Search results

Because systemically important banks' takeovers in the US were expected to contain the 2008 global financial crisis (GFC) but were found to have imposed large cost on shareholders, this paper examines the effectiveness of these acquisitions during the GFC and investigates what went wrong with the market for corporate control of large banks.

This paper presents a model of the disciplinary takeover based on the efficient market hypothesis which provides appropriate measures for it to examine the financial performance of acquiring banks after takeover.

The results indicate that the takeover market for large banks was ineffective in two aspects: the market did not distinguish strong banks from weak banks before the crisis and acquirers performed worse after takeover. Such ineffectiveness reflects the fundamental deficiencies of large bank takeovers arising from some key distinguishing characteristics of large banks.

The sample size of systemically important banks' takeovers is small so large-sample standard statistical inferences cannot be used.

The deficiencies of large bank takeovers need to be rectified in order to aid in resolving future crises.

This paper provides rare and detailed insight based on case studies of large US bank takeovers during the GFC.

To raise the quality of regulatory capital, Basel III capital rules recognize unrealized gains and losses on all available-for-sale (AFS) securities in Common Equity Tier 1 Capital (CET1). However, by examining the correlations between U.S. GDP growth rate, interest rates and regulatory capital ratios computed using Basel III regulatory capital definition for six U.S. global systemically important banks (G-SIBs) since 2007, this chapter finds that Basel III regulatory capital will enhance the pro-cyclicality of Basel III leverage ratio and Tier 1 capital ratio and their sensitivity to long-term interest rates. Therefore, Basel III capital standards may have significant implications for bank supervision and bank capital risk management in the near future. As banks will hold more high-quality liquid assets (HQLAs) as required by Basel III Liquidity Coverage Ratio (LCR), the weight of unrealized gains and losses arising from fair value accounting will increase in Basel III Tier 1 capital base, the consequent increase of pro-cyclicality in a bank’s regulatory capital ratios may distort the true picture of bank capital adequacy. If an expected loss approach (EL) is used as the provisioning model, such capital risk may be increased further. Moreover, as U.S. monetary policy has started tapering quantitative easing, long-term interest rates will increase inevitably. This may increase the negative impact of unrealized gains and losses on AFS securities on bank capital. As a result, it may be difficult for banks to maintain appropriate capital ratios to meet regulatory requirements and support business activities.

This paper aims to explore the mechanism of the slip phenomenon at macro/micro scales, and analyze the effect of slip on fluid flow and heat transfer, to reduce drag and enhance heat transfer.

The improved tangential momentum accommodation coefficient scheme incorporated with Navier’s slip model is introduced to the discrete unified gas kinetic scheme as a slip boundary condition. Numerical tests are simulated using the D2Q9 model with a code written in C++.

Velocity contour with slip at high Re is similar to that without slip at low Re. For flow around a square cylinder, the drag is reduced effectively and the vortex shedding frequency is reduced. For flow around a delta wing, drag is reduced and lift is increased significantly. For Cu/water nanofluid in a channel with surface mounted blocks, drag can be reduced greatly by slip and the highest value of drag reduction (DR) (67.63%) can be obtained. The highest value of the increase in averaged Nu (11.78%) is obtained by slip at Re = 40 with volume fraction φ=0.01, which shows that super-hydrophobic surface can enhance heat transfer by slip.

The present study introduces and proposes an effective and superior method for the numerical simulation of fluid/nanofluid slip flow, which has active guidance meaning and applied value to the engineering practice of DR, heat transfer, flow control and performance improvement.

With respect to the multiple-attribute decision-making problem with subjective preference for a certain attribute whose weight-value range have been given over other attributes whose weight values are unknown, a method based on the mean value of the grey number is proposed to analyse the decision-making problem. This method is used to choose a supply-chain partner under the condition that the decision makers have a preference for a certain attribute of various alternatives. The paper aims to discuss these issues.

First, the middle value of the preferred attribute’s weight-value range is supposed to be its weight value according to the content of the mean value of the grey number. Second, to reflect the decision maker’s subjective preference information, an improved optimisation model that requests the minimum deviation between the actual and expected numerical value of each attribute is constructed to assess the attributes’ weights. Third, the correlated degree and the correlation matrix, which are determined by the weight values of all attributes, are used to rank all the alternatives.

This paper provides a method for making a decision when decision makers have a preference for a certain attribute from an array of various alternatives, and the range of the certain attribute’s weight value is given but the weight value of the other attributes is unknown. When applied to supply-chain partner selection, this method proves feasible and effective.

This method is feasible and effective when applied to supply-chain partner selection, and can be applied to other kinds of decision-making problems. This means it has significant theoretical importance and extensive practical value.

Based on the mean value of the grey number, an optimisation model is built to determine the importance degree of each attribute, then the correlated degree of each alternative is combined to rank all the alternatives. This method can suit the decision makers’ subjective preference for a certain attribute well.