Forecasting Financial Crises and Contagion in Asia Using Dynamic Factor Analysis

In this paper we compare the performance of a regional indicator of vulnerability in predicting, out of sample, the crisis events affecting the South East Asian region during the 1997-98 period. A Dynamic Factor method was used to retrieve the vulnerability indicator and stochastic simulation is used to produce probability forecasts. The empirical findings suggest evidence of financial contagion.Financial contagion, Dynamic factor model

Model Spasial Resiko Banjir Rob karena Pemanasan Global sebagai Masukan Perencanaan Pesisir (Studi Kasus: Pesisir Kota Semarang)

This research will examine how local zoning predictions of flood risk in 2050 rob of 1‐3 m (Oceane World Conference 2007). This can not be separated from the prediction that global warming is happening now has melted the polar ice caps that increasethe volume of sea water, besides that warming temperatures would increase the number rising tide to the mainland that caused flooding rob (Diposaptono, 2008 and Kodatie, 2003 ). The purpose of this research is to develop models rob floods in 2050 with a Geographic Information System to obtain prediction of disaster risk zoning in these predictions are used spatial model approach. The data acquired and processed by spatially derived variables vulnerability and vulnerability, the vulnerability variables caused by the higher average sea level rise and the decline in the face of the land, and variables such as vulnerability vulnerability of settlements, infrastructure vulnerability, institutional vulnerability and social vulnerability . Of this application can be concluded that the model is dynamic enough to be developed following the development of customized ariable conditions in the study area was kepecayaan level, but in essence the model of disaster risk zoning susceptibility and vulnerability factors must exist to determine the level ofrisk while the variables can be adjusted.

Accounting for Seismic Risk in Financial Analysis of Property Investment

A methodology is presented for making property investment decisions using loss analysis and the principles of decision analysis. It proposes that the investor choose among competing investment alternatives on the basis of the certainty equivalent of their net asset value which depends on the uncertain discounted future net income, uncertain discounted future earthquake losses, initial equity and the investor’s risk tolerance. The earthquake losses are modelled using a seismic vulnerability function, the site seismic hazard function, and an assumption that strong shaking at a site follows a Poisson process. A building-specific vulnerability approach, called assembly-based vulnerability, or ABV, is used. ABV involves a simulation approach that includes dynamic structural analyses and damage analyses using fragility functions and probability distributions on unit repair costs and downtimes for all vulnerable structural and nonstructural components in a building. The methodology is demonstrated using some results from a seven-storey reinforced-concrete hotel in Los Angeles

Combining Static and Dynamic Analysis for Vulnerability Detection

In this paper, we present a hybrid approach for buffer overflow detection in C code. The approach makes use of static and dynamic analysis of the application under investigation. The static part consists in calculating taint dependency sequences (TDS) between user controlled inputs and vulnerable statements. This process is akin to program slice of interest to calculate tainted data- and control-flow path which exhibits the dependence between tainted program inputs and vulnerable statements in the code. The dynamic part consists of executing the program along TDSs to trigger the vulnerability by generating suitable inputs. We use genetic algorithm to generate inputs. We propose a fitness function that approximates the program behavior (control flow) based on the frequencies of the statements along TDSs. This runtime aspect makes the approach faster and accurate. We provide experimental results on the Verisec benchmark to validate our approach.Comment: There are 15 pages with 1 figur

Network hierarchy evolution and system vulnerability in power grids

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.The seldom addressed network hierarchy property and its relationship with vulnerability analysis for power transmission grids from a complex-systems point of view are given in this paper. We analyze and compare the evolution of network hierarchy for the dynamic vulnerability evaluation of four different power transmission grids of real cases. Several meaningful results suggest that the vulnerability of power grids can be assessed by means of a network hierarchy evolution analysis. First, the network hierarchy evolution may be used as a novel measurement to quantify the robustness of power grids. Second, an antipyramidal structure appears in the most robust network when quantifying cascading failures by the proposed hierarchy metric. Furthermore, the analysis results are also validated and proved by empirical reliability data. We show that our proposed hierarchy evolution analysis methodology could be used to assess the vulnerability of power grids or even other networks from a complex-systems point of view.Peer ReviewedPostprint (author's final draft

Forecasting Financial Crises and Contagion in Asia using Dynamic Factor Analysis

In this paper we use principal components analysis to obtain vulnerability indicators able to predict financial turmoil. Probit modelling through principal components and also stochastic simulation of a Dynamic Factor model are used to produce the corresponding probability forecasts regarding the currency crisis events a®ecting a number of East Asian countries during the 1997-1998 period. The principal components model improves upon a number of competing models, in terms of out-of-sample forecasting performance.Financial Contagion, Dynamic Factor Model

Dynamic Effects Increasing Network Vulnerability to Cascading Failures

We study cascading failures in networks using a dynamical flow model based on simple conservation and distribution laws to investigate the impact of transient dynamics caused by the rebalancing of loads after an initial network failure (triggering event). It is found that considering the flow dynamics may imply reduced network robustness compared to previous static overload failure models. This is due to the transient oscillations or overshooting in the loads, when the flow dynamics adjusts to the new (remaining) network structure. We obtain {\em upper} and {\em lower} limits to network robustness, and it is shown that {\it two} time scales $\tau$ and $\tau_0$, defined by the network dynamics, are important to consider prior to accurately addressing network robustness or vulnerability. The robustness of networks showing cascading failures is generally determined by a complex interplay between the network topology and flow dynamics, where the ratio $\chi=\tau/\tau_0$ determines the relative role of the two of them.Comment: 4 pages Latex, 4 figure

Regional Vulnerability : The Case of East Asia

In a case study of six East Asian economies, we use dynamic factor analysis to estimate a regional component of the exchange market pressure index (EMPI) as a measure of regional financial stress. The extent to which this indicator is explained by regional economic and financial factors is interpreted as regional vulnerability to crisis. We find that regional external liabilities and exuberance in domestic stock and credit markets, as well as the US high yield spread, were positively correlated with regional vulnerability. Individual country EMPIs are also explained by regional factors, with country-specific factors and trade linkages playing little role.currency crisis ; contagion ; vulnerability ; dynamic factor analysis

Vulnerability assessment of urban building stock: a hierarchic approach

In the last decades the evaluation of the seismic risk are of rising concern, considered essential in the activity and definition of strategy planning and urban management. The evaluation of the seismic vulnerability of the existent building stock in the perspective of the seismic risk mitigation should not be placed only in relation to the isolated buildings of relevant historical and cultural importance, but also, in relation to the agglomerate of buildings in urban centres. The chronological construction process frequently results in characteristic heterogeneity of masonry and wall connection quality. In addition, buildings do not constitute independent units given that they share the mid-walls with adjacent buildings and the façade walls are aligned. This way, as post-seismic observations proved, buildings do not have an independent structural behaviour, but they interact amongst themselves, mainly for horizontal actions and so the structural performance should be studied at the level of the aggregate and not only for each isolated building. In most cases, for masonry structures there is no need for sophisticated dynamic analyses for seismic resistance verification or vulnerability assessment. This is even more relevant when an assessment at the level of a city centre is pursued. In this work, the results of evaluation of the vulnerability will be presented in accordance to three proposed methodologies based on a vulnerability index that consequently allows the evaluation of damage and creation of loss scenarios (economical and human) not only at the level of the building and its façade walls but also at the level of the aggregates. It will be discussed and evaluated the application of the referred methodologies and its integration in an SIG platform

Evaluation of analytical methodologies to derive vulnerability functions

The recognition of fragility functions as a fundamental tool in seismic risk assessment has led to the development of more and more complex and elaborate procedures for their computation. Although vulnerability functions have been traditionally produced using observed damage and loss data, more recent studies propose the employment of analytical methodologies as a way to overcome the frequent lack of post-earthquake data. The variation of the structural modelling approaches on the estimation of building capacity has been the target of many studies in the past, however, its influence in the resulting vulnerability model, impact in loss estimations or propagation of the uncertainty to the seismic risk calculations has so far been the object of restricted scrutiny. Hence, in this paper, an extensive study of static and dynamic procedures for estimating the nonlinear response of buildings has been carried out in order to evaluate the impact of the chosen methodology on the resulting vulnerability and risk outputs. Moreover, the computational effort and numerical stability provided by each approach were evaluated and conclusions were obtained regarding which one offers the optimal balance between accuracy and complexity