Using Matched Samples to Test for Differences in Trade Execution Costs

Davies, Ryan J.; Kim, Sang Soo

doi:10.2139/ssrn.555182

Cited by 34 publications

(35 citation statements)

References 62 publications

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“…We consider two types of control samples: (a) "pooled unmatched control sample", and (b) "pairwise matched control sample". As Goldstein, Hotchkiss and Sirri (2007) and Davies and Kim (2009) point out, both approaches of forming control samples have their own merits and applicability, and are optimal. Nevertheless, there are 7 We thank the anonymous referee for beneficial suggestions on these three methodological issues.…”

Section: Datamentioning

confidence: 99%

Did CDS trading improve the market for corporate bonds?

Das

Kalimipalli

Nayak

2014

Journal of Financial Economics

121

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Did CDS Trading Improve the Market for Corporate Bonds?Financial innovation through the creation of new markets and securities impacts related markets as well, changing their efficiency, quality (pricing error) and liquidity. The credit default swap (CDS) market was undoubtedly one of the salient new markets of the past decade. In this paper we examine whether the advent of CDS trading was beneficial to the underlying secondary market for corporate bonds. We employ econometric specifications that account for information across CDS, bond, equity, and volatility markets. We also develop a novel methodology to utilize all observations in our data set even when continuous daily trading is not evidenced, because bonds trade much less frequently than equities. Using an extensive sample of CDS and bond trades over 2002-2008, we find that the advent of CDS was largely detrimental -bond markets became less efficient, evidenced no reduction in pricing errors, and experienced no improvement in liquidity. These findings are robust to various slices of the data set and specification of our tests.

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Section: Datamentioning

confidence: 99%

Did CDS trading improve the market for corporate bonds?

Das

Kalimipalli

Nayak

2014

Journal of Financial Economics

121

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“…In order to see whether the abnormal trading activity on the SSCB day is also documented in other stocks with similar firm characteristics, we conduct a diff‐in‐diff test using a matched sample of stocks that are not subject to the trading halts due to an SSCB trigger. In particular, following Davies and Kim (), we match each SSCB stock one‐to‐one to a control stock within the same index, that is, S&P500 or Russell 1000, based on the share price and market capitalization . The results reported in Panel B in Table are very similar to the results shown in Panel A, which are also confirmed by the graphical evidence provided in Figure .…”

Section: Single‐stock Circuit Breaker Stocksmentioning

confidence: 99%

Intraday Rallies and Crashes: Spillovers of Trading Halts

Cui

Gozluklu

2016

Int. J Fin Econ

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This paper analyses a set of intraday rally and crash events at the firm level during the single‐stock circuit breaker program and documents the cross‐sectional spillover effects of such events on non‐halted stocks. We test whether such major price jumps, and subsequent trading halts, affect related stocks through the destabilizing eme price movements that trigger the circuit breakers at the firm level are accompanied by a massive surge in volume, spread and short‐term volatility, which gradually revert back to normal. Speculative strategies of arbitrageurs such as momentum and pairs trading cause cross‐sectional spillovers in volume and volatility during the trading halt. Copyright © 2016 John Wiley & Sons, Ltd.

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“…Such methods, in fact, allow comparing the execution costs on different exchanges, or across various groups of securities. For instance, Davies and Kim (2009) consider two groups of stocks that differ in their listing status and match them in pairs according to various characteristics. We focus on bank bonds because the sample size of non-financial bonds traded on DomesticMOT only is not suitable for the matching exercise.…”

Section: The Impact Of Fragmentation On Liquidity: Evidence From a Mamentioning

confidence: 99%

The Liquidity of Dual-Listed Corporate Bonds. Empirical Evidence from Italian Markets

et al. 2014

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We compute some indicators (zero-trade, turnover ratio, Amihud price impact, and Roll bid-ask spread) to examine the liquidity conditions of corporate bonds traded on the main Italian retail bond markets from January 2010 to June 2013. In order to compare market liquidity for identical securities, our analysis focuses on fragmented bonds, i.e. bonds traded concurrently on two different venues: either DomesticMOT and EuroTLX, or ExtraMOT and EuroTLX. As for bonds traded on DomesticMOT and EuroTLX, the Amihud and the Roll statistics suggest EuroTLX being more liquid. Moreover, irrespective of the trading venue, on average bank bonds are less liquid than bonds issued by non-financial companies, especially from 2011 due to the impact of the sovereign debt crisis. With regard to bonds traded across ExtraMOT and EuroTLX, the latter is characterized by better liquidity conditions, with bank bonds being more liquid than non-financial ones. Furthermore, we find evidence of better liquidity figures for Italian bonds (nationality), structured bonds (complexity), and securities with greater minimum trading size (MTS). We also find that bonds' features (issuers' nationality and industry; bonds' residual maturity, complexity, rating, etc…) affect liquidity differently depending upon the trading venue, thus supporting the view that market microstructure may play a relevant role. Finally, we investigate the effect of fragmentation by comparing the liquidity of dual-listed bank bonds fragmented across DomesticMOT and EuroTLX with otherwise similar bank bonds traded exclusively on DomesticMOT. Italian fragmented bank bonds turn out to be slightly more liquid than similar Italian bonds traded exclusively on DomesticMOT; whereas, the opposite holds for foreign bank bonds. However, overall there is not a clear-cut evidence on the effect of fragmentation on bond liquidity, probably because it is intertwined with bonds' attributes, such as the issue size (in our sample, higher for the Italian bank bonds).JEL Classification: G01, G10, G12, G18

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Using Matched Samples to Test for Differences in Trade Execution Costs

Cited by 34 publications

References 62 publications

Did CDS trading improve the market for corporate bonds?

Did CDS trading improve the market for corporate bonds?

Intraday Rallies and Crashes: Spillovers of Trading Halts

The Liquidity of Dual-Listed Corporate Bonds. Empirical Evidence from Italian Markets

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