|
on Risk Management |
| By: | Gareth W. Peters (Department of Statistical Sciences - University College London UK); Pavel V. Shevchenko (CSIRO Australia); Bertrand K. Hassani (Centre d'Economie de la Sorbonne, Grupo Santander); Ariane Chapelle (Department of Computer Science - University College London UK) |
| Abstract: | This response has been put together by academics and in total independence of any corporate or individual interests. Our results are solely driven by scientific analysis and presented in the interest of the financial and business community, both the regulated entities and the regulators alike. The response addresses the Standardised Measurement Approach (SMA) proposed in the Basel Committee for Banking Supervision consultative document "Standardised Measurement Approach for operational risk" (issued in March 2016 for comments by 3 June 2016) [BCBSd355,2016]; and closely related Operational risk Capital-at-Risk (OpCar) model proposed in the Committee consultative document "Operational risk - revisions to the simpler approaches" October 2014 [BCBSd291] |
| Keywords: | operational risk; standardized measurement approach; loss distribution approach; advanced measurement approach; Basel Committee for Banking Supervision regulations |
| JEL: | G28 G21 C18 |
| Date: | 2016–06 |
| URL: | http://d.repec.org/n?u=RePEc:mse:cesdoc:16064&r=rmg |
| By: | Pierre-Charles Pradier (Centre d'Economie de la Sorbonne & LabEx RéFi); Hamza El Khalloufi (PRISM & LabEx RéFi) |
| Abstract: | As Europe is subject to a protracted recession, it should be asked whether the reform of the financial sector is not costly in terms of potential growth. Our analysis shows that the negative effect of the Basel III package excepted by the pre-QE studies are almost annihilated today. The recession must then have other causes: falling corporate lending volumes resulted from falling demand in the aftermath of the financial crisis, but this is longer the case. The EU is trying to incentivize corporate lending, via forward guidance as well as ‘supporting factor’ cutting down the Basel capital requirements. The macroeconomic theorists are trying to account for future success of monetary policy around zero nominal interest rate via the risk-taking channel. All these clever initiatives failed to deliver. As a consequence, we might infer that banks are simply not taking any risks: rather than appealing to risk aversion, we would like to argue that the banks seem especially embarrassed by future regulatory developments, which appear remote and uncertain. The binding constraint for corporate lending and growth in the EU is then plausibly a combination of banks' expectations of future regulation and strong uncertainty aversion. While we offer some mitigation prospects, we hope that the theoretical developments of the recent years will quickly yield both theoretical advances and practical results |
| Keywords: | banking, financial regulation |
| JEL: | G22 G28 G01 |
| Date: | 2016–09 |
| URL: | http://d.repec.org/n?u=RePEc:mse:cesdoc:16061&r=rmg |
| By: | Gareth W. Peters (Department of Statistical Sciences - University College London UK); Pavel V. Shevchenko (CSIRO Australia); Bertrand K. Hassani (Centre d'Economie de la Sorbonne, Grupo Santander); Ariane Chapelle (Department of Computer Science - University College London UK) |
| Abstract: | Recently, Basel Committee for Basel Committee for Banking Supervision proposed to replace all approaches, including Advanced Measurement Approach (AMA), for operational risk capital with a simple formula referred to as the Standardised Measurement Approach (SMA). This paper discusses and studies the weaknesses and pitfalls of SMA such as instability, risk insensitivity, super-additivity and the implicit relationship between SMA capital model and systemic risk in the banking sector. We also discuss the issues with closely related operational risk Capital-ar-Risk (OpCar) Basel Committee proposed model which is the precursor to the SMA. In conclusion, we advocate to maintain the AMA internal model framework and suggest as an alternative a number of standardization recommendations that could be considered to unify internal modelling of operational risk. The findings and views presented in this paper have been discussed with and supported by many OpRisk practitioners and academics in Australia, Europe, UK and USA, and recently at OpRisk Europe 2016 conference in London |
| Keywords: | operational risk; standardized measurement approach; loss distribution approach; advanced measurement approach; Basel Committee for Banking Supervision regulations |
| JEL: | G28 G21 C18 |
| Date: | 2016–07 |
| URL: | http://d.repec.org/n?u=RePEc:mse:cesdoc:16065&r=rmg |
| By: | Ingo Fender; Ulf Lewrick |
| Abstract: | As the Basel III package nears completion, the emphasis is shifting to monitoring its implementation and assessing the impact of the reforms. This paper presents a simple conceptual framework to assess the macroeconomic impact of the core Basel III reforms, including the leverage ratio surcharge that is being considered for global systemically important banks (G-SIBs). We use historical data for a large sample of major banks to generate a conservative approximation of the additional amount of capital that banks would need to raise to meet the new regulatory requirements, taking the potential impact of current efforts to enhance G-SIBs' total loss-absorbing capacity into account. To provide a high-level proxy for the effect of changes in capital allocation and bank business models on the estimated net benefits of regulatory reform, we simulate the effect of banks converging towards the "critical" average risk weights (or "density ratios") implied by the combined risk-weighted and leverage ratio-based capital requirements. While keeping in mind that quantifying the regulatory impact remains subject to caveats, the results suggest that Basel III can be expected to generate sizeable macroeconomic net benefits even after the implied changes to bank business models have been taken into account. |
| Keywords: | Basel III, density ratio, global systemically important banks, leverage ratio, macroeconomic impact, risk-shifting |
| Date: | 2016–11 |
| URL: | http://d.repec.org/n?u=RePEc:bis:biswps:591&r=rmg |
| By: | Dominique Guegan (Centre d'Economie de la Sorbonne); Bertrand K. Hassani (Centre d'Economie de la Sorbonne, Grupo Santander) |
| Abstract: | To measure the major risks experienced by financial institutions, for instance Market, Credit and Operational, regarding the risk measures, the distributions used to model them and the level of confidence, the regulation either offers a limited choice or demands the implementation of a particular approach. In this paper, we highlight and illustrate the paradoxes and issues observed when implementing an approach over another, the inconsistencies between the methodologies suggested and the problems related to their interpretation. Starting from the notion of coherence, we discuss their properties, we propose alternative solutions, new risk measures like spectrum and spatial approaches, and we provide practitioners and supervisor with some recommendations to assess, manage and control risks in a financial institution |
| Keywords: | Risk measures; Sub-additivity; Level of confidence; Distributions; Financial regulation; Distortion; Spectral measure; Spectrum |
| JEL: | C02 C13 C19 G01 G21 G28 D81 G31 |
| Date: | 2016–10 |
| URL: | http://d.repec.org/n?u=RePEc:mse:cesdoc:16066&r=rmg |
| By: | Xisong Jin; Francisco Nadal De Simone |
| Abstract: | This study provides the first available estimates of systemic risk in the financial sector comprising the banking and investment fund industries during 2009Q42015Q4. Systemic risk is measured in three forms: as risk common to the financial sector; as contagion within the financial sector and; as the buildup of financial sector's vulnerabilities over time, which may unravel in a disorderly manner. The methodology models the financial sector components' default dependence statistically and captures the timevarying non-linearities and feedback effects typical of financial markets. In addition, the study estimates the common components of the financial sector's default measures and by identifying the macro-financial variables most closely associated with them, it provides useful input into the formulation of macroprudential policy. The main results suggest that: (1) interdependence in the financial sector decreased in the first three years of the sample, but rose again later coinciding with ECB's references to increased search for yield in the financial sector. (2) Investment funds are a more important source of contagion to banks than the other way round, and this is more the case for European banking groups than for Luxembourg banks. (3) For tracking the growth of vulnerabilities over time, it is better to monitor the most vulnerable part of the financial sector because the common components of systemic risk measures tend to lead these measures. |
| Keywords: | financial stability? macro-prudential policy? banking sector; investment funds; default probability? non-linearities? generalized dynamic factor model? dynamic copulas |
| JEL: | C1 E5 F3 G1 |
| Date: | 2016–10 |
| URL: | http://d.repec.org/n?u=RePEc:bcl:bclwop:bclwp102&r=rmg |
| By: | Amrita Dhillon, Andrew Pickering and Tomas Sjöström |
| Abstract: | We examine default decisions under different political systems. If democratically elected politicians are unable to make credible commitments to repay externally held debt, default rates are inefficiently high because politicians internalize voter utility loss from repayment. A politician who is motivated by election concerns is more likely to default in order to avoid voter utility losses, and, since lenders recognize this, interest rates and risk premia rise. Therefore, democracy potentially confers a credit market disadvantage. Institutions that are shielded from political competition, such as independent central banks, may ameliorate the disadvantage by adopting a more farsighted perspective, taking into account how interest rates respond to default risk. Using a numerical measure of institutional farsightedness obtained from the Government Insight Business Risk and Conditions database, we find that the observed relationship between credit-ratings and democratic status is indeed strongly conditional on farsightedness. With myopic institutions, democracy is estimated to cost on average about 2.5 investment grades. With farsighted institutions there is, if anything, a democratic advantage.Keywords: Sovereign debt, Default, Risk premia, Autocracy, Democracy, Institutions JEL Classification: H63, F55, D72, D82, H75, O43, C72. |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:cge:wacage:308&r=rmg |
| By: | Katrien Antonio; Sander Devriendt; Wouter de Boer; Robert de Vries; Anja De Waegenaere; Hok-Kwan Kan; Egbert Kromme; Wilbert Ouburg; Tim Schulteis; Erica Slagter; Michel Vellekoop; Marco van der Winden; Corné van Iersel |
| Abstract: | The quantification of longevity risk in a systematic way requires statistically sound forecasts of mortality rates and their corresponding uncertainty. Actuarial associations have a long history and continue to play an important role in the development, application and dispersion of mortality projections for the countries they represent. This paper gives an in depth presentation and discussion of the mortality projections as published by the Dutch (in 2014) and Belgian (in 2015) actuarial associations. The goal of these institutions was to publish a stochastic mortality projection model in line with both rigorous standards of state-of-the art academic work as well as the requirements of practical work such as robustness and transparency. Constructed by a team of authors from both academia and practice, the developed mortality projection standard is a Li & Lee type multi-population model. To project mortality, a global Western European trend and a country-specific deviation from this trend are jointly modelled with a bivariate time series model. We motivate and document all choices made in the model specification, calibration and forecasting process as well as the model selection strategy. We show the model fit and mortality projections and illustrate the use of the model in several pension-related applications. |
| Keywords: | stochastic mortality models, projected mortality, stochastic multi-population mortality, Li & Lee model, Lee & Carter model, Poisson regression, pension calculations, longevity risk, professional actuarial associations |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:ete:afiper:554572&r=rmg |
| By: | Damiano Brigo; Fr\'ed\'eric Vrins |
| Abstract: | A key driver of Credit Value Adjustment (CVA) is the possible dependency between exposure and counterparty credit risk, known as Wrong-Way Risk (WWR). At this time, addressing WWR in a both sound and tractable way remains challenging: arbitrage-free setups have been proposed by academic research through dynamic models but are computationally intensive and hard to use in practice. Tractable alternatives based on resampling techniques have been proposed by the industry, but they lack mathematical foundations. This probably explains why WWR is not explicitly handled in the Basel III regulatory framework in spite of its acknowledged importance. The purpose of this paper is to propose a new method consisting of an appealing compromise: we start from a stochastic intensity approach and end up with a pricing problem where WWR does not enter the picture explicitly. This result is achieved thanks to a set of changes of measure: the WWR effect is now embedded in the drift of the exposure, and this adjustment can be approximated by a deterministic function without affecting the level of accuracy typically required for CVA figures. The performances of our approach are illustrated through an extensive comparison of Expected Positive Exposure (EPE) profiles and CVA figures produced either by (i) the standard method relying on a full bivariate Monte Carlo framework and (ii) our drift-adjustment approximation. Given the uncertainty inherent to CVA, the proposed method is believed to provide a promising way to handle WWR in a sound and tractable way. |
| Date: | 2016–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1611.02877&r=rmg |
| By: | Bertrand Hassani (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | In this chapter, we argue that conduct risk arising from the way financial institutions are conducting business with respect to their customers might be prevented, mitigated and potentially annihilated. Indeed, we believe that data science, proper segmentation, product design and control will lead to a tremendous reduction of conduct rusk exposure and a such these topics are addressed here. |
| Keywords: | Data science,Conduct risk,Scenario analysis,Risk management |
| Date: | 2016–10 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-01391106&r=rmg |
| By: | Wolfgang Karl Härdle; Phoon Kok Fai; David Lee Kuo Chuen |
| Abstract: | We analyse a sample of funds and other securities each assigned a total rating score by an unknown expert entity. The scores are based on a number of risk and complexity factors, each assigned a category (factor score) of Low, Medium, or High by the expert entity. A principal component analysis of the data reveals that based on the chosen risk factors alone we cannot identify a single underlying latent source of risk in the data. Conversely, the chosen complexity factors are clearly related to one or two underlying sources of complexity. For the sample we nd a clear positive relation between the rst principal component and the total expert score. An attempt to match the securities' expert score by linear projection of their individual factor scores yields a best case correlation between expert score and projection of 0.9952. However, the sum of squared di erences is, at 46.5552, still notable. |
| JEL: | C01 G00 G17 G24 |
| Date: | 2016–11 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2016-046&r=rmg |
| By: | Gadat, Sébastien; Panloup, Fabien; Saadane, Sofiane |
| Abstract: | This paper deals with a natural stochastic optimization procedure derived from the so-called Heavy-ball method differential equation, which was introduced by Polyak in the 1960s with his seminal contribution [Pol64]. The Heavy-ball method is a second-order dynamics that was investigated to minimize convex functions f. The family of second-order methods recently received a large amount of attention, until the famous contribution of Nesterov [Nes83], leading to the explosion of large-scale optimization problems. This work provides an in-depth description of the stochastic heavy-ball method, which is an adaptation of the deterministic one when only unbiased evalutions of the gradient are available and used throughout the iterations of the algorithm. We first describe some almost sure convergence results in the case of general non-convex coercive functions f. We then examine the situation of convex and strongly convex potentials and derive some non-asymptotic results about the stochastic heavy-ball method. We end our study with limit theorems on several rescaled algorithms. |
| Keywords: | Stochastic optimization algorithms; Second-order methods; Random dynamical systems. |
| Date: | 2016–10 |
| URL: | http://d.repec.org/n?u=RePEc:tse:wpaper:31104&r=rmg |
| By: | Beccue, Phillip; Huntington, Hillard |
| Abstract: | The probability of the size and duration of another oil disruption is critical to estimating the value of any policies for reducing the economic damages from a sudden oil supply disruption. The Energy Modeling Forum at Stanford University developed a risk assessment framework and evaluated the likelihood of one or more foreign oil disruptions over the next ten years. The risk assessment was conducted through a series of two workshops attended by leading geopolitical, military and oil-market experts who provided their expertise on the probability of different events occurring, and their corresponding link to major disruptions in key oil market regions. The study evaluated 5 primary regions of production: Saudi Arabia, Other Persian Gulf, Africa, Latin America, and Russian / Caspian States. The final results of the risk assessment convey a range of insights across the three dimensions of magnitude, likelihood, and length of a disruption. These conclusions are net of offsets (e.g., OPEC spare capacity), with the notable exception that the SPR is not included as a source of offsets. At least once during the 10-year time frame (2016-2025), the probability of a net (of offsets) disruption of 2 MMBD (million barrels per day) or more lasting at least 1 month is approximately 80%. |
| Keywords: | Oil supply disruptions; risk assessment |
| JEL: | Q34 Q41 |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:74986&r=rmg |
| By: | Pierre-Charles Pradier (Centre d'Economie de la Sorbonne & LabEx RéFi); Arnaud Chneiweiss (Fédération Française de l'Assurance) |
| Abstract: | The Solvency 2 package, which went on force on January 11, 2016, has had strong implications on the insurance companies' market conduct, consumer relation and solvency; an ongoing process with the FSB and the IAIS due to address systemic risk is also impacting systemic insurers. These milestones of insurance regulation are aimed at solving the social cost of the failure of financial institutions, in order to prevent future crisis. The paper at hand reviews the detail of these considerable reforms and show the consistence of the whole: prevention of systemic and microeconomic risk is first seen as prevention of regulatory arbitrage with the banking sector. This thorough legal package has but a cost, not only for every firm (cost of implementation of reforms, recurring cost of compliance including direct cost of funding supervisory authorities, indirect administrative costs and cost of regulatory capital) but also for the sector as a whole. We show that most of these costs have been played down so far, since the crisis prompted the authorities to appear tough on finance and set examples. Unfortunately, costs lead to market concentration and uniformization, which have significant systemic implications. To address this issue, finance future growth, advance market integration and development, we offer some insights on simplification and focusing of insurance regulation |
| Keywords: | insurance, financial regulation |
| JEL: | G22 G28 G01 |
| Date: | 2016–09 |
| URL: | http://d.repec.org/n?u=RePEc:mse:cesdoc:16060&r=rmg |
| By: | Milan Kumar Das; Anindya Goswami; Tanmay S. Patankar |
| Abstract: | This paper studies pricing derivatives in an age-dependent semi-Markov modulated market. We consider a financial market where the asset price dynamics follow a regime switching geometric Brownian motion model in which the coefficients depend on finitely many age-dependent semi-Markov processes. We further allow the volatility coefficient to depend on time explicitly. Under these market assumptions, we study locally risk minimizing pricing of a class of European options. It is shown that the price function can be obtained by solving a non-local B-S-M type PDE. We establish existence and uniqueness of a classical solution of the Cauchy problem. We also find another characterization of price function via a system of Volterra integral equation of second kind. This alternative representation leads to computationally efficient methods for finding price and hedging. Finally, we analyze the PDE to establish continuous dependence of the solution on the instantaneous transition rates of semi-Markov processes. An explicit expression of quadratic residual risk is also obtained. |
| Date: | 2016–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1611.02026&r=rmg |