银行间同业拆借利率的影响因素模型实证研究

本文选取银行间同业拆借市场利率作为货币市场利率的代表,分析银行间同业拆借市场利率变化的影响因素;基于变量的平稳性检验、协整性检验和格兰杰因果关系检验结果,对影响银行间同业拆借市场利率的主要因素进行了实证研究。误差修正模型结果表明,从长期看,拆借利率与贷款利率和超额准备金利率成正比,与存款利率成反比;从短期看,拆借利率与当期贷款利率、滞后一期的拆借利率、滞后一期的超额准备金利率成正比,与滞后一期的存款利率成反比,最后探讨了该模型的政策含义。     

我国金融市场中基准利率的选择

本文从资产定价角度给出了基准利率选择的理论框架,并对我国市场中的利率体系进行研究。我们发现,在均值一方差标准下,银行间隔夜同业拆借利率和银行间隔夜国债回购利率并不是最有效的;银行间同业拆借市场与银行间国债回购市场内部各利率与期限之间的关系不是单调的;银行间同业拆借市场利率与银行间国债回购利率之间并不存在绝对的占优关系;相比之下,存款利率尤其是活期存款利率最有效从而更适合作为其他资产定价的依据,应该成为我国目前金融市场的基准利率。最后,本文给出了相应的建议。     

我国同业拆借市场的现状及问题

银行同业拆借是银行之间的融资 ,主要通过买卖他们在中央银行的超额存款准备金来达到短期融资的目的 ,同业拆借市场是迄今为止中国货币市场中发展最快、成交额最大的一类市场。我国同业拆借市场于８０年代中期形成 ,１９９６年全国统一同业拆借市场开始运行。商业银行总行、商业银行授权分行、城市商业银行、融资中心成员通过全国银行间拆借中心的电子网络交流拆借信息 ,被称为“一级网” ;其他金融机构仍主要由融资中心组织拆借。由于央行对金融机构拆借统计信息和公布银行间拆借利率的需要 ,各省融资中心要将数据通过计算机网络报告人民银…     

全国银行间同业拆借中心发布银行间回购定盘利率

回购定盘利率（Fixing Repo Rate）是中国人民银行授权全国银行间同业拆借中心发布的全国银行间债券市场具有基准性质的市场利率之一，是银行羊市场指标体系的重要组成部分。银行羊回购定盘利率是以银行间市场每天上午9：00-11：00间的回购交易利率为基础同时借鉴国际经验编制而成的基准性利率指标，     

我国银行间同业拆借市场有效性分析

从市场内部和外部两个角度实证分析银行间同业拆借市场的有效性,结果表明:银行间同业拆借市场利率服从随机游走过程,而且相互间存在协整关系,从市场内部可以判断市场是有效的;银行间同业拆借市场与债券回购市场同期限的利率具有正向的协整关系,两个市场的利率具有趋同性,从市场外部判断市场也是有效的.银行间同业拆借市场的有效性对我国基准利率的选择、利率市场化以及货币政策的有效性等方面具有重要启示.     

我国民间信贷利率影响因素研究

近年来,我国"二元化"结构逐渐形成,正规经济市场上的长期金融结构失衡突显,银行在投融资体系中的地位有所下降,新常态下放宽民间信贷的政策将促使民间经济进一步发展。其中,利率是民间信贷的动力机制,也是民间金融市场运作的核心问题。本文从多角度分析各种影响因素与民间信贷利率之间的互动关系,选取2010年—2016年之间银行一年短期贷款利率、存款准备金率、银行间同业拆借利率、居民消费价格总指数、GDP增长率的季度数据,利用VAR模型,得出民间利率与一年期贷款利率、存款准备金率、同业拆借利率之间有着一定的相互作用关系,而与居民消费价格指数、GDP增长率基本没有关系。最后希望政府加强顶层构建,建立好监测体系与征信体系,以期民间信贷健康发展。     

知识窗

一、SHIBOR推出的背景 目前，我国货币市场存在多种利率，包括债券回购利率、同业拆借利率、央行票据发行利率、短期国债利率、短期融资券利率、商业票据利率等，但是缺乏真正市场化的基准利率。近年来央行一直在努力构建我国货币市场的基准利率体系。1996年开始推出银行间同业拆借利率即CHIBOR。2004年10月，银行同业拆借中心发布债券7天回购利率作为货币市场基准利率的参考指标。2006年3月，同业拆借中心又对外发布了期限为隔夜和7天的银行间回购定盘利率，     

利率市场化时机和实施步骤的思考

利率市场化是大势所趋,现在贷款已经完全放开利率管制,存款还没有放开。放开存款利率上限管制,虽然是一种政府决策行为,但是也不是一种“拍脑袋”行为,而是由利率市场化内在规律在起作用,过早或过晚放开存款利率上限管制都不合适。本文就存款利率市场化应具备的几个经济金融条件和具体实施步骤提出了自己的思考．指出存款资金不再是较稀缺资源是存款利率市场化时机成熟的市场外部条件,银行经营以价值创造而不是以存款市场份额为核心的经营理念是存款利率市场化时机成熟的银行内部条件,银行存款利率与市场需求利率相接近时是存款利率市场化时机成熟的技术条件,实施存款保险制度是存款利率市场化的控险兜底条件,放开银行间拆借市场是实施利率市场化的第一步,放开银行理财产品是实施利率市场化的第二步,逐步提高存款利率浮动幅度限制是实施利率市场化的第三步,这样可以实现利率市场化的自然过渡而不至于引起经济金融的大幅波动。     

同业市场缩量运行 利率企稳尚需时日——2003年第三季度银行间同业拆借与债券系统交易情况综述

2003年第三季度，全国银行间同业市场拆借利率与回购利率打破长期在低位徘徊的沉寂局面、大幅上涨；市场资金面由松趋紧，受此影响，银行间拆借回购利率不断攀升；现券市场走出一轮下跌行情，收益率震荡走高，季末呈现缩量运行的态势。     

“钱荒”是怎么回事？

进入6月份,银行间同业拆借市场利率迅速攀升,其中隔夜拆借利率涨幅尤为迅猛,从4．5％起步,盘中先后攻破10％、20％、30％大关,不断刷新银行间市场成立以来的历史纪录。一时间,银行缺钱的言论甚嚣尘上,“钱荒”一词随处可见。     

Modelling the emergence of the interbank networks

Interbank contagion has become a buzzword in the aftermath of the financial crisis that led to a series of shocks to the interbank market and to periods of pronounced market disruptions. However, little is known about how interbank networks are formed and about their sensitivity to changes in key bank parameters (for example, induced by common exogenous shocks or by regulatory initiatives). This paper aims to shed light on these issues by modelling endogenously the formation of interbank networks, which in turn allows for checking the sensitivity of interbank network structures and hence, their underlying contagion risk to changes in market-driven parameters as well as to changes in regulatory measures such as large exposures limits. The sequential network formation mechanism presented in the paper is based on a portfolio optimization model, whereby banks allocate their interbank exposures while balancing the return and risk of counterparty default risk and the placements are accepted taking into account funding diversification benefits. The model offers some interesting insights into how key parameters may affect interbank network structures and can be a valuable tool for analysing the impact of various regulatory policy measures relating to banks’ incentives to operate in the interbank market.     

Contagion in the interbank market and its determinants

Carrying out interbank contagion simulations for the German banking sector for the period from the first quarter of 2008 to the second quarter of 2011, we obtain the following results: (i) The system becomes less vulnerable to direct interbank contagion over time. (ii) The loss distribution for each point in time can be condensed into one indicator, the expected number of failures, without much loss of information. (iii) Important determinants of this indicator are the banks’ capital, their interbank lending in the system, the loss given default and how equal banks spread their claims among other banks.     

A network model of systemic risk: stress testing the banking system1

Although there are many definitions of systemic risk, most agree that it manifests itself by an initial shock that results in the failure of one or more banks and then spreads out to the entire system by a contagion mechanism which can result in the failure of more banks in the system. Assuming that bank failures in the initial shock are randomly dependent on the failure probabilities of the individual banks and that the ensuing contagion process is deterministic, depending on interbank exposures, in this paper we propose a network model to analyse systemic risk in the banking system that, in contrast to other proposed models, seeks to obtain the probability distribution of losses for the financial system resulting from the shock/contagion process. Thus, calculating the probabilities of joint failures by simulation and assuming that the matrix of bilateral interbank exposures is known, we represent systemic risk in the financial system by means of a graph and use discrete modelling techniques to characterize the dynamics of contagion and corresponding losses within the network. The probability distribution of losses, risk profile for the Mexican banking system, is obtained through an efficient, complete enumeration procedure of all possible bank default events in the system. This, in turn, allows the use of the wide variety of well-established risk measures to describe the fragility of the financial system. Additionally, the model allows us to perform stress tests along both the bank default probabilities and the interbank exposures and is used to assess the risk of the Mexican banking system. Copyright © 2009 John Wiley & Sons, Ltd.     

Interbank Credit Lines as a Channel of Contagion

This paper assesses the potential for contagion in the Swiss interbank market using new data on bilateral bank exposures as well as on credit lines. A simulation approach is applied to assess the banking system's inherent instability. Moreover, the spill-over effects of a simulated default situation in the interbank market on the liquidity and solvency of banks are measured. The main findings are, first, that there is a substantial potential for contagion. Second, the exposure as well as the credit line contagion channel are relevant for Switzerland. Third, a lender of last resort intervention could reduce spill-over effects remarkably. Finally, the structure of the interbank market has considerable impact on its resilience against spill-over effects: Centralized markets are more prone to contagion than homogenous ones. JEL classification: C81, G21. The opinions expressed herein are my own and not those of the Swiss National Bank.     

The effect of the interbank network structure on contagion and common shocks

This paper proposes a dynamic multi-agent model of a banking system with central bank. Banks optimize a portfolio of risky investments and riskless excess reserves according to their risk, return, and liquidity preferences. They are linked via interbank loans and face stochastic deposit supply. Comparing different interbank network structures, it is shown that money-centre networks are more stable than random networks. Evidence is provided that the central bank stabilizes interbank markets in the short run only. Systemic risk via contagion is compared with common shocks and it is shown that both forms of systemic risk require different optimal policy responses.     

Investigating risk contagion initiated by endogenous liquidity shocks: evidence from the US and eurozone interbank markets

This paper investigates liquidity spillovers between the US and European interbank markets during turbulent and tranquil periods. We show that an endogenous model with time-varying transition probabilities is effective in describing the propagation of liquidity shocks within the interbank market, while predicting liquidity crashes characterised by changed dynamics. We show that liquidity shocks, originating from movements of the spread between the Asset Backed Commercial Paper and T-bill, drive regime changes in the euro fixed-float OIS swap rate. Our results support the idea of endogenous contagion from the US money market to the eurozone money market during the global financial crisis.     

Financial contagion and the role of the central bank

We investigate the role of a central bank (CB) in preventing and avoiding financial contagion. The CB, by imposing reserve requirements on the banking system, trades off the cost of reducing the resources available for long-term investment with the benefit of raising liquidity to face an adverse shock that could cause contagious crises. We argue that contagion is not due to the structure of the interbank deposit market, but to the impossibility to sign contracts contingent on unforeseen contingencies. As long as incomplete contracts are present, the CB may have a useful role in curbing contagion. Moreover, the CB allows the banking system to reach first-best allocation in all the states of the world when the notion of incentive-efficiency is considered. If the analysis is restricted to constrained-efficiency, the CB still avoids contagion without, however, reaching first-best consumption allocation. The model provides a rationale for reserve requirements without the presence of fiat money or asymmetric information.     

Assessing financial contagion in the interbank market: Maximum entropy versus observed interbank lending patterns

Interbank markets allow banks to cope with specific liquidity shocks. At the same time, they may represent a channel for contagion as a bank default may spread to other banks through interbank linkages. This paper analyses how contagion propagates within the Italian interbank market using a unique data set including actual bilateral exposures. Based on the availability of information on actual bilateral exposures for all Italian banks, the results obtained by assuming the maximum entropy are compared with those reflecting the observed structure of interbank claims. The comparison indicates that, under certain circumstances, depending on the structure of the interbank linkages, the recovery rates of interbank exposures and banks’ capitalisation, the maximum entropy approach overrates the scope for contagion.     

Modelling Deposit Insurance Scheme Losses in a Basel 2 Framework

This paper extends the existing literature on deposit insurance by proposing a new approach for the estimation of the loss distribution of a Deposit Insurance Scheme (DIS) that is based on the Basel 2 regulatory framework. In particular, we generate the distribution of banks’ losses following the Basel 2 theoretical approach and focus on the part of this distribution that is not covered by capital (tail risk). We also refine our approach by considering two major sources of systemic risks: the correlation between banks’ assets and interbank lending contagion. The application of our model to 2007 data for a sample of Italian banks shows that the target size of the Italian deposit insurance system covers up to 98.96% of its potential losses. Furthermore, it emerges that the introduction of bank contagion via the interbank lending market could lead to the collapse of the entire Italian banking system. Our analysis points out that the existing Italian deposit insurance system can be assessed as adequate only in normal times and not in bad market conditions with substantial contagion between banks. Overall, we argue that policy makers should explicitly consider the following when estimating DIS loss distributions: first, the regulatory framework within which banks operate such as (Basel 2) capital requirements; and, second, potential sources of systemic risk such as the correlation between banks’ assets and the risk of interbank contagion.     

Contagion risk in the interbank market: a probabilistic approach to cope with incomplete structural information

One lesson of the financial crisis erupting in 2008 has been that domino effects constitute a serious threat to the stability of the financial sector, i.e. the failure of one node in the interbank network might entail the danger of contagion to large parts of the entire system. How important this effect is, depends on the exact topology of the network on which the supervisory authorities have typically very incomplete knowledge. In order to explore the extent of contagion effects and to analyse the effectiveness of macroprudential measures to contain such effects, a reconstruction of the quantitative features of the empirical network would be needed. We propose a probabilistic approach to such a reconstruction: we propose to combine some important known quantities (like the size of the banks) with a realistic stochastic representation of the remaining structural elements. Our approach allows us to evaluate relevant measures for the contagion risk after default of one unit (i.e. the number of expected subsequent defaults, or their probabilities). For some quantities we are able to derive closed form solutions, others can be obtained via computational mean-field approximations.