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.     

Financial Support from the Family Network and Illegal Immigration

Barriers to immigration of low‐skilled workers from developing countries into the advanced countries prevent many potential migrants from leaving their countries of origin. With very low home‐country wages in relation to the cost of undocumented migration, the opportunity to migrate often hinges on the possibility of obtaining credit from a human smuggling organization or family and friends. This paper examines the conditions under which migration is optimal for an individual who lacks liquid assets, with a focus on alternative options for financing migration costs. One is by accumulating the required amount of savings out of source‐country income, with or without financial support from the family or social network. The other is debt‐bonded migration, which involves borrowing from a smuggling organization and paying off the loan while working in the host country. I find that greater financial support from the family network increases the attractiveness of debt‐bonded relative to self‐financed migration.     

Forecasting high-frequency excess stock returns via data analytics and machine learning

Borsa Istanbul introduced data analytics to present additional information about its market conditions. We examine whether this product can be utilized via various machine learning methods to predict intraday excess returns. Accordingly, these analytics provide significant prediction ratios above 50% with ideal profit ratios that can reach up to 33%. Among all the methods considered, XGBoost (logistic regression) performs better in predicting excess returns in the long-term analysis (short-term analysis). Results provide evidence for the benefits of both the analytics and the machine learning methods and raise further discussion on the semistrong market efficiency.     

Autocatalytic Growth and Development and the South-North Convergence

Abstract:

This article engages with the issue of income convergence between North and South by using the autocatalytic hypothesis of growth and development. Two system models describe positive and negative feedback loops which govern economic flows between North and South. The analysis of endogenous and exogenous negative feedbacks points to the process that would slowly push the world economy towards vanishing growth rates and, eventually, halt its material growth. The present work rejects convergence in per capita GDP between North and South from the theoretical perspective. Such an outcome would stand against one of the fundamental properties of autocatalytic dynamics—centripetality— that has its causal roots in the competitive process and capitalist institutions. In that sense, the autocatalytic hypothesis provides a theoretical explanation for those empirical analyses that dismisses convergence.     

STABILITY OF THE UTILITY MAXIMIZATION PROBLEM WITH RANDOM ENDOWMENT IN INCOMPLETE MARKETS

We perform a stability analysis for the utility maximization problem in a general semimartingale model where both liquid and illiquid assets (random endowments) are present. Small misspecifications of preferences (as modeled via expected utility), as well as views of the world or the market model (as modeled via subjective probabilities) are considered. Simple sufficient conditions are given for the problem to be well posed, in the sense that the optimal wealth and the marginal utility‐based prices are continuous functionals of preferences and probabilistic views.     

Contribution of financial market segments at different stages of development: Transition,cohesion and mature economies compared

What is the impact of financial sector segments at different stages of development? We apply a production function approach to investigate the impact of the credit, bond and stock segments in nine EU-accession countries over early years of transition (1996–2000) and compare these to mature market economies and to countries at intermediate stage. We find that the transfer mechanisms differ over the development cycle (from bond markets to educational attainment to labor participation) and that financial market segments with links to the public sector (but not stock markets) contributed to stability and growth in transition economies.