Money Market Integration and Sovereign CDS Spreads Dynamics in the New EU States

When the first phase of the crisis focused primarily on the interbank market volatility, the second phase spread on the instability of public finance. Although the overall stance of public finances of the new members is better than the old member countries, the differences within the new group are significant (from the performer Estonia to the laggard Hungary). Sovereign CDS spreads have become major variables focused on risks and expectations about the fiscal situation of different countries. In the paper we investigate, first, whether there is a link in the new member states (NMS) between the expectations about the condition of their public finances and the dynamics of money markets,including integration of national money markets with the euro area.....Our study confirm that the strong link between monetary and public finance risk as apart of total systemic risk increase during the crisis especially for currency boards regimes, when the link becomes stronger and pronounced. For the inflation targeting countries the link became weaker and less pronounced.money markets, sovereign CDS spreads, EU enlargement, monetary regimes, financial crisis

Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models

This paper investigates whether structural breaks and long memory are relevant features in modeling and forecasting the conditional volatility of oil spot and futures prices using three GARCH-type models, i.e., linear GARCH, GARCH with structural breaks and FIGARCH. By relying on a modified version of Inclan and Tiao (1994)'s iterated cumulative sum of squares (ICSS) algorithm, our results can be summarized as follows. First, we provide evidence of parameter instability in five out of twelve GARCH-based conditional volatility processes for energy prices. Second, long memory is effectively present in all the series considered and a FIGARCH model seems to better fit the data, but the degree of volatility persistence diminishes significantly after adjusting for structural breaks. Finally, the out-of-sample analysis shows that forecasting models accommodating for structural break characteristics of the data often outperform the commonly used short-memory linear volatility models. It is however worth noting that the long memory evidence found in the in-sample period is not strongly supported by the out-of-sample forecasting exercise.

A Threshold Vector Autoregression Model of Exchange Rate Pass-Through in Mexico

International audienceConsidering nonlinearities in the exchange rate pass-through to domesticprices, this paper estimates exchange rate pass-through in Mexico. We examine responses of domestic prices to a positive one unit exchange rate shock by estimating a threshold vector autoregression (TVAR) model. A monthly rate of inflation of 0.79% acts as a threshold. The exchange rate pass-through to domestic prices is statistically significant above the threshold level of the inflation rate and statistically insignificant below it

Empirical Investigation of Systemic Risk in the New EU States

Sovereign CDS spreads have become major variables focused on risks and expectations about the fiscal situation of different countries. In the paper we investigate, first, whether there is a link in the new member states between the expectations about the condition of their public finances and the dynamics of money markets, including integration of national money markets with the Euro area. Second, we look on the particularities of this relationship through the different phases of the crisis and across the different countries using different monetary regimes. This concerns mostly two opposite extreme monetary regimes, namely, currency boards (and quasi-fixed exchange rate) - Bulgaria, Estonia, Latvia, Lithuania, or inflation targeting - Poland, Czech Republic, Hungary and Romania. The results obtained form the high frequency panel data models support the theoretical hypotheses and policy intuition that exists strong relationship between the liquidity risk (measured by the short term money markets) and fiscal risk (measured by CDS) and that this link is extremely unstable and in some sense nonlinear during the financial crisis. Our study confirm that the strong link between monetary and public finance risk as apart of total systemic risk increase during the crisis especially for currency boards regimes, when the link becomes stronger and pronounced. For the inflation targeting countries the link became weaker and less pronounced.money markets, sovereign CDS spreads, monetary regimes, financial crisis

GARCH models : evidence from Tunisian Exchange market

This paper deals with statistics�and econometrics�properties of fractionally integra- ted GARCH (FIGARCH). We compare these characteristics with those of traditional models. We insist on the GARCH exponential/IGARCH in�nite decrease of volatility impact. Then, we apply it on three Tunisian exchange rate series between 1994 and 2006. As Beine, Laurent and Lecourt (2002), the contributions of the FIGARCH model are extended by accounting for the observed kurtosis through a student-t based maximum likelihood estimation. This estimation improves the goodness of �t properties of this model and may lead to di¤erent interest parameters estimates.Long memory, Volatility, persistence, exchange rate

The Contribution of Global Sourcing to the Economic Performance of Organizations: Analysis of the Points of View of the Supply Chain Participants

Purpose: This paper aims at investigating the reasons for the complex and long lead time from global suppliers that causes inventory shortages. It focuses on supply chain risk management in global sourcing. This study has revealed all the specific risks of a global sourcing project and has provided some solutions for risk management: three-step risk management, safety stock, data sharing and driving supplier performance. Design/methodology/approach: A qualitative study is conducted to propose concrete recommendations on three topics: risk management, safety stock and information sharing. A semistructured survey-guided interview was used to collect related data, and the answers were assessed using syntactic, lexical, thematical and NVivo software analysis. Findings: This study has revealed all the specific risks of a global sourcing project and has provided some solutions for risk management: three-step risk management, safety stock, data sharing and driving supplier performance. Originality/value: Through research work, we have noticed that the world of the Supply Chain is constantly evolving and that it is becoming more and more complex. Through these interviews, we have noticed that the role of purchasing is changing differently in each sector.Peer Reviewe

Self-Stabilizing Message Routing in Mobile ad hoc Networks

We present a self-stabilizing algorithm for routing messages between arbitrary pairs of nodes in a mobile ad hoc network. Our algorithm assumes the availability of a reliable GPS service, which supplies mobile nodes with accurate information about real time and about their own geographical locations. The GPS service provides an external, shared source of consistency for mobile nodes, allowing them to label and timestamp messages, and thereby aiding in recovery from failures. Our algorithm utilizes a Virtual Infrastructure programming abstraction layer, consisting of mobile client nodes, virtual stationary timed machines called Virtual Stationary Automata (VSAs), and a local broadcast service connecting VSAs and mobile clients. VSAs are associated with predetermined regions in the plane, and are emulated in a self-stabilizing manner by the mobile nodes. VSAs are relatively stable in the face of node mobility and failure, and can be used to simplify algorithm development for mobile networks. Our routing algorithm consists of three subalgorithms: [(1)] a VSA-to-VSA geographical routing algorithm, [2] a mobile client location management algorithm, and [3] the main algorithm, which utilizes both location management and geographical routing. All three subalgorithms are self-stabilizing, and consequently, the entire algorithm is also self-stabilizing

Asymmetric and nonlinear pass-through of energy prices to CO2 emission allowance prices

We use the recently developed nonlinear autoregressive distributed lags (NARDL) model to examine the pass-through of changes in crude oil prices, natural gas prices, coal prices and electricity prices to the CO2 emission allowance prices. This approach allows one to simultaneously test the short- and long-run nonlinearities through the positive and negative partial sum decompositions of the predetermined explanatory variables. It also offers the possibility to quantify the respective responses of the CO2 emission prices to positive and negative shocks to the prices of their determinants from the asymmetric dynamic multipliers. We find that: (i) the crude oil prices have a long-run negative and asymmetric effect on the CO2 allowance prices; (ii) the falls in the coal prices have a stronger impact on the carbon prices in the short-run than the increases; (iii) the natural gas prices and electricity prices have a symmetric effect on the carbon prices, but this effect is negative for the former and positive for the latter. Policy implications are provided.COMPETE, QREN, FEDER, Fundação para a Ciência e a Tecnologia (FCT

Long memory and structural breaks in modeling the return and volatility dynamics of precious metals

We investigate the potential of structural changes and long memory (LM) properties in returns and volatility of the four major precious metal commodities traded on the COMEX markets (gold, silver, platinum and palladium). Broadly speaking, a random variable is said to exhibit long memory behavior if its autocorrelation function is not integrable, while structural changes can induce sudden and significant shifts in the time-series behavior of that variable. The results from implementing several parametric and semiparametric methods indicate strong evidence of long range dependence in the daily conditional return and volatility processes for the precious metals. Moreover, for most of the precious metals considered, this dual long memory is found to be adequately captured by an ARFIMA-FIGARCH model, which also provides better out-of-sample forecast accuracy than several popular volatility models. Finally, evidence shows that conditional volatility of precious metals is better explained by long memory than by structural breaks