Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5

VaR Related Abstracts

5 Measuring Tail-Risk Spillover in the International Banking Industry

Authors: Lidia Sanchis-Marco, Antonio Rubia


In this paper we analyze the state-dependent risk-spillover in different economic areas. To this end, we apply the quantile regression-based methodology developed in Adams, Füss and Gropp approach to examine the spillover in conditional tails of daily returns of indices of the banking industry in the US, BRICs, Peripheral EMU, Core EMU, Scandinavia, the UK and Emerging Markets. This methodology allow us to characterize size, direction and strength of financial contagion in a network of bilateral exposures to address cross-border vulnerabilities under different states of the economy. The general evidence shows as the spillover effects are higher and more significant in volatile periods than in tranquil ones. There is evidence of tail spillovers of which much is attributable to a spillover from the US on the rest of the analyzed regions, specially on European countries. In sharp contrast, the US banking system show more financial resilience against foreign shocks.

Keywords: spillover effects, Bank Contagion, SDSVaR, expected shortfall, VaR, expectiles

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4 Assesments of Some Environment Variables on Fisheries at Two Levels: Global and Fao Major Fishing Areas

Authors: Hyelim Park, Juan Martin Zorrilla


Climate change influences very widely and in various ways ocean ecosystem functioning. The consequences of climate change on marine ecosystems are an increase in temperature and irregular behavior of some solute concentrations. These changes would affect fisheries catches in several ways. Our aim is to assess the quantitative contribution change of fishery catches along the time and express them through four environment variables: Sea Surface Temperature (SST4) and the concentrations of Chlorophyll (CHL), Particulate Inorganic Carbon (PIC) and Particulate Organic Carbon (POC) at two spatial scales: Global and the nineteen FAO Major Fishing Areas divisions. Data collection was based on the FAO FishStatJ 2014 database as well as MODIS Aqua satellite observations from 2002 to 2012. Some data had to be corrected and interpolated using some existing methods. As the results, a multivariable regression model for average Global fisheries captures contained temporal mean of SST4, standard deviation of SST4, standard deviation of CHL and standard deviation of PIC. Global vector auto-regressive (VAR) model showed that SST4 was a statistical cause of global fishery capture. To accommodate varying conditions in fishery condition and influence of climate change variables, a model was constructed for each FAO major fishing area. From the management perspective it should be recognized some limitations of the FAO marine areas division that opens to possibility to the discussion of the subdivision of the areas into smaller units. Furthermore, it should be treated that the contribution changes of fishery species and the possible environment factor for specific species at various scale levels.

Keywords: granger causality, chlorophyll, VaR, fisheries-catch, FAO FishStatJ, MODIS Aqua, sea surface temperature (SST), particulate inorganic carbon (PIC), particulate organic carbon (POC)

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3 CPPI Method with Conditional Floor: The Discrete Time Case

Authors: Hachmi Ben Ameur, Jean Luc Prigent


We propose an extension of the CPPI method, which is based on conditional floors. In this framework, we examine in particular the TIPP and margin based strategies. These methods allow keeping part of the past gains and protecting the portfolio value against future high drawdowns of the financial market. However, as for the standard CPPI method, the investor can benefit from potential market rises. To control the risk of such strategies, we introduce both Value-at-Risk (VaR) and Expected Shortfall (ES) risk measures. For each of these criteria, we show that the conditional floor must be higher than a lower bound. We illustrate these results, for a quite general ARCH type model, including the EGARCH (1,1) as a special case.

Keywords: VaR, arch, CPPI, conditional floor, expected ehortfall

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2 The Impact of Monetary Policy on Aggregate Market Liquidity: Evidence from Indian Stock Market

Authors: Byomakesh Debata, Jitendra Mahakud


The recent financial crisis has been characterized by massive monetary policy interventions by the Central bank, and it has amplified the importance of liquidity for the stability of the stock market. This paper empirically elucidates the actual impact of monetary policy interventions on stock market liquidity covering all National Stock Exchange (NSE) Stocks, which have been traded continuously from 2002 to 2015. The present study employs a multivariate VAR model along with VAR-granger causality test, impulse response functions, block exogeneity test, and variance decomposition to analyze the direction as well as the magnitude of the relationship between monetary policy and market liquidity. Our analysis posits a unidirectional relationship between monetary policy (call money rate, base money growth rate) and aggregate market liquidity (traded value, turnover ratio, Amihud illiquidity ratio, turnover price impact, high-low spread). The impulse response function analysis clearly depicts the influence of monetary policy on stock liquidity for every unit innovation in monetary policy variables. Our results suggest that an expansionary monetary policy increases aggregate stock market liquidity and the reverse is documented during the tightening of monetary policy. To ascertain whether our findings are consistent across all periods, we divided the period of study as pre-crisis (2002 to 2007) and post-crisis period (2007-2015) and ran the same set of models. Interestingly, all liquidity variables are highly significant in the post-crisis period. However, the pre-crisis period has witnessed a moderate predictability of monetary policy. To check the robustness of our results we ran the same set of VAR models with different monetary policy variables and found the similar results. Unlike previous studies, we found most of the liquidity variables are significant throughout the sample period. This reveals the predictability of monetary policy on aggregate market liquidity. This study contributes to the existing body of literature by documenting a strong predictability of monetary policy on stock liquidity in an emerging economy with an order driven market making system like India. Most of the previous studies have been carried out in developing economies with quote driven or hybrid market making system and their results are ambiguous across different periods. From an eclectic sense, this study may be considered as a baseline study to further find out the macroeconomic determinants of liquidity of stocks at individual as well as aggregate level.

Keywords: Monetary Policy, vector autoregressive model, VaR, market liquidity, order driven market

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1 An Association between Stock Index and Macro Economic Variables in Bangladesh

Authors: Shamil Mardi Al Islam, Zaima Ahmed


The aim of this article is to explore whether certain macroeconomic variables such as industrial index, inflation, broad money, exchange rate and deposit rate as a proxy for interest rate are interlinked with Dhaka stock price index (DSEX index) precisely after the introduction of new index by Dhaka Stock Exchange (DSE) since January 2013. Bangladesh stock market has experienced rapid growth since its inception. It might not be a very well-developed capital market as compared to its neighboring counterparts but has been a strong avenue for investment and resource mobilization. The data set considered consists of monthly observations, for a period of four years from January 2013 to June 2018. Findings from cointegration analysis suggest that DSEX and macroeconomic variables have a significant long-run relationship. VAR decomposition based on VAR estimated indicates that money supply explains a significant portion of variation of stock index whereas, inflation is found to have the least impact. Impact of industrial index is found to have a low impact compared to the exchange rate and deposit rate. Policies should there aim to increase industrial production in order to enhance stock market performance. Further reasonable money supply should be ensured by authorities to stimulate stock market performance.

Keywords: VaR, deposit rate, DSEX, industrial index

Procedia PDF Downloads 14