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Martin Scheicher

Horizontal Line Supervision

Division

Credit Risk Experts

Current Position

Adviser

Fields of interest

Financial Economics

Email

[email protected]

Education
1994-1996

Doctorate in Economics, University of Vienna

1993-1994

MSc in Economics, London School of Economics

1989-1993

Undergraduate Studies, University of Vienna

Professional experience
2014-

Adviser - DG-Microprudential Supervision 1, European Central Bank

2010-2014

Principal Economist - ESRB Secretariat, European Central Bank

2005-2010

Senior Economist - Financial Research Division, European Central Bank

2004-2005

Expert - Financial Supervision Division, European Central Bank

1999-2004

Economist - Austrian Central Bank

1994-1999

Assistant Professor - University of Vienna

Teaching experience
2012-2018

Joint Vienna Institute

5 April 2023
OCCASIONAL PAPER SERIES - No. 314
Details
Abstract
In this paper we aim to provide a holistic understanding of the Initial Margin (IM) models used by Central Counterparties (CCPs) in Europe. In addition to discussing their relevance in terms of CCP risk management and their importance for the functioning of financial markets, we provide an overview of the main modelling frameworks used, including Standard Portfolio Analysis of Risk (SPAN) and Value at Risk (VaR) models.By leveraging on publicly available data, we provide an up-to-date picture of current modelling practices for specific cleared product classes, as well as various trends in IM modelling practices in Europe. We show how IM model frameworks vary materially, depending on the CCP’s past choices and the products it clears. Despite a propensity to switch to VaR models, idiosyncrasies and differences across CCPs are likely to persist.We conclude by highlighting current and upcoming challenges and risks to CCP IM model frameworks and linking the current status quo with ongoing and upcoming regulatory work at European and international level.
JEL Code
G15 : Financial Economics→General Financial Markets→International Financial Markets
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
G19 : Financial Economics→General Financial Markets→Other
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
15 February 2019
WORKING PAPER SERIES - No. 2242
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Abstract
Using a novel regulatory dataset of fully identified derivatives transactions, this paper provides the first comprehensive analysis of the structure of the euro area interest rate swap (IRS) market after the start of the mandatory clearing obligation. Our dataset contains 1.7 million bilateral IRS transactions of banks and non-banks. Our key results are as follows: 1) The euro area IRS market is highly standardised and concentrated around the group of the G16 Dealers but also around a significant group of core ”intermediaries" (and major CCPs). 2) Banks are active in all segments of the IRS euro market, whereas non-banks are often specialised. 3) When using relative net exposures as a proxy for the “flow of risk" in the IRS market, we find that risk absorption takes place in the core as well as the periphery of the network. 4) Among the Basel III capital and liquidity ratios, the leverage ratio plays a key role in determining a bank's IRS trading activity. 5) Also, after mandatory central clearing, there is still a large dispersion in IRS transaction prices, which is partly determined by bank characteristics, such as the leverage ratio.
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
29 March 2017
WORKING PAPER SERIES - No. 2041
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Abstract
We develop a framework to analyse the Credit Default Swaps (CDS) market as a network of risk transfers among counterparties. From a theoretical perspective, we introduce the notion of flow-of-risk and provide sufficient conditions for a bow-tie network architecture to endogenously emerge as a result of intermediation. This architecture shows three distinct sets of counterparties: i) Ultimate Risk Sellers (URS), ii) Dealers (indirectly connected to each other), iii) Ultimate Risk Buyers (URB). We show that the probability of widespread distress due to counterparty risk is higher in a bow-tie architecture than in more fragmented network structures. Empirically, we analyse a unique global dataset of bilateral CDS exposures on major sovereign and financial reference entities in 2011 - 2014. We find the presence of a bow-tie network architecture consistently across both reference entities and time, and that the flow-of-risk originates from a large number of URSs (e.g. hedge funds) and ends up in a few leading URBs, most of which are non-banks (in particular asset managers). Finally, the analysis of the CDS portfolio composition of the URBs shows a high level of concentration: in particular, the top URBs often show large exposures to potentially correlated reference entities.
JEL Code
G10 : Financial Economics→General Financial Markets→General
G15 : Financial Economics→General Financial Markets→International Financial Markets
20 February 2014
WORKING PAPER SERIES - No. 1638
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Abstract
We use an extensive data set of bilateral exposures on credit default swap (CDS) to estimate the impact on collateral demand of new margin and clearing practices and regulations. We decompose collateral demand for both customers and dealers into several key components, including the
JEL Code
G20 : Financial Economics→Financial Institutions and Services→General
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
G15 : Financial Economics→General Financial Markets→International Financial Markets
29 August 2013
WORKING PAPER SERIES - No. 1583
Details
Abstract
This paper analyses the network structure of the credit default swap (CDS) market, using a unique sample of counterparties’ bilateral notional exposures to CDS on 642 sovereign and financial reference entities. We study the network structure, similarly to the literature on interbank and payment systems, by computing a variety of network metrics at the aggregated level and for several subnetworks. At a reference entity level, we analyse the determinants of some key network properties for large reference entities. Our main results, obtained on a sub-sample of 191 reference entities, are the following. First, the CDS network shows topological similarities with the interbank network, as we document a “small world” structure and a scale-free degree distribution for the CDS market. Second, there is considerable heterogeneity in the network structures across reference entities. In particular, the outstanding debt volume and its structure (maturity, collateralization), the riskiness, the type (sovereign/financial) and the location (European/non-European) of reference entities significantly influence the size, the activity and the concentration of the CDS exposure network. For instance, the network on a high-volatility reference entity is typically more active, larger in size and less concentrated.
JEL Code
G15 : Financial Economics→General Financial Markets→International Financial Markets
1 December 2010
WORKING PAPER SERIES - No. 1271
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Abstract
This paper studies the relative pricing of euro area sovereign CDS and the underlying government bonds. Our sample comprises weekly CDS and bond spreads of ten euro area countries for the period from January 2006 to June 2010. We first compare the determinants of CDS spreads and bond spreads and test how the crisis has affected market pricing. Then we analyse the ‘basis’ between CDS spreads and bond spreads and which factors drive pricing differences between the two markets. Our first main finding is that the recent repricing of sovereign credit risk in the CDS market seems mostly due to common factors. Second, since September 2008, CDS spreads have on average exceeded bond spreads, which may have been due to ‘flight to liquidity’ effects and limits to arbitrage. Third, since September 2008, market integration for bonds and CDS varies across countries: In half of the sample countries, price discovery takes place in the CDS market and in the other half, price discovery is observed in the bond market.
JEL Code
G00 : Financial Economics→General→General
G01 : Financial Economics→General→Financial Crises
26 May 2009
WORKING PAPER SERIES - No. 1056
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Abstract
This paper investigates the market pricing of subprime mortgage risk on the basis of data for the ABX.HE family of indices, which have become a key barometer of mortgage market conditions during the recent financial crisis. After an introduction into ABX index mechanics and a discussion of historical pricing patterns, we use regression analysis to establish the relationship between observed index returns and macroeco-nomic news as well as market based proxies of default risk, interest rates, liquidity and risk appetite. The results imply that declining risk appetite and heightened concerns about market illiquidity - likely due in part to significant short positioning activity -have provided a sizeable contribution to the observed collapse in ABX prices since the summer of 2007. In particular, while fundamental factors, such as indicators of housing market activity, have continued to exert an important influence on the subordinated ABX indices, those backed by AA and AAA exposures have tended to react more to the general deterioration of the financial market environment. This provides further support for the inappropriateness of pricing models that do not sufficiently account for factors such as risk appetite and liquidity risk, particularly in periods of heightened market pressure. In addition, as related risk premia can be captured by unconstrained investors, ABX pricing patterns appear to lend support to government measures aimed at taking troubled assets off banks' balance sheets - such as the US Troubled Asset Relief Program (TARP) in its original form.
JEL Code
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G13 : Financial Economics→General Financial Markets→Contingent Pricing, Futures Pricing
G14 : Financial Economics→General Financial Markets→Information and Market Efficiency, Event Studies, Insider Trading
31 March 2009
WORKING PAPER SERIES - No. 1037
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Abstract
Implied volatility indices should have information about risk parameters, once they are cleansed of the influence of normal volatility dynamics and macro-economic uncertainty. Building on intuition from the dynamic asset pricing literature, we uncover unobserved risk aversion and fundamental uncertainty from the observed time series of the VIX and the credit spreads while controlling for realized volatility, expectations about the macroeconomic outlook, and interest rates. We apply this methodology to monthly data from both Germany and the US. We find that implied volatilities contain a substantial amount of information regarding risk aversion whereas credit spreads have a lot to say about both risk aversion and uncertainty. Moreover, there is a significant comovement in the German and US risk aversion.
JEL Code
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
17 November 2008
WORKING PAPER SERIES - No. 968
Details
Abstract
We investigate the risk of holding credit default swaps(CDS) in the trading book and compare the Value at Risk (VaR) of a CDS position to the VaR for investing in the respective firm's equity using a sample of CDS - stock price pairs for 86 actively traded firms over the period from March 2003 to October 2006. We find that the VaR for a stock is usually far larger than the VaR for a position in the same firm's CDS. However, the ratio between CDS and equity VaR is markedly smaller for firms with high credit risk. The ratio also declines for longer holding periods. We also observe a positive correlation between CDS and equity VaR. Panel regressions suggest that our findings are consistent with qualitative predictions of the Merton (1974) model.
JEL Code
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G13 : Financial Economics→General Financial Markets→Contingent Pricing, Futures Pricing
30 June 2008
WORKING PAPER SERIES - No. 910
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Abstract
This paper applies regression analysis to investigate the fundamental factors of the variation of CDS index tranches. The sample comprises daily data on the tranche premia of the European iTraxx and North American CDX index from the start of the market in summer 2004 to January 2008. I estimate the relationship between tranche premia and market-based measures of credit risk, liquidity risk and interest rate risk. In this context, I analyse how the set of explanatory factors has changed since the start of the credit market turmoil in 2007. Overall, I find that pricing of CDX and iTraxx tranches differs although the specifications of the two contracts are very similar. Since July 2007, tranche investors appear to have repriced CDX contracts to a larger extent than iTraxx contracts. Credit risk and liquidity factors are priced in almost all tranches with liquidity risk playing a larger role since the start of the turmoil.
JEL Code
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G13 : Financial Economics→General Financial Markets→Contingent Pricing, Futures Pricing
G14 : Financial Economics→General Financial Markets→Information and Market Efficiency, Event Studies, Insider Trading
22 December 2005
OCCASIONAL PAPER SERIES - No. 42
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Abstract
Following the adoption by the Basel Committee of new capital rules for banks, aprocess is now taking place in the EU to transpose the rules into Community law and, ultimately, into national legislation. This paper gives an overview of the main issues that relate to the EU implementation, mainly from theperspectives of financial stability and financial integration. Although the EU rules are to a large extent based on the texts of the Basel Committee, modifications have been introduced to account for the specific legal and institutional setting, as well as for some features of the European financial system. The paper gives an overview of these modifications and deals in greater detail with a number of selected topics: the monitoring of procyclicality, the role of the consolidating supervisor and the treatment of real estate lending and covered bonds. The paper concludes with an outlook for the future.
JEL Code
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
1 January 2003
WORKING PAPER SERIES - No. 212
Details
Abstract
In this paper we study risk-neutral densities (RNDs) for the German stock market. The use of option prices allows us to quantify the risk-neutral probabilities of various levels of the DAX index. For the period from December 1995 to November 2001, we implement the mixture of log-normals model and a volatility-smoothing method. We discuss the time series behaviour of the implied PDFs and we examine the relations between the moments and observable factors such as macroeconomic variables, the US stock markets and credit risk. We find that the risk-neutral densities exhibit pronounced negative skewness. Our second main observation is a significant spillover of volatility, as the implied volatility and kurtosis of the DAX RND are mostly driven by the volatility of US stock prices.
JEL Code
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
C51 : Mathematical and Quantitative Methods→Econometric Modeling→Model Construction and Estimation
G13 : Financial Economics→General Financial Markets→Contingent Pricing, Futures Pricing
G15 : Financial Economics→General Financial Markets→International Financial Markets
2018
Journal of Financial Stability 35, 136-158
How did the Greek credit event impact the credit default swap market?
  • G. Halaj, T. Peltonen and M.Scheicher
2018
Journal of Financial Stability 35, 53-74
How does risk flow in the credit default swap market?
  • M. D’Errico, S. Battiston, T. Peltonen and M.Scheicher
2018
Securitisation: Past, present and future
Securitisation: Key trends after the crisis
  • M.Scheicher and S.Wehmeyer
2016
Journal of Banking & Finance 62, 126–140
An analysis of euro area sovereign CDS and their relation with government bonds
  • A. Fontana and M.Scheicher
2015
Journal of Financial Economics 116, 237 - 256
Central Clearing and Collateral Demand
  • D. Duffie, M.Scheicher and G. Vuillemey
2014
Journal of Financial Stability 13, 118–133
The network structure of the CDS market and its determinants
  • T. Peltonen, M.Scheicher and G. Vuillemey
2013
Banque de France Financial Stability Review, 17, 2013, 123-134
Assessing contagion risks in the CDS market
  • M. Brunnermeier, L. Clerq and M.Scheicher
2011
Journal of Risk, 13, 3-29
A value-at-risk analysis of credit default swaps
  • B.Raunig and M.Scheicher
2010
Oxford Handbook of Banking
Securitisation: Instruments and Implications
  • D. Marquez, M. Scheicher
2009
Stock Market Volatility
The correlation of a firm’s credit spread with its stock price: Evidence from credit default swaps
  • M.Scheicher
2009
Applied Financial Economics, 19, 1925 - 1945
The pricing of subprime mortgage risk in good times and bad: Evidence from the ABX.HE indices
  • I. Fender and M.Scheicher
2008
Journal of Credit Risk 4, 2008, 1 - 26
Asset correlations and credit portfolio risk: An empirical analysis
  • K. Duellmann, C. Schmieder, M. Scheicher
2006
Studies in Nonlinear Dynamics & Econometrics 10/4, 2006, 1-35
The volatility of stock market returns: Markov chain Monte Carlo analysis of a switching ARCH model
  • S. Kaufmann, M. Scheicher
2005
Journal of Futures Markets 25, 2005, 515 -536
What moves the tail? The determinants of the option-implied probability density function of the DAX index
  • E. Glatzer, M. Scheicher
2002
BIS Papers No. 12 - Market functioning and central bank policy, 181-200, 2002
The determinants of credit spread changes in the euro area
  • M. Boss, M.Scheicher
2002
Journal of Banking & Finance 26, 2002, 323-45
GARCH vs. Stochastic Volatility: Option Pricing and Risk Management
  • A. Lehar, M.Scheicher, C. Schittenkopf
2001
Financial Markets & Portfolio Management 15, 2001, 500-515
Trade Versus Time Series Based Volatility Forecasts: Evidence from the Austrian Stock Market
  • A. Lehar, M. Scheicher, G. Strobl
2001
International Journal of Finance & Economics 6, 2001, 27-39
The Comovements of Stock Markets in Hungary, Poland and the Czech Republic.
  • M. Scheicher
2000
European Journal of Finance 6, 2000, 70-91
Time-Varying Risk in the German Stock Market
  • M.Scheicher
1999
Empirical Economics 24, 1999, 45-59
Nonlinear Dynamics: Evidence for a Small Stock Exchange
  • M. Scheicher