nep-rmg New Economics Papers
on Risk Management
Issue of 2007‒12‒08
four papers chosen by
Stan Miles
Thompson Rivers University

  1. Ratings Versus Market-Based Measures of Default Risk of East Asian Banks By Eric Wong; Cho-Hoi Hui; Chi-fai Lo
  2. An empirical analysis of asset-backed securitization By Vink, Dennis; Thibeault, André E.
  3. "Estimating Stochastic Volatility Models Using Daily Returns and Realized Volatility Simultaneously" By Makoto Takahashi; Yasuhiro Omori; Toshiaki Watanabe
  4. Exchange rate volatility, macro announcements and the choice of intraday seasonality filtering method By Laakkonen, Helinä

  1. By: Eric Wong (Research Department, Hong Kong Monetary Authority); Cho-Hoi Hui (Research Department, Hong Kong Monetary Authority); Chi-fai Lo (Institute of Theoretical Physics and Department of Physics, The Chinese University of Hong Kong)
    Abstract: This paper assesses whether agency ratings and market-based default risk measures are consistent for East Asian banks during the period 1996 to 2006. While the market-based measures are broadly consistent with the credit rating assessments for banks in developed economies, the discrepancy between ratings and the market-based measures for East Asian banks is significant. Credit ratings for East Asian banks were adjusted slowly during the onset of the Asian financial crisis. The relatively higher default risk implied by ratings during the post-crisis period is partly due to the conservatism of rating agencies and the unsolicited ratings. Discrepancies still exist after taking these two factors into account. From perspective of banking policies, the use of agency-based and market-based measures for calculating capital requirements for exposures to banks and deposit insurance premiums in East Asian economies could result in systematic differences.
    Keywords: Asian financial crisis, credit rating agencies, credit risk models
    JEL: G14 G13 G21 G32
    Date: 2007–08
  2. By: Vink, Dennis; Thibeault, André E. (Nyenrode Business Universiteit)
    Abstract: In this study we provide empirical evidence demonstrating a relationship between the nature of the assets and the primary market spread. The model also provides predictions on how other pricing characteristics affect spread, since little is known about how and why spreads of asset-backed securities are influenced by loan tranche characteristics. We find that default and recovery risk characteristics represent the most important group in explaining loan spread variability. Within this group, the credit rating dummies are the most important variables to determine loan spread at issue. Nonetheless, credit rating is not a sufficient statistic for the determination of spreads. We find that the nature of the assets has a substantial impact on the spread across all samples, indicating that primary market spread with backing assets that cannot easily be replaced is significantly higher relative to issues with assets that can easily be obtained. Of the remaining characteristics, only marketability explains a significant portion of the spreads’ variability. In addition, variations of the specifications were estimated in order to asses the robustness of the conclusions concerning the determinants of loan spreads.
    Keywords: asset securitization, asset-backed securitisation, bank lending, default risk, risk management, everaged financing
    Date: 2007
  3. By: Makoto Takahashi (Graduate School of Economics, University of Tokyo); Yasuhiro Omori (Faculty of Economics, University of Tokyo); Toshiaki Watanabe (Institute of Economic Research, Hitotsubashi University)
    Abstract: Realized volatility, which is the sum of squared intraday returns over a certain interval such as a day, has recently attracted the attention of financial economists and econometricians as an accurate measure of the true volatility. In the real market, however, the presence of non-trading hours and market microstructure noise in transaction prices may cause the bias in the realized volatility. On the other hand, daily returns are less subject to the noise and therefore may provide additional information on the true volatility. From this point of view, we propose modeling realized volatility and daily returns simultaneously based on well-known stochastic volatility model. Using intraday data of Tokyo stock price index, we show that this model can estimate realized volatility biases and parameters simultaneously.We take a Bayesian approach and propose an efficient sampling algorithm to implement the Markov chain Monte Carlo method for our simultaneous model. The result of the model comparison between the simultaneous models using both naive and scaled realized volatilities indicates that the effect of non-trading hours is more essential than that of microstructure noise but still the latter has to be considered for better fitting. Our Bayesian approach has an advantage over the conventional two-step correction procedure in that we are able to take the uncertainty in estimation of both biases and parameters into account for the prediction and the evaluation of Value-at-Risk.
    Date: 2007–09
  4. By: Laakkonen, Helinä (University of Jyväskylä)
    Abstract: Filtering intraday seasonality in volatility is crucial for using high frequency data in econometric analysis. This paper studies the effects of filtering on statistical inference concerning the impact of news on exchange rate volatility. The properties of different methods are studied using a 5-minute frequency USD/EUR data set and simulated returns. The simulation results suggest that all the methods tend to produce downward-biased estimates of news coefficients, some more than others. The study supports the Flexible Fourier Form method as the best for seasonality filtering.
    Keywords: high-frequency; volatility; macro announcements; seasonality
    JEL: C22 C49 C52 E44
    Date: 2007–11–28

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