Risk and Decision Analysis - Volume 6, issue 4

Authors: Ching, Wai-Ki | Gu, Jia-Wen | Li, Xiaoyue | Siu, Tak-Kuen | Zheng, Harry

Article Type: Research Article

Abstract: In this paper, we propose a general framework for modeling discrete-time default risk where default processes for all the entities are governed by predictable interacting default probabilities. We give a general formula for the joint distribution of two important random variables featuring the severity of the crisis: duration of a crisis (T ) and severity of the defaults (W T ). In particular, we present a two-sector Markovian infectious model, where the default probability is switching over time and depends on the current number of defaults of both sectors. The central idea of this model …is that the causality of defaults of two sectors is in both directions, which enrich dynamics of the dependent default risk. The Bayesian Information Criterion (BIC) is adopted to compare the proposed model with the two-sector model in credit literature using real data. Numerical experiments are given to demonstrate that our proposed model is statistically better. Show more

Keywords: Infectious models, correlated defaults, crisis duration

DOI: 10.3233/RDA-170131

Citation: Risk and Decision Analysis, vol. 6, no. 4, pp. 249-261, 2017

Authors: Yeo, Joongyeub | Papanicolaou, George

Article Type: Research Article

Abstract: This paper deals with the risk associated with the mis-estimation of mean-reversion of residuals in statistical arbitrage. The main idea in statistical arbitrage is to exploit short-term deviations in returns from a long-term equilibrium across several assets. This kind of strategy heavily relies on the assumption of mean-reversion of idiosyncratic returns, reverting to a long-term mean after some time. But little is known regarding the assessment of this kind of risk. In this paper, we propose a simple scheme that controls the risk associated with estimating mean-reversions by using portfolio selections and screenings. Realizing that each residual has a different …mean-reversion time, the ones that are fast mean-reverting are selected to form portfolios. Further control is imposed by allowing the trading activity only when the goodness-of-fit of the estimation for trading signals is sufficiently high. We design a dynamic asset allocation strategy with market and dollar neutrality, formulated as a constrained optimization problem, which is implemented numerically. The improved reliability and robustness of this strategy is demonstrated through back-testing with real data. It is observed that its performance is robust to a variety of market conditions. We further provide some answers to the puzzle of choosing the number of factors to use, the length of estimation windows, and the role of transaction costs, which are crucial issues with direct impact on the strategy. Show more

Keywords: Mean-reversion time, statistical arbitrage, portfolio selection, market neutrality, principal components, factor models, residuals

DOI: 10.3233/RDA-170132

Citation: Risk and Decision Analysis, vol. 6, no. 4, pp. 263-290, 2017

Authors: Tapiero, Charles S.

Article Type: Research Article

Abstract: This paper is a short introduction on (Big) Data Science and Intelligence for the RDA educational corner. Its purpose is to motivate a greater discussion of what is Big Data, how it is transforming the future of finance and what are the essential opportunities and concerns when using Big Data. “Intelligence” in Big Data is used to emphasize that mathematics is an essential part of the algorithmic and the statistical approaches we use when searching, estimating or seeking answers to our problems. When we use the power of IT, Mathematical and Statistical Intelligence embedded in numerous applications and studies seek …to bridge theoretical constructs and their computational realizations. Their integration is a complete system of automatic and learning know how (we may call AI, Learning Machines or what not and by any other name). It is now expanded by systemic computing, data analytics and management to do much more with a lot less. However, in the long run, doing more without Intelligence, replacing intentionality by machine rationality, lead to an evolution where choices are no longer made but instead, are imposed by a data complexity and expert systems that may embed far greater risks than we can expect. In this case, without the power of a human intelligence and a mathematical (objective) rationality, our use of BIG data without science are similar to seeking to go from one place to another without a map. Show more

Keywords: Data Science, finance, statistics, analytics

DOI: 10.3233/RDA-180133

Citation: Risk and Decision Analysis, vol. 6, no. 4, pp. 291-298, 2017

Authors: Zakaria, Firano | Fatine, Filali Adib

Article Type: Research Article

Abstract: Analysis of contagion continues to attract growing interest from both regulatory authorities and the academic world and we are witnessing the development of analytical approaches for assessing the risk of contagion in the interbank market. Indeed, given its role in financial stability and monetary policy, the Central Bank must be able to accurately determine the level of international vulnerability associated with various scenarios for cross-border contagion, both to prevent than to manage situations systemic crises. The purpose of this study is to assess the risk of cross-border contagion of the Moroccan banking system through the data of the “BIS”. The …methodology is to first approximate the gross bilateral exposures using data from the banks’ financial statements. Then simulations based on contagion algorithm integrating counterparty risk are conducted to assess the risk of contagion. Also centrality of indicators and measurement of systemic importance are presented. The results were synthesized in indicators to assess the systemic importance of the French banking system internationally to Morocco; the fall of the latter is a significant risk of contagion. Show more

Keywords: Contagion risk, financial stability, systemic risk, cross border

DOI: 10.3233/RDA-180134

Citation: Risk and Decision Analysis, vol. 6, no. 4, pp. 299-315, 2017