Diversification and systemic risk

Louis Raffestin. Diversification and systemic risk. Journal of Banking & Finance, 2014; 46 DOI: 10.1016/j.jbankfin.2014.05.014

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Author(s)

Louis Raffestin

Abstract

Portfolio diversification makes investors individually safer but creates connections between them through common asset holdings. Such connections create “endogenous covariances” between assets and investors, and enhance systemic risk by propagating shocks swiftly through the system. We provide a theoretical model in which shocks spread through constrained selling from N diversified portfolio investors in a network of asset holdings with home bias, and study the desirability of diversification by comparing the multivariate distribution of implied losses for every level of diversification. There may be a region on the parameter set for which the propagation effect dominates the individually safer one. We derive analytically the general element of the covariance between two assets i and j. We find agents may minimize their exposure to endogenous risk by spreading their wealth across more and more distant assets. The resulting network enhances systemic stability.

Mathematical Analysis of Average Rates of Return and Investment Decisions: The Missing Link

Carlo Alberto Magni. Mathematical Analysis of Average Rates of Return and Investment Decisions: The Missing Link. The Engineering Economist, 2014; 59 (3) DOI: 10.1080/0013791X.2014.881174

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Author(s)

Carlo Alberto Magni

Abstract

This article expands Teichroew, Robichek, and Montalbano’s (TRM; 1965a, 1965b) rate-of-return model into a complete and general model of economic profitability for investment decision making. Specifically, TRM’s assumptions are relaxed and a project rate of return is derived, expressing the project’s overall economic profitability; direct relations among rates, costs of capital, and net present value are supplied. The various value drivers are identified and isolated, and the net present value (NPW) is decomposed into financing NPV and investment NPV. The approach allows for any pattern of financing rates, investment rates, and costs of capital. Relations with old literature and new literature on rates of return are shown: the link between them is obtained by making use of the mean operator (i.e., affine combinations of rates) and via the one-to-one correspondence between rates and invested capitals.

Risk models-at-risk

Christophe M. Boucher, Jón Daníelsson, Patrick S. Kouontchou, Bertrand B. Maillet. Risk models-at-risk. The Journal of Banking & Finance, 2014; 44 DOI: 10.1016/j.jbankfin.2014.03.019

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Author(s)

Christophe M. Boucher, Jón Daníelsson, Patrick S. Kouontchou, Bertrand B. Maillet

Abstract

The experience from the global financial crisis has raised serious concerns about the accuracy of standard risk measures as tools for the quantification of extreme downward risks. A key reason for this is that risk measures are subject to a model risk due, e.g. to specification and estimation uncertainty. While regulators have proposed that financial institutions assess the model risk, there is no accepted approach for computing such a risk. We propose a remedy for this by a general framework for the computation of risk measures robust to model risk by empirically adjusting the imperfect risk forecasts by outcomes from backtesting frameworks, considering the desirable quality of VaR models such as the frequency, independence and magnitude of violations. We also provide a fair comparison between the main risk models using the same metric that corresponds to model risk required corrections.