دانلود مقاله ISI انگلیسی شماره 13742
ترجمه فارسی عنوان مقاله

تجارت و اطلاعات در بازار اوراق قرضه شرکتی

عنوان انگلیسی
Trade and information in the corporate bond market
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
13742 2013 43 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Financial Markets, Volume 16, Issue 1, February 2013, Pages 61–103

ترجمه کلمات کلیدی
- نقدینگی بازار اوراق قرضه - کارآیی اطلاعاتی - اوراق قرضه بالا - بردار اتوماتیک رگرسیون - تجارت سازمانی - مقایسه بازار متقابل
کلمات کلیدی انگلیسی
Bond market liquidity,Informational efficiency,Top bond,Vector auto-regression, Institutional trade,Cross market comparison
پیش نمایش مقاله
پیش نمایش مقاله  تجارت و اطلاعات در بازار اوراق قرضه شرکتی

چکیده انگلیسی

This paper examines the impact of shifting liquidity and institutional trading in the corporate bond market on inferences regarding informational efficiency. We find that when institutional trade dominance and other bond trading features are accounted for, stock leads evidenced in earlier studies surprisingly disappear. Short windows after firm-specific news releases are examined, and bond trading advantages are shown to be pronounced particularly when equity market liquidity is low (during after-market hours). Cross-sectionally, the effect of credit risk and other firm/bond level characteristics are determined. Finally, ‘top bonds’ are identified, and their common ex ante identifiable characteristics are determined.

مقدمه انگلیسی

The market efficiency of corporate bonds has not been established in the literature without controversy. Indeed, there are seemingly conflicting results (and hence conclusions) regarding the market efficiency of corporate bonds. In this paper, we demonstrate that the lack of consensus regarding bond market efficiency can be reconciled when bond market liquidity patterns and other institutional features specific to the bond market are explicitly considered. Specifically, we examine the importance of incorporating these features when examining efficiency and the extent of price discovery of corporate bonds, as well as for the comparison of informational efficiency across markets in general. First, since for any given firm there typically is a multiplicity of bond issues, examining the efficiency of a firm's bonds in pair-wise comparisons with the issuer's stock can lead to misleading inferences, as liquidity and informed trading in different issues may differ cross-sectionally and over time. Second, the corporate bond market in the United States has been shown to have a dominant institutional presence, with potential trade disadvantages for retail traders. Since retail trades account for about 65% of transactions (but represent only 1.8% of volume), tests that do not differentiate between the two trading sectors may artificially magnify the effect of potentially noisier retail trades. Third, the around-the-clock corporate bond market may provide an important informational role when the equity market displays low liquidity and poor price discovery. The impact of these observations can be significant not only when examining the efficiency of the market in isolation (or relative to that of equity market), but can also contribute to recent advances in corporate bond liquidity research. On a methodological note, this paper aims to address some of the difficulties inherent in the comparison of informational efficiency across markets. Analysis in early studies that has focused on the relative informational efficiency of the bond and equity markets using a Vector Autoregression (VAR) approach based on pair-wise comparisons of each bond with the issuer's stock can be misleading. Resulting inferences are limited, in that they cannot reveal more than whether the firm's bonds are on average slower in reflecting information than the firm's stock. Further, inferences regarding this ‘average’ are predicated on the implicit assumption that liquidity and trading activity of the issuer's bonds are immediately comparable both across bonds and uniformly with the equity. As the variation in both of these is known to be considerable, relying on an average may create a bias towards finding a stock lead. In fact, accounting for dynamic liquidity, trade size and timing effects can generate surprising reversals of previously documented results: Granger-causality tests indicate that stock leads disappear, and that bond efficiency can be deemed comparable to that of the equity. More importantly, these tests cannot uncover the information most desired by traders (i.e., whether there are some bonds on an informational par with equity). Further, if these bonds switch off over time, such liquidity patterns cannot be captured by pair-wise comparisons within a time series framework. Indeed, we find that institutional trade in a firm's bonds following earnings announcements is highly concentrated in certain issues. We define the bond with the highest institutional trade volume immediately following an earnings announcement (and before NYSE market open) as the ‘top bond’ for the firm. We show that the identity of these top bonds changes over time, and that they share common characteristics, such as age, maturity, credit quality, and bond complexity. Moreover, their identity can be predicted ex ante based on these common characteristics, and a logistic model yields a fairly high degree of out-of-sample predictive accuracy. Notably, the majority of price discovery for these bonds occurs before the equity market opens. These results point to the importance of conducting efficiency analysis that incorporates both the intraday trading patterns and the dynamic liquidity of different bonds issued by the same firm. Ignoring such factors underestimates the ability of a trader to move on firm-specific information using a fixed income instrument. We examine trading and price discovery at short time windows around earnings announcements and find that information incorporation patterns differ systematically across different traders and bonds. Tests conducted on samples that are pooled across trade sizes are shown to yield results driven by the predominant (in terms of frequency) noisy small trades, thereby masking informational efficiency. This result holds even after we account for the potentially confounding effect of a few large issuers dominating the bond market, the timing of earnings announcements, and issuer and issue characteristics. Further, we find that the nature of information impacts the way in which it is impounded into prices, with patterns differing on good and bad news days. Finally, BBB-rated bonds with imminent downgrades (within one year) display rapid reactions to news, on a par with high-yield issues. Opportunities to preempt equity traders may exist immediately after earnings announcements, which most often occur overnight. While equity traders are relatively liquidity-disadvantaged in the market for NYSE-listed stocks during these hours, the around-the-clock over-the-counter bond market provides a useful vehicle for trading on information. This is particularly true for institutional bond traders who are shown to be dominant players in this market. In fact, our collective results are indicative of strategic information-based trading. Since increasing benefits or stakes should encourage greater information gathering/absorption for large traders, situations that offer bond traders comparative advantages should be marked by a greater propensity to trade. The ability of bond investors to trade in large amounts, particularly when liquidity is low in the equity market, renders the corporate bond market a legitimate vehicle for information revelation. We also examine the timing of the earnings announcements and its relationship to the intraday distribution of trades. We find some evidence that bad news gets released later in the early morning hours, closer to market open, than good news. Even after controlling for announcement times, we find evidence of bond trades occurring significantly before regular trading hours for some bonds and news events. On a policy note, the comparative advantages of institutional traders can be potentially mitigated by decreasing the permissible trade reporting lag for dealers. We find evidence of increased price discovery accompanying TRACE reporting lag window decreases implemented in a phased-in fashion over our sample period. Specifically, retail trade disadvantages are alleviated in that price dispersions decrease with the regulatory changes, suggesting that additional reductions in mandatory reporting windows could further improve terms of trade for retail investors. This paper is organized as follows. Section 1 discusses and reviews some salient characteristics of corporate bond market trade and illustrates the importance of incorporating liquidity and trading patterns in empirical tests of bond market efficiency. Section 2 describes the TRACE data used in this study and provides evidence regarding the distribution of institutional trades in our sample. Section 3 uses a VAR approach to revisit the lead-lag relations between stocks and bonds, and illustrates the importance of explicitly accounting for shifting liquidity and other bond trading patterns in statistical analysis. Section 4 examines overnight liquidity and weighted price contributions. We identify common salient characteristics of top bonds and discuss their link to liquidity and ex ante determination. We present our predictive model and out-of-sample tests for a priori identification of top bonds. Section 5 analyzes the effect of trade size, as well as the firm-level and bond-specific features on the sensitivity to information. Additionally, we examine the impact of the timing of earnings announcements on the reaction to information. Section 6 concludes.