscal policies directly stimulate aggregate demand through government expenditure or tax cuts, but their effectiveness is highly dependent on direct crowding-out of private sector expenditure, spill-over effects to the private sector through a higher risk premium on interest rates, and the interaction between fiscal policy and monetary policy. Using an open-economy dynamic stochastic general equilibrium model for South Africa, we identify the effect of six different fiscal policy instruments on short-term and long-term interest rates. These disaggregated expenditure and revenue shocks raise long-term real yields between 18 and 29 basis points, but there are non-negligible differences in the dynamic responses to each fiscal instrument. Our main findings suggest that, in the context of fiscal sustainability, an investment-driven debt-financed fiscal stimulus programme would reduce the government debt-to-GDP ratio, especially in periods of economic slack when monetary policy would typically be more accommodative. In fact, since the global financial crisis, monetary policy has reduced the burden of fiscal adjustment in response to rising debt and a rising risk premium. But further shocks to the risk premium could offset any gains from the current stance of monetary policy (for example, a credit rating shock raises the long-term government bond rate 155 basis points). [ABSTRACT FROM AUTHOR]

The large inflow of less-educated immigrants into the United States in recent decades may have affected US natives' labor market outcomes in many ways, including their working conditions. Although the general consensus is that low-skilled immigrants tend to hold "worse" jobs than US natives, the impact of immigration on natives' working conditions has received little attention. This study examines how immigration has affected US natives' occupational exposure to workplace hazards and the compensating differential paid for such exposure from 1990 to 2018. Results indicate that immigration causes less-educated natives' exposure to workplace hazards to fall, and instrumental variables results show a larger impact among women than among men. The corresponding compensating differential appears to fall among men, but not after accounting for immigration-induced changes in the financial returns to occupational skills. [ABSTRACT FROM AUTHOR]

Based on the typical positions of S&P 500 option market makers, we derive a funding illiquidity measure from quoted prices of S&P 500 derivatives. Our measure significantly affects the returns of leveraged managed portfolios; hedge funds with negative exposure to changes in funding illiquidity earn high returns in normal times and low returns in crisis periods when funding liquidity deteriorates. The results are not driven by existing measures of funding illiquidity, market illiquidity, and proxies for tail risk. Our funding illiquidity measure also affects leveraged closed-end mutual funds and, to an extent, asset classes where leveraged investors are marginal investors.

The latest development in empirical Asset Pricing is the use of Machine Learning methods to address the problem of the factor zoo. These techniques offer great flexibility and prediction accuracy but require special care as they strongly depart from traditional Econometrics. We review and critically assess the most recent and relevant contributions in the literature grouping them into five categories defined by the Machine Learning (ML) approach they employ: regularization, dimension reduction, regression trees/random forest (RF), neural networks (NNs), and comparative analyses. We summarize the empirical findings with particular attention to their economic interpretation providing hints for future developments. [ABSTRACT FROM AUTHOR]

Based on all daily A-share data from January 2006 to December 2021, this study examines the relationship between overnight and intraday returns and market beta using Fama-Macbeth regressions and panel regressions to explore the reasons for the weak correlation between systematic risk and full-day returns in the Chinese A-share market. The results show that the overnight risk premium of the Chinese A-share market is significantly negative. The intraday risk premium is negligible when portfolios are sorted by beta, industry and Book-to-Market ratios, and stock characteristics. The slope of the securities market line (SML) tends to zero due to the interaction of the uncertain intraday risk premium and the negative correlation between overnight returns and market risk. [ABSTRACT FROM AUTHOR]

There has always been controversy among researchers over how dividend policies affect share prices, and this equivocal relationship varies throughout international markets. This study is set to examine the relation between share prices and number of dividend policy and profitability variables. Based on the information from five insurance companies that are listed on Kuwait Stock Exchange (KSE) over the period 2014 and 2022, findings indicates that 55.3% of stock prices could be explained by factors related to profitability and dividend policy. The relationship between stock price, as a dependent variable, and earnings per share (EPS), dividend yield (DY), earning to price ratio (EP), risk premium (RP), and retention ratio (RR), as independent variables, was investigated in this study using OLS regression approach. The results of the regression analysis demonstrated a significant direct relationship between stock price and earnings per share (EPS), suggesting that investors choose highly profitable shares. At the 99% confidence level, the earnings to price ratio (EP) likewise revealed a statistically significant direct relationship with the stock price. At 90% confidence level, risk premium (RP) also shown a substantial direct relationship. The only variable that significantly correlated negatively with share prices was dividend yield (DY), suggesting that investors choose more stable payouts over uncertain future capital gains. Conversely, the retention ratio (RR) demonstrated a negligible direct impact on share prices. [ABSTRACT FROM AUTHOR]

For years, the cost of capital in Poland has been among the highest in the EU. While in 2005–2015, interest rates on long-term loans for enterprises in Czechia and Estonia were at levels similar to Germany, in Poland, rates were always higher – in 2009–2013, even twice as high. Throughout the 18-year analysis period, enterprises in Poland paid 35% more interest than those in Czechia, and 41% more than in Estonia. Over the entire period, Polish enterprises paid PLN 57 bn more interest than if rates had been the same as in Czechia, PLN 74 bn more than in Estonia, and PLN 118 bn more than in Germany. This has resulted in higher debt among Polish enterprises, along with lower levels of innovation, creditworthiness, competitiveness, salaries, tax base, and investment profitability, and thus slower development and weaker future development prospects for the Polish economy.

Climate change and environmental issues have received increasing attention across the world. China’s governmental targets for carbon peak and carbon neutralization show the ambition and efforts necessary in challenging these problems. The transportation industry will be crucial in reducing carbon emissions. Based on the green patent application data in China’s new energy vehicle (NEV) industry from 2006 to 2021, this article focuses on risk premium of green technology innovation. In particular, the premium effects of the green technology innovation and the cooperative network are empirically examined. Furthermore, two channels that play a role in generating the premium are investigated, i.e., attracting market attention and reducing financing constraints. The empirical results show that the stock returns are positively correlated to the green technology innovation and the company’s central position in the cooperative network, i.e., there exist the premium effects of green technology innovation in China’s NEV industry. The positional advantage in the cooperative innovation network can further increase analyst following and reduce financing constraints. The research can provide evidence and policy implications for the government, companies and investors.

Research aims: Illiquidity risk is one of the complex issues that institutional investors and market participants continually face over time. It is because the constructs of illiquidity risk are sometimes complicated, robust, and not so evident in secondary markets. Hence, this study aims to empirically explore illiquidity risk before and during the COVID-19 pandemic to understand how much investors were expected to lose if they invested in stock markets during these periods. Design/Methodology/Approach: This study used a GARCH model and the Amihud illiquidity ratio to achieve its objective. Trading volumes and price returns for the JSE, CAC 40, DAX, Nasdaq, BIST 100, and SSE were from June 30, 2017, to June 30, 2019, and January 1, 2020, to December 31, 2021. Research findings: As expected, the findings revealed higher illiquidity risk during periods of financial distress, such as the COVID-19 pandemic. During the financial crisis, investors could lose up to $22268.44 a day in less developed markets, such as the JSE, while the average loss in developed markets ranged between $0.22 to $11.53 in the Nasdaq and DAX, respectively. On average, a much lower figure was observed before the financial crisis. The BIST100, CAC 40, DAX, and Nasdaq are excellent options for those seeking lower-risk premiums. Theoretical and Practitioner/Policy implication: Policies such as adequate market microstructure and greater transparency in trading are strongly recommended for less developed markets, especially during periods of financial distress. Also, the findings of this study provide valuable insight into short-term traders and market participants attracted to liquid markets, where they can easily enter and exit their positions with minimal transaction costs. To the author's knowledge, this paper is the first to model illiquidity risk in stock markets. Research limitation/Implication: It is possible that the current study did not accurately capture the cost of illiquidity in the sampled financial markets and cannot be applied to other financial markets.

AbstractRisk premium plays an important role in stock investing. Experiments have shown that value stocks typically have a higher average return than growth stocks; however, this effect persists indefinitely, even disappearing in some stages. Some studies suggested high volatility in the series of returns, broken structures, market volatility, or the impact of financial crises. This study aimed to build the uncertainty index and control it in the regression analysis model to solve the limitations above. The empirical analysis in Ho Chi Minh Stock Exchange (HOSE) showed that a value premium exists, and value stocks have a higher average return than growth stocks due to the higher overall risk. Furthermore, this study combined the Support Vector Regression (SVR) algorithm with the risk premium theoretical framework for the forecasting model; consequently, it is the most efficient model.

Economic benefits and risk premiums significantly affect the production system decision making of farmers and government departments. This study evaluated the economic feasibility and estimated the risk premium of 12 rainfed soybean production systems with various planting densities, fertilization rates and planting patterns by considering the impact of soybean price fluctuation. There were two planting densities (D1: 160,000 plants ha−1 and D2: 320,000 plants ha−1), two fertilization rates (F1: 20 kg ha−1 N, 30 kg ha−1 P, 30 kg ha−1 K; F2: 40 kg ha−1 N, 60 kg ha−1 P, 60 kg ha−1 K) and three planting patterns (F+W0: flat cultivation with no irrigation; R+W0: plastic-mulched ridge-furrow cultivation (PMRF) with no irrigation; R+W1: PMRF with supplemental irrigation of 30 mm at the pod-filling stage). Based on the two-year (2019–2020) field data in a semi-humid drought-prone region of northwest China and soybean price fluctuation from January 2014 to June 2021, the net income (NI) was calculated by considering the impact of soybean price fluctuation and assuming constant soybean production costs. The net present value (NPV) method and the stochastic efficiency with respect to a function (SERF) method were used to evaluate the profitability of protective alternatives and the risk of these alternatives. The results showed that the 12 proposed soybean production systems were economically feasible. Reducing the fertilization rate reduced the input costs, but it did not necessarily result in a decrease in soybean yield and NI. The payback period of all production systems was within two years for farmers investing through loans. High-fertilizer and high-density production systems made personal investment obtain the highest economic benefit in this study, which was not the best investment strategy from the perspective of production-to-investment ratio and environmental protection departments. The preferences of farmers with various risk aversion and environmental protection departments in terms of risk premium were also proposed. The economic and risk assessment framework of this study can enhance the understanding of the adjustment of production systems from different perspectives, and provide strategies for promoting the protection of economic, environmental and socially sustainable agricultural systems. [ABSTRACT FROM AUTHOR]

We uncover two channels of effect in the financial market when investors face macroeconomic uncertainty. Conditional on a common mispricing index, we find that economic uncertainty exposure (EUE) induces disagreement, which amplifies mispricing. The highest EUE quintile produces an annualised mispricing alpha of 9.96%, more than double the unconditional mispricing effect. An ambiguity premium of 3.84% alpha is documented in the "non‐mispricing" quintile. The EUE‐induced mispricing effect is different from the existing limits of arbitrage explanations. The ambiguity premium is predictably observed during the unfolding of shocks of COVID‐19 to the market. [ABSTRACT FROM AUTHOR]

This paper reports our findings on the return dynamics of Bitcoin and Ethereum using high-frequency data (minute-by-minute observations) from 2015 to 2022 for Bitcoin and from 2016 to 2022 for Ethereum. The main objective of modeling these two series was to obtain a dynamic estimation of risk premium with the intention of characterizing its behavior. To this end, we estimated the Generalized Autoregressive Conditional Heteroskedasticity in Mean with Normal-Inverse Gaussian distribution (GARCH-M-NIG) model for the residuals. We also estimated the other parameters of the model and discussed their evolution over time, including the skewness and kurtosis of the Normal-Inverse Gaussian distribution. Similarly, we determined the parameters that define the evolution of the estimated variance, i.e., the parameters related to the fitted past variance, square error and long-term average value. We found that, despite the market uncertainty during the COVID-19 emergency period (2020 and 2021), the selected cryptocurrencies' return volatility and kurtosis were even greater for several other subperiods within our sample's time frame. Our model represents an analytical tool that estimates the risk premium that should be delivered by Bitcoin and Ethereum and is therefore of interest to risk managers, traders and investors. [ABSTRACT FROM AUTHOR]

Based on Epstein and Zin's recursive utility function, this paper integrates generalized disappointment aversion preferences to derive an intertemporal equilibrium asset pricing model (ICAPM). We show that in addition to discount-rate news, cash-flow news, and news about future risk, four factors related to disappointment are priced. These four factors are a downstate factor, discount-rate downside news, cash-flow downside news, and downside news about future risk. We find that our seven-factor model can explain the cross-section of expected returns across portfolios sorted by size, book-to-market, investment, operating profitability, and momentum. Both the seven-beta ICAPM and the restricted seven-beta ICAPM suggest that disappointment-averse investors are more sensitive to cash-flow news and cash-flow downside news than other news terms and therefore demand higher premiums. Our results show that the seven-beta ICAPM has better performance for most portfolios and provides empirical support for investors' asymmetric preferences. [ABSTRACT FROM AUTHOR]

The term structure of equity risk premium is moderately downward-sloping unconditionally, markedly downward-sloping in good times, and markedly upward-sloping in bad times. An asset-pricing model featuring time-varying correlation between realized and expected cashflow shocks explains these puzzling empirical findings. Indeed, the model-implied slope of the equity term structure is in line with the data, both conditionally and unconditionally, because the estimated cashflow shock correlation is volatile, counter-cyclical, and negative on average. The model also generates realistic asset-pricing moments and a positive relation between the equity risk premium, slope of the equity term structure, and the dividend yield. This paper was accepted by David Sraer, finance. Funding: The authors thank the University of Texas at Dallas and the University of Toronto for financial support. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.4565. [ABSTRACT FROM AUTHOR]

This paper examines the cross-sectional drivers of credit returns for Swiss franc corporate bonds in a comprehensive sample including trade-based prices and effective bid-ask spreads from 2007 to 2022. Characteristics for momentum, carry, value, and defensive explain a significant part of the variation in future credit returns across companies. Value is based on a market-based credit risk model. Except for carry, the characteristics also deliver positive risk-adjusted returns. These results are robust for trade-based prices and different subsamples but transaction costs significantly reduce the profitability of the characteristics. After transaction costs, value and a combination of the characteristics remain profitable and continue to deliver significant risk-adjusted returns. [ABSTRACT FROM AUTHOR]

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Asset pricing theory suggests that the correct proxy for the market portfolio should contain both the debt and equity claims of the economy, whereas prevailing empirical studies fail to include the debt claim. Motived by the discrepancy between the theoretical and empirical models and the difficulty in constructing proxies, the study uses the Credit Default Swaps (CDS) market index as a proxy for the debt market and empirically tests its explanatory power in explaining stock return variations. Employing panel regression and Fama-MacBeth regression of all publicly traded U.S. companies from 2005 to 2020, the study finds a negative relationship between CDS index returns and stock returns. On average, a one standard deviation increase in CDS index return is associated with a 0.02% decrease in daily stock returns. Results of two-stage regressions show that the estimated systematic credit risk is positively priced in stock returns with similar economic magnitude as the well-documented beta risk. These results support asset pricing theories in the inclusion of debt claim and the risk-return tradeoff, while contradicting the credit risk puzzle documented in prior studies.

In this study, we investigate the geopolitical risk premium in the commodity futures market. By estimating the exposure of cross‐sectional commodity futures excess returns on a historical geopolitical risk index, we find that commodities with low‐risk betas generate 9.05% higher annual risk‐adjusted returns than those with high‐risk betas. The results indicate that low‐geopolitical‐risk‐related commodity futures contracts require extra compensation by risk‐averse investors due to hedging demand. We also explore the time‐varying characteristics of the geopolitical risk premium: It appears more pronounced during high‐geopolitical‐risk periods and before the year 2000. Finally, we exploit the subcategories of geopolitical risk and find that geopolitical threats better explain the variation of the geopolitical risk premium than do geopolitical acts, making it a main source of the geopolitical risk premium. [ABSTRACT FROM AUTHOR]