Early warning system of finance stress for India

This paper develops a composite Financial Sector Stress Index (FSSI) for the Indian financial system as a whole by combining three sub-indices for currency markets, the banking sector and the stock market, to gauge the level of financial stress in the Indian financial system. Such a continuous-valued index can be used to track the varying magnitude and dynamics of financial stress in the country over time. The FSSI provides an ordinal measure of stress in the financial system. Changes in the FSSI are useful in assessing whether financial stress is rising or falling, and in ascertaining extreme events in the financial system. The paper, then, objectively identifies extreme stress periods in the financial system based on movements of the index. We recognise that such extreme/tail events pose special econometric challenges as they are rare events but with a big impact. Hence, we use a more robust and analytically sound technique of Extreme Value Theory (EVT) to identify extreme events in the financial system. Once the extreme stress events are identified, we use a binary dependent variable model (logit model) to estimate the impact of various macroeconomic and financial variables on the probability of extreme stress in the financial system.     

Entrepreneurship: The role of extreme events

We use aggregate country data as well as individual level survey to uncover, for the first time, the effect of extreme events such as natural disasters and terrorist attacks on entrepreneurial activity. We find that natural disasters and terrorist attacks influence individual perceptions of the rewards to entrepreneurship and, more surprisingly, extreme events affect entrepreneurship rates positively in a robust and significant way.     

Oil and US stock market shocks: Implications for Canadian equities

Oil and US stock market shocks are relevant to Canadian equities because Canada is an oil exporter exposed to market developments in the wider continent. We evaluate how the relationship between Canadian stock market indices and such external shocks change under extraordinary events. To do this, we subject statistically identified oil and S&P 500 market shocks to a surprise filter, which detects shocks with the greatest magnitude occurring over a given lookback period, and an outlier filter, which detects extrema shocks that exceed a normal range. Then, we examine how the dependence structure between shocks and Canadian equities change under the extreme surprise and outlier episodes through various co-moment spillover tests. Our results show co-moments beyond correlation are important in reflecting the changes occurring in the relationships between external shocks and Canadian equities in extreme events. Additionally, the differences in findings under extreme positive and negative shocks provide evidence for asymmetric spillover effects from the oil and US stock markets to Canadian equities. Moreover, the observed heterogeneity in the relationships between disaggregated Canadian equities and shocks in the crude oil and S&P 500 markets are useful to policy-makers for revealing sector-specific vulnerabilities and provide portfolio diversification opportunities for investors to exploit.     

Extreme daily changes in U.S. Dollar London inter-bank offer rates

The likelihood of extreme daily changes in London Interbank Offer rates are estimated using the peaks-over-threshold method developed from extreme value theory. Value at risk and expected shortfall for high quantiles are produced for the left and right tails of the distributions for each maturity. The Generalized Pareto distribution of the peaks-over-threshold method is found to be unsuitable for modeling exceedances above a high threshold for samples of simple daily changes in the LIBOR. When the series are transformed to logarithmic daily changes, extreme value analysis proceeds smoothly and yields useful information about the relative frequency or magnitudes of extreme events. The main consequence of this is that the risk statistics associated with a given change in the LIBOR depend on the initial rate level; at higher (lower) interest rates, changes of a given size are more (less) likely to occur.     

To be consumed with moderation

We study the optimal behavior of a hyperbolic discounting agent who has incomplete information about his own preferences and can only learn them through consumption. We show that, even if moderate current consumption and moderate future consumption always dominates abstinence, the agent may optimally decide not to consume as a commitment device against inefficient learning that would lead to future excesses. This provides a rationale for why smokers, gamblers or compulsive buyers stick to second-best personal rules of behavior - such as “abstinence” - without invoking standard habit formation arguments. We also study how urges modify the strategy of the individual.     

Mechanism Design under Alternative Information Structures and Constrained Capacity

In applied models, the choice of a particular incomplete information structure appears to have been motivated primarily by technical convenience. The information structures used can be classified as either probabilistic or partitional. Information is probabilistic if no agent can rule out any type profile of the remaining agents and, for at least one type of one agent, the conditional and marginal probability distributions over the remaining agents' types are not equal. Information is partitional if the only information the agents have is that one or more agents (individually) can rule out type profiles of the remaining agents and, for at least one type of one agent, that agent has information about the remaining agents. Partitional information includes complete information as a special case. Existing results on complete information environments suggest that partitional information might simplify implementation problems. Within the context of an applied agency model in which capacity is constrained, we provide results that seem to challenge this intuition.Journal of Economic LiteratureClassification Numbers: C72, D82.     

Subjective probabilities on “small” domains

The Savagian choice-theoretic construction of subjective probability does not apply to preferences, like those in the Ellsberg Paradox, that reflect a distinction between risk and ambiguity. We formulate two representation results—one for expected utility, the other for probabilistic sophistication—that derive subjective probabilities but only on a “small” domain of risky events. Risky events can be either specified exogenously or in terms of choice behavior; in the latter case, both the values and the domain of probability are subjective. The analysis identifies a mathematical structure—called a mosaic—that is intuitive for both exogenous and behavioral specifications of risky events. This structure is weaker than an algebra or even a λ-system.     

A range-based volatility approach to measuring volatility contagion in securitized real estate markets

We use a newly-developed time-varying range-based volatility model to capture the dynamics of securitized real estate volatility. The novelty of the model is the use of a smooth transition copula function to capture the nonlinear comovements between major REIT markets in the presence of structural changes. We then investigate the impact of extreme events on the volatility dependence in a broad set of 13 developed countries over the period from 1990 to 2012. We find that information transmission through the volatility channel can exhibit either bi- or uni-directional causality. In addition, financial contagion following the subprime crisis is found between the U.S. and Australia.     

El Niño and La Niña induced volatility spillover effects in the U.S. soybean and water equity markets

This paper examined links between U.S. soybean prices and the Dow Jones U.S. Water Index (DJUSWU). We particularly studied the impact of El Niño and La Niña events on price risk spillovers. Results showed that La Niña significantly increases the linkages between soybean and water equity markets. Based on this, we identified a new soybean hedge strategy that would be possible if a futures contract for the DJUSWU existed. This new strategy improves on the effectiveness of both a conventional naïve soybean market hedge, and a traditional time-varying hedge. The findings can be used to assist soybean agents in managing increased market risks associated with extreme weather events.     

Subjective probabilistic expectations,household air pollution,and health: Evidence from cooking fuel use patterns in West Bengal,India

An increasing number of empirical studies have investigated the determinants of cooking fuel choice in developing countries, where health risks from household air pollution are one of the most important issues. We contribute to this stream of literature by examining individuals’ subjective probabilistic expectations about health risks when using different types of fuel and their role in cooking fuel usage patterns. We also explore how these patterns, in turn, are associated with health status. Using data collected from 557 rural Indian households, we find that subjective probabilistic expectations of becoming sick from dirty fuel usage are negatively and significantly associated with the fraction of days of dirty fuel usage in households. Concurrently, dirty fuel usage and self-reported health status of the individual being sick are also significantly correlated. We then conduct a policy simulation of information provision regarding the health risks of dirty fuel usage. Our simulation demonstrates that although the provision of information results in statistically significant changes in households’ cooking fuel usage patterns and in individuals’ health status, these changes may be small in size.     

Economic Policy in the Face of Severe Tail Events

From time to time, something occurs which is outside the range of normal expectations. We will call these “tail events” in the sense that they are way out of the tail of a probability distribution. I consider the question of the implications of tail events for economic policy and climate‐change economics. This issue has been analyzed by Martin Weitzman who proposed a Dismal Theorem. The general idea is that, under limited conditions concerning the structure of uncertainty and risk aversion, society has an indefinitely large expected loss from high‐consequence, low‐probability events. Under such conditions, standard economic tools such as cost‐benefit analysis cannot be applied. The present study is intended to put the Dismal Theorem in context and examine the range of its relevance, with an application to catastrophic climate change. I conclude that tail events are sometimes of extreme importance, and we must be extremely careful to include them in situations of deep uncertainty. However, we conclude that no loaded gun of strong tail dominance has been uncovered to date.     

Overnight borrowing, interest rates and extreme value theory

We examine the dynamics of extreme values of overnight borrowing rates in an inter-bank money market before a financial crisis during which overnight borrowing rates rocketed up to (simple annual) 4000 percent. It is shown that the generalized Pareto distribution fits well to the extreme values of the interest rate distribution. We also provide predictions of extreme overnight borrowing rates using pre-crisis data. The examination of tails (extreme values) provides answers to such issues as to what are the extreme movements to be expected in financial markets; is there a possibility for even larger movements and, are there theoretical processes that can model the type of fat-tails in the observed data? The answers to such questions are essential for proper management of financial exposures and laying ground for regulations.     

Portfolio management with tail dependence

Many publications, that treated with Portfolio Management, were devastating for all asset allocation models in the context of portfolios. The elimination of extreme events (asymmetric or tail dependence) during the portfolio construction process can reduce the skills of asset managers to reduce risk through diversification. The copula theory allows us to calculate an alternative to measure the dependence of extreme events in assets through the index lower tail dependence. We check that the strategies with tail dependence overcame Talmud rule, the Markowitz model and the model of Tu and Zhou by simulating 1,000 portfolios with 3, 5, 10 and 20 randomly selected assets from DJIA for the period 03/1990 until 12/2016. We conclude that models of tail dependence and Markowitz had more performance ex-ante than Talmud and the Tu and Zhou model for portfolios with 3, 5, 10 and 20 assets. Tail dependence models overcome Markowitz, in terms of cumulative return, in over 60% of months considered in the analysis. The results indicate that the Talmud rule should be discarded in a context of constructing portfolios with individual stocks ahead strategies with tail dependence.     

Private polling in elections and voter welfare

We study elections in which two candidates poll voters about their preferred policies before taking policy positions. In the essentially unique equilibrium, candidates who receive moderate signals adopt more extreme platforms than their information suggests, but candidates with more extreme signals may moderate their platforms. Policy convergence does not maximize voters' welfare. Although candidates' platforms diverge in equilibrium, they do not do so as much as voters would like. We find that the electorate always prefers less correlation in candidate signals, and thus private over public polling. Some noise in the polling technology raises voters' welfare.     

Structural modeling, including temporal dimensions as an aid to study complex system governabilities and to foresee unforecastable alternative futures

To describe evolutions of phenomena, we have to design some kind of models of the studied field. Systems analysis offers a possible way in this respect. Structural modeling is the simplest available technique. Very often, structures of the real world are actually complex and not simply hierarchized. Moreover, we have to take into account the time-related dimensions in order to develop more realistic structural models. Thus some mechanical aid is required to explore the intricate mesh of interacting things. We described a coherent set of programs, and the input-output data language is called STRINGDALE (Structural Modeling Data Language, E added for euphony).Complex systems too often cross the threshold of internal instability, which should not prevent defining their governability in accordance with given policies. Here also the help of the computer is very fruitful in searching for internal stresses and conflicts behind their evolution. Last but not least, conservative results are inevitably obtained when studying a system modeled by a steady structure closed on itself. Inherently, a system is comparatively closed on itself, although always interacting with the outside environment. We propose to model this environment by a discrete set of random foreseeable events that affect system evolution when they occur. We show how strategies of governability are modified when taking into account these probabilistic events.     

The Economics of American Higher Education,ed., William E. Becker and Darrell R. Lewis

The author describes a protocol for classroom experiments for courses that introduce undergraduates to signaling games. Signaling games are conceptually difficult because, when analyzing the game, students are not naturally inclined to think in probabilistic, Bayesian terms. The experimental design explicitly presents the posterior frequencies of the unobserved events. The protocol's emphasis on the posterior enhances convergence to the equilibrium prediction, relative to a treatment in which posterior frequencies are not explicitly computed. This convergence reinforces the development of the theory in subsequent lecture periods.     

What can we learn from the history of gasoline crack spreads?: Long memory,structural breaks and modeling implications

In this paper, we investigate the long-range auto-correlations of crack spreads using a nonparametric method, named detrended moving average (MF-DMA). We find that the auto-correlations display multiscaling behaviors and are dominated by the anti-persistence (mean-reversion) in the long-term. Moreover, the auto-correlations are multifractal, indicating that various small and large fluctuations display different scaling behaviors. Using a technique of rolling windows, we find that some extreme events can drive the degree of anti-persistence and the multifractality (complexity) to rise up. In other words, these events have negative impacts on market efficiency. However, the effects of these events are not alike. We also detect long-range auto-correlations in crack spread volatilities and find a strong persistent behavior and multifractality. Finally, we discuss the modeling implications of the findings on long-range auto-correlated patterns. Our results indicate that ARFIMA-GARCH models can capture the major dynamics of large fluctuations. For small fluctuations, they are misspecified. Interestingly, we find that the strong long-range auto-correlated behaviors do not imply that ARFIMA model which takes long memory into account can outperform random walk model in the sense of out-of-sample prediction. The major reason may be that market complexity exploited in this paper causes the low predictability of ARFIMA model.     

Ambiguous events and maxmin expected utility

We study the properties associated to various definitions of ambiguity [L.G. Epstein, J. Zhang, Subjective probabilities on subjectively unambiguous events, Econometrica 69 (2001) 265-306; P. Ghirardato et al., Differentiating ambiguity and ambiguity attitude, J. Econ. Theory 118 (2004) 133-173; K. Nehring, Capacities and probabilistic beliefs: a precarious coexistence, Math. Soc. Sci. 38 (1999) 197-213; J. Zhang, Subjective, ambiguity, expected utility and Choquet expected utility, Econ. Theory 20 (2002) 159-181] in the context of Maximin Expected Utility (MEU). We show that each definition of unambiguous events produces certain restrictions on the set of priors, and completely characterize each definition in terms of the properties it imposes on the MEU functional. We apply our results to two open problems. First, in the context of MEU, we show the existence of a fundamental incompatibility between the axiom of “Small unambiguous event continuity” (Epstein and Zhang, 2001) and the notions of unambiguous event due to Zhang (2002) and Epstein and Zhang (2001). Second, we show that, in the context of MEU, the classes of unambiguous events according to either Zhang (2002) or Epstein and Zhang (2001) are always λ-systems. Finally, we reconsider the various definitions in light of our findings, and identify some new objects (Z-filters and EZ-filters) corresponding to properties which, while neglected in the current literature, seem relevant to us.     

Tail risk in emerging markets of Southeastern Europe

This article examines the left-tail behaviour of returns on stocks in Southeastern Europe (SEE). We apply conditional extreme value theory (EVT) approach on daily returns of six stock market indices from SEE between 2004 and 2013. Predictive performance of value-at-risk (VaR) and expected shortfall (ES) based on EVT is compared against several alternatives, such as historical simulation and analytical approach based on GARCH with a single conditional distribution. Model backtesting with daily returns shows that EVT-based models provide more reliable VaR and ES forecasts than the alternative models in all six markets. Unlike the alternatives, the EVT-based models cannot be rejected as VaR confidence level is increased. This emphasizes the importance of extreme events in SEE markets and indicates that the ability of a model to capture volatility clustering accurately is not sufficient for a correct assessment of risk in these markets.