Lack of Critical Slowing Down Suggests that Financial Meltdowns Are Not Critical Transitions, yet Rising Variability Could Signal Systemic Risk

Complex systems inspired analysis suggests a hypothesis that financial meltdowns are abrupt critical transitions that occur when the system reaches a tipping point. Theoretical and empirical studies on climatic and ecological dynamical systems have shown that approach to tipping points is preceded by a generic phenomenon called critical slowing down, i.e. an increasingly slow response of the system to perturbations. Therefore, it has been suggested that critical slowing down may be used as an early warning signal of imminent critical transitions. Whether financial markets exhibit critical slowing down prior to meltdowns remains unclear. Here, our analysis reveals that three major US (Dow Jones Index, S&P 500 and NASDAQ) and two European markets (DAX and FTSE) did not exhibit critical slowing down prior to major financial crashes over the last century. However, all markets showed strong trends of rising variability, quantified by time series variance and spectral function at low frequencies, prior to crashes. These results suggest that financial crashes are not critical transitions that occur in the vicinity of a tipping point. Using a simple model, we argue that financial crashes are likely to be stochastic transitions which can occur even when the system is far away from the tipping point. Specifically, we show that a gradually increasing strength of stochastic perturbations may have caused to abrupt transitions in the financial markets. Broadly, our results highlight the importance of stochastically driven abrupt transitions in real world scenarios. Our study offers rising variability as a precursor of financial meltdowns albeit with a limitation that they may signal false alarms.

Global Systemic Risk and International Regulatory Coordination: Squaring Sovereignty and Financial Stability

In recent years much attention has been given to systemic risk and maintaining financial stability. Much of the focus, rightly, has been on market failures and the role of regulation in addressing them. This article looks at the role of domestic policies and government actions as sources of global instability. The global financial system is built upon global markets controlled by national financial and macroeconomic policies. In this context, regulatory asymmetries, diverging policy preferences, and government failures add a further dimension to global systemic risk not present at the national level.
Systemic risk is a result of the interplay between two independent variables: an underlying trigger event, in this analysis a domestic policy measure, and a transmission channel. The solution to systemic risk requires tackling one of these variables. In a domestic setting, the centralization of regulatory power into one single authority makes it easier to balance the delicate equilibrium between enhancing efficiency and reducing instability. However, in a global financial system in which national financial policies serve to maximize economic welfare, regulators will be confronted with difficult policy and legal tradeoffs.
We investigate the role that financial regulation plays in addressing domestic policy failures and in controlling the danger of global financial interdependence. To do so we analyse global financial interconnectedness, and explain its role in transmitting instability; we investigate the political economy dynamics at the origin of regulatory asymmetries and government failures; and we discuss the limits of regulation.

Systemic risk for financial institutions in UK

Marginal Expected Shortfall (MES) is an approach used to measure the systemic risk financial institutions face. It estimates how significantly systemic events (poor market performance, out of 1.6 times Standard Deviation borders) are expected to affect market capitalization of a particular firm. The concept was developed in the late 2000s and is widely used for cross-country comparisons of financial firms. For the purposes of generalization of this technique it is often used with market data containing non-domestic currencies for some financial firms. That may lead to results having currency noise in them as it is shown for 77 UK financial firms in our analysis between 2001 and 2014.

A Network model of systemic risk : identifying the sources of dependence across institutions

We design a financial network model that explicitly incorporates linkages across institutions through a direct contagion channel, as well as an indirect common exposure channel. In particular, common exposure is setup so as to link the financial to the real sector. The model is calibrated to balance sheet data on the colombian financial sector. Results indicate that commercial banks are the most systemically important financial institutions in the system. Whereas government owned institutions are the most vulnerable institutions in the system.

International office investment in global cities: the production of financial space and systemic risk

The paper explores the relationships between UK commercial real estate and regional economic development as a foundation for the analysis of the role of real estate investment in local economic development. Linkages between economic growth, development, real estate performance and investment allocations are documented. Long-run regional property performance is not the product of long-run economic growth, and weakly related to indicators of long-run supply and demand. Changes in regional portfolio weights seem driven by neither market performance nor underlying fundamentals. In the short run, regional investment shifts show no clear leads or lags with market performance.

We're Chained: an analysis of systemic risk in finance

This dissertation presents two papers on how to deal with simple systemic risk measures to assess portfolio risk characteristics. The first paper deals with the Granger-causation of systemic risk indicators based in correlation matrices in stock returns. Special focus is devoted to the Eigenvalue Entropy as some previous literature indicated strong re- sults, but not considering different macroeconomic scenarios; the Index Cohesion Force and the Absorption Ratio are also considered. Considering the S&P500, there is not ev- idence of Granger-causation from Eigenvalue Entropies and the Index Cohesion Force. The Absorption Ratio Granger-caused both the S&P500 and the VIX index, being the only simple measure that passed this test. The second paper develops this measure to capture the regimes underlying the American stock market. New indicators are built using filtering and random matrix theory. The returns of the S&P500 is modelled as a mixture of normal distributions. The activation of each normal distribution is governed by a Markov chain with the transition probabilities being a function of the indicators. The model shows that using a Herfindahl-Hirschman Index of the normalized eigenval- ues exhibits best fit to the returns from 1998-2013.

Systemic risk in dynamical networks with stochastic failure criterion

Complex non-linear interactions between banks and assets we model by two time-dependent Erdos-Renyi network models where each node, representing a bank, can invest either to a single asset (model I) or multiple assets (model II). We use a dynamical network approach to evaluate the collective financial failure -systemic risk- quantified by the fraction of active nodes. The systemic risk can be calculated over any future time period, divided into sub-periods, where within each sub-period banks may contiguously fail due to links to either i) assets or ii) other banks, controlled by two parameters, probability of internal failure p and threshold T-h ("solvency" parameter). The systemic risk decreases with the average network degree faster when all assets are equally distributed across banks than if assets are randomly distributed. The more inactive banks each bank can sustain (smaller T-h), the smaller the systemic risk -for some Th values in I we report a discontinuity in systemic risk. When contiguous spreading becomes stochastic ii) controlled by probability p(2) -a condition for the bank to be solvent (active) is stochasticthe- systemic risk decreases with decreasing p(2). We analyse the asset allocation for the U.S. banks. Copyright (C) EPLA, 2014

Granger causality and systemic risk

Building on the concept of Granger causality in risk in Hong et al. (2009), and focusing on an international sample of large-capitalization banks, we test for predictability in comovements in the left tails of returns of individual banks and the global system. The main results show that large individual shocks (defined as balance-sheet contractions exceeding the 1% VaR level) are a strong predictor of subsequent shocks in the global system. This evidence is particularly strong for US banks with large desks of proprietary trading. Similarly, we document strong evidence of financial vulnerabilities (exposures) to systemic shocks in US subprime creditors.

Confidence sets for asset correlations in portfolio credit risk

Asset correlations are of critical importance in quantifying portfolio credit risk and economic capitalin financial institutions. Estimation of asset correlation with rating transition data has focusedon the point estimation of the correlation without giving any consideration to the uncertaintyaround these point estimates. In this article we use Bayesian methods to estimate a dynamicfactor model for default risk using rating data (McNeil et al., 2005; McNeil and Wendin, 2007).Bayesian methods allow us to formally incorporate human judgement in the estimation of assetcorrelation, through the prior distribution and fully characterize a confidence set for the correlations.Results indicate: i) a two factor model rather than the one factor model, as proposed bythe Basel II framework, better represents the historical default data. ii) importance of unobservedfactors in this type of models is reinforced and point out that the levels of the implied asset correlationscritically depend on the latent state variable used to capture the dynamics of default,as well as other assumptions on the statistical model. iii) the posterior distributions of the assetcorrelations show that the Basel recommended bounds, for this parameter, undermine the levelof systemic risk.

Ownership, occupation and risk: a view of the City of London office market

Office returns in the City of London are more volatile than in other UK markets. This volatility may reflect fluctuations in capital flows associated with changing patterns of ownership and the growing linkage between real estate and financial markets in the City. Using current and historical data, patterns of ownership in the City are investigated. They reveal that overseas ownership has grown markedly since 1985, that owners are predominantly FIRE-sector firms and that there are strong links between ownership and occupation. This raises concerns about future volatility and systemic risk in a market strongly influenced by the cyclical behaviour and shocks of the international financial system.

International investment, ownership and risk in the City of London office market: an analysis of trends 1972-1997

Office returns in the City of London are more volatile than in other UK markets. This volatility may reflect fluctuations in capital flows associated with changing patterns of ownership and the growing linkage between real estate and financial markets in the City. Using current and historical data, patterns of ownership in the City are investigated. They reveal that overseas ownership has grown markedly since 1985, that owners are predominantly FIRE sector firms and that there are strong links between ownership and occupation. This raises concerns about future volatility and systemic risk.

Essays on Bank Risk

This PhD Thesis is composed of three chapters, each discussing a specific type of risk that banks face. The first chapter talks about Systemic Risk and how banks get exposed to it through the Interbank Funding Market. Exposures in the said market have Systemic Risk implications because the market creates linkages, where the failure of one party can affect the others in the market. By showing that CDS Spreads, as bank risk indicators, are positively related to their Net Interbank Funding Market Exposures, this chapter establishes the above Systemic Risk Implications of Interbank Funding. Meanwhile, the second chapter discusses how banks may handle Illiquidity Risk, defined as the possibility of having sudden funding needs. Illiquidity Risk is embodied in this chapter through Loan Commitments as they oblige banks to lend to its clients, up to a certain amount of funds at any time. This chapter points out that using Securitization as funding facility, could allow the banks to manage this Illiquidity Risk. To make this case, this chapter demonstrates empirically that banks having an increase in Loan Commitments, may experience an increase in risk profile but such can be offset by an accompanying increase in Securitization Activity. Lastly, the third chapter focuses on how banks manage Credit Risk also through Securitization. Securitization has a Credit Risk management property by allowing the offloading of risk. This chapter investigates how banks use such property by looking at the effect of securitization on the banks’ loan portfolios and overall risk and returns. The findings are that securitization is positively related to loan portfolio size and the portfolio share of risky loans, which translates to higher risk and returns. Thus, this chapter points out that Credit Risk management through Securitization may be have been done towards higher risk taking for high returns.

Implant therapy in a surgical specialty clinic: an analysis of patients, indications, surgical procedures, risk factors, and early failures

PURPOSE The aim of this study was to analyze the patient pool referred to a specialty clinic for implant surgery over a 3-year period. MATERIALS AND METHODS All patients receiving dental implants between 2008 and 2010 at the Department of Oral Surgery and Stomatology were included in the study. As primary outcome parameters, the patients were analyzed according to the following criteria: age, sex, systemic diseases, and indication for therapy. For the inserted implants, the type of surgical procedure, the types of implants placed, postsurgical complications, and early failures were recorded. A logistic regression analysis was performed to identify possible local and systemic risk factors for complications. As a secondary outcome, data regarding demographics and surgical procedures were compared with the findings of a historic study group (2002 to 2004). RESULTS A total of 1,568 patients (792 women and 776 men; mean age, 52.6 years) received 2,279 implants. The most frequent indication was a single-tooth gap (52.8%). Augmentative procedures were performed in 60% of the cases. Tissue-level implants (72.1%) were more frequently used than bone-level implants (27.9%). Regarding dimensions of the implants, a diameter of 4.1 mm (59.7%) and a length of 10 mm (55.0%) were most often utilized. An early failure rate of 0.6% was recorded (13 implants). Patients were older and received more implants in the maxilla, and the complexity of surgical interventions had increased when compared to the patient pool of 2002 to 2004. CONCLUSION Implant therapy performed in a surgical specialty clinic utilizing strict patient selection and evidence-based surgical protocols showed a very low early failure rate of 0.6%.