nep-rmg New Economics Papers
on Risk Management
Issue of 2017‒02‒05
nine papers chosen by
Stan Miles
Thompson Rivers University

  1. Optimal Dynamic Capital Requirements By Caterina Mendicino; Kalin Nikolov; Javier Suarez; Dominik Supera
  2. Simulated Western Kentucky Grain Farm Cash Flows, Working Capital Erosion, and Evaluation of Risk Management Tools to Manage these Risks By Davis, Todd; Mark, Tyler; Shepherd, Jonathan
  3. Managing the Risks of Corporate Bond Portfolios: New Evidence in the Light of the Sub-Prime Crisis By Giovanni Barone-Adesi; Nicola Carcano; Hakim Dall'O
  4. Non-parameteric news impact curve: a variational approach By Matthieu Garcin; Clément Goulet
  5. Macroeconomic Determinants of Stock Market Volatility and Volatility Risk-Premiums By Valentina Corradi; Walter Distaso; Antonio Mele
  6. Backtesting European Stress Tests By Thomas Philippon; Pierre Pessarossi; Boubacar Camara
  7. A Simple Mechanism for Financial Bubbles: Time-Varying Momentum Horizon By Li Lin; Didier Sornette
  8. Does Competition Affect Bank Risk? By Liangliang Jiang; Ross Levine; Chen Lin
  9. Dimensional Analysis and Market Microstructure Invariance By Albert S. Kyle; Anna Obizhaeva

  1. By: Caterina Mendicino (European Central Bank); Kalin Nikolov (European Central Bank); Javier Suarez (CEMFI); Dominik Supera (CEMFI, Centro de Estudios Monetarios y Financieros)
    Abstract: We characterize welfare maximizing capital requirement policies in a macroeconomic model with household, firm and bank defaults calibrated to Euro Area data. We optimize on the level of the capital requirements applied to each loan class and their sensitivity to changes in default risk. We find that getting the level right (so that bank failure risk remains small) is of foremost importance, while the optimal sensitivity to default risk is positive but typically smaller than under Basel IRB formulas. When starting from low levels, initially both savers and borrowers benefit from higher capital requirements. At higher levels, only savers are in favour of tighter and more time-varying capital charges.
    Keywords: Macroprudential policy, bank fragility, capital requirements, financial frictions, default risk.
    JEL: E3 E44 G01 G21
    Date: 2016–12
  2. By: Davis, Todd; Mark, Tyler; Shepherd, Jonathan
    Abstract: A stochastic simulation model is used to evaluate the profitability and liquidity of a low cost / low debt and high cost / high debt Western Kentucky corn-soybean farm over a five-year period. The model evaluates the effectiveness of crop insurance, government programs, and cash-forward contracts risk management tools and the impact on liquidity and profitability.
    Keywords: simulation, grain, insurance, farm policy, price risk, Agricultural Finance, Farm Management, Risk and Uncertainty, Q,
    Date: 2017
  3. By: Giovanni Barone-Adesi (Swiss Finance Institute, University of Lugano, and Ecole Polytechnique Fédérale de Lausanne); Nicola Carcano (University of Lugano); Hakim Dall'O (Swiss Finance Institute and University of Lugano)
    Abstract: We consider modeling errors in the hedging of a portfolio composed from BBB†rated bonds. By doing this, we open a new perspective to the debate on the relationship between corporate bonds and CDS spreads. We find that in ordinary times the added value of indexlinked credit derivatives is very limited: hedging portfolios including only T-bond futures can reduce the variance by 80-85%. This compares well to the maximum variance reduction of 50% reported by previous studies. On the contrary, in times of extraordinary volatility – such as the years 2008 and 2009 - T-bond futures would have been insufficient to successfully hedge the bond portfolio. However, including the 5-year CDX contract would have only slightly improved the quality of hedging. This is consistent with the literature identifying an important non†default component within corporate bond spreads. Our results encourage the offering of collateralized credit spread forwards as more effective hedging instruments than non†collateralized CDS contracts.
    Keywords: hedging, corporate bonds, model errors
    JEL: C51 G13 G32
  4. By: Matthieu Garcin (Natixis Asset Management et LabEX ReFi); Clément Goulet (Centre d'Economie de la Sorbonne et LabEX ReFi)
    Abstract: In this paper, we propose an innovative methodology for modelling the news impact curve. The news impact curve provides a non-linear relation between past returns and current volatility and thus enables to forecast volatility. Our news impact curve is the solution of a dynamic optimization problem based on variational calculus. Consequently, it is a non-parametric and smooth curve. To our knowledge, this is the first time that such a method is used for volatility modelling. Applications on simulated heteroskedastic processes as well as on financial data show a better accuracy in estimation and forecast for this approach than for standard parametric (symmetric or asymmetric ARCH) or non-parametric (Kernel-ARCH) econometric techniques
    Keywords: Volatility modeling; news impact curve; calculus of variations; wavelet theory; ARCH
    JEL: C02 C14 C22 C51 C53 C58 C61
    Date: 2015–09
  5. By: Valentina Corradi (University of Warwick); Walter Distaso (Imperial College Business School); Antonio Mele (Swiss Finance Institute, University of Lugano, and Centre for Economic Policy Research (CEPR))
    Abstract: How does stock market volatility relate to the business cycle? We develop, and estimate, a no-arbitrage model to study the cyclical properties of stock volatility and the risk-premiums the market requires to bear the risk of uctuations in this volatility. The level of stock market volatility cannot be explained by the mere existence of the business cycle. Rather, it relates to the presence of some unobserved factor. At the same time, our model predicts that such an unobservable factor cannot explain the ups and downs stock volatility experiences over time - the "volatility of volatility." Instead, the volatility of stock volatility relates to the business cycle. Finally, volatility risk-premiums are strongly countercyclical, even more so than stock volatility, and are partially responsible for the large swings in the VIX index occurred during the 2007-2009 subprime crisis, which our model does capture in out-of-sample experiments.
    Keywords: Aggregate stock market volatility, volatility risk-premiums, volatility of volatility, business cycle, no-arbitrage restrictions, simulation-based inference
    JEL: C15 C32 E37 E44 G13 G17
  6. By: Thomas Philippon; Pierre Pessarossi; Boubacar Camara
    Abstract: We provide a first evaluation of the quality of banking stress tests in the European Union. We use stress tests scenarios and banks’ estimated losses to recover bank level exposures to macroeconomic factors. Once macro outcomes are realized, we predict banks’ losses and compare them to actual losses. We find that stress tests are informative and unbiased on average. Model-based losses are good predictors of realized losses and of banks’ equity returns around announcements of macroeconomic news. When we perform our tests for the Union as a whole, we do not detect biases in the construction of the scenarios, or in the estimated losses across banks of different sizes and ownership structures. There is, however, some evidence that exposures are underestimated in countries with ex-ante weaker banking systems. Our results have implications for the modeling of credit losses, quality controls of supervision, and the political economy of financial regulation.
    JEL: G01 G18 G2 G21 G28 G32
    Date: 2017–01
  7. By: Li Lin (East China University of Science and Technology (ECUST)); Didier Sornette (ETH Zurich and Swiss Finance Institute)
    Abstract: Building on the notion that bubbles are transient self-fulfilling prophecies created by positive feedback mechanisms, we construct the simplest continuous price process whose expected returns and volatility are functions of momentum only. The momentum itself is measured by a simple continuous moving average of past prices over a given time horizon. We introduce a simple dynamics of the time horizon used by the representative investor, which is motivated by the race of trend-following agents to forerun their competitors. Moreover, we make explicit the price processes that exclude risk-free arbitrage opportunities but allow for momentum trading strategies with time-varying horizons. The model consists finally in one specification for the non-bubble regime and a second specification for the bubble regime, with the transition from one to the other controlled by the crossing of a momentum threshold. The proposed price generating process generates the main stylized facts of empirical financial time series. Moreover, it produces realistic regime shifts between non-bubble and bubble regimes. We construct a quasi-likelihood methodology to calibrate the model to empirical financial time series, which is applied to eight empirical historical cases that exhibit large volatility bursts and are candidates for the presence of bubbles. The calibration supports the relevance of the proposed model to represent a significant component of historical bubble regimes.
    Keywords: Financial Bubbles, Momentum, Positive Feedback, Time-Horizon, Quasi-Likelihood, Regime Shifts
    JEL: C52 G01 G17
  8. By: Liangliang Jiang; Ross Levine; Chen Lin
    Abstract: Although policymakers often discuss tradeoffs between bank competition and stability, past research provides differing theoretical perspectives and empirical results on the impact of competition on risk. In this paper, we employ a new approach for identifying exogenous changes in the competitive pressures facing individual banks and discover that an intensification of competition materially boosts bank risk. With respect to the mechanisms, we find that competition reduces bank profits, charter values, and relationship lending and increases banks’ provision of nontraditional banking services.
    JEL: G21 G28 G32 L1
    Date: 2017–01
  9. By: Albert S. Kyle (Robert H. Smith School of Business, University of Maryland); Anna Obizhaeva (New Economic School)
    Abstract: Market microstructure is the subfield of finance and econophysics1 which studies how prices result from the process of trading securities. Large trades move prices2 and incur trading costs. Here we combine dimensional analysis, leverage neutrality, and a principle of market microstructure invariance to derive scaling laws which express transaction costs functions, bid-ask spreads, bet sizes, number of bets, and other financial variables in terms of trading volume and volatility. For example, market liquidity is proportional to the cube root of the ratio of dollar volume to return variance. We illustrate the scaling by showing that bid-ask spreads in Russian stocks indeed scale with the cube root. In addition to being of interest to risk managers and traders, these scaling laws provide scientific benchmarks for evaluating controversial issues related to high frequency trading, market crashes, and liquidity measurement as well as guidelines for designing policies in the aftermath of financial crisis.
    Date: 2017–01

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