Security analyst networks, performance and career outcomes

Authors' draft. Final version to be published in The Journal of Finance. Available online at http://onlinelibrary.wiley.com/Using a sample of 42,376 board directors and 10,508 security analysts we construct a social network, mapping the connections between analysts and directors, between directors, and between analysts. We use social capital theory and techniques developed in social network analysis to measure the analyst’s level of connectedness and investigate whether these connections provide any information advantage to the analyst. We find that better-connected (better-networked) analysts make more accurate, timely, and bold forecasts. Moreover, analysts with better network positions are less likely to lose their job, suggesting that these analysts are more valuable to their brokerage houses. We do not find evidence that analyst innate forecasting ability predicts an analyst’s future network position. In contrast, past forecast optimism has a positive association with building a better network of connections

Systemic Risk in a Unifying Framework for Cascading Processes on Networks

We introduce a general framework for models of cascade and contagion processes on networks, to identify their commonalities and differences. In particular, models of social and financial cascades, as well as the fiber bundle model, the voter model, and models of epidemic spreading are recovered as special cases. To unify their description, we define the net fragility of a node, which is the difference between its fragility and the threshold that determines its failure. Nodes fail if their net fragility grows above zero and their failure increases the fragility of neighbouring nodes, thus possibly triggering a cascade. In this framework, we identify three classes depending on the way the fragility of a node is increased by the failure of a neighbour. At the microscopic level, we illustrate with specific examples how the failure spreading pattern varies with the node triggering the cascade, depending on its position in the network and its degree. At the macroscopic level, systemic risk is measured as the final fraction of failed nodes, $X^\ast$, and for each of the three classes we derive a recursive equation to compute its value. The phase diagram of $X^\ast$ as a function of the initial conditions, thus allows for a prediction of the systemic risk as well as a comparison of the three different model classes. We could identify which model class lead to a first-order phase transition in systemic risk, i.e. situations where small changes in the initial conditions may lead to a global failure. Eventually, we generalize our framework to encompass stochastic contagion models. This indicates the potential for further generalizations.Comment: 43 pages, 16 multipart figure

Priority for the Worse Off and the Social Cost of Carbon

The social cost of carbon (SCC) is a monetary measure of the harms from carbon emission. Specifically, it is the reduction in current consumption that produces a loss in social welfare equivalent to that caused by the emission of a ton of CO2. The standard approach is to calculate the SCC using a discounted-utilitarian social welfare function (SWF)—one that simply adds up the well-being numbers (utilities) of individuals, as discounted by a weighting factor that decreases with time. The discounted-utilitarian SWF has been criticized both for ignoring the distribution of well-being, and for including an arbitrary preference for earlier generations. Here, we use a prioritarian SWF, with no time-discount factor, to calculate the SCC in the integrated assessment model RICE. Prioritarianism is a well-developed concept in ethics and theoretical welfare economics, but has been, thus far, little used in climate scholarship. The core idea is to give greater weight to well-being changes affecting worse off individuals. We find substantial differences between the discounted-utilitarian and non-discounted prioritarian SCC

The Forward-Discount Puzzle in Central and Eastern Europe

This paper adds to evidence that the forward-discount puzzle is at least partly explained as a compensation for taking crash-risk. A number of Central and Eastern European exchange rates are compared. A Hidden Markov Model is used to identify two regimes for most of the exchange rates. These two regimes can be characterised as being either periods of stability or periods of instability. The level of international risk aversion and changes in US interest rates affect the probability of switching from one regime to the other. This model is then used to assess the way that these two factors affect the probability of a currency crisis. While the Czech Republic, Hungary and Bulgaria are very sensitive to international financial conditions, Poland and Romania are relatively immune. JEL classifications: C24, F31, F32; Key words: Exchange rates, uncovered interest parity, foreign exchange risk discount, hidden-Markov model, carry-trad

Measuring and managing liquidity risk in the Hungarian practice

The crisis that unfolded in 2007/2008 turned the attention of the financial world toward liquidity, the lack of which caused substantial losses. As a result, the need arose for the traditional financial models to be extended with liquidity. Our goal is to discover how Hungarian market players relate to liquidity. Our results are obtained through a series of semistructured interviews, and are hoped to be a starting point for extending the existing models in an appropriate way. Our main results show that different investor groups can be identified along their approaches to liquidity, and they rarely use sophisticated models to measure and manage liquidity. We conclude that although market players would have access to complex liquidity measurement and management tools, there is a limited need for these, because the currently available models are unable to use complex liquidity information effectively

A kinetic equation for economic value estimation with irrationality and herding

A kinetic inhomogeneous Boltzmann-type equation is proposed to model the dynamics of the number of agents in a large market depending on the estimated value of an asset and the rationality of the agents. The interaction rules take into account the interplay of the agents with sources of public information, herding phenomena, and irrationality of the individuals. In the formal grazing collision limit, a nonlinear nonlocal Fokker-Planck equation with anisotropic (or incomplete) diffusion is derived. The existence of global-in-time weak solutions to the Fokker-Planck initial-boundary-value problem is proved. Numerical experiments for the Boltzmann equation highlight the importance of the reliability of public information in the formation of bubbles and crashes. The use of Bollinger bands in the simulations shows how herding may lead to strong trends with low volatility of the asset prices, but eventually also to abrupt corrections

Economic Activity of Firms and Asset Prices

In this review we survey the recent research on the fundamental determinants of stock returns. These studies explore how firms' systematic risk and their investment and production decisions are jointly determined in equilibrium. Models with production provide insights into several types of empirical patterns, including (a) the correlations between firms' economic characteristics and their risk premia, (b) the comovement of stock returns among firms with similar characteristics, and (c) the joint dynamics of asset returns and macroeconomic quantities. Moreover, by explicitly relating firms' stock returns and cash flows to fundamental shocks, models with production connect the analysis of financial markets with the research on the origins of macroeconomic fluctuations

Explaining co-movements between equity and CDS bid-ask spreads

In this paper I show that the co-movements between bid-ask spreads of equities and credit default swaps vary over time and increase over crisis periods. The co-movements are strongly related to systematic risk factors and to the theoretical debt-to-equity hedge ratio. I document that hedging and asymmetric information, besides higher funding costs and market volatility risk, are driving factors of the commonality and are significantly priced in CDS bid-ask spreads