nep-fmk New Economics Papers
on Financial Markets
Issue of 2016‒01‒03
four papers chosen by

  1. Choosing Expected Shortfall over VaR in Basel III Using Stochastic Dominance By Chia-Lin Chang; Juan-Ángel Jiménez-Martín; Esfandiar Maasoumi; Michel McAleer; Teodosio Pérez-Amaral
  2. Short-Term Liquidity Contagion in the Interbank Market By Carlos León; Constanza Martínez; Freddy Cepeda
  3. From Organization to Activity in the US Collateralized Interbank Market By Oet, Mikhail V.; Ong, Stephen J.
  4. The Determinants of CoCo Bond Prices By Masror Khah, Sara Abed; Vermaelen, Theo; Wolff, Christian C

  1. By: Chia-Lin Chang (National Chung Hsing University, Taichung, Taiwan); Juan-Ángel Jiménez-Martín (Complutense University of Madrid, Spain); Esfandiar Maasoumi (Emory University, USA); Michel McAleer (National TsingHua University, Taiwan; Erasmus School of Economics, Erasmus University Rotterdam, and Tinbergen Institute, the Netherlands; Complutense University of Madrid, Spain); Teodosio Pérez-Amaral (Complutense University of Madrid, Spain)
    Abstract: Bank risk managers follow the Basel Committee on Banking Supervision (BCBS) recommendations that recently proposed shifting the quantitative risk metrics system from Value-at-Risk (VaR) to Expected Shortfall (ES). The Basel Committee on Banking Supervision (2013, p. 3) noted that: “a number of weaknesses have been identified with using VaR for determining regulatory capital requirements, including its inability to capture tail risk”. The proposed reform costs and impact on bank balances may be substantial, such that the size and distribution of daily capital charges under the new rules could be affected significantly. Regulators and bank risk managers agree that all else being equal, a “better” distribution of daily capital charges is to be preferred. The distribution of daily capital charges depends generally on two sets of factors: (1) the risk function that is adopted (ES versus VaR); and (2) their estimated counterparts. The latter is dependent on what models are used by bank risk managers to provide for forecasts of daily capital charges. That is to say, while ES is known to be a preferable “risk function” based on its fundamental properties and greater accounting for the tails of alternative distributions, that same sensitivity to tails can lead to greater daily capital charges, which is the relevant (that is, controlling) practical reference for risk management decisions and observations. In view of the generally agreed focus in this field on the tails of non-standard distributions and low probability outcomes, an assessment of relative merits of estimated ES and estimated VaR is ideally not limited to mean variance considerations. For this reason, robust comparisons between ES and VaR will be achieved in the paper by using a Stochastic Dominance (SD) approach to rank ES and VaR.
    Keywords: Stochastic dominance; Value-at-Risk; Expected Shortfall; Optimizing strategy; Basel III Accord
    JEL: G32 G11 G17 C53 C22
    Date: 2015–12–15
  2. By: Carlos León; Constanza Martínez; Freddy Cepeda
    Abstract: We implement a modified version of DebtRank, a measure of systemic impact inspired in feedback centrality, to recursively measure the contagion effects caused by the default of a selected financial institution. In our case contagion is a liquidity issue, measured as the decrease in financial institutions’ short-term liquidity position across the Colombian interbank network. Concurrent with related literature, unless contagion dynamics are preceded by a major –but unlikely- drop in the short-term liquidity position of all participants, we consistently find that individual and systemic contagion effects are negligible. We find that negative effects resulting from contagion are concentrated in a few financial institutions. However, as most of their impact is conditional on the occurrence of unlikely major widespread illiquidity events, and due to the subsidiary contribution of the interbank market to the local money market, their overall systemic importance is still to be confirmed.
    Keywords: Financial networks, contagion, default, liquidity, DebtRank.
    Date: 2015–12–24
  3. By: Oet, Mikhail V. (Federal Reserve Bank of Cleveland); Ong, Stephen J. (Federal Reserve Bank of Cleveland)
    Abstract: This paper studies and connects market organization and activity in the US collateralized interbank market using an assumption-neutral approach. We apply cluster analysis to aggregate activity factors suggested by prior studies to support two market organizations: three-tier and core-periphery. We find that four bank-specific factors and one economic conditions factor explain interbank activity for both alternative organizations. We also find evidence that the interbank market organization affects institutions’ borrowing and lending. While both organizations moderate interbank activity, the three-tier structure detects distinct market operations which are not represented in the core-periphery structure.
    Keywords: collateralized interbank market; market organization; tiering; interbank activity factors; cluster analysis; latent factor analysis
    JEL: C30 C38 E44 G10 G21
    Date: 2015–12–14
  4. By: Masror Khah, Sara Abed; Vermaelen, Theo; Wolff, Christian C
    Abstract: This study aims to empirically test the theoretical and financial determinants of contingent convertible (CoCo) bond prices. These determinants can be identified based on the theoretical framework and also CoCo’s anatomy. Here, we use two broad pricing approaches namely Merton and Equity Derivatives Models. For this purpose, we carry out regression analyses on relationship between coco price and key variables suggested by financial theory. The explanatory power of the determinants can be tested using the reported R-squared. If the explanatory power is relatively high, we can conclude that the variable drawn from the theory is clearly important in explaining the pricing of this new asset class. We find that the significance of estimated coefficients are highly consistent with theory. Our results indicate that both Models perform well in CoCo pricing context. Our findings also show that including additional control variables do not considerably improve the predictability power of the above mentioned models
    Keywords: contingent capital bonds
    JEL: G2
    Date: 2015–12

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