Measuring financial systemic stress for Turkey: A search for the best composite indicator

In this study, we aim to construct a single financial stress indicator (FSI) for Turkey adopting weekly data from between April 2005 and December 2016. To do so, we compose 15 different FSIs using 14 variables that will represent five different markets, i.e. the money market, the bond market, the foreign exchange market, the equity market and the banking sector. We aggregate these five different markets using a variety of techniques, including principal component analysis (PCA), basic portfolio theory, variance equal weights and the Bayesian dynamic factor model. We compare 15 different FSIs on the basis of their relation to, and the forecasting power of, different variables such as the growth rate of industrial production, the OECD business condition index and the OECD composite leading indicator for Turkey. Our results suggest that there is no simple best indicator for Turkey to measure financial systemic stress. Some indicators offer good forecasting power for economic growth while others have a stronger correlation with systemic risk. Therefore, we offer a final FSI for Turkey conducting a model averaging method via a rolling correlation based weighting scheme to benefit from the information content of all the FSIs and observe that the final FSI successfully indicates the tension periods.     

Systemic financial risk indicators and securitised assets: an agent-based framework

The paper presents an agent-based model of a credit economy which includes a securitisation process and a bailout mechanism for bank bankruptcies. Within this framework, banks are able to sell mortgages to a financial vehicle corporation, which finances its activity by creating mortgage-backed securities and selling them to a mutual fund. In turn, the mutual fund collects liquidity by selling shares to households and remunerates them with a monthly interest. The impact of this mechanism is analysed by means of computational experiments for different levels of banks’ securitisation propensity. Furthermore, we study a set of systemic risk indicators which have the aim of assessing the imbalances in the financial system. Two of them are the mortgage-to-GDP ratio and the capital adequacy ratio, which are constructed to detect only the on-balance sheet changes in banks’ credit exposure. We consider two additional indicators, similar to the previous ones with the only difference that they are also able to account for the off-balance sheet items. Moreover, we adopt an indicator, the so-called “virtuous–unvirtuous cycle” indicator, which, besides off-balance assets, targets also the GDP. The results show that higher securitisation propensity weakens the financial stability of banks with relevant effects on different sectors of the economy. Most importantly, the analysis of systemic risk reveals the important issue of designing suitable systemic risk indicators for predicting incoming financial crises, finding that an essential feature of these indicators should be to integrate banks’ off-balance sheet assets.

     

Market perception of sovereign credit risk in the euro area during the financial crisis

We study market perception of sovereign credit risk in the euro area during the financial crisis. In our analysis we use a parsimonious CDS pricing model to estimate the probability of default (PD) and the loss given default (LGD) as perceived by financial markets. In our empirical results the estimated LGDs perceived by financial markets stay comfortably below 40% in most of the samples. Global financial indicators are positively and strongly correlated with the market perception of sovereign credit risk; whilst macroeconomic and institutional developments were at best only weakly correlated with the market perception of sovereign credit risk.     

中国宏观审慎监管预警指标选取及模型构建——基于对国外指标的比较和实证检验

2011年9月国际货币基金组织提议各国构建宏观审慎监管预警系统。在此背景下,本文对中国宏观审慎监管预警指标的选取和模型构建进行了研究。本文首先对亚洲开发银行、欧洲中央银行、国际货币基金组织提出的宏观审慎监管预警指标集进行比较分析,并通过实证检验得出对国外金融危机起到良好预警作用的指标在中国的适用性进行考察。在此基础上,本文选取中国经济体系中反映银行业内部、外部各方面风险来源的指标作为预警指标集,建立线性概率模型,用历史数据进行实证检验,并采用脉冲响应函数对宏观审慎监管指标集中的指标传导机制进行了分析,提出了建立中国监管当局宏观审慎监管预警模型的基本设想。     

The recurrence of financial distress: A survival analysis

Companies often suffer periods of financial distress before filing for bankruptcy. Unlike one-off bankruptcies, financial distress can occur repeatedly within the same individual firm. This paper is focused on the recurrence of financial distress and studies the Chinese stock market, where Special Treatment – an official indicator of financial distress – can be repeatedly applied to a listed company. We employ a stratified hazard model to predict the probability of subsequent distress with variables, including duration dependency, event-based factors, institutional variables, financial ratios, market-based variables and macroeconomic conditions. Our empirical results show that accounting and market-based variables have limited power in predicting the recurrence of distress, whereas the duration of recovery, restructuring events and their interaction terms with the accounting and macroeconomic factors affect the recurrent risk significantly. Tested on out-of-time samples, our proposed hazard models show a robust performance in the prediction of recurrent risk over time.     

Forecasting systemic impact in financial networks

We propose a methodology for forecasting the systemic impact of financial institutions in interconnected systems. Utilizing a five-year sample including the 2008/9 financial crisis, we demonstrate how the approach can be used for the timely systemic risk monitoring of large European banks and insurance companies. We predict firms’ systemic relevance as the marginal impact of individual downside risks on systemic distress. So-called systemic risk betas account for a company’s position within the network of financial interdependencies, in addition to its balance sheet characteristics and its exposure to general market conditions. Relying only on publicly available daily market data, we determine time-varying systemic risk networks, and forecast the systemic relevance on a quarterly basis. Our empirical findings reveal time-varying risk channels and firms’ specific roles as risk transmitters and/or risk recipients.     

Topological properties of reconstructed credit networks and banking systemic risk

Financial bipartite networks provide channels for contagion risks and their topological properties determine financial stability. We enrich the bipartite network reconstruction methods proposed by Ramadiah et al. (2020) and extend them to the Chinese banking system. By comparing the reproducibility of the real credit market and the corresponding systemic risk, the impact of topological properties for different reconstructed bipartite networks on financial stability is analyzed. The empirical evidence shows that network reconstruction methods based on maximum entropy ensembles capture more properties in the real credit network. It also highlights that the different systemic risk level is mainly contributed by the topological properties based on common exposures. These analyses for topological properties provide regulatory insights for systemic risk prevention. It shows that reducing credit similarity across banks while increasing credit diversification in different sectors helps to control systemic risk. The results imply the possibility of increasing financial stability through the macro-regulation of the credit market structure.     

Assessment of time-varying systemic risk in credit default swap indices: Simultaneity and contagiousness

This study assesses systemic risk inherent in credit default swap (CDS) indices using empirical and statistical analyses. We define systemic risk in two perspectives: the possibilities of simultaneous and contagious defaults, and then quantify them separately across benchmark models. To do so, we employ a Marshall-Olkin copula model to measure simultaneous default risk, and an interacting intensity-based model to capture contagious default risk. For an empirical test, we collect daily data for the iTraxx Europe CDS index and its tranche prices in the period from 2005 to 2014, and calibrate model parameters varying across time. In addition, we select forecasting models that have minimal prediction errors for the calibrated time series. Finally, we identify significant changes in each dynamic of systemic risk indicator before and after default and downgrade-related episodes that have occurred in the global financial crisis and European sovereign debt crisis.     

Do credit squeezes influence firm survival? An empirical investigation of China

This paper analyses the effect of a “credit squeeze” policy that was set by the Chinese government in 2007, increasing the strictness for firm-level bank loans. We adopt the difference-in-difference (DID) model to compare the survival rate change before and after the policy was implemented. We further explore the mechanism behind how the “credit squeeze” policy reduced the probability of firms surviving the market from perspectives such as financial constraints and ownership structures. The “credit squeeze” policy significantly increased firms’ operating costs and lowered firms’ productivity. In addition, we find that the zombie firm phenomenon existing in state-owned enterprises has a large impact on our estimation. Our results provide practical policy implications regarding the compromise between systematic debt risk and firm survival.     

TrAffic LIght system for systemic Stress: TALIS3

For the purposes of financial stability, identifying financial institutions that, when in distress, could have a significant adverse impact on financial markets is important. A TrAffic LIght System for Systemic Stress (TALIS-cube) is proposed that provides a comprehensive color-based classification for grouping companies according to both the stress reaction level of the system when the company is in distress and the company’s stress level. TALIS³ can integrate multiple signals from the interaction between different risk metrics. Starting from specific risk indicators, companies are classified by combining two loss functions—one for the system and one for each company—evaluated over time and as a cross section. An aggregated index is also obtained from the color-based classification of companies. TALIS³ can be used to enhance the performance and robustness of existing systemic risk measures. An empirical analysis of the U.S. market is also provided.     

Financial distress and bankruptcy prediction: An appropriate model for listed firms in Vietnam

This paper aims to develop a comprehensive model, the first of its kind in Vietnam, for the purpose of predicting financial distress and bankruptcy at Vietnamese listed firms. The period 2003–2016 is used to study the likelihood of financial distress in different scenarios. Various factors are utilized, including (1) accounting factors in the emerging market score model; (2) market factors in the distance-to-default model; and (3) macroeconomic indicators. The area under the receiver operating characteristics (AUC) curve is used to compare the usefulness of various models that predict financial distress and bankruptcy. Empirical findings from this study show that accounting and market factors, together with macroeconomic fundamental factors, both affect financial distress when they are considered in isolation. However, in a comprehensive model, the effects from accounting factors appear to be more significant than those from market-based factors. The default prediction model, which includes accounting factors with macroeconomic indicators, appears to perform much better than the model comprising market-based factors with macroeconomic fundamentals.     

Economic indicators and stock market volatility in an emerging economy

By analyzing the daily realized volatility series calculated from intraday stock price observations, this study examines the direct causality between one-day-ahead aggregate stock market volatility and several economic and financial indicators in the Korean market, a leading emerging market. Using the predictive regression and superior predictive ability tests, we find that the model-free implied volatility index (VKOSPI) and stock market indicators both lead the daily market volatility. However, daily economic indicators provide no predictive information beyond that contained in historical volatility. Though in-sample causality does not guarantee a better out-of-sample forecasting performance, the VKOSPI and combinations of predictors exhibit significant predictive ability regardless of the time period. Our study verifies the information role of the VKOSPI as an indicator of daily market risk.     

Analyzing credit risk transmission to the nonfinancial sector in Europe: A network approach

We use a factor model and elastic net shrinkage to model a high-dimensional network of European credit default swap (CDS) spreads. Our empirical approach allows us to assess the joint transmission of bank and sovereign risk to the nonfinancial corporate sector. Our findings identify a sectoral clustering in the CDS network, where financial institutions are in the center and nonfinancial entities as well as sovereigns are grouped around the financial center. The network has a geographical component reflected in different patterns of real-sector risk transmission across countries. Our framework also provides dynamic estimates of risk transmission, a useful tool for systemic risk monitoring.     

Credit default swaps and sovereign debt markets

This study investigates the link between the price discovery dynamics in sovereign credit default swaps (CDS) and bond markets and the degree of financial integration of emerging markets. Using CDS and sovereign bond spreads, the price discovery mechanism was tested using a vector error correction model. Financial integration is measured using news-based methods. We find that sovereign CDS and bond markets are co-integrated. In five out of seven sovereigns (71%), the bond market leads in price discovery by adjusting to new information regarding credit risk before CDS. In 29% of times, CDS markets are the source of price discovery. We also find a positive correlation of 0.67 between the degree of financial integration and the bond market information share. The evidence suggests that changes in sovereign credit risk and bond yields are significantly influenced by common external (global) factors, while country-specific factors play an insignificant role.     

Robustness of banking networks to idiosyncratic and systemic shocks: a network-based approach

We propose a network-based structural model of credit risk to demonstrate how idiosyncratic and systemic shocks propagate across the banking system and evaluate the costs. The banking system is built as a network of heterogeneous banks which are connected with one another. In such a system, single credit events propagate through the interbank market from debtors to creditors and across the system. The shock is imposed as an unexpected event. We demonstrate that while idiosyncratic shocks cannot substantially disturb the banking system, a systemic shock of even a moderate magnitude can be highly detrimental. Such shock includes a huge contagious potential. We demonstrate that the costs of the shock are largely determined by the extent of contagion and range from negligible to catastrophic. The results imply that a severe crisis has to be initiated by a systemic shock of at least moderate magnitude. Capital ratio and the bank size are two additional factors of the banking system stability. Finally, credit risk analysis is sensitive to the network topology and exhibits a profound nonlinear characteristic.     

Spillover effects in oil-related CDS markets during and after the sub-prime crisis

This paper investigates the return and volatility spillover effects across oil-related credit default swaps (CDSs), the oil market, and financial market risks for the US during and after the subprime crises. The empirical analysis is based on monthly return and realized volatility data from February 2004 to April 2020. We estimate both static and dynamic generalized dynamic spillover measures based on vector autoregressive (VAR) models. Our full sample empirical findings show that the oil market is the primary source of risk transmission for all the oil-related credit default swaps, while the bond market is the highest source of risk transmission to the stock market and vice versa. We also provide evidence that the regulated monopoly US utility sector has the least role in volatility transmission. Furthermore, the bailout program conducted by the US Treasury and Federal Reserve helped stabilize the US financial market through the purchase of toxic assets after the subprime financial crisis. We find strong evidence that the federal funds rate hike cycles lessen total risk transmission throughout the US bond market. Finally, our findings assert that oil price shocks have a significant effect on the oil-related CDSs in some sub-periods via the demand and supply transmission channels.     

Central bank disclosure as a macroprudential tool for financial stability

The Basel Capital Accord (pillar 3) states that disclosure of information (transparency) is essential to financial stability. This study analyzes, through inflation reports, the disclosure of information from the Central Bank of Brazil concerning the credit market. We consider credit risk and capital buffers as measures of financial stability in this analysis. Furthermore, in order to measure the perception of the monetary authority on the credit market, we built two indices based on the central bank’s communication on credit development. We performed a panel data analysis based on a sample of 125 banks for the period from June 1999 to September 2014 (7000 observations). The findings suggest that central bank communication regarding expectations concerning the credit market contributes to financial stability. Therefore, this kind of communication of central banks (about credit development) may constitute an important macroprudential tool to improve financial stability.     

Market Risk Disclosures and Investment Efficiency: International Evidence from the Gulf Cooperation Council Financial Firms

This study examines the association between market risk disclosures (MRDs) and the investment efficiency of financial firms from six emerging markets in the Gulf Cooperation Council (GCC) region. Based on a sample of 553 firm‐year observations over the 2007–2011 period, we find that MRDs are significantly and negatively associated with both under‐investment and over‐investment and that this association is more pronounced for larger firms. We also find that the association between MRDs and under‐investment is moderated during periods of economic distress such as the Global Financial Crisis of 2008 and that the association between MRDs and over‐investment is magnified during periods of reduced financial distress. Our results are consistent with the idea that MRDs reduce information asymmetry, which ultimately improves investment efficiency. We contribute to the literature in an emerging market context by providing empirical evidence on the association between MRDs and investment efficiency across six emerging GCC capital markets. This study also fills a gap in the literature by providing evidence on the factors affecting the investment efficiency of financial firms.     

Assessing optimal credit growth for an emerging banking system

The paper sets forth a novel way to estimate the optimal level of credit growth for an emerging banking system. Contrary to the traditional credit-to-GDP gap indicator, credit growth is considered to be optimal when it does not accelerate credit risk measured by loan loss provisions. We provide empirical support for modelling the provision charge ratio dynamic by the quadratic function of the credit growth deviation from its optimal level. The operational framework consists of a simplified financial satellite with two equations representing credit growth and change in the provision charge ratio. Our empirical results show that a 3 percent (±1 pp margin) quarterly increase in credit to the private sector is, in nominal terms, optimal for financial stability and sustainable growth in Romania.     

Banks’ risk taking,financial innovation and macroeconomic risk

This paper shows how financial innovation in combination with the fall of macroeconomic risk can explain the strong growth of the primary and secondary credit markets in the U.S. economy. We document empirically the fall in macroeconomic risk, the expansion of the prime and secondary credit market and we provide evidence that changes in macroeconomic risk are closely related to the evolution of the prime market. In the theoretical part of the paper we study in a simple portfolio optimization framework the effect of financial innovation and macroeconomic risk on banks’ risk taking. The results of the model show that financial innovation increases bank appetite for risky investment both in the prime and secondary markets and that this effect is stronger in environments with low aggregate macroeconomic risk. In addition the banking system becomes less stable because of the portfolio risk of each individual bank increases.