A Bayesian Networks Approach to Operational Risk

A system for Operational Risk management based on the computational paradigm of Bayesian Networks is presented. The algorithm allows the construction of a Bayesian Network targeted for each bank using only internal loss data, and takes into account in a simple and realistic way the correlations among different processes of the bank. The internal losses are averaged over a variable time horizon, so that the correlations at different times are removed, while the correlations at the same time are kept: the averaged losses are thus suitable to perform the learning of the network topology and parameters. The algorithm has been validated on synthetic time series. It should be stressed that the practical implementation of the proposed algorithm has a small impact on the organizational structure of a bank and requires an investment in human resources limited to the computational area

DebtRank: A microscopic foundation for shock propagation

The DebtRank algorithm has been increasingly investigated as a method to estimate the impact of shocks in financial networks, as it overcomes the limitations of the traditional default-cascade approaches. Here we formulate a dynamical "microscopic" theory of instability for financial networks by iterating balance sheet identities of individual banks and by assuming a simple rule for the transfer of shocks from borrowers to lenders. By doing so, we generalise the DebtRank formulation, both providing an interpretation of the effective dynamics in terms of basic accounting principles and preventing the underestimation of losses on certain network topologies. Depending on the structure of the interbank leverage matrix the dynamics is either stable, in which case the asymptotic state can be computed analytically, or unstable, meaning that at least one bank will default. We apply this framework to a dataset of the top listed European banks in the period 2008-2013. We find that network effects can generate an amplification of exogenous shocks of a factor ranging between three (in normal periods) and six (during the crisis) when we stress the system with a 0.5% shock on external (i.e. non-interbank) assets for all banks

Pathways towards instability in financial networks

Following the financial crisis of 2007-2008, a deep analogy between the origins of instability in financial systems and complex ecosystems has been pointed out: in both cases, topological features of network structures influence how easily distress can spread within the system. However, in financial network models, the details of how financial institutions interact typically play a decisive role, and a general understanding of precisely how network topology creates instability remains lacking. Here we show how processes that are widely believed to stabilize the financial system, that is, market integration and diversification, can actually drive it towards instability, as they contribute to create cyclical structures which tend to amplify financial distress, thereby undermining systemic stability and making large crises more likely. This result holds irrespective of the details of how institutions interact, showing that policy-relevant analysis of the factors affecting financial stability can be carried out while abstracting away from such details

Distress propagation in complex networks: The case of non-linear DebtRank

We consider a dynamical model of distress propagation on complex networks, which we apply to the study of financial contagion in networks of banks connected to each other by direct exposures. The model that we consider is an extension of the DebtRank algorithm, recently introduced in the literature. The mechanics of distress propagation is very simple: When a bank suffers a loss, distress propagates to its creditors, who in turn suffer losses, and so on. The original DebtRank assumes that losses are propagated linearly between connected banks. Here we relax this assumption and introduce a one-parameter family of non-linear propagation functions. As a case study, we apply this algorithm to a data-set of 183 European banks, and we study how the stability of the system depends on the non-linearity parameter under different stress-test scenarios. We find that the system is characterized by a transition between a regime where small shocks can be amplified and a regime where shocks do not propagate, and that the overall stability of the system increases between 2008 and 2013

The Role of Multiparametric Magnetic Resonance in Volumetric Modulated Arc Radiation Therapy Planning for Prostate Cancer Recurrence After Radical Prostatectomy: A Pilot Study

Background and Purpose: Volumetric modulated arc radiotherapy (RT) has become pivotal in the treatment of prostate cancer recurrence (RPC) to optimize dose distribution and minimize toxicity, thanks to the high-precision delineation of prostate bed contours and organs at risk (OARs) under multiparametric magnetic resonance (mpMRI) guidance. We aimed to assess the role of pre-treatment mpMRI in ensuring target volume coverage and normal tissue sparing. Material and Methods: Patients with post-prostatectomy RPC eligible for salvage RT were prospectively recruited to this pilot study. Image registration between planning CT scan and T2w pre-treatment mpMRI was performed. Two sets of volumes were outlined, and DWI images/ADC maps were used to facilitate precise gross tumor volume (GTV) delineation on morphological MRI scans. Two rival plans (mpMRI-based or not) were drawn up. Results: Ten patients with evidence of RPC after prostatectomy were eligible. Preliminary data showed lower mpMRI-based clinical target volumes than CT-based RT planning (p = 0.0003): median volume difference 17.5 cm3. There were no differences in the boost volume coverage nor the dose delivered to the femoral heads and penile bulb, but median rectal and bladder V70Gy was 4% less (p = 0.005 and p = 0.210, respectively) for mpMRI-based segmentation. Conclusions: mpMRI provides high-precision target delineation and improves the accuracy of RT planning for post-prostatectomy RPC, ensures better volume coverage with better OARs sparing and allows non-homogeneous dose distribution, with an aggressive dose escalation to the GTV. Randomized phase III trials and wider datasets are needed to fully assess the role of mpMRI in optimizing therapeutic strategies

Dyspnea in Patients Receiving Radical Radiotherapy for Non-Small Cell Lung Cancer: A Prospective Study

Background and Purpose: Dyspnea is an important symptomatic endpoint for assessment of radiation-induced lung injury (RILI) following radical radiotherapy in locally advanced disease, which remains the mainstay of treatment at the time of significant advances in therapy including combination treatments with immunotherapy and chemotherapy and the use of local ablative radiotherapy techniques. We investigated the relationship between dose-volume parameters and subjective changes in dyspnea as a measure of RILI and the relationship to spirometry. Material and Methods: Eighty patients receiving radical radiotherapy for non-small cell lung cancer were prospectively assessed for dyspnea using two patient-completed tools: EORTC QLQ-LC13 dyspnea quality of life assessment and dyspnea visual analogue scale (VAS). Global quality of life, spirometry and radiation pneumonitis grade were also assessed. Comparisons were made with lung dose-volume parameters. Results: The median survival of the cohort was 26 months. In the evaluable group of 59 patients there were positive correlations between lung dose-volume parameters and a change in dyspnea quality of life scale at 3 months (V30 p=0.017; V40 p=0.026; V50 p=0.049; mean lung dose p=0.05), and a change in dyspnea VAS at 6 months (V30 p=0.05; V40 p=0.026; V50 p=0.028) after radiotherapy. Lung dose-volume parameters predicted a 10% increase in dyspnea quality of life score at 3 months (V40; p=0.041, V50; p=0.037) and dyspnea VAS score at 6 months (V40; p=0.027) post-treatment. Conclusions: Worsening of dyspnea is an important symptom of RILI. We demonstrate a relationship between lung dose-volume parameters and a 10% worsening of subjectiv

Impact of gastrointestinal side effects on patients’ reported quality of life trajectories after radiotherapy for prostate cancer: Data from the prospective, observational pros-it CNR study

Radiotherapy (RT) represents an important therapeutic option for the treatment of localized prostate cancer. The aim of the current study is to examine trajectories in patients’ reported quality of life (QoL) aspects related to bowel function and bother, considering data from the PROState cancer monitoring in ITaly from the National Research Council (Pros-IT CNR) study, analyzed with growth mixture models. Data for patients who underwent RT, either associated or not associated with androgen deprivation therapy, were considered. QoL outcomes were assessed over a 2-year period from the diagnosis, using the Italian version of the University of California Los Angeles-Prostate Cancer Index (Italian-UCLA-PCI). Three trajectories were identified for the bowel function; having three or more comorbidities and the use of 3D-CRT technique for RT were associated with the worst trajectory (OR = 3.80, 95% CI 2.04–7.08; OR = 2.17, 95% CI 1.22–3.87, respectively). Two trajectories were identified for the bowel bother scores; diabetes and the non-Image guided RT method were associated with being in the worst bowel bother trajectory group (OR = 1.69, 95% CI 1.06–2.67; OR = 2.57, 95% CI 1.70–3.86, respectively). The findings from this study suggest that the absence of comorbidities and the use of intensity modulated RT techniques with image guidance are related with a better tolerance to RT in terms of bowel side effects

Disease-specific and general health-related quality of life in newly diagnosed prostate cancer patients: The Pros-IT CNR study

Background: The National Research Council (CNR) prostate cancer monitoring project in Italy (Pros-IT CNR) is an observational, prospective, ongoing, multicentre study aiming to monitor a sample of Italian males diagnosed as new cases of prostate cancer. The present study aims to present data on the quality of life at time prostate cancer is diagnosed. Methods: One thousand seven hundred five patients were enrolled. Quality of life is evaluated at the time cancer was diagnosed and at subsequent assessments via the Italian version of the University of California Los Angeles-Prostate Cancer Index (UCLA-PCI) and the Short Form Health Survey (SF-12). Results: At diagnosis, lower scores on the physical component of the SF-12 were associated to older ages, obesity and the presence of 3+ moderate/severe comorbidities. Lower scores on the mental component were associated to younger ages, the presence of 3+ moderate/severe comorbidities and a T-score higher than one. Urinary and bowel functions according to UCLA-PCI were generally good. Almost 5% of the sample reported using at least one safety pad daily to control urinary loss; less than 3% reported moderate/severe problems attributable to bowel functions, and sexual function was a moderate/severe problem for 26.7%. Diabetes, 3+ moderate/severe comorbidities, T2 or T3-T4 categories and a Gleason score of eight or more were significantly associated with lower sexual function scores at diagnosis. Conclusions: Data collected by the Pros-IT CNR study have clarified the baseline status of newly diagnosed prostate cancer patients. A comprehensive assessment of quality of life will allow to objectively evaluate outcomes of different profile of care

Early warning of systemic risk in global banking: eigen-pair R number for financial contagion and market price-based methods

We analyse systemic risk in the core global banking system using a new network-based spectral eigen-pair method, which treats network failure as a dynamical system stability problem. This is compared with market price-based Systemic Risk Indexes, viz. Marginal Expected Shortfall, Delta Conditional Value-at-Risk, and Conditional Capital Shortfall Measure of Systemic Risk in a cross-border setting. Unlike paradoxical market price based risk measures, which underestimate risk during periods of asset price booms, the eigen-pair method based on bilateral balance sheet data gives early-warning of instability in terms of the tipping point that is analogous to the R number in epidemic models. For this regulatory capital thresholds are used. Furthermore, network centrality measures identify systemically important and vulnerable banking systems. Market price-based SRIs are contemporaneous with the crisis and they are found to covary with risk measures like VaR and betas