Oil price dynamics and airline earnings predictability

This study examines the effect of oil price dynamics on quarterly earnings and their predictability with a sample of 30 airlines for 1994–2017. First, we document a significantly positive impact of demand-driven oil shocks on airline earnings, suggesting that the revenue effect from shifting air travel demands dominates the cost effect of aviation fuels. Regarding earnings predictability, we find evidence of deterioration in oil-volatile quarters as indicated by both the earnings variability based on common benchmarks and the quality of analyst forecasts issued early in the quarter. We further show that supply-driven oil shocks have a more detrimental impact on earning predictability than demand-driven oil shocks. Finally, we do not find supporting evidence for the possible moderating effect of hedging.     

Information on sellers and buyers characteristics: added value to explain price formation at primary fish markets in managed French scallop fisheries

The aim of this article is to explore, through a hedonic approach, the factors that might explain the price variability for the French-managed fishery of scallop at primary fish markets. In addition to factors classically identified in the current literature like intrinsic product characteristics or markets situation, the characteristics of operators are tested. The relationships of loyalty between sellers and buyers, and market assiduity are notably considered.     

Violation behavior in vertical restraint: Empirical analyses in the case of retail price maintenance

An extensive body of work within the marketing and economics literature has been devoted to studying vertical restraints, yet only a few researchers have investigated the violation behavior of retailers. In this paper, we investigate violation behavior in the context of retailer price maintenance. We investigate this behavior using a unique data set from a subsidy program in China, which includes transaction-level information that shows retail price maintenance (RPM) practices in multiple product categories by multiple manufacturers across multiple markets. The results from our fixed effects regression show that retailer violations are more likely to occur when intra-product competition is high. However, how retailer violation likelihood varies with inter-product competition may depend on the product category. We find that inter-product competition, is negatively associated with the likelihood of violation, for “less popular” product categories in the program such as washing machines, air conditioners, etc., but is positively associated with the likelihood of violation for “popular” product categories such as refrigerators, televisions, and cell phones. Our research provides some of the first empirical evidence about retailer violation behavior under RPM in the world’s largest emerging market by focusing on the relationship between violation behavior and market structure. We discuss the implications for monitoring efforts of manufacturers and regulators.     

双重重压下六国化工盈利能力分析及突围之路探析

2012年下半年以来，由于市场不景气导致中国化工行业产品价格下降，而成本却不断攀升，企业盈利能力不容乐观，六国化工也不例外。文章对六国化工进行了介绍，并利用杜邦体系分析法等盈利能力指标对其分析，进而提出了相关建议，以便于六国化工找到突破困境的途径，获得持久的竞争优势及长期可持续发展。     

How to measure competition in an economy in transition

This paper attempts to find a robust method of measuring competition when firms' operational activities are subject to frictions. The first part theoretically tests the indicative quality of two competition measures, the price‐cost margin (PCM) and the profit elasticity, in a model of monopolistic competition. The second part studies the empirical performance of the indices for a panel of Ukrainian manufacturing firms. This study offers a new approach to measuring profit elasticity that relies on structural estimation of a production function. The estimation methodology retrieves a productivity index that is adjusted to imperfect competition. The proposed method of measuring profit elasticity is found to be robust to frictions, but the PCM and traditional profit elasticity are biased, especially when the intensity of competition is low. Empirical findings show that competition exhibits a significantly positive correlation with aggregate productivity performance, while its impact on firm productivity is nonlinear.     

Macroeconomic Announcements and the Distribution of Price-Endings in the U.S. Treasury Market

We investigate how new information impacts quote clustering in the bond market. We find that clustering, along with quote activity, price volatility and bid-ask spreads, increases sharply in the minutes following releases of macroeconomic news. Each returns to near-normal levels within the hour. Effects are strongest for more liquid on-the-run notes and for the announcements typically associated with substantial information flow. The strong positive comovement of clustering, quote activity, price volatility, and bid-ask spreads supports the conclusion that innovations of these variables are endogenous to the arrival and incorporation of information into prices.     

CONVEX RISK MEASURES FOR GOOD DEAL BOUNDS

We study convex risk measures describing the upper and lower bounds of a good deal bound, which is a subinterval of a no‐arbitrage pricing bound. We call such a convex risk measure a good deal valuation and give a set of equivalent conditions for its existence in terms of market. A good deal valuation is characterized by several equivalent properties and in particular, we see that a convex risk measure is a good deal valuation only if it is given as a risk indifference price. An application to shortfall risk measure is given. In addition, we show that the no‐free‐lunch (NFL) condition is equivalent to the existence of a relevant convex risk measure, which is a good deal valuation. The relevance turns out to be a condition for a good deal valuation to be reasonable. Further, we investigate conditions under which any good deal valuation is relevant.     

House price determinants in Athens: a spatial econometric approach

In this paper, we try to identify the price determinants in the biggest real estate market of Greece, the metropolitan area of Athens. For that purpose, various spatial econometric models are used to explore their prediction ability and we are displaying the variations in property prices for the wider area of Athens. These models have been compared based on different criteria such as model fit, the Akaike information criterion and variance of the residuals. Our results indicate that, in our case, the spatial general model is the most appropriate simultaneous autoregressive model when dealing with spatially autocorrelated prices of housing properties data, in terms of our selection criteria.     

Relationship between oil,stock prices and exchange rates: A vine copula based GARCH method

In this paper, we apply a vine copula approach to investigate the dynamic relationship between energy, stock and currency markets. Dependence modeling using vine copulas offers a greater flexibility and permits the modeling of complex dependency patterns for high-dimensional distributions. Using a sample of more than 10 years of daily return observations of the WTI crude oil, the Dow Jones Industrial average stock index and the trade weighted US dollar index returns, we find evidence of a significant and symmetric relationship between these variables. Considering different sample periods show that the dynamic of the relationship between returns is not constant over time. Our results indicate also that the dependence structure is highly affected by the financial crisis and Great Recession, over 2007–2009. Finally, there is evidence to suggest that the application of the vine copula model improves the accuracy of VaR estimates, compared to traditional approaches.     

FIRE SALES FORENSICS: MEASURING ENDOGENOUS RISK

We propose a tractable framework for quantifying the impact of loss‐triggered fire sales on portfolio risk, in a multi‐asset setting. We derive analytical expressions for the impact of fire sales on the realized volatility and correlations of asset returns in a fire sales scenario and show that our results provide a quantitative explanation for the spikes in volatility and correlations observed during such deleveraging episodes. These results are then used to develop an econometric framework for the forensic analysis of fire sales episodes, using observations of market prices. We give conditions for the identifiability of model parameters from time series of asset prices, propose a statistical test for the presence of fire sales, and an estimator for the magnitude of fire sales in each asset class. Pathwise consistency and large sample properties of the estimator are studied in the high‐frequency asymptotic regime. We illustrate our methodology by applying it to the forensic analysis of two recent deleveraging episodes: the Quant Crash of August 2007 and the Great Deleveraging following the default of Lehman Brothers in Fall 2008.