| Περίληψη : | The concept of informed trading is closely linked to the activity of speculators. Speculators utilize the information they possess, regarding the prospects of a firm, to profit from undertaking certain trading positions. Essentially, speculators trade because their beliefs about the intrinsic value of the asset differs from the observed market price. By buying underpriced or by selling overpriced securities, they profit from the convergence of a security‟s price towards its “fair” value. Speculators can be categorized in styles for formulating their views about a firm‟s security price as well as for translating their beliefs into certain trading strategies. On one hand, value traders evaluate all the available information so as to determine the fundamental value of an instrument, hence, assessing whether an instrument‟s market price properly reflects its intrinsic value. On the other hand, news traders focus on changes in the fundamental value of an instrument, should any news arise in the market. News traders consider that the current market prices represent all the available information in the market, but the news they observe. In order to be profitable, news traders have to respond much quicker to any public news relative to other traders. Finally, arbitrageurs search for discrepancies in the market prices of similar instruments, usually traded in different markets, which are driven by the same fundamental factors. In a sense, they exploit inefficiencies in the markets that can be attributed to market frictions. In short, informed traders increase market efficiency by moving market prices towards equilibrium values, while uninformed traders (noise traders) trade for reasons that are exogenous to the fundamental value of the asset. In search of the fundamental value of an asset, all trading styles of informed trading are exposed to liquidity risk. Liquidity risk affects the capacity of traders in executing their orders without affecting the quoted prices. In a sense, liquidity risk limits the arbitrage opportunities of informed traders. Liquidity risk can take the form of systematic liquidity that curtails the ability of all market participants to trade, or of idiosyncratic liquidity that affects the price of a particular asset. Systematic liquidity risk can arise from money market contagion or from an increase of counterparty risk. Whereas, idiosyncratic liquidity can stem from adverse selection risk or price uncertainty. So far, we have subtly touched on three distinct components that are expected to be priced in a firm‟s credit spreads. The first component regards the fundamental value of the asset, the second considers systematic liquidity conditions while the third pertains to the idiosyncratic liquidity of the asset. As far as the first component is concerned, it focuses on the information contained in a firm‟s financial statements1. Financial statements constitute the most typical source of information that is periodically available to all investors. Essentially, fundamental value strategies are motivated by the information residing in financial statements. However, while there is an entire industry2 dedicated to translating the wealth of information that is contained in the published financial reports of a company into some objective indication of its credit standing, the way by which this information is absorbed by the credit markets is still unclear. To state it differently, credit picking, being the essence of value trading, remains a rather opaque process. At the same time, part of the information contained in the forthcoming financial statements, may be translated into fundamental value strategies before the announcement day by informed investors. In a sense, informed trading could facilitate the convergence between the fundamental value of an asset and its market price before the official release of financial statements. The second constituent concentrates on the impact of systematic liquidity on the formation of a firm‟s credit risk premium. The price of a security depends on the capacity of arbitrageurs to access the required capital so as to implement their strategies, which would drive market prices towards an equilibrium level. Hence, dislocation in the money or/and capital markets can lead to a severe disruption in the assets market. Indeed, the withdrawal of funding after the Lehman‟s collapse forced arbitrageurs to liquidate their positions, causing a steep drop in asset prices. As arbitrageurs ceased to provide liquidity and started to require liquidity from the market, the price of liquidity skyrocketed. Specifically, on 16 September 2008 the price for accessing the unsecured interbank market more than tripled3 to reach 6.4%. At the same time, repo haircuts for securities other than Treasuries soared from less than 1%, prior to Lehman‟s collapse, to 45% (Gorton and Metrick 2011). Elevated information asymmetry during that period hampered investors from identifying the credit risk of each market participant. Hence, they demanded a higher compensation for providing financing across counterparties, or at the extreme of adverse selection fears they became unwilling to lend at all. The substantial rise in the funding cost even for major investment banks curtailed their ability to draw short-term funding, so leading to a substantial increase in their distress risk as reflected in their CDS spreads. Rehypothecation lenders were deterred from rolling over their financing not only to arbitrageurs (hedge funds) but also to investment banks, since their counterparties were more prone to failure and themselves lacked infrastructure to manage the risks arising from holding less liquid securities in their portfolios. Consequently, the capacity of investment banks to fund their own balance sheets as well as their clients was substantially diminished. Essentially, the clients of investment banks were compelled to deleverage in their portfolios, so further plummeting asset prices. In short, systematic liquidity risk enters the credit spread as an exogenous trading cost component that has to be priced. However, to what extent the corporate credit spreads encompass any systematic liquidity premiums arising from the conditions in the local or/and in the global markets, and whether these premiums are affected by changes in the credit standing of a firm‟s home country, remain pending issues not investigated until now. Information can be publicly available to everyone or solely held by privately informed investors. Public information is utilized by news traders, while private information is employed by value traders and arbitrageurs in setting up their trading strategies. Value traders are subject to the risk of being adverse selected by the dealer in case he believes that value traders hold valuable private information. That is, in implementing their strategies, value traders have to bear with any idiosyncratic liquidity cost components, which arise from adverse selection and/or asset price uncertainty. These surcharges required by the liquidity provider are endogenous, as they are subject both to the value of the asset and the counterparty participating in the trade. In a sense, dealers‟ quote adjustment practices would shape the profits of value traders under the price discovery process, so giving rise to a two-fold question. The first part relates to whether dealers are right in classifying their clients into informed and uninformed, conditional on the excess returns that each investor category subsequently enjoys. A manifestation of the adverse selection cost component can be the premium that dealers surcharge on their informed clients. While the second part questions whether the quoting strategy followed by the dealers proves to be profitable for the dealers themselves. To state it differently, the extent that dealers may manage to front-run informed traders, so that they share part of the value traders‟ profits, is something that has not been studied as such yet. The credit risk markets offer us the opportunity to assess the importance of all those components and confirm the mechanism that underlies their formation. For this purpose, we pursue under this study a comprehensive investigation of the informational content and trading cost components of credit spreads. In doing so, we unfold our empirical research into three distinct, yet complementary, parts. That is, each section of the analysis concentrates on a different component of corporate credit spreads. Initially, we distinguish informed trading motivated by the financial statement announcement into different trading styles. To state it differently, we identify what are the useful pieces of information contained in a firm‟s financial statements that attract the attention of each trading style. Considering that arbitrage strategies between equity and CDS markets suggest that price discovery in the one market should affect prices in the other and vice versa, we examine the actual importance of the officially published accounting data for the value trader in the credit market. Essentially, the information available to CDS traders act as an upper informativeness bound in the formation of credit spreads, whereas CDS spreads controlled for the information of equity traders provide the respective lower floor. Our results indicate that value traders are the main speculators in the CDS market, since we find fundamental analysis to be relevant for determining CDS spread changes. Whereas, news trading is only relevant for earnings and cash flow protection information around the announcement date window. Overall, financial ratios are statistically significant in the pricing of CDS spreads, even after controlling for the information already present in the equity market or the macroeconomic environment. This finding implies that part of the fundamental value information is discovered through alternative markets. Indeed, it might be that arbitrageurs profit by trading both in the equity and in the CDS markets. Changes in financial ratios are absorbed gradually by the CDS market, with a significant part already captured in a firm‟s CDS spread well before the announcement date. This part also reflects information that has already been disseminated in the market prior to the official release of financial statements (e.g. issuance of a new bond that leads to an increase in leverage). Furthermore, the CDS market appears to precede the equity market in assimilating certain financial ratios both before and after the announcement date of financial statements. Hence, it supports the preference of privately informed traders for the CDS market as well as the bridging role of arbitrageurs between the two markets. Our results also verify the asymmetrical impact of financial ratios on the market‟s perception of a company‟s credit risk, by identifying changes in the magnitude and in the statistical significance among the regressors that drive CDS widening vs. tightening. Finally, our findings suggest that value traders have already priced part of both the imminent negative and positive news related to a firm‟s leverage and liquidity before the announcement date. Whereas, most of the good and bad news “surprises” regarding a firm‟s profitability are absorbed around the announcement date. For the second part of our empirical research we first establish whether systematic liquidity is priced in the corporate CDS spreads and then examine any differentiation in its impact across countries or/and sectors and ratings events. Our findings indicate an exogenous systematic liquidity cost component in corporate CDS spreads, since dealers that are exposed to funding risk via the money market channel price it into their quoted credit spreads. Regarding the country sensitivity analysis, we find that an increase in systematic liquidity risk in North America, as it is reflected in TED spread, tighten corporate CDS spreads outside North America. In a sense, our findings complement the literature that explores contagion effects among countries by identifying how increased systematic liquidity in the USA is translated into CDS returns for firms located outside the USA. On the other hand, we discover that a rise in the domestic systematic liquidity risk, as captured by the spread over GCRR4, widens local firms‟ CDS spreads. The sector analysis suggests that claims on financial firms, across all countries examined, are more vulnerable to systematic liquidity risk compared to non-financial firms. To sum up, the systematic liquidity premium is influenced by systematic liquidity risk conditions not only inside a firm‟s home country but also outside a firm‟s home country as well as by the sector that a firm belongs. Changes in the credit standing of the home country also affected the systematic liquidity cost components in the CDS spreads of its local firms. Our results indicate that when the issuer country was downgraded, an increase in TED spread exacerbated the widening of corporate CDS spreads. In a sense, our findings suggest increased vulnerability of the downgraded country to systematic shocks. Whereas, when a country‟s upgrade coincided with a rise in systematic liquidity risk outside the country, home firms‟ CDS spreads further tightened. In other words, country credit rating changes amplified the pricing impact of systematic liquidity on the CDS spreads of their local firms. Finally, we find some evidence that the CDS spreads of firms located in vulnerable economies with positive outlook changes, tightened due to “local” while widened due to “global” heightened systematic liquidity risk. That is, the precarious economic conditions in a country rendered its home firms more susceptible to negative global developments. Overall, our analysis suggests that the systematic liquidity cost component that value traders have to pay depends also on the credit standing changes of the country where a firm is located. In the third part of this study we examine whether the dealers‟ quote adjustment strategies vary across clients belonging to different investor categories. Our empirical evidence suggests that dealers pre-classify their clients into informed and uninformed based on their identities, giving rise to dealers‟ “prejudice” costs. That is, our analysis identifies an extra parameter that dealers consider in their quote setting process, other than the size, the direction and the sequence of the last few orders they fill according to market microstructure theory. In doing so, dealers update accordingly their expectations regarding the price of a security, and in a sense, try to share in the value traders profits. To state it differently, our findings suggests the presence of an endogenous cost component in a firm‟s credit spread, as traders are being overcharged by the liquidity provider (dealer). This finding is further substantiated by complementing our empirical conclusions with a theoretical model that explicitly incorporates the investor category in the quote setting process adopted by the dealers as well as with a simulation exercise. The results of the simulation exercise suggest that the P&L generated for a dealer that uses our extended sequential trade model is significantly higher relative to the respective P&L that he would have enjoyed if he had employed the model of Easley O‟Hara (1992). Considering that the excess returns enjoyed by each investor category have to be proportional to the level of the private information it possesses, we next find evidence that institutional investors do earn more often than not in the longer horizons, while retail investors do lose more often than not in the longer horizons. Hence, we assert that dealers are right in a-priory classifying institutional investors as value traders and retail investors as noise traders. The aforementioned pre-classification proves also to be much more profitable for the dealers themselves, relative to a “naive” strategy that would uniformly classify all investors as uninformed. Essentially, dealers appear to “front-run” successfully value traders. Last but not least, our results imply that dealers, being the market makers, are most efficient as news-traders. Indeed, they are the ones benefiting more often than not in trades propelled by public information releases. Overall, our analysis suggests that value traders are the main type of speculators in the market, while news traders are the dealers. The findings of this empirical research can be translated into a series of important implications for various stakeholders. These include, among others, the following: 1. Comprehensive models, which combine variables both from a firm‟s financial statements and from the equity market, are the ones used by speculators. 2. Default risk cannot all be inferred from the equity market. 3. The identification of the asymmetric impact of factors that drive the narrowing vs. the widening of CDS spreads can help us make out the utility function of risk-averse participants. At the same time, it can facilitate market participants to better manage the risk of their positions as well as properly formulate their investments strategies. 4. Systematic liquidity cannot be ignored in the pricing of credit risk, as it gives rise to significant cost components in corporate CDS spreads. 5. The appropriateness of measures taken by the central banks in the USA and in Europe in supporting the financial system during the latest financial crisis is confirmed. 6. Models analysing adverse selection risk or the quote-adjustment mechanism should take into account some sort of counterparty “prejudice” from the point of view of the dealer.
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