How Do Banks Determine Their Capital Buffer? Evidence from Indonesian Bank

Objective: This study aims to investigate how banks determine their capital buffer. Return on Equity (ROE), Non-Performing Loans (NPL), Capital Buffer Lag (BUFFt-1), Loan to Total Assets (LOTA), and Income Diversification (IDIV) are some of the variables examined in this study. Research Design & Methods: Purposive sampling was used to collect samples for this study. It was 20 of the 42 conventional commercial banks that were listed on the Indonesia Stock Exchange in 2012-2016. In this study, multiple regression analysis was used, as well as the ordinary and two-stage least squares methods. Findings: The results of this study have shown that the capital buffer has a negative impact on return on equality (ROE) and income diversification (IDIV). The capital buffer was affected by Lag of Capital Buffer. This research examines how a bank can make a profit from the negative impact of ROE. Based on the results of the tests, the Indonesian Bank has not pursued the highest possible capital buffer. Implications & Recommendations: Companies will use their profit to further profitable activities when they fulfill a minimum capital buffer requirement. Contribution & Value Added: The results of this study try to give an idea for the management of capital and capital buffers and to determine the ideal strategy for investors and banks to meet the Basel and Government regulation. This research tries to add insight into the internal factors that determine capital buffers at conventional commercial banks in Indonesia, as well as research references in the field of financial management, particularly capital buffers.

A Novel Control Theoretic Model for Resilient Packet Ring (RPR) Fairness

Resilient Packet Ring (RPR) is a new Data Link Layer ring protocol. In RPR, the ring is a shared medium for multiple nodes compete to get a portion of shared bandwidth. Fairness algorithm is responsible for allocating fair bandwidth among competing nodes. In our research, we address the stability problems of the current RPR Fairness and introduce a new solution. The present work is the first control theoretic approach to RPR Fairness and Congestion Control that rigorously models the dynamics of RPR Fairness algorithm by using control theory. The key idea is to involve the active nodes in the Fairness and Queue Congestion Control process which means developing a decentralized control system. In RPR, when the number of nodes or the distance between the RPR nodes is high, the delay plays an important role in the behavior of the fairness which may lead to oscillation, instability and packet loss. We propose the implementation of Smith predictor as a valuable technique to overcome the effects of this delay and achieve higher throughput. Our new theoretical insights allow us to design fairness and congestion control algorithms that achieve fair bandwidth allocation and high throughput with small buffer requirement even in presence of large delay and large number of active nodes in the ring.

A Novel Control Theoretic Model for Resilient Packet Ring (RPR) Fairness

Resilient Packet Ring (RPR) is a new Data Link Layer ring protocol. In RPR, the ring is a shared medium for multiple nodes compete to get a portion of shared bandwidth. Fairness algorithm is responsible for allocating fair bandwidth among competing nodes. In our research, we address the stability problems of the current RPR Fairness and introduce a new solution. The present work is the first control theoretic approach to RPR Fairness and Congestion Control that rigorously models the dynamics of RPR Fairness algorithm by using control theory. The key idea is to involve the active nodes in the Fairness and Queue Congestion Control process which means developing a decentralized control system. In RPR, when the number of nodes or the distance between the RPR nodes is high, the delay plays an important role in the behavior of the fairness which may lead to oscillation, instability and packet loss. We propose the implementation of Smith predictor as a valuable technique to overcome the effects of this delay and achieve higher throughput. Our new theoretical insights allow us to design fairness and congestion control algorithms that achieve fair bandwidth allocation and high throughput with small buffer requirement even in presence of large delay and large number of active nodes in the ring.

Part V Liquidity and Leverage, 23 The Leverage Ratio

This chapter discusses the leverage ratio under Basel 3. The leverage ratio was initially implemented as a disclosure standard, with the aim of becoming a mandatory requirement as from 1 January 2018. Basel 3 provides that the original 2014 standard should become binding as a requirement from 2018 to 2021, with the revised Basel 3 requirement taking effect as from 1 January 2022. All banks are required to maintain a leverage ratio of 3 per cent at all times. However, in addition to the 3 per cent requirement, they must also meet a leverage ratio buffer requirement. Both of these requirements must be met with tier 1 capital. The leverage ratio buffer will be set at 50 per cent of a bank's G-SIB buffer.

Nonpermutation flow line scheduling by ant colony optimization

A flow line is a conventional manufacturing system where all jobs must be processed on all machines with the same operation sequence. Line buffers allow nonpermutation flowshop scheduling and job sequences to be changed on different machines. A mixed-integer linear programming model for nonpermutation flowshop scheduling and the buffer requirement along with manufacturing implication is proposed. Ant colony optimization based heuristic is evaluated against Taillard's (1993) well-known flowshop benchmark instances, with 20 to 500 jobs to be processed on 5 to 20 machines (stages). Computation experiments show that the proposed algorithm is incumbent to the state-of-the-art ant colony optimization for flowshop with higher job to machine ratios, using the makespan as the optimization criterion.

Network Calculus Based Dimensioning for Industrial Wireless Mesh Networks

Wireless Mesh network is widely adopted in both wideband mobile communication network and short distance RF industrial network. As for the latter field, network robustness and real-time are two important issues. Network dimensioning is therefore required for this kind of networks. We models wireless mesh network as four tuples and present a topology transform methodology to change the mesh topology to a cluster tree. Research results from network calculus theory are then applied to obtain key merits such as buffer requirement, bandwidth requirement and end to end delay bound.

Analyzing Buffer Requirement for Wireless Enhancement of TCP in Network Mobility

On-board TCP (obTCP) has been shown to address the dual wireless link related issues in network mobility (NEMO) effectively. obTCP uses agents at both base station (BS) and mobile router (MR). The agents store incoming TCP packet in a buffer for future possible retransmissions over the wireless links. Since the number of TCP connections passing through the MR could be very large, the amount of memory space required for the buffers may become very high. This may put the deployment of obTCP in question. So, in this paper, the authors investigate the buffer requirement problem of obTCP at MR for each TCP connection. For this purpose, they describe a Markov model to keep track of the packet transmission process of MR. The buffer size for each TCP connection is represented as a function of loss probability of the wireless links. Interestingly, from the numerical results, the authors find that the buffer size requirement at MR is significantly low for each TCP connections. This observation claims possible implementation of obTCP in NEMO.