This book provides the most comprehensive treatment of the theoretical concepts and modelling techniques of quantitative risk management. Whether you are a financial risk analyst, actuary, regulator or student of quantitative finance, Quantitative Risk Management gives you the practical tools you need to solve real-world problems. Describing the latest advances in the field, Quantitative Risk Management covers the methods for market, credit and operational risk modelling. It places standard industry approaches on a more formal footing and explores key concepts such as loss distributions, risk measures and risk aggregation and allocation principles. The book's methodology draws on diverse quantitative disciplines, from mathematical finance and statistics to econometrics and actuarial mathematics. A primary theme throughout is the need to satisfactorily address extreme outcomes and the dependence of key risk drivers. Proven in the classroom, the book also covers advanced topics like credit derivatives. Fully revised and expanded to reflect developments in the field since the financial crisis Features shorter chapters to facilitate teaching and learning Provides enhanced coverage of Solvency II and insurance risk management and extended treatment of credit risk, including counterparty credit risk and CDO pricing Includes a new chapter on market risk and new material on risk measures and risk aggregation

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Quantitative Risk Management: Concepts, Techniques, and Tools

In this article we compare three models of the stochastic behavior of commodity prices that take into account mean reversion, in terms of their ability to price existing futures contracts, and their implication with respect to the valuation of other financial and real assets. The first model is a simple one-factor model 'in which the logarithm of the spot price of the commodity is assumed to follow a mean reverting process. The second model takes into account a second stochastic factor, the convenience yield of the commodity, which is assumed to follow a mean reverting process. Finally, the third model also includes stochastic interest rates. The Kalman filter methodology is used to estimate the parameters of the three models for two commercial commodities, copper and oil, and one precious metal, gold. The analysis reveals strong mean reversion in the commercial commodity prices. Using the estimated parameters, we analyze the implications of the models for the term structure of futures prices and volatilities beyond the observed contracts, and for hedging contracts for future delivery. Finally, we analyze the implications of the models for capital budgeting decisions. THE STOCHASTIC BEHAVIOR OF commodity prices plays a central role in the models for valuing financial contingent claims on the commodity, and in the procedures for evaluating investments to extract or produce the commodity. Earlier studies, by assuming that interest rates and convenience yields are constant allowed for a straight forward extension of the procedures developed for common stock option pricing to the valuation of financial and real commodity contingent claims. The assumption, however, is clearly not very satisfactory since it implies that the volatility of future prices is equal to the volatility of spot prices, and that the distribution of future spot prices under the equivalent martingale measure has a variance that increases without bound as the horizon increases. In an equilibrium setting we would expect that when prices are relatively high, supply will increase since higher cost producers of the commodity will enter the market putting a downward pressure on prices. Conversely, when prices are relatively low, supply will decrease since some of

The stochastic behavior of commodity prices: Implications for valuation and hedging

We estimate and compare a variety of continuous-time models of the short-term riskless rate using the Generalized Method of Moments. We find that the most successful models in capturing the dynamics of the short-term interest rate are those that allow the volatility of interest rate changes to be highly sensitive to the level of the riskless rate. A number of well-known models perform poorly in the comparisons because of their implicit restrictions on term structure volatility. We show that these results have important implications for the use of different term structure models in valuing interest rate contingent claims and in hedging interest rate risk.

https://www.ucm.es/data/cont/media/www/pag-41459/CKLS%20An%20empirical%20comparison.pdf

An Empirical Comparison of Alternative Models of the Short‐Term Interest Rate

机构投资者作为证券市场中的重要力量,越来越受到理论界和实务界的关注。论文对宾夕法尼亚大学沃顿商学院会计学教授布赖恩-布希（Brian Bushee）的论文＂The influence of institutional investors on myopic R＆D investment behavior＂（机构投资者对企业短视研发投资行为的影响,以下简称Bushee（1998））进行评价并提出相关的建议和研究方向。

《The influence of institutional investors on myopic R＆D investment behavior》述评

This paper investigates the performance and capital inflows of private equity partnerships. Average fund returns (net of fees) approximately equal the SP however, established funds are less sensitive to cycles than new entrants. Several of these results differ markedly from those for mutual funds. THE PRIVATE EQUITY INDUSTRY, primarily venture capital (VC) and buyout (LBO)

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Private Equity Performance: Returns, Persistence, and Capital Flows

This paper develops and empirically tests a two-factor model for pricing financial and real assets contingent on the price of oil. The factors are the spot price of oil and the instantaneous convenience yield. The parameters of the model are estimated using weekly oil futures contract prices from January 1984 to November 1988, and the model's performance is assessed out of sample by valuing futures contracts over the period November 1988 to May 1989. Finally, the model is applied to determine the present values of one barrel of oil deliverable in one to ten years time.

https://www.jstor.org/stable/pdfplus/2328801.pdf

Stochastic Convenience Yield and the Pricing of Oil Contingent Claims

We conduct an experiment assessing the extent to which people trade off the economic costs of truthfulness against the intrinsic costs of lying. The results allow us to reject a type-based model. People's preferences for truthfulness do not identify them as only either "economic types" (who care only about consequences) or "ethical types" (who care only about process). Instead, we find that preferences for truthfulness are heterogeneous among individuals. Moreover, when examining possible sources of intrinsic costs of lying and their interplay with economic costs of truthfulness, we find that preferences for truthfulness are also heterogeneous within individuals.

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Preferences for Truthfulness: Heterogeneity among and within Individuals

In this study, we first estimate the level of financial integration for twenty five emerging stock markets over the last decade. Using a multivariate GARCH(1,1)-M return generating model allowing for partial market integration as well as for the pricing of systematic emerging market risk, we find that these countries still remain to a large extent segmented and that the process of financial integration has been slowed down by the various financial crises that have struck these countries during the 1990s. We then investigate the relationship between the level of a country's trade concentration and its level of financial integration, postulating that financial integration could act as a natural hedge against potential lack of trade diversification. We find that, indeed, countries with an undiversified trade structure tend to have less segmented financial markets. Finally, our results also suggest that countries less open to trade are more segmented.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID781924_code58008.pdf?abstractid=658021&mirid=2

Financial Integration, Economic Instability and Trade Structure in Emerging Markets

https://www.econbiz.de/archiv1/2008/50147_emerging_markets.pdf

Financial integration, economic instability and trade structure in emerging markets

In this study, we examine whether aggregate market liquidity risk is priced in the US stock market. We define a bivariate Garch (1,1)-in-mean specification for the market portfolio excess returns and the changes in the standardized number of shares in the S&P 500 Index, the aggregate market liquidity proxy. The findings, based on monthly data, suggest that systematic liquidity risk is priced in the US over the period January 1973–December 1997. The liquidity premium represents a non-negligible, negative and time-varying component of the total market risk premium whose magnitude is not influenced by the October’87 Crash.

Rajna Gibson

Papers

Stochastic Convenience Yield and the Pricing of Oil Contingent Claims

Preferences for Truthfulness: Heterogeneity among and within Individuals

Financial Integration, Economic Instability and Trade Structure in Emerging Markets

Financial integration, economic instability and trade structure in emerging markets

The pricing of systematic liquidity risk: Empirical evidence from the US stock market