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Als geladener Sachverständiger argumentierte Martin Götz bei der öffentlichen Anhörung des Finanzausschusses des Deutschen Bundestags und in seiner vorliegenden Stellungnahme, dass durch die zügige Umsetzung der Richtlinie 2014/59/EU die Selbstregulierung von Kreditinstituten und Wertpapierfirmen weiter gestärkt wird und das aufsichtsrechtliche Instrumentarium um marktorientierte Mechanismen ausgebaut wird. Er erwartet, dass das Umsetzungsgesetz die Finanzstabilität in Deutschland fördert. Positiv sei insbesondere die Ausgestaltung der Möglichkeit einer verpflichtenden Gläubigerbeteiligung („Bail-in“) im Rahmen der Abwicklung, da der Bail-in nicht nur Fragen der Privathaftung im Abwicklungsfall klärt, sondern auch gute Anreize zur Selbstregulierung von Kreditinstituten setzt. Den Verzicht auf die Umsetzung der in der Abwicklungsrichtlinie enthaltenen staatlichen Stabilisierungsmöglichkeiten bewertet er als positiv und sieht darin einen wichtigen Baustein zur Förderung der Selbstregulierung von Finanzinstituten. Die Verlängerung der Laufzeit des Finanzmarktstabilisierungsfonds sei problematisch, da die explizite Möglichkeit einer staatlichen Hilfe dem Anreiz zur Selbstregulierung von Finanzinstituten entgegensteht.
Stellungnahme zum Entwurf eines Gesetzes zur Umsetzung der Richtlinie 2014/59/EU (BRRD-Umsetzungsgesetz) der Bundesregierung vom 22.09.2014
Der Gesetzentwurf der Bundesregierung zur Umsetzung der EU-Richtlinie 2014/59/EU zur Festlegung eines Rahmens für die Sanierung und Abwicklung von Kreditinstituten und Wertpapierfirmen (“BRRD-Umsetzungsgesetz“) berührt auch die Frage der institutionellen Struktur für die Zuständigkeit für Bankenaufsicht und Geldpolitik. Es gibt gewichtige Gründe dafür, auf lange Sicht die Geldpolitik von der Bankenaufsicht und möglichen Bankenabwicklungs- und -restrukturierungsfragen institutionell zu trennen. Bei einer Trennung ist zu beachten, dass alle Institutionen für ihre jeweiligen Mandate gleichberechtigt auf erstklassige Daten über die Kapitalmärkte und die Transaktionen und Bilanzen der Banken zugreifen müssen. Ein Y-Modell, in dem zwei voneinander unabhängige Institutionen auf eine gemeinsame Datenbasis aufsetzen, kann im deutschen Kontext erreicht werden, indem die Bundesbank und die Bafin in einer Institution zusammengeführt werden, wobei sowohl die Aufsicht wie auch die Geldpolitik als Anstalt in der Anstalt (AIDA) geführt werden. Im Rahmen dieser „doppelten AIDA“-Lösung können beide Anstalten gleichberechtigt auf eine Datenbasis zugreifen. Die Daten werden im Rahmen der Mandate von Geldpolitik und Aufsicht wie bisher bundesweit erhoben. Die Entwicklung und spätere Einführung des Y-Modells („doppelte AIDA“) würde auch einen Modellcharakter für die noch zu führende Debatte um eine sinnvolle Institutionenstruktur für Europa haben.
SAFE Professor Michalis Haliassos was a member of the National Council for Research and Technology (ESET) established by the Government of Greece for the period 2010-2013. The council, consisting of eleven scientists from a range of disciplines, has now published their communiqué "National Strategic Framework for Research and Innovation 2014 -2020".
To promote the advancement of research, technology and innovation in Greece, the strategic plan proposed by the authors seeks to identify areas of existing research strength and excellence that can be further advanced to become engines for progress and growth in Greece, as well as flaws inherent to the present system. The authors stress the need to address current constraints to growth, which include the declining education system; the confusion and weaknesses of R&D governance and management; the discontinuities and inefficiencies of resource allocation and investment; the lack of adaptation to clearly-defined national priorities; and the inadequate opportunities and funding for high-quality research and development to flourish. They stress the need for prioritisation and efficient allocation; stability of the policy frame; predictability of planning; provision of opportunity; recognition of excellence; and responsiveness to current and future needs.
How special are they? - Targeting systemic risk by regulating shadow banking : (October 5, 2014)
(2014)
This essay argues that at least some of the financial stability concerns associated with shadow banking can be addressed by an approach to financial regulation that imports its functional foundations more vigorously into the interpretation and implementation of existing rules. It shows that the general policy goals of prudential banking regulation remain constant over time despite dramatic transformations in the financial and technological landscape. Moreover, these overarching policy goals also legitimize intervention in the shadow banking sector. On these grounds, this essay encourages a more normative construction of available rules that potentially limits both the scope for regulatory arbitrage and the need for ever more rapid updates and a constant increase in the complexity of the regulatory framework. By tying the regulatory treatment of financial innovation closely to existing prudential rules and their underlying policy rationales, the proposed approach potentially ends the socially wasteful race between hare and tortoise that signifies the relation between regulators and a highly dynamic industry. In doing so it does not generally hamper market participants’ efficient discoveries where disintermediation proves socially beneficial. Instead, it only weeds-out rent-seeking circumventions of existing rules and standards.
Advertising arbitrage
(2014)
Speculators often advertise arbitrage opportunities in order to persuade other investors and thus accelerate the correction of mispricing. We show that in order to minimize the risk and the cost of arbitrage an investor who identifies several mispriced assets optimally advertises only one of them, and overweights it in his portfolio; a risk-neutral arbitrageur invests only in this asset. The choice of the asset to be advertised depends not only on mispricing but also on its "advertisability" and accuracy of future news about it. When several arbitrageurs identify the same arbitrage opportunities, their decisions are strategic complements: they invest in the same asset and advertise it. Then, multiple equilibria may arise, some of which inefficient: arbitrageurs may correct small mispricings while failing to eliminate large ones. Finally, prices react more strongly to the ads of arbitrageurs with a successful track record, and reputation-building induces high-skill arbitrageurs to advertise more than others.
Has economic research been helpful in dealing with the financial crises of the early 2000s? On the whole, the answer is negative, although there are bright spots. Economists have largely failed to predict both crises, largely because most of them were not analytically equipped to understand them, in spite of their recurrence in the last 25 years. In the pre-crisis period, however, there have been important exceptions – theoretical and empirical strands of research that largely laid out the basis for our current thinking about financial crises. Since 2008, a flurry of new studies offered several different interpretations of the US crisis: to some extent, they point to potentially complementary factors, but disagree on their relative importance, and therefore on policy recommendations. Research on the euro debt crisis has so far been much more limited: even Europe-based researchers – including CEPR ones – have often directed their attention more to the US crisis than to that occurring on their doorstep. In terms of impact on policy and regulatory reform, the record is uneven. On the one hand, the swift and massive liquidity provision by central banks in the wake of both crises is, at least partly, to be credited to previous research on the role of central banks as lenders of last resort in crises and on the real effects of bank lending and monetary policy. On the other hand, economists have had limited impact on the reform of prudential and security market regulation. In part, this is due to their neglect of important regulatory choices, which policy-makers are therefore left to take without the guidance of academic research-based analysis.
Consumption-based asset pricing with rare disaster risk : a simulated method of moments approach
(2014)
The rare disaster hypothesis suggests that the extraordinarily high postwar U.S. equity premium resulted because investors ex ante demanded compensation for unlikely but calamitous risks that they happened not to incur. Although convincing in theory, empirical tests of the rare disaster explanation are scarce. We estimate a disaster-including consumption-based asset pricing model (CBM) using a combination of the simulated method of moments and bootstrapping. We consider several methodological alternatives that differ in the moment matches and the way to account for disasters in the simulated consumption growth and return series. Whichever specification is used, the estimated preference parameters are of an economically plausible size, and the estimation precision is much higher than in previous studies that use the canonical CBM. Our results thus provide empirical support for the rare disaster hypothesis, and help reconcile the nexus between real economy and financial markets implied by the consumption-based asset pricing paradigm.
The long-run consumption risk (LRR) model is a promising approach to resolve prominent asset pricing puzzles. The simulated method of moments (SMM) provides a natural framework to estimate its deep parameters, but caveats concern model solubility and weak identification. We propose a two-step estimation strategy that combines GMM and SMM, and for which we elicit informative macroeconomic and financial moment matches from the LRR model structure. In particular, we exploit the persistent serial correlation of consumption and dividend growth and the equilibrium conditions for market return and risk-free rate, as well as the model-implied predictability of the risk-free rate. We match analytical moments when possible and simulated moments when necessary and determine the crucial factors required for both identification and reasonable estimation precision. A simulation study – the first in the context of long-run risk modeling – delineates the pitfalls associated with SMM estimation of a non-linear dynamic asset pricing model. Our study provides a blueprint for successful estimation of the LRR model.
he predictive likelihood is of particular relevance in a Bayesian setting when the purpose is to rank models in a forecast comparison exercise. This paper discusses how the predictive likelihood can be estimated for any subset of the observable variables in linear Gaussian state-space models with Bayesian methods, and proposes to utilize a missing observations consistent Kalman filter in the process of achieving this objective. As an empirical application, we analyze euro area data and compare the density forecast performance of a DSGE model to DSGE-VARs and reduced-form linear Gaussian models.
We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semi-martingale log asset price process which is subject to noise and non-synchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance estimates. The latter originate from a local method of moments (LMM) which recently has been introduced by Bibinger et al. (2014). We extend the LMM estimator to allow for autocorrelated noise and propose a method to adaptively infer the autocorrelations from the data. We prove the consistency and asymptotic normality of the proposed spot covariance estimator. Based on extensive simulations we provide empirical guidance on the optimal implementation of the estimator and apply it to high-frequency data of a cross-section of NASDAQ blue chip stocks. Employing the estimator to estimate spot covariances, correlations and betas in normal but also extreme-event periods yields novel insights into intraday covariance and correlation dynamics. We show that intraday (co-)variations (i) follow underlying periodicity patterns, (ii) reveal substantial intraday variability associated with (co-)variation risk, (iii) are strongly serially correlated, and (iv) can increase strongly and nearly instantaneously if new information arrives.