The urgency of estimating the impact of climate risks on the financial system is increasingly recognized among scholars and practitioners. By adopting a network approach to financial dependencies, we look at how climate policy risk might propagate through the financial system. We develop a network-based climate stress-test methodology and apply it to large Euro Area banks in a ‘green’ and a ‘brown’ scenario. We find that direct and indirect exposures to climate-policy-relevant sectors represent a large portion of investors’ equity portfolios, especially for investment and pension funds. Additionally, the portion of banks’ loan portfolios exposed to these sectors is comparable to banks’ capital. Our results suggest that climate policy timing matters. An early and stable policy framework would allow for smooth asset value adjustments and lead to potential net winners and losers. In contrast, a late and abrupt policy framework could have adverse systemic consequences.
We analyze American put options in a hyper-exponential jump-diffusion model. Our contribution is threefold. Firstly, by following a maturity randomization approach, we solve the partial integro-differential equation and obtain a tight lower bound for the American option price. Secondly, our method allows us to disentangle the contributions of jump and diffusion for the American early exercise premium. Finally, using American-style options on S\&P 100 index from 2007 until 2013, we estimate a range of hyper-exponential specifications and investigate the implications for option pricing and jump-diffusion disentanglement. We find that jump risk accounts for a large part of early exercise premium.
We conduct a standardized survey on risk preferences in 53 countries worldwide and estimate cumulative prospect theory parameters from the data. The parameter estimates show that significant differences on the cross-country level are to some extent robust and related to economic and cultural differences. In particular, a closer look on probability weighting underlines gender differences, economic effects, and cultural impact on probability weighting. The data set is a useful starting point for future research that investigates the impact of risk preferences on the market level.
Based on the literature on the relationship between culture, emotion, and loss aversion, we derive that culture can influence the degree of loss aversion. To test our hypotheses, we conduct a standardized survey in 53 countries worldwide that includes the questions from the Hofstede survey on cultural dimensions as well as lottery questions on loss aversion. The results show that individualism, power distance, and masculinity increase loss aversion as predicted, whereas the impact of uncertainty avoidance is less significant. Moreover, we also find a relation between the distribution of major religions in a country and loss aversion. In comparison, the connection of loss aversion to macroeconomic variables seems to be much smaller.
The recent credit crisis of 2007/08 has raised a debate about the so-called knife-edge properties of financial markets. The paper contributes to the debate shedding light on the controversial relation between risk-diversification and financial stability. We model a financial network where assets held by borrowers to meet their obligations, include claims against other borrowers and securities exogenous to the network. The balance-sheet approach is conjugated with a stochastic setting and by a mean-field approximation the law of motion of the system's fragility is derived. We show that diversification has an ambiguous effect and beyond a certain levels elicits financial instability. Moreover, we find that risk-sharing restrictions create a socially preferable outcome. Our findings have significant implications for future policy recommendation.
The univariate collapsing method (UCM) for portfolio optimization is based on obtaining the predictive mean and a risk measure such as variance or expected shortfall of the univariate pseudo-return series generated from a given set of portfolio weights and multivariate set of assets under interest and, via simulation or optimization, repeating this process until the desired portfolio weight vector is obtained. The UCM is well-known conceptually, straightforward to implement, and possesses several advantages over use of multivariate models, but, among other things, has been criticized for being too slow. As such, it does not play prominently in asset allocation and receives little attention in the academic literature. This paper proposes use of fast model estimation methods combined with new heuristics for sampling, based on easily-determined characteristics of the data, to accelerate and optimize the simulation search. An extensive empirical analysis confirms the viability of the method.
What is the added value of a security which qualifies as a “high-quality liquid asset” (HQLA) under the Basel III “Liquidity Coverage Ratio” (LCR)? In this paper, we quantify the added value in terms of yield changes and, as suggested by Stein (2013), call it “HQLA premium”. To do so, we exploit the introduction of the LCR in Switzerland as a unique quasi-natural experiment and we find evidence for the existence of an HQLA premium in the order of 4 basis points. Guided by theoretical considerations, we claim that the HQLA premium is state dependent and argue that our estimate is a lower bound measure. Furthermore, we discuss the implications of an economically significant HQLA premium. Thereby, we contribute to a better understanding of the LCR and its implications for financial markets.
Assuming the classic contingent claim setting, a number of financial asset demand tests of Expected Utility have been developed and implemented in experimental settings. However the domain of preferences of these asset demand tests differ from the mixture space of distributions assumed in the traditional binary lottery laboratory tests of von Neumann-Morgenstern Expected Utility preferences. We derive new sets axioms that are necessary and sufficient for preferences over contingent claims to be representable by an Expected Utility function. We also indicate the additional axioms required to extend the representation to the more general case of preferences over risky prospects.
We show that in a consumption-based asset-pricing model with hyperbolic discounting leading to dynamically inconsistent time preferences value premium increases nonlinearly with the degree of discounting and thus affects cross section of returns. To test our model empirically, we relate the size of the value premium in 41 countries to the degree of hyperbolic discounting across those countries. The latter was found in an International Test of Risk Attitudes (INTRA). Our result is robust to the inclusion of other variables from INTRA, such as risk aversion, as well as micro- and macro-economic variables from the 41 countries.
