nep-rmg New Economics Papers
on Risk Management
Issue of 2020‒02‒10
23 papers chosen by

  1. Intra-Horizon Expected Shortfall and Risk Structure in Models with Jumps By Walter Farkas; Ludovic Mathys; Nikola Vasiljevic
  2. Quantile Mixing and Model Uncertainty Measures By Thierry Cohignac; Nabil Kazi-Tani
  3. A tail dependence-based MST and their topological indicators in modelling systemic risk in the European insurance sector By Anna Denkowska; Stanis{\l}aw Wanat
  4. Investor Happiness and Predictability of the Realized Volatility of Oil Price By Matteo Bonato; Konstantinos Gkillas; Rangan Gupta; Christian Pierdzioch
  5. Cross-border loan portfolio diversification, capital requirements, and the European Banking Union By Jokivuolle, Esa; Virén, Matti
  6. A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting By Zhengkun Li; Minh-Ngoc Tran; Chao Wang; Richard Gerlach; Junbin Gao
  7. Refined model of the covariance/correlation matrix between securities By Sebastien Valeyre
  8. Pareto models for risk management By Arthur Charpentier; Emmanuel Flachaire
  9. Modeling multivariate operational losses via copula-based distributions with g-and-h marginals By Marco Bee; Julien Hambuckers
  10. Markov risk mappings and risk-averse optimal stopping under ambiguity By Randall Martyr; John Moriarty
  11. Semi-metric portfolio optimisation: a new algorithm reducing simultaneous asset shocks By Nick James; Max Menzies; Jennifer Chan
  12. Banking crisis prediction with differenced relative credit By Kauko, Karlo; Tölö, Eero
  13. A Note on Investor Happiness and the Predictability of Realized Volatility of Gold By Matteo Bonato; Konstantinos Gkillas; Rangan Gupta; Christian Pierdzioch
  14. Exchange Rates and Political Uncertainty: The Brexit Case By P. Manasse; G. Moramarco; G. Trigilia
  15. Portfolio configuration and foreign entry decisions: A juxtaposition of real options and risk diversification theories By Rene Belderbos; Tony W Tong; Shubin Wu
  16. Volatility Dependent Structured Products By Artem Dyachenko; Walter Farkas; Marc Oliver Rieger
  17. Asymptotics of the time-discretized log-normal SABR model: The implied volatility surface By Dan Pirjol; Lingjiong Zhu
  18. A Note on Oil Price Shocks and the Forecastability of Gold Realized Volatility By Riza Demirer; Rangan Gupta; Christian Pierdzioch; Syed Jawad Hussain Shahzad
  19. Implied Volatility Changes and Corporate Bond Returns By Jie Cao; Amit Goyal; Xiao Xiao; Xintong Zhan
  20. Sharpe Ratio in High Dimensions: Cases of Maximum Out of Sample, Constrained Maximum, and Optimal Portfolio Choice By Mehmet Caner; Marcelo Medeiros; Gabriel Vasconcelos
  21. Improving portfolios global performance using a cleaned and robust covariance matrix estimate By Emmanuelle Jay; Thibault Soler; Eugénie Terreaux; Jean-Philippe Ovarlez; Frédéric Pascal; Philippe de Peretti; Christophe Chorro
  22. Risk-Neutral Momentum and Market Fear By Wolfgang Schadner
  23. Las entidades de contrapartida central en la mitigación del riesgo de contraparte y de liquidez: El caso de los derivados cambiarios en Colombia By Ricardo Mariño-Martínez; Carlos León; Carlos Cadena-Silva

  1. By: Walter Farkas (University of Zurich - Department of Banking and Finance; Swiss Finance Institute; ETH Zurich); Ludovic Mathys (University of Zurich - Department of Banking and Finance); Nikola Vasiljevic (University of Zurich, Department of Banking and Finance)
    Abstract: The present article deals with intra-horizon risk in models with jumps. Our general understanding of intra-horizon risk is along the lines of the approach taken in [BRSW04], [Ro08], [BMK09], [BP10], and [LV19]. In particular, we believe that quantifying market risk by strictly relying on point-in-time measures cannot be deemed a satisfactory approach in general. Instead, we argue that complementing this approach by studying measures of risk that capture the magnitude of losses potentially incurred at any time of a trading horizon is necessary when dealing with (m)any financial position(s). To address this issue, we propose an intra-horizon analogue of the expected shortfall for general profit and loss processes and discuss its key properties. Our intra-horizon expected shortfall is well-defined for (m)any popular class(es) of Levy processes encountered when modeling market dynamics and constitutes a coherent measure of risk, as introduced in [CDK04]. On the computational side, we provide a simple method to derive the intra-horizon risk inherent to popular Levy dynamics. Our general technique relies on results for maturity-randomized first-passage probabilities and allows for a derivation of diffusion and single jump risk contributions. These theoretical results are complemented with an empirical analysis, where popular Levy dynamics are calibrated to S&P 500 index data and an analysis of the resulting intra-horizon risk is presented.
    Keywords: Intra-Horizon Risk, Value at Risk, Expected Shortfall, Levy Processes, Hyper-Exponential Distribution, Risk Decomposition
    JEL: C32 C63 G01
    Date: 2019–12
  2. By: Thierry Cohignac; Nabil Kazi-Tani (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)
    Abstract: In this paper, we introduce a new simple methodology for combining two models, which are given in the form of two probability distributions. We use convex combinations of quantile functions, with weights depending on the quantile level. We choose the weights by comparing, for each quantile level, a given measure of model uncertainty calculated for the two probability distributions that we want to combine. This methodology is particularly useful in insurance and reinsurance of natural disasters, for which there are various physical models available, along with historical data. We apply our procedure to a real portfolio of insurance losses, and show that the model uncertainty measures have a similar behavior on the set of various insurance losses that we consider. This article serves also as an introduction to the use of model uncertainty measures in actuarial practice.
    Keywords: Model combination,Model uncertainty,Quantiles,Risk management,Catastrophe models
    Date: 2019–12–11
  3. By: Anna Denkowska; Stanis{\l}aw Wanat
    Abstract: In the present work we analyze the dynamics of indirect connections between insurance companies that result from market price channels. In our analysis we assume that the stock quotations of insurance companies reflect market sentiments which constitute a very important systemic risk factor. Interlinkages between insurers and their dynamics have a direct impact on systemic risk contagion in the insurance sector. We propose herein a new hybrid approach to the analysis of interlinkages dynamics based on combining the copula-DCC-GARCH model and Minimum Spanning Trees (MST). Using the copula-DCC-GARCH model we determine the correlation coefficients in the distribution tails. Then, for each analysed period we construct MST based on these coefficients. The dynamics is analysed by means of time series of selected topological indicators of the MSTs. Our empirical results show the usefulness of the proposed approach to the analysis of systemic risk in the insurance sector. The times series obtained from the proposed hybrid approach reflect the phenomena occurring on the market. The analysed MST topological indicators can be considered as systemic risk predictors.
    Date: 2020–01
  4. By: Matteo Bonato (Department of Economics and Econometrics, University of Johannesburg, Auckland Park, South Africa and IPAG Business School, 184 Boulevard Saint-Germain, 75006 Paris, France); Konstantinos Gkillas (Department of Business Administration, University of Patras – University Campus, Rio, P.O. Box 1391, 26500 Patras, Greece); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa); Christian Pierdzioch (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany)
    Abstract: We use the heterogeneous autoregressive realized volatility (HAR-RV) model to analyze both in sample and out-of-sample whether a measure of investor happiness predicts the daily realized volatility of oil-price returns, where we use high-frequency intradaily data to measure realized volatility. Full-sample estimates reveal that realized volatility is significantly negatively linked to investor happiness at a short forecast horizon. Similarly, out-of-sample results indicate that investor happiness significantly improves accuracy of forecasts of realized volatility at a short forecast horizon. Results for a medium and a long forecast horizon are insignificant. We argue that our results shed light on the role played by speculation in oil products and the potential function of oil-related products as a hedge against risks in traditional financial assets.
    Keywords: Investor Happiness, Oil market, Realized Volatility, Forecasting
    JEL: G15 G17 Q02
    Date: 2020–01
  5. By: Jokivuolle, Esa; Virén, Matti
    Abstract: We provide preliminary evidence of potential risk reduction benefits from banks’ loan portfolio diversification cross-border within the Euro area. Using aggregate data on banking sector cor-porate loan losses for each Euro area member-state, our estimates suggest that the static diversification benefit could be substantial. The minimum capital needed to withstand the max-imum annual loss from a hypothetical fully diversified Euro area bank loan portfolio over the period 2001-2017 would have been only 40 % of the total capital needed to withstand the maximum losses on a country by country basis. We also calibrate the country-specific loan loss distributions and the Euro area portfolio’s loss distribution to the Vasicek (2002) model, which underlies the Basel framework’s Internal Ratings Based Approach. We find that the im-plied asset correlation parameter of a median country portfolio is about twice as large as that of the fully diversified Euro area portfolio.
    Keywords: pankit,luotot,euroalue
    Date: 2019
  6. By: Zhengkun Li; Minh-Ngoc Tran; Chao Wang; Richard Gerlach; Junbin Gao
    Abstract: Value-at-Risk (VaR) and Expected Shortfall (ES) are widely used in the financial sector to measure the market risk and manage the extreme market movement. The recent link between the quantile score function and the Asymmetric Laplace density has led to a flexible likelihood-based framework for joint modelling of VaR and ES. It is of high interest in financial applications to be able to capture the underlying joint dynamics of these two quantities. We address this problem by developing a hybrid model that is based on the Asymmetric Laplace quasi-likelihood and employs the Long Short-Term Memory (LSTM) time series modelling technique from Machine Learning to capture efficiently the underlying dynamics of VaR and ES. We refer to this model as LSTM-AL. We adopt the adaptive Markov chain Monte Carlo (MCMC) algorithm for Bayesian inference in the LSTM-AL model. Empirical results show that the proposed LSTM-AL model can improve the VaR and ES forecasting accuracy over a range of well-established competing models.
    Date: 2020–01
  7. By: Sebastien Valeyre
    Abstract: A new methodology has been introduced to clean the correlation matrix of single stocks returns based on a constrained principal component analysis using financial data. Portfolios were introduced, namely "Fundamental Maximum Variance Portfolios", to capture in an optimal way the risks defined by financial criteria ("Book", "Capitalization", etc.). The constrained eigenvectors of the correlation matrix, which are the linear combination of these portfolios, are then analyzed. Thanks to this methodology, several stylized patterns of the matrix were identified: i) the increase of the first eigenvalue with a time scale from 1 minute to several months seems to follow the same law for all the significant eigenvalues with 2 regimes; ii) a universal law seems to govern the weights of all the "Maximum variance" portfolios, so according to that law, the optimal weights should be proportional to the ranking based on the financial studied criteria; iii) the volatility of the volatility of the "Maximum Variance" portfolios, which are not orthogonal, could be enough to explain a large part of the diffusion of the correlation matrix; iv) the leverage effect (increase of the first eigenvalue with the decline of the stock market) occurs only for the first mode and cannot be generalized for other factors of risk. The leverage effect on the beta, which is the sensitivity of stocks with the market mode, makes variable the weights of the first eigenvector.
    Date: 2020–01
  8. By: Arthur Charpentier (UQAM - Université du Québec à Montréal); Emmanuel Flachaire (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - ECM - Ecole Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique - AMU - Aix Marseille Université - EHESS - École des hautes études en sciences sociales)
    Date: 2019–12–26
  9. By: Marco Bee; Julien Hambuckers
    Abstract: We propose a family of copula-based multivariate distributions with g-and- h marginals. After studying the properties of the distribution, we develop a two-step estimation strategy and analyze via simulation the sampling distribution of the estimators. The methodology is used for the analysis of a 7-dimensional dataset containing 40,871 operational losses. The empirical evidence suggests that a distribution based on a single copula is not flexible enough, thus we model the dependence structure by means of vine copulas. We show that the approach based on regular vines improves the fit. Moreover, even though losses corresponding to different event types are found to be dependent, the assumption of perfect positive dependence is not supported by our analysis. As a result, the Value-at-Risk of the total operational loss distribution obtained from the copula- based technique is substantially smaller at high confidence levels, with respect to the one obtained using the common practice of summing the univariate Value-at-Risks.
    Keywords: loss model; dependence structure; vine copula; Value-at-Risk
    JEL: C46 C63
    Date: 2020
  10. By: Randall Martyr; John Moriarty
    Abstract: We aim to analyse a Markovian discrete-time optimal stopping problem for a risk-averse decision maker under model ambiguity. In contrast to the analytic approach based on transition risk mappings, a probabilistic setting is introduced based on novel concepts of regular conditional risk mapping and Markov update rule. To accommodate model ambiguity we introduce appropriate notions of history-consistent updating and of transition consistency for risk mappings on nested probability spaces.
    Date: 2020–01
  11. By: Nick James; Max Menzies; Jennifer Chan
    Abstract: This paper proposes a new method for financial portfolio optimisation based on reducing simultaneous asset shocks across a portfolio of assets. We adopt the new semi-metrics of \citep{James2019} to determine the distance between two time series' structural breaks. We build on the optimal portfolio theory of \citep{Markowitz1952}, but utilize distance between asset structural breaks, rather than portfolio variance, as our penalty function. Our experiments are promising: on synthetic data, they indicate that our proposed method does indeed diversify among time series with highly similar structural breaks. On real data, experiments illustrate that our proposed optimisation method produces higher risk-adjusted returns than mean variance portfolio optimisation. The predictive distribution is superior in every measure, producing a higher mean, lower standard deviation and less kurtosis. The main implication for this method in portfolio management is reducing simultaneous asset shocks and potentially sharp associated drawdowns, during periods of highly similar structural breaks, such as a market crisis.
    Date: 2020–01
  12. By: Kauko, Karlo; Tölö, Eero
    Abstract: Indicators based on the ratio of credit to GDP have been found to be highly useful predictors of banking crises. We study the difference in this ratio as an early warning indicator. We test a large number of different versions of the differenced credit-to-GDP ratio with data on Euro area members. The optimal time interval of the difference is about two years. Using the moving average of GDP instead of the latest annual data has little impact on forecasting performance. The indicator is a particularly promising choice at relatively short forecasting horizons, such as two or three years.
    Keywords: banking crises,early warning indicators,differenced relative credit,credit intensity,countercyclical capital buffer
    JEL: G01 G17 G28
    Date: 2019
  13. By: Matteo Bonato (Department of Economics and Econometrics, University of Johannesburg, Auckland Park, South Africa and IPAG Business School, 184 Boulevard Saint-Germain, 75006 Paris, France); Konstantinos Gkillas (Department of Business Administration, University of Patras – University Campus, Rio, P.O. Box 1391, 26500 Patras, Greece); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa); Christian Pierdzioch (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany)
    Abstract: We apply the heterogeneous autoregressive realized volatility (HAR-RV) model to examine the importance of investor happiness in predicting the daily realized volatility of gold returns. We estimate daily realized volatility by employing intraday data providing both in-sample and out-of sample predictions. Our in-sample results reveal that realized volatility is negatively linked to investor happiness. Moreover, our out-of-sample results show that extending the HAR-RV model to include investor happiness significantly improves the accuracy of forecasts of realized volatility at short- and medium-run forecast horizons.
    Keywords: Investor Happiness, Gold, Realized Volatility, Forecasting
    JEL: G15 G17 Q02
    Date: 2020–01
  14. By: P. Manasse; G. Moramarco; G. Trigilia
    Abstract: This paper studies the impact of political risk on exchange rates. We focus on the Brexit Referendum as it provides a natural experiment where both exchange rate expectations and a time-varying political risk factor can be measured directly. We build a simple portfolio model which predicts that an increase in the Leave probability triggers a depreciation of the British Pound, both on account of exchange rate expectations and of political risk. We estimate the model for multilateral and bilateral British Pound exchange rates. The results confirm the model’s main implications. When we extend the analysis to a portfolio model of multiple currencies, we find that the cross-currencies restrictions implied by the theory are not rejected by our system estimation. Moreover, the joint estimates of the multi-currency model in the presence of time-varying political risk premium are in many cases consistent with the Uncovered Interest Parity.
    JEL: F31 F41 G11 G15
    Date: 2020–02
  15. By: Rene Belderbos; Tony W Tong; Shubin Wu
    Abstract: Research Summary: Research on foreign market entry has rarely considered that multinational firms’ new entries may be affected by the configuration of their existing affiliates. We argue that in making entry decisions, firms take into account how an entry into a new location helps increase the operational flexibility of their affiliate portfolios due to options to switch operations across affiliates in case of diverging labor cost developments across host countries. We juxtapose this real options based explanation with a risk diversification explanation. Analysis of Japanese multinational firms’ foreign entry decisions suggests that the two explanations are complementary. We also establish portfolio-level boundary conditions to the influence of operational flexibility considerations on entry, in the form of product diversification and the nature of dispersion of labor cost levels.
    Keywords: Market entry, multinational firm, real options, flexibility, risk diversification, portfolio
    Date: 2020–01–17
  16. By: Artem Dyachenko (University of Trier - Faculty of Economics); Walter Farkas (University of Zurich - Department of Banking and Finance; Swiss Finance Institute; ETH Zurich); Marc Oliver Rieger (University of Trier)
    Abstract: We construct a derivative that depends on the SPY and VIX and, in this way, incorporates both the market risk premium and the variance risk premium. We show that our product has a Sharpe ratio that is at least as high as the Sharpe ratio of the SPY. If one could invest $10,000 either in the product or the SPY at the end of 2008, the payoff of the product would be around $80,000 at the end of 2018 whereas the payoff of the SPY - around $30,000.
    Keywords: asset pricing, structured products, derivatives
    JEL: G12 G13
    Date: 2019–12
  17. By: Dan Pirjol; Lingjiong Zhu
    Abstract: We propose a novel time discretization for the log-normal SABR model $dS_t = \sigma_t S_t dW_t, d\sigma_t = \omega \sigma_t dZ_t$, with $\mbox{corr}(W_t,Z_t)=\varrho$, which is a variant of the Euler-Maruyama scheme, and study its asymptotic properties in the limit of a large number of time steps $n\to \infty$ at fixed $\beta = \frac12\omega^2 n^2\tau,\rho = \sigma_0\sqrt{\tau}$. We derive an almost sure limit and a large deviations result for the log-asset price in the $n\to \infty$ limit. The rate function of the large deviations result does not depend on the discretization time step $\tau$. The implied volatility surface $\sigma_{\rm BS}(K,T)$ for arbitrary maturity and strike in the limit $\omega^2 T \to 0 , \sigma_0^2 T \to \infty$ at fixed $(\omega^2 T)(\sigma_0^2 T)$ is represented as an extremal problem. Using this representation we obtain analytical expansions of $\sigma_{\rm BS}(K,T)$ for small maturity and extreme strikes.
    Date: 2020–01
  18. By: Riza Demirer (Department of Economics and Finance, Southern Illinois University Edwardsville, Edwardsville, IL 62026-1102, USA); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa); Christian Pierdzioch (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany); Syed Jawad Hussain Shahzad (Montpellier Business School, Montpellier, France and South Ural State University, Chelyabinsk, Russian Federation)
    Abstract: We examine the predictive power of disentangled oil price shocks over gold market volatility via the heterogeneous autoregressive realized volatility (HAR-RV) model. Our in- and out-of-sample tests show that combining the information from both oil supply and demand shocks with the innovations associated with financial market risks improves the forecast accuracy of realized volatility of gold. While financial risk shocks are important on their own, including oil price shocks in the model provides additional forecasting power in out-of-sample tests. Compared to the benchmark HAR-RV model, the extended model with all the three shocks included outperforms, in a statistically significant manner, all other variants of the HAR-RV framework for short-, medium, and long-run forecasting horizons. The findings highlight the predictive power of cross-market information in commodities and suggest that disentangling supply and demand related factors associated with price shocks could help improve the accuracy of forecasting models.
    Keywords: Oil Shocks, Risk Shocks, Gold, Realized Volatility, Forecasting
    JEL: C22 C53 Q02
    Date: 2020–01
  19. By: Jie Cao (The Chinese University of Hong Kong (CUHK) - CUHK Business School); Amit Goyal (University of Lausanne; Swiss Finance Institute); Xiao Xiao (Erasmus University Rotterdam (EUR) - Erasmus School of Economics (ESE)); Xintong Zhan (The Chinese University of Hong Kong (CUHK) - CUHK Business School)
    Abstract: Option implied volatility change has significant cross-sectional predictive power for the underlying firms’ bond returns. Corporate bonds with large increases in implied volatilities over the past month underperform those with large decreases in implied volatilities by approximately 0.6% per month. The results are robust to various bond characteristics and volatility related variables, as well as to stock and bond factor models. Our results are consistent with the notion that informed traders with new information about default risk prefer to trade in the option market, and that the corporate bond market is slow in incorporating that information.
    Keywords: Corporate bonds, implied volatility changes, default risk, information diffusion
    JEL: G10 G12 G14
    Date: 2019–06
  20. By: Mehmet Caner; Marcelo Medeiros; Gabriel Vasconcelos
    Abstract: In this paper, we analyze maximum Sharpe ratio when the number of assets in a portfolio is larger than its time span. One obstacle in this large dimensional setup is the singularity of the sample covariance matrix of the excess asset returns. To solve this issue, we benefit from a technique called nodewise regression, which was developed by Meinshausen and Buhlmann (2006). It provides a sparse/weakly sparse and consistent estimate of the precision matrix, using the Lasso method. We analyze three issues. One of the key results in our paper is that mean-variance efficiency for the portfolios in large dimensions is established. Then tied to that result, we also show that the maximum out-of-sample Sharpe ratio can be consistently estimated in this large portfolio of assets. Furthermore, we provide convergence rates and see that the number of assets slow down the convergence up to a logarithmic factor. Then, we provide consistency of maximum Sharpe Ratio when the portfolio weights add up to one, and also provide a new formula and an estimate for constrained maximum Sharpe ratio. Finally, we provide consistent estimates of the Sharpe ratios of global minimum variance portfolio and Markowitz's (1952) mean variance portfolio. In terms of assumptions, we allow for time series data. Simulation and out-of-sample forecasting exercise shows that our new method performs well compared to factor and shrinkage based techniques.
    Date: 2020–02
  21. By: Emmanuelle Jay (Quanted & Europlace Institute of Finance, Fideas Capital); Thibault Soler (Fideas Capital, CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Eugénie Terreaux (DEMR, ONERA, Université Paris Saclay [Palaiseau] - ONERA - Université Paris-Saclay); Jean-Philippe Ovarlez (DEMR, ONERA, Université Paris Saclay [Palaiseau] - ONERA - Université Paris-Saclay); Frédéric Pascal (L2S - Laboratoire des signaux et systèmes - CNRS - Centre National de la Recherche Scientifique - CentraleSupélec - UP11 - Université Paris-Sud - Paris 11, CentraleSupélec); Philippe de Peretti (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, UP1 - Université Panthéon-Sorbonne); Christophe Chorro (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, UP1 - Université Panthéon-Sorbonne)
    Abstract: This paper presents how the most recent improvements made on covariance matrix estimation and model order selection can be applied to the portfolio optimization problem. The particular case of the Maximum Variety Portfolio is treated but the same improvements apply also in the other optimization problems such as the Minimum Variance Portfolio. We assume that the most important information (or the latent factors) are embedded in correlated Elliptical Symmetric noise extending classical Gaussian assumptions. We propose here to focus on a recent method of model order selection allowing to efficiently estimate the subspace of main factors describing the market. This non-standard model order selection problem is solved through Random Matrix Theory and robust covariance matrix estimation. Moreover we extend the method to non-homogeneous assets returns. The proposed procedure will be explained through synthetic data and be applied and compared with standard techniques on real market data showing promising improvements.
    Keywords: Maximum Variety Portfolio,Elliptical Symmetric Noise,Robust Covariance Matrix Estimation,Model Order Selection,Random Matrix Theory,Portfolio Optimisation,Financial Time Series,Multi-Factor Model
    Date: 2019–10
  22. By: Wolfgang Schadner
    Abstract: This study models a link between ex-ante autocorrelation in expected returns and risk-neutral momentum, enabling a straightforward interpretation of market sentiment. Correspondingly, concepts of fractal Brownian motion are applied to option implied volatility term structures. Based on an empirical investigation of daily SP500 and Euro Stoxx 50 data (2006{2018), we find that the expected return momentum varies over time, as fear spreads much faster than investor confidence can be regained. Thus, we conclude that risk-neutral momentum is a novel perspective for further research in the fields of risk management, asset allocation, and behavioral finance.
    Keywords: momentum, sentiment, implied volatility, long-term memory, fractal Brownian motion, market fear
    JEL: C22 G01 G12
    Date: 2019–11
  23. By: Ricardo Mariño-Martínez (Banco de la República de Colombia); Carlos León (Banco de la República de Colombia); Carlos Cadena-Silva (Banco de la República de Colombia)
    Abstract: Las entidades de contrapartida central (ECC) se interponen entre compradores y vendedores para eliminar sus obligaciones bilaterales y así mitigar el riesgo de contraparte. Es de esperar que esta interposición afecte la manera en que interactúan los participantes en los mercados financieros. Con base en datos transaccionales de las operaciones de intercambio a plazo peso-dólar sin entrega (COP/USD FX-non-delivery forwards) y en el análisis de redes, este artículo compara las transacciones cuando se acuerda la compensación y liquidación por intermedio de la Cámara de Riesgo Central de Contraparte de Colombia (CRCC) con aquellas en las que se acuerda la compensación y liquidación bilateral –sin la CRCC. El efecto de la interposición de la CRCC es el esperado. La red de transacciones en las que se acuerda la interposición de la CRCC muestra un aumento significativo en la conectividad (i.e. mayor densidad, reciprocidad y agrupamiento), y una disminución significativa en la distancia entre participantes. Esto sugiere que acordar la interposición de la CRCC permite mitigar el riesgo de liquidez. Con la interposición, la red de exposiciones resultante presenta una menor conectividad y mayor distancia, lo cual es consistente con la mitigación del riesgo de contraparte. Las diferencias en la estructura de las redes son significativas. Los resultados son relevantes porque permiten visualizar y cuantificar el efecto que tiene la CRCC en la administración del riesgo.**** ABSTRACT: A central counterparty (CCP) interposes itself between buyers and sellers of financial contracts to extinguish their bilateral exposures and –thus- to reduce counterparty risk. Therefore, this interposition should affect the way market participants engage in financial markets. Based on transactional data corresponding to the Colombian Peso non-delivery forward market and network analysis basics, this article compares transactions agreed to be cleared and settled by Cámara de Riesgo Central de Contraparte de Colombia (CRCC, the sole CCP in Colombia) with those to be cleared and settled bilaterally. The effect corresponds to what is expected. Networks of transactions to be cleared and settled by CRCC show significantly higher connectivity (i.e. higher density, reciprocity and transitivity), along with a lower distance among participating financial institutions. This suggests that agreeing on clearing and settlement by CRCC reduces liquidity risk. With the interposition of CRCC the resulting exposures networks show lower connectivity and higher distances, which concurs with counterparty risk mitigation. Differences in the structure of networks are significant. Results are important as they enable to visualize and quantify the effect of clearing and settlement by CRCC in risk management.
    Keywords: Riesgo de contraparte, riesgo de liquidez, redes, compensación central
    JEL: D85 L14 G2 E42
    Date: 2020–02

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