nep-rmg New Economics Papers
on Risk Management
Issue of 2008‒05‒31
seven papers chosen by
Stan Miles
Thompson Rivers University

  1. Liquidity Stress-Tester: A macro model for stress-testing banks' liquidity risk By Jan Willem van den End
  2. Predicting Stock Market Returns by Combining Forecasts By Laurence Fung; Ip-wing Yu
  3. Cash Sub-additive Risk Measures and Interest Rate Ambiguity By Nicole EL KAROUI; Claudia RAVANELLI
  4. Continuous Monitoring: Look before You Leap By Lindset, Snorre; Persson, Svein-Arne
  5. Financial Analysts impact on Stock Volatility. A Study on the Pharmaceutical Sector By Clara I. Gonzalez; Ricardo Gimeno
  6. Investment Model Uncertainty and Fair Pricing By Los, Cornelis A.; Tungsong, Satjaporn
  7. A Leading Indicator Model of Banking Distress ¡V Developing an Early Warning System for Hong Kong and Other EMEAP Economies By Jim Wong; Eric Wong; Phyllis Leung

  1. By: Jan Willem van den End
    Abstract: This paper presents a macro stress-testing model for market and funding liquidity risks of banks, which have been main drivers of the recent financial crisis. The model takes into account the first and second round (feedback) effects of shocks, induced by behavioural reactions of heterogeneous banks, and idiosyncratic reputation effects. The impact on liquidity risk is simulated by a Monte Carlo approach. This generates distributions of liquidity buffers for each scenario round, including the probability of a liquidity shortfall. An application to Dutch banks illustrates that the second round effects have more impact than the first round effects and hit all types of banks, indicative of systemic risk. This lends support policy initiatives to enhance banks' liquidity buffers and liquidity risk management, which could also contribute to prevent financial stability risks.
    Keywords: banking; financial stability; stress-tests; liquidity risk
    JEL: C15 E44 G21 G32
    Date: 2008–05
  2. By: Laurence Fung (Research Department, Hong Kong Monetary Authority); Ip-wing Yu (Research Department, Hong Kong Monetary Authority)
    Abstract: The predictability of stock market returns has been a challenge to market practitioners and financial economists. This is also important to central banks responsible for monitoring financial market stability. A number of variables have been found as predictors of future stock market returns with impressive in-sample results. Nonetheless, the predictive power of these variables has often performed poorly for out-of-sample forecasts. This study utilises a new method known as "Aggregate Forecasting Through Exponential Re-weighting (AFTER)" to combine forecasts from different models and achieve better out-of-sample forecast performance from these variables. Empirical results suggest that, for longer forecast horizons, combining forecasts based on AFTER provides better out-of-sample predictions than the historical average return and also forecasts from models based on commonly used model selection criteria.
    Keywords: Forecasting, Model combination, Model uncertainty
    JEL: G11 G12 C13
    Date: 2008–03
  3. By: Nicole EL KAROUI (Ecole Polytechnique (France)); Claudia RAVANELLI (University of Zurich)
    Abstract: A new class of risk measures called cash sub-additive risk measures is introduced to assess the risk of future financial, non financial and insurance positions. The debated cash additive axiom is relaxed into the cash sub-additive axiom to preserve the original difference between the numeraire of the current reserve amounts and future positions. Consequently, cash sub-additive risk measures can model stochastic and/or ambiguous interest rates or defaultable contingent claims. Practical examples are presented and in such contexts cash additive risk measures cannot be used. Several representations of the cash sub-additive risk measures are provided. The new risk measures are characterized by penalty functions defined on a set of sub-linear probability measures and can be represented using penalty functions associated with cash additive risk measures defined on some extended spaces. The issue of the optimal risk transfer is studied in the new framework using inf-convolution techniques. Examples of dynamic cash sub-additive risk measures are provided via BSDEs where the generator can locally depend on the level of the cash sub-additive risk measure.
    Keywords: Risk measures, Fenchel-Legendre transform, model uncertainty, inf-convolution, backward stochastic di®erential equations.
    JEL: D81
    Date: 2008–04
  4. By: Lindset, Snorre (Trondheim Business School); Persson, Svein-Arne (Dept. of Finance and Management Science, Norwegian School of Economics and Business Administration)
    Abstract: We present a model for pricing credit risk protection for a limited liability non-life insurance company. The protection is typically provided by a guaranty fund. In the case of continuous monitoring, i.e., where the market values of the company's assets and liabilities are continuously observable, and where the market values of assets and liabilities follow continuous processes, the regulators can liquidate the insurance company at the instant the market value of its assets equals the market value of its liabilities, implying that the credit protection is worthless. When jumps are included in the claims process, the protection provided by the guaranty fund has a strictly positive market value. We argue that the ability to continuously monitor the equity value of a company can be a new explanation for why jump processes may be important in models of credit risk.
    Keywords: Credit risk for non-life insurers; guarantee fund; continuous monitoring; barrier options
    JEL: G13 G23 G33
    Date: 2008–03–12
  5. By: Clara I. Gonzalez; Ricardo Gimeno
    Abstract: The arrival of new information helps financial markets to value assets, but it may has the side-effect of increasing their volatilities. A better knowledge of the mechanism that links relevant news and stock prices would help both private and institutional agents to improve the calibration of the risks implies in a given asset. Financial analysts play a key role in distinguishing which news are relevant for the valuation of a particular asset, and the changes in their recommendations are signals of new information in the market. This paper studies the impact those buy or sell recommendations have on returns and also on volatility instead of the traditional literature that focuses only on prices. The pharmaceutical companies in the New York Stock Exchange are especially suited for this type of analysis given the frequent discontinuities in their expected profits derived from the success or failure in the development of new drugs. Twenty stocks are daily tracked for five years along with the recommendations given by financial analysts. We have modeled stock returns by a Markov Regime Switching model as in Schaller and van Norden (1997) and found two states of low and high volatilities. We have also found strong evidence that the probability of being in the estate of high volatility increases when a Financial Analyst changes his recommendation.
    Date: 2008–05
  6. By: Los, Cornelis A.; Tungsong, Satjaporn
    Abstract: Modern investment theory takes it for granted that a Security Market Line (SML) is as certain as its "corresponding" Capital Market Line. (CML). However, it can be easily demonstrated that this is not the case. Knightian non-probabilistic, information gap uncertainty exists in the security markets, as the bivariate "Galton's Error" and its concomitant information gap proves (Journal of Banking & Finance, 23, 1999, 1793-1829). In fact, an SML graph needs (at least) two parallel horizontal beta axes, implying that a particular mean security return corresponds with a limited Knightian uncertainty range of betas, although it does correspond with only one market portfolio risk volatility. This implies that a security' risk premium is uncertain and that a Knightian uncertainty range of SMLs and of fair pricing exists. This paper both updates the empirical evidence and graphically traces the financial market consequences of this model uncertainty for modern investment theory. First, any investment knowledge about the securities risk remains uncertain. Investment valuations carry with them epistemological ("modeling") risk in addition to the Markowitz-Sharpe market risk. Second, since idiosyncratic, or firm-specific, risk is limited-uncertain, the real option value of a firm is also limited-uncertain This explains the simultaneous coexistence of different analyst valuations of investment projects, particular firms or industries, included a category "undecided." Third, we can now distinguish between "buy", "sell" and "hold" trading orders based on an empirically determined collection of SMLs, based this Knightian modeling risk. The coexistence of such simultaneous value signals for the same security is necessary for the existence of a market for that security! Without epistemological investment uncertainty, no ongoing markets for securities could exist. In the absence of transaction costs and other inefficiencies, Knightian uncertainty is the necessary energy for market trading, since it creates potential or perceived arbitrage (= trading) opportunities, but it is also necessary for investors to hold securities. Knightian uncertainty provides a possible reason why the SEC can't obtain consensus on what constitutes "fair pricing." The paper also shows that Malkiel's recommended CML-based investments are extremely conservative and non-robust.
    Keywords: capital market line; security market line; beta; investments; decision-making; Knightian uncertainty; robustness; information-gap; Galton's Error; real option value
    JEL: G12 G11 C20 G13
    Date: 2008–05–24
  7. By: Jim Wong (Research Department, Hong Kong Monetary Authority); Eric Wong (Research Department, Hong Kong Monetary Authority); Phyllis Leung (Research Department, Hong Kong Monetary Authority)
    Abstract: This study develops a probit econometric model to identify a set of leading indicators of banking distress and estimate banking distress probability for Hong Kong and other EMEAP economies. Macroeconomic fundamentals, currency crisis vulnerability, credit risk of banks and companies, asset price bubbles, credit growth, and the occurrence of distress of other economies in the region are found to be important leading indicators of banking distress in the home economy. The predictive power of the model is reasonably good. A case study of Hong Kong based on the latest estimate of banking distress probability and stress testing results shows that currently the banking sector in Hong Kong is healthy and should be able to withstand well certain possible adverse shocks. Under some extreme shocks originating from real GDP growth and property prices such as those that occurred during the Asian financial crisis, the model indicates a non-negligible risk of an occurrence of banking distress in Hong Kong. However, the chances of the occurrence of such severe events are extremely low. Simulation results also suggest that compared to the period before the Asian financial crisis, the local banking sector is currently more capable of withstanding shocks similar to those that occurred during that crisis. The study also finds that banking distress is contagious, suggesting that to be effective in monitoring banking distress, close cooperation between central banks should be in place.
    Keywords: Banking distress, Asia Pacific economies, econometric model
    JEL: E44 E47 G21
    Date: 2007–12

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