nep-fmk New Economics Papers
on Financial Markets
Issue of 2011‒09‒05
ten papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Financial market spillovers around the globe By Thomas Dimpfl; Robert Jung
  2. The 2007 subprime market crisis through the lens of European Central Bank auctions for short-term funds By Nuno Cassola; Ali Hortacsu; Jakub Kastl
  3. Stock Market Reaction to the Global Financial Crisis: testing for the Lehman Brothers' Event By Becchetti, Leonardo; Ciciretti, Rocco
  4. Sovereign and Bank Credit Risk during the Global Financial Crisis By Irina Stanga
  5. An analysis of firm and market volatility By Susan Sunila Sharma; Paresh Kumar Narayan; Xinwei Zheng
  6. Has the structural break slowed down growth rates of stock markets? By Paresh Kumar Narayan; Seema Narayan
  7. Are credit default swaps a sideshow? Evidence that information flows from equity to CDS markets By Jens Hilscher; Joshua M. Pollet; Mungo Wilson
  8. Volatility Transmission in Emerging European Foreign Exchange Markets By Evzen Kocenda; Vit Bubak; Filip Zikes
  9. Some hypothesis on commonality in liquidity: New evidence from the Chinese stock market By Paresh Kumar Narayan; Xinwei Zheng; Zhichao Zhang
  10. Fresh evidence on herding behaviour from the Chinese stock market By Paresh Kumar Narayan; Xinwei Zheng

  1. By: Thomas Dimpfl; Robert Jung (University of Erfurt, Staatswissenschaftliche Fakultät)
    Abstract: Financial market spillovers around the globeThis paper investigates the transmission of return and volatility spillovers around the globe. It draws on index futures of three representative indices, namely the Dow Jones Euro Stoxx 50, the S&P 500 and the Nikkei 225. Devolatised returns and realised volatilities are modeled separately using a structural vector autoregressive model, thereby accounting for the particular sequential time structure of the trading venues. Within this framework, we test hypotheses in the spirit of Granger causality tests, investigate the short-run dynamics in the three markets using impulse response functions, and identify leadership effects through variance decomposition. Our key results are as follows. We find weak and shortlived return spillovers, in particular from the USA to Japan. Volatility spillovers are more pronounced and persistent. The information from the home market is most important for both returns and volatilities; the contribution from foreign markets is less pronounced in the case of returns than in the case of volatility. Possible gains in terms of forecasting precision when applying our modelling strategy are illustrated by a forecast evaluation.
    Keywords: pillovers, Index Futures, Realized Volatility, Structural VAR model
    Date: 2011–08–22
  2. By: Nuno Cassola (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Ali Hortacsu (The University of Chicago, Department of Economics, 1126 E. 59th Street, Chicago, IL 60637, USA.); Jakub Kastl (Stanford University, Department of Economics, Landau Economics Building, 579 Serra Mall, USA.)
    Abstract: We study European banks’ demand for short-term funds (liquidity) during the summer 2007 subprime market crisis. We use bidding data from the European Central Bank’s auctions for one-week loans, their main channel of monetary policy implementation. Our analysis provides a high-frequency, disaggregated perspective on the 2007 crisis, which was previously studied through comparisons of collateralized and uncollateralized interbank money market rates which do not capture the heterogeneous impact of the crisis on individual banks. Through a model of bidding, we show that banks’ bids reflect their cost of obtaining short-term funds elsewhere (e.g., in the interbank market) as well as a strategic response to other bidders. The strategic response is empirically important: while a naïve interpretation of the raw bidding data may suggest that virtually all banks suffered an increase in the cost of short-term funding, we find that for about one third of the banks, the change in bidding behavior was simply a strategic response. We also find considerable heterogeneity in the short-term funding costs among banks: for over one third of the bidders, funding costs increased by more than 20 basis points, and funding costs vary widely with respect to the country-of-origin. Estimated funding costs of banks are also predictive of market- and accounting-based measures of bank performance, suggesting the external validity of our findings. JEL Classification: D44, E58, G01.
    Keywords: Multiunit auctions, primary market, structural estimation, subprime market, liquidity crisis.
    Date: 2011–08
  3. By: Becchetti, Leonardo (University of Rome “Tor Vergata"); Ciciretti, Rocco (University of Rome “Tor Vergata")
    Abstract: We analyse with an event study approach the stock market reaction to Lehman Brothers' ling for chapter 11. Our inquiry on abnormal returns of about 2,700 stocks around the event date documents that RiskMetrics-KLD corporate governance and product quality indexes capture factors a ecting investors' reaction to the shock. We also nd that investors rationally attribute more value to the information on each rating domain than to affiliation/non-affiliation to the FTSE KLD 400 Social Index. Investors seem to discover, after the event, that KLD ratings provide original information which is not captured by traditional nancial rating indicators.
    Keywords: Global Financial Crisis; Event Study; Corporate Governance; Product Quality; Ratings
    Date: 2011–08–25
  4. By: Irina Stanga
    Abstract: This paper investigates the interaction of market views on the sustainability of sovereign debt and the perceived credit risk of banks. This interaction came into spotlight during the recent financial crisis, as government interventions in support of the financial sector were associated with increases in fiscal burden. I analyze and quantify the effect of government interventions in the domestic financial system on the default risks of the banking sector and sovereign borrowers. The paper focuses on the cases of Ireland and Spain, which experienced large public interventions in the domestic banking system and at a later stage highly volatile bond markets. For each country, I estimate a Vector Autoregression model to trace the interaction among sovereign CDS spreads, bank CDS spreads, and a measure of the business cycle over the sample period 2007-2011. I identify shocks by imposing sign restrictions on the impulse response functions. The results point towards a risk transfer from the financial to the sovereign sector, which generates an increase in the credit risk of the latter but only a temporary drop in that of banks.
    Keywords: Financial Crises; Sovereign Debt; VAR; Sign Restrictions
    JEL: C32 E44 H63
    Date: 2011–08
  5. By: Susan Sunila Sharma; Paresh Kumar Narayan; Xinwei Zheng
    Abstract: In this paper, using time series data for the period 2 January 1998 to 31 December 2008, for 560 firms listed on the NYSE, we examine whether firm volatility is related to market volatility. The main contribution of this paper is that we develop the analytical framework motivating the firm-market volatility relationship. We unravel three new findings on volatility. First, we discover significant evidence of common volatility; for 12 out of 14 sectors, market volatility has a statistically significant effect on firm volatility for at least 50 percent of firms. Second, we discover significant evidence of size effects: for small sized firms, there is weak evidence of commonality in volatility, while for large sized firms there is high evidence (as much as 75 percent of firms) of commonality in volatility. Third, we find that market volatility predicts firm volatility for firms belonging to five of the 14 sectors.
    Keywords: Volatility; Size Effects; Firms; Market
    JEL: G15
    Date: 2011–08–29
  6. By: Paresh Kumar Narayan; Seema Narayan
    Abstract: In this paper, we use the common structural break test suggested by Bai et al. (1998) to test for a common structural break in the stock prices of the US, the UK, and Japan. On the basis of the structural break, we divide each country‟s stock price series into sub-samples and investigate whether or not the structural break had slowed down the growth of stock markets. Our main findings are that when stock markets are modeled in a trivariate sense the common structural break turns out to be 1990:02, with the confidence interval including several episodes, such as the asset price bubble when housing prices and stock prices in Japan reached a peak in 1988/1989, the early 1990s recession in the UK, the business cycle peak of July 1990, the August 1990 Iraqi invasion of Kuwait and the March 1991 business cycle trough. Annual average growth rates suggest that the structural break has slowed down the growth rate of the US, UK and Japanese stock markets.
    Keywords: Common Structural Break Test, Stock Markets
    JEL: C22 G14 G15
    Date: 2011–08–29
  7. By: Jens Hilscher (International Business School, Brandeis University); Joshua M. Pollet (Broad College of Business, Michigan State University); Mungo Wilson (Saïd Business School, Oxford University)
    Abstract: In this paper we provide evidence that equity returns lead credit protection returns at daily and weekly frequencies, while credit protection returns do not lead equity returns. Our results indicate that informed traders are primarily active in the equity market rather than the CDS market. These findings are consistent with standard theories of market selection by informed traders in which market selection is determined partially by transaction costs. We also find that credit protection returns respond more quickly during salient news events (earnings announcement days) compared to days with similarly volatile equity returns. This evidence regarding the response of credit protection returns to news provides support for explanations related to investor inattention.
    Keywords: CDS, Market Segmentation, Inattention
    JEL: G12
    Date: 2011–07
  8. By: Evzen Kocenda; Vit Bubak; Filip Zikes
    Abstract: This paper studies the dynamics of volatility transmission between Central European (CE) currencies and the EUR/USD foreign exchange using model-free estimates of daily exchange rate volatility based on intraday data. We formulate a flexible yet parsimonious parametric model in which the daily realized volatility of a given exchange rate depends both on its own lags as well as on the lagged realized volatilities of the other exchange rates. We find evidence of statistically significant intra-regional volatility spillovers among the CE foreign exchange markets. With the exception of the Czech and, prior to the recent turbulent economic events, Polish currencies, we find no significant spillovers running from the EUR/USD to the CE foreign exchange markets. To measure the overall magnitude and evolution of volatility transmission over time, we construct a dynamic version of the Diebold-Yilmaz volatility spillover index and show that volatility spillovers tend to increase in periods characterized by market uncertainty.
    Keywords: Foreign exchange markets; Volatility; Spillovers; Intraday data; Nonlinear dynamics; European emerging markets
    JEL: C5 F31 G15
    Date: 2011–07–01
  9. By: Paresh Kumar Narayan; Xinwei Zheng; Zhichao Zhang
    Abstract: In this paper, we examine four specific hypotheses relating to commonality in liquidity on the Chinese stock markets. These hypotheses are: (a) that market-wide liquidity determines liquidity of individual stocks; (b) that liquidity varies with firm size; (c) that sectoral-based liquidity affects individual stock liquidities differently; and (d) that commonality in liquidity has an asymmetric effect. Based on a two-year dataset on the Shanghai and Shenzhen stock exchanges comprising of over 34 and 48 million transactions respectively, we find strong support for commonality in liquidity and a greater influence of industry-wide liquidity in explaining liquidity of individual stocks. Moreover, our results suggest that of the three main sectors – financial, industrial, and resources – industrial sector‟s liquidity is most important in explaining individual stock liquidities. Finally, we do not find any evidence of size effects, and document an asymmetric effect of market-wide liquidity on liquidity of individual stocks.
    Keywords: Commonality in Liquidity; Asymmetric Information; Size Effects; Chinese
    JEL: G10 G15
    Date: 2011–08–29
  10. By: Paresh Kumar Narayan; Xinwei Zheng
    Abstract: In this paper, we examine four specific hypotheses relating to herding behavior on the Chinese stock market. These hypotheses are that: (a) herding behavior exists on the Chinese stock market; (b) herding behavior exists in the pre-September 2008 financial crisis and the crisis period (post- September 2008 period) on the Chinese stock market; (c) herding behavior exists under different market conditions (rises and declines) in China; and (d) sector-specific (commerce, conglomerate, industrial, property and public utility sectors) herding behavior exists in the pre-September 2008 financial crisis and the crisis period (post- September 2008 period) and under different market conditions (rises and declines) in China. Based on 15 years of daily data for all firms dual-listed A and B shares on the Shanghai Stock Exchange (SHSE) and the Shenzhen Stock Exchange (SZSE), we find that herding behavior exists on Chinese stock market except in the case of the Shanghai B share market. Second, in the pre-crisis period, herding behavior is existed on SHSEA, SZSEA and SZSEB. In the crisis period, herding behavior is only existed on SHSEB. Third, herding behavior is existed on SHSEA, SZSEA and SZSEB regardless of whether the market is up or down. Herding behavior on down market is higher than up market. Fourth, we find that regardless of whether the market is on the rise or on the decline, herding behavior is the highest for the industrial sector. Lastly, we find a positive and significant relationship for full sample, pre financial crisis and the crisis period and all the sectors.
    Keywords: Herding behaviour, chinese stock market
    Date: 2011–08–29

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