Microstructure of the Euro‐Area Government Bond Market

Darbha, Madhucchand; Dufour, Alfonso

doi:10.1002/9781118681145.ch3

Cited by 18 publications

(12 citation statements)

References 37 publications

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“…On the contrary, quoted depth shows a weak and negative correlation with volatility. Similar results have been documented in Darbha and Dufour [2013a] where spreads are small for bonds with low volatility and large depth. Inferentially, when the variation in price changes increases, the size quoted by market makers shrinks.…”

Section: Descriptive Statisticssupporting

confidence: 87%

“…A smaller percentage of quasi-government and structured bonds (asset-backed securities and covered bonds) are also listed and traded on MTS platforms. It was launched in 1988 by the Italian Treasury and the Bank of Italy in an effort to enhance liquidity and transparency of the Italian secondary government bond market [Darbha and Dufour, 2013a]. The electronic platform was expanded in later years to include all major European countries and domestic MTS markets were subsequently developed 2 .…”

Section: The Mts Marketmentioning

confidence: 99%

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Measuring and Analyzing Liquidity and Volatility Dynamics in the Euro-Area Government Bond Market

O’Sullivan¹,

Papavassiliou²

2019

Handbook of Global Financial Markets

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This chapter examines the impact the European sovereign debt market crisis had on liquidity and volatility dynamics and their interdependencies in the eurozone government bond market. In particular, we examine the impact across different countries and across different maturity buckets within individual countries. A comprehensive high-frequency dataset from MTS, Europe's premier electronic fixed-income trading market, is employed to construct a variety of microstructure liquidity and volatility measures. We analyze important trends in these measures over both tranquil and crisis periods. Additionally, we study time-varying correlations as well as the intertemporal interactions of liquidity proxies with volatility and returns. Our findings provide useful insights to regulators and policy makers on the relative strengths and weaknesses of domestic and global financial systems.

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Section: Descriptive Statisticssupporting

confidence: 87%

Section: The Mts Marketmentioning

confidence: 99%

Measuring and Analyzing Liquidity and Volatility Dynamics in the Euro-Area Government Bond Market

O’Sullivan¹,

Papavassiliou²

2019

Handbook of Global Financial Markets

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“…Here we describe the market features that are most relevant for our analysis. Detailed information on the MTS market structure is given in Darbha and Dufour (2013). There are two parallel platforms for benchmark bonds: the MTS domestic markets devoted to trading domestic bonds and the EuroMTS market where all benchmark securities across countries can be traded.…”

Section: Institutional Detailsmentioning

confidence: 99%

“…However, percentage spreads are not stable during the sovereign debt crisis. According to Darbha and Dufour (2013), the spreads of European government bonds have significantly increased during the crisis period. When defining the threshold for removing extreme percentage spreads, a successful filter needs to reflect the development of the liquidity conditions.…”

Section: Choosing Filtersmentioning

confidence: 99%

Modeling intraday volatility of European bond markets: A data filtering application

Zhang

Dufour

2019

International Review of Financial Analysis

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This paper studies the intraday volatility of European government bonds under the framework of the multiplicative component GARCH model (Engle and Sokalska, 2012). Intraday return volatility is specified as the product of daily volatility, intraday seasonality, and a unit GARCH process. The model is applied to 10-year European government bonds during the sovereign debt crisis. We observe large transitory intraday volatility often due to illiquidity effects and outliers. We suggest a flexible and effective procedure for jointly filtering mid-quote prices and estimating volatility models. Finally, we show that intraday data contain relevant information for daily volatility forecasts.

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“…We create seven portfolios based on bonds' residual maturities equal to 3 years, 5 years, 7 years, 10 years, 15 years, 30 years, and less than or equal to 6 months. The 6‐month portfolio is included to control for liquidity noise (see Darbha & Dufour, ) and the potential presence of coupon‐stripping operations.…”

mentioning

confidence: 99%

Explaining repo specialness

et al. 2019

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We study the dynamics of specialness for 1‐day repo contracts on Italian government bonds over a 10‐year sample period. As predicted by Duffie's (1996) model, our results show that collateral supply is a significant factor for specialness. However, we enrich that finding by also showing a clear impact from repo liquidity, collateral riskiness, information uncertainty, and short‐selling proxies, revealing the importance of speculative bond demand for specialness. During crisis periods, bond fire sales and European Central Bank interventions also have a large impact on repo specialness. We identify recurrent patterns for specialness around bond auctions. Specialness increases steadily from the auction announcement date until a few days before the auction settlement date, which is consistent with overbidding behaviour and a short selling of treasuries (via reverse repos) from primary dealers ahead of auctions.

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Microstructure of the Euro‐Area Government Bond Market

Cited by 18 publications

References 37 publications

Measuring and Analyzing Liquidity and Volatility Dynamics in the Euro-Area Government Bond Market

Measuring and Analyzing Liquidity and Volatility Dynamics in the Euro-Area Government Bond Market

Modeling intraday volatility of European bond markets: A data filtering application

Explaining repo specialness

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