Conditional Properties of Hedge Funds: Evidence from Daily Returns*

Using daily returns on a set of hedge fund indices, we study (i) the properties of the indices' conditional density functions and (ii) the presence of asymmetries in conditional correlations between hedge fund indices and other investments and between hedge fund indices themselves. We use the SNP approach to obtain estimates of conditional densities of hedge fund returns and then proceed to examine their properties. In general, a nonparametric GARCH(1,1) model appears to provide the best fit for all strategies. We find that the conditional third and fourth moments are significantly affected by changes in the current volatility of returns on hedge fund indices. We examine changes in the conditional probability of tail events and report significant changes in the probability of extreme events when the conditioning information changes. These results have important implications for models of hedge fund risk that rely on probability of tail events. We formally test for the presence of asymmetries in conditional correlations to determine if there is contagion between hedge funds and other investments and between various hedge fund indices in extreme down markets versus extreme up markets. We generally do not find strong evidence in support of asymmetric correlations.     

The future of service: The power of emotion in human-robot interaction

Astoundingly, recent technological advancements have enabled robots to display emotions. Yet, while emotional expression is valued in the field of service, understanding emotions in human-robot interaction remains underexplored. Since emotions are contagious/transmittable, this study utilised Instagram data to uncover how emotional robots influence potential consumers’ affective feelings. By employing machine learning algorithms and sentiment analysis, the findings suggest that the expressions of surprise and happiness are key to creating positive impacts on potential consumers. The cross-disciplinary nature of this study lays the groundwork for next-level social, design, and creative experiences in artificial intelligence research regarding consumer service and experience contexts.     

Exploring differences in corruption: the role of neighboring countries

The aim of this paper is to study whether corruption spreads across neighboring countries. Spatial econometric techniques are used to analyze corruption interactions, testing whether the perception of corruption in neighboring countries affect a country’s own corruption once other variables are controlled for. For a given country it is found that corruption varies neither with the behavior of its neighbors (there is no endogenous interaction) nor with their exogenous characteristics (there is no contextual interaction). Corruption is therefore not contagious, but neighboring countries tend to show similar levels of corruption because they face similar characteristics and similar institutional environments.     

Potential Contagion Effects on OECD Countries: A FAVAR Model under Bayesian Framework

This paper studies whether and how US shocks impact the OECD countries in the case of a simulated crisis. Using Bayesian estimation methods we extract constrained factors (global, country and variable type specific) from a sample of 153 economic and financial OECD variables from 1980–2008. These factors are the transmission channels through which national shocks spread to other countries, as in a pandemic. The Bayesian interpretable factors are used to estimate FAVAR models. Our main findings suggest that differences exist in the contagion effects. This implies that no generalizations can be made for OECD countries even of equal economic size and in the same geographic region. In addition, our results show that a large portion of the variance of domestic economic variables is explained by global factors; and that the interest rate shock appears to play an important role in the spillover mechanism from the United States to the rest of the world. More precisely, Australia, the United Kingdom and Scandinavian countries appear to be most sensitive to the US shocks.     

Foreign Shocks on Chilean Financial Markets: Spillovers and Comovements Between Bond and Equity Markets

Abstract:

The domestic impact of external shocks will depend on the degree of coupling of domestic assets to foreign markets, but also on the spillovers among assets. The covariance between different types of assets could be affected by new information. Changes in the covariance, for example, could come from a stronger rebalancing between stocks and bonds. Therefore, we will analyze four different assets-government bonds, corporate bonds, money market instruments, and equities-and study the conditional correlation between them. We find that the corporate bond market tends to increase coupling in turbulent times, while the money market decreases coupling. We propose to test international spillovers taking into account a methodology for estimating the conditional mean, variance, and covariance on domestic bond and equity markets, while considering that shocks may have asymmetric effects depending on whether the news is good or bad.     

The Causes of Contagion： Rational or Irrational Behavior？

The threats concerning financial stability seriously affect the overall functioning of the economy at a local, regional, national, and continental level instead of a global level, and therefore, the emphasis is laid on analyzing the causes and effects of such threats. Financial crises in the current decade, as well as those in the past have shown that a major cause of instability in the global market is the so-called financial contagion. This leads to a natural question： whether similar authorities could specify and mitigate these shocks through efficient calculation followed by stability measures taken by banking networks. To answer this question, an empirical research was conducted by analyzing the degree of contagion induced by markets in Central and Eastern Europe, based on an econometric model, involving over 17 European countries, from January 2006 to January 2013.     

Trading with Asymmetric Volatility Spillovers

Abstract:  We study the profitability of trading strategies based on volatility spillovers between large and small firms. By using the Volatility Impulse-Response Function of Lin (1997) and its extensions, we detect that any volatility shock coming from small companies is important to large companies, but the reverse is only true for negative shocks coming from large firms. To exploit these asymmetric patterns in volatility, different trading rules are designed based on the inverse relationship existing between expected return and volatility. We find that most strategies generate excess after-transaction cost profits, especially after very bad news and very good news coming from large or small firm markets. These results are of special interest because of their implications for risk and portfolio management.     

Intra‐industry bankruptcy contagion: Evidence from the pricing of industry recovery rates

How does bankruptcy contagion propagate among industry peers? We study the debt recovery channel of industry contagion by examining whether the cost of a company's debt is affected by the observed recovery rates of its bankrupt industry peers. Our results show that lower industry recovery rates are associated with higher loan spreads, but only when the contracts were originated during industry bankruptcy waves. Consistent with the debt recovery channel of industry contagion, we find that the negative effects of industry recovery rates are significantly stronger under situations where the effect is expected to be more salient.     

A risk assessment model for banks

Summary. This paper proposes a model to assess risk for banks. Its main innovation is to incorporate endogenous interaction among banks, where the actual risk an individual bank bears also depends on its interaction with other banks and investors. We develop a two-period general equilibrium model with three active heterogeneous banks, incomplete markets, and endogenous default. The model is calibrated against UK banking data and therefore can be implemented as a risk assessment tool for regulators and central banks. We address the impact of monetary and regulatory policy, credit and capital shocks in the real and financial sectors.We are grateful to Lea Zicchino, an anonymous referee, seminar participants at the Bank of England, and the third Conference in Research in Economic Theory and Econometrics, Syros, for helpful comments. The views expressed are those of the authors and do not necessarily reflect those of the Bank of England.This revised version was published online in January 2005 with corrections to the Cover date.     

金融传染理论与政策取向

一个地区的流动性冲击能通过金融传染扩散到其他地区,完全的金融市场对于金融传染是稳健的,而不完全市场面对金融传染则是脆弱的,另外金融抑制能对金融传染的扩散起到短期抑制作用。