Announcement effects of bank mergers in Europe and the US

We investigate the announcement effect of large bank mergers in the European and US stock market. Cumulative abnormal returns are calculated on the basis of the performance vis-à-vis the market and a sector index. Mergers result in small positive abnormal returns. Target banks realize significantly higher returns than bidders. In many respects, there is a difference between the announcement effects of European bank mergers compared to those in the US.     

房地产三种评估价格的比较分析

简要的阐述了比准价格、收益价格、积算价格三种房地产评估价格的形成机理及理论依据，并从对一种观点的局限性分析出发，综合运用市场供求理论、均衡理论以及短边原则，对不同市场背景下三种估价方法得出的评估价格进行经济比较分析。     

Risk management under extreme events

This article presents two applications of extreme value theory (EVT) to financial markets: computation of value at risk (VaR) and cross-section dependence of extreme returns (i.e., tail dependence). We use a sample comprised of the United States, Europe, Asia, and Latin America. Our main findings are the following. First, on average, EVT gives the most accurate estimate of VaR. Second, tail dependence of paired returns decreases substantially when both heteroscedasticity and serial correlation are filtered out by a multivariate GARCH model. Both findings are in agreement with previous research in this area for other financial markets.     

Value relevance of proportionate consolidation versus the equity method: Evidence from Hong Kong

Whether proportionate consolidation (PC) or the equity method (EM) provides more informative financial statements is a controversial issue. This study uses data from listed companies in Hong Kong to investigate the value relevance of the EM compared with PC during 2005–2008 when the local word-for-word equivalent HKAS 31 offered the same options. The results of this study provide evidence that PC does not offer higher value relevance than the EM. PC’s horizontal aggregation of a portion of the operations, assets and liabilities of the jointly controlled entities with those of the venturer is less informative to investors than the EM’s vertical aggregation.     

Non-coercive influence: Scale development and validation based on resource and relational paradigms

To overcome competition in an increasingly network dependent market, retailers are required to influence upstream channel partners while sustaining relationships. However, the contemporary supply chain literature has not sufficiently leveraged the resource and relational paradigms to examine influence. Grounded on resource dependency theory and commitment-trust theory paradigms, this study describes conceptualization and operationalization of a 12-item scale for measuring non-coercive influence on upstream channel partners in retail supply chain management (R-SCM) context. The study is based on responses from 547 retail professionals in India obtained over four successive surveys. Psychometric properties were assessed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The proposed scale demonstrates construct validity. Invariance-testing carried out over 4-levels of increasingly demanding equivalence confirmed cross-validation. Nomological validity of the scale was tested by evaluating association with suppliers’ intention to cooperate. The results indicate existence of three dimensions of non-coercive influence: collaborative intent, market intelligence dissemination, and operational support. Retailers can use the scale to assess their personnel's non-coercive influence behavior over suppliers.     

Optimizing the credit term decisions in supply chain finance

We study a credit term determination problem in the context of a supplier-buyer supply chain. The supplier's credit term decision is simultaneously made with its production and inventory decisions, and most importantly, it is impacted by the buyer's order quantity. We present a new game-theoretic framework to model this problem, which captures the interaction between the supplier's credit term decision and the buyer's order decision in a multi-period setting. An exact method based on nonlinear programming is implemented to obtain the optimal solutions. We apply our methodologies on a real world case. The computational results show that our approach significantly outperforms the heuristics with fixed credit terms, and either a short or a long credit term can be sub-optimal for the supplier in profitability. Our work offers the first data-driven model and solution approach that assists purchasing and supply managers to make optimal dynamic credit term decision in conjunction with production, ordering and inventory decisions in a game-theoretic setting.     

Dynamical macroprudential stress testing using network theory

The increasing frequency and scope of financial crises have made global financial stability one of the major concerns of economic policy and decision makers. This has led to the understanding that financial and banking supervision has to be thought of as a systemic task, focusing on the interdependent relations among the institutions. Using network theory, we develop a dynamic model that uses a bipartite network of banks and their assets to analyze the system’s sensitivity to external shocks in individual asset classes and to evaluate the presence of features underlying the system that could lead to contagion. As a case study, we apply the model to stress test the Venezuelan banking system from 1998 to 2013. The introduced model was able to capture monthly changes in the structure of the system and the sensitivity of bank portfolios to different external shock scenarios and to identify systemic vulnerabilities and their time evolution. The model provides new tools for policy makers and supervision agencies to use for macroprudential dynamical stress testing.     

Pricing CDS spreads with Credit Valuation Adjustment using a mixture copula

Credit derivatives pricing models before Basel III ignored losses in market value stemming from higher probability of counterparty default. We propose a general credit derivatives pricing model to evaluate a Credit Default Swap (CDS) with counterparty risk, including the Credit Valuation Adjustment (CVA) in order to optimize the economic capital allocation. We work from the model proposed by Luciano (2003, Working Paper, International Center of Economic Research) and the general pricing representation established by Sorensen and Bollier (Financial Analysts Journal 1994;50(3):23–33) to provide a model close to the market practice, easy to implement and fitting with Basel III framework. We approach the dependence between counterparty risk and that of the reference entity with a technical tool: the copula, in particular, the mixture one that combines common “extreme” copulas. We study the CDS's vulnerability in extreme dependence cases. By varying Spearman's rho, the mixture copula covers a broad spectrum of dependence and ensures closed form prices. We end up with an application on real market data.     

REAL OPTIONS AND THE CROSS‐SECTION OF EXPECTED STOCK RETURNS

This paper surveys the theoretical literature investigating the effect of firms’ investment flexibility on the cross‐section of expected stock returns. Real options analysis derives firms’ value‐maximizing investment policies as functions of exogenous fundamental drivers of profitability and calculates firms’ market values as functions of the same variables. These functions yield the relationship between expected stock returns and firm fundamentals. Several plausible explanations for the value premium – the high average stock returns earned by firms with high book‐to‐market ratios – emerge from this literature.     

EXTREME VALUE THEORY IN FINANCE: A SURVEY

Extreme value theory is concerned with the study of the asymptotic distribution of extreme events, that is to say events which are rare in frequency and huge in magnitude with respect to the majority of observations. Statistical methods derived from it have been employed increasingly in finance, especially for risk measurement. This paper surveys some of those main applications, namely for testing different distributional assumptions for the data, for Value‐at‐Risk and Expected Shortfall calculations, for asset allocation under safety‐first type constraints, and for the study of contagion and dependence across markets under conditions of stress.