Financial Networks and Trading in Bond Markets
G. Geoffrey Booth
Eli Broad Graduate School of Management
Michigan State University
(517) 353 1745
Umit G. Gurun
School of Management
University of Texas at Dallas
(972) 883 4777
Harold H. Zhang
School of Management
University of Texas at Dallas
(972) 883 5917
Acknowledgements: We thank Rick Green, Bing Han, Andrei Simonov, Chester Spatt, Allan Zabedee, and seminar participants at the Bilkent University, Istanbul Stock Exchange, University of Hong Kong, University of Texas at Dallas, the 2007 European Financial Management Association Annual Meetings, and the 2008 China International Conference in Finance for their comments and Istanbul Stock Exchange, Turkish Bank Association for providing the data used in this study. All errors are our own.
Financial Networks and Trading in
Bond Markets
This paper examines how financial networks influence asset prices and trading performance. Consistent with theoretical studies on the role of communication networks in information dissemination, we posit that financial institutions with more extensive financial networks can more efficiently acquire and process information pertaining to asset trading thus have better trading performance than financial institutions with limited financial networks. Using transaction-level Turkish government bond trading data, we find that financial institutions with global financial networks exhibit a stronger tendency to trade in the more liquid bonds and consistently trade at more favorable prices suggesting that global financial institutions have information advantages. They enjoy better trading performance than local financial institutions on informed trades. The information advantage afforded global financial institutions tends to decline over time suggesting possible learning by local financial institutions as a result of trading with global financial institutions.
Key Words: Financial Networks, Information Advantage, Bond Market Trading
1. Introduction
Although it is well established that information moves security prices, how information flows through financial markets and is impounded in the prices of financial assets is not as well understood. Traditional asset pricing models assume that individuals behave anonymously with new information becoming known by all the agents in the market simultaneously, thereby making the information common knowledge. As a result, traditional approaches disregard the possibility that agent behavior (individually and collectively) may be influenced by a communication network. Information, however, can also gradually disseminate in the market by word-of-mouth and observational learning. Because of differences in institutional structures and traders’ information processing abilities, it is unlikely that information diffusion will be amorphous. Instead, information is likely to spread more rapidly within trading firms than between trading firms, not only because of the presence of an intra-firm network but also because of financial incentives provided to traders that are related to firm profitability.
This paper examines the role of financial network in influencing asset prices and trading performances of financial institutions with different financial networks. Consistent with the implications of theoretical studies on the role of communication networks on information dissemination, we posit that a financial institution with a more extensive financial network (global financial institutions) can more efficiently acquire and process information closely related to asset trading in global financial markets than an institution with a more limited local network (local financial institutions). This may lead to different trading performances between global and local financial institutions. We conduct an extensive empirical investigation on trading in bond markets participated primarily by financial institutions with different financial networks. Our empirical analyses show that global financial networks tend to trade more liquid bonds and enjoy more favorable transaction prices suggesting an information advantage over local financial institutions. Consistent with an information advantage, they also have better trading performance than their local counterparts on informed trades.
Models of trading dynamics recognize the presence of asymmetric information. The distinction between informed and uninformed traders leads to a number of useful insights. For instance, informed traders tend to respond more quickly to news, tend to trade in more liquid markets, and tend to show better performance than uninformed traders. Yet it is not entirely clear who the informed traders are or how they become informed. In this regard several empirical studies show that individuals who reside and work in the same location tend to make similar financial decisions, which suggests the presence of internal group communication.[1] The idea is that traders who are spatially or electronically close are exposed to similar information that is diffused via networks within the same group once the information is received by one or more of the traders. For example, anecdotal evidence suggests that Twitter, a social network, plays a role in assessing the markets in the agricultural commodity sector (Berry and Rees, 2009).
Existing research on whether certain types of traders are more informed than others often focuses on whether foreign or domestic traders are more informed using data on trading in equity markets. The logic favoring domestic traders being more informed than foreign traders is that they may be able to gather more timely and accurate information about the prospects of a company through formal and informal local networks, be more familiar with local laws and information disclosure policies and be able to avoid information distortions caused by linguistic and cultural differences. Supporting the position that the foreign investors are more informed is that these investors may be able to exploit their prior investment experience and expertise as well as their superior (supposedly) knowledge of international business conditions. Foreign investors may also employ locals who are familiar with the domestic market, thereby partially offsetting domestic advantages.
The empirical evidence regarding which group is more informed, however, is mixed. Several empirical studies involving a variety of equity markets suggest that domestic investors are more informed than their foreign counterparts (e.g., Dahlquist and Robertsson, 2004; Lee et al., 2004; Choe, Kho and Stulz, 2005; Dvorák, 2006) while others report the opposite (e.g., Grinblatt and Keloharju, 2000; Bacmann and Bollinger, 2003; Bailey, Mao and Sirodom, 2004; Huang and Shiu, 2005). These inconsistent results suggest that the conclusions are market specific or that the foreign-domestic classification provides only a partial explanation.
We address this inconsistency by examining the trading behaviors of government bonds of financial institutions with different financial networks. We choose government bond markets because they typically provide little pre-trading transparency (Biais and Green, 2005), and, compared to equities, the information driving government bond prices is more likely to be eventually known to the public. Together these attributes define a venue where information channels are important and better informed traders are able to exploit their superior information. In this regard, the Turkish Bonds and Bills Market is particularly suitable for our study for three reasons. First, this market is well-developed, easily accessible to the global investment community, and operates with limited government interference. Because it is not a financial hub, information affecting short-term movements in bond prices worldwide, such as order flows in the major bond and equity markets, tends to flow to the Turkish market and not from it. Second, participants in this market are typically banks or brokerage firms, either acting on their own behalf or at the behest of others, as opposed to the mixture of financial and non-financial institutions as well as households that is often found in equity markets. This improves the likelihood that the characteristic that distinguishes the performances of different financial institutions is indeed their financial network structure. Finally, detailed transaction data, including the identities of the transacting counterparties, are available, which allows us to analyze the trading behaviors of different types of financial institutions.
We classify the sample institutions as those that have offices in the local economy only (local financial institutions) and those that have offices both in the local economy and in major bond trading markets such as New York City and London (global financial institutions). We define a financial network to be a set of offices that are linked together by an electronic communication system. According to our classification of a global financial network, all of the international financial institutions that participate in the Bonds and Bills Market have global financial networks. Further, some domestic financial institutions also have global financial networks.[2] This indicates that our classification of the scope of financial networks (global versus local) does not correspond simply to the dichotomy of foreign versus domestic traders. Indeed, a robustness check suggests that our findings on the effect of the scope of financial networks continue to hold when we use data on domestic financial institutions only. Thus, our classification, as opposed to the foreign-domestic dichotomy, permits us to explicitly focus on the flow of information through different types of intra-firm networks after controlling for size effect.[3]
We find that global financial institutions tend to trade more heavily than their local counterparts in the liquid (active) portion of the bond market. Chowdhry and Nanda (1991) suggest that informed investors tend to trade in more liquid assets, presumably to camouflage their information advantage. Our finding on the different trading patterns across global and local financial institutions is consistent with the view that global financial institutions may have an information advantage and strategically use the more liquid bonds to conceal their superior information.
Our empirical analysis also uncovers that the average delayed price impact of trades initiated by global financial institutions is consistently larger than that initiated by local counterparts (both large and small). Specifically, for every one million Turkish Lira (TL) traded by global financial institutions, the price changes TL 0.09 or 6 U.S. cents more in a 10-minute interval than if the TL 1 million were traded by a typical large financial institution. This represents a price advantage of 11 basis points. As argued in Hasbrouck (1991), the delayed price impact of a trade measures the informativeness of the trader. This finding lends support to the conjecture that global financial institutions have an information advantage, as it suggests that global financial institutions can consistently buy at a lower (or sell at a higher) price than their local counterpart. These results are robust to excluding foreign financial institutions from our analysis and/or limiting attention to the subsample of liquid bonds.[4] This suggests that our findings go beyond the usual foreign versus domestic dichotomy and are unlikely to be attributed to liquidity.
Building upon the findings on the informativeness of trades for different financial institutions, we find that global financial institutions earn higher profits on informed trades than their local counterparts. Specifically, global financial institutions earn 0.006 percentage point higher day-trading profit per trading cycle on informed trades than typical large financial institutions which in turn earn 0.008 percentage point higher profit per trading cycle than local financial institutions. This is consistent with the prediction that financial institutions with an information advantage are likely to perform better on asset trading than others. We also find that day-trading profitability exhibits some persistence for all financial institutions. High interest rate volatility reduces day-trading profitability and investor participation in day-trading.
Finally, we find the price impact of trades by global financial institutions declined over time. Consistent with the declined price impact of these trades, while global financial institutions still perform better on informed trades in bond day-trading than their local counterparts, the outperformance has declined over the same time period. This may suggest possible learning by local financial institutions as a result of repeated trading with global financial institutions. Using the approach introduced in Seru, Shumway, and Stoffman (2009), we identify statistically significant learning effect by local financial institutions, in particular local small financial institutions, as they accumulate more experience trading with other informed financial institutions.
We organize the remainder of our paper as follows. Section 2 describes the Turkish government bond market and trading system, and Section 3 defines our classification of traders as global versus local financial institutions and presents summary statistics on our data. In Section 4, we provide empirical analysis and discuss our results. Finally, we make concluding remarks in Section 5.
2. The Bonds and Bills Market
2.1 The Market
Turkey’s public debt market, the Bonds and Bills Market, is an important investment and trading venue for financial institutions. Using total market capitalization standardized by GDP as a measure of importance, according to World Bank Database on Financial Development and Structure, Turkey ranked 9th out of 30 major world bond markets, with its bond market being 2.3 times as large as its equity market (see Beck et al., 2000 for details).
Almost every month, the Turkish Treasury auctions bonds with maturities ranging from one month to 10 years. After the primary market allocation, these bonds are traded on an automated secondary market, the Bonds and Bills Market. The institutions that are authorized to trade on the Bonds and Bills Market are Istanbul Stock Exchange (ISE) member banks and member brokerage houses. These financial institutions typically trade on their own accounts. Sometimes they fill retail buy orders from their inventory, but if their inventory is insufficient they may go to market to meet demand.
Each institution employs multiple traders who form an information network. They are in constant contact with each other throughout the trading day, permitting them to be better informed of the local buy and sell order flow. For instance, it is common for traders to inform the participants in their network that they have learned that a particular financial institution is a net buyer today or that another financial institution is trying to liquidate a sizeable position. Some institutions have home offices in multiple markets while others have branches; such organizational structures create multi-market trader networks that facilitate the transmission of information relevant to the local market.
Bond market participants are a diverse mix of small and large Turkish financial institutions and large international financial institutions. These institutions have different arrangements to disseminate information. International banks, for instance, have their bond trading floors connected by a “hoot”. Nowadays a “hoot” refers to an electronic communication system, but originally it was a device devoted to a single trading floor. “Hoot” transmissions tend to flow from New York and London to other markets. In contrast, bond traders of Turkish banks (especially large Turkish banks) gather information by making phone calls to fellow bond traders in overseas financial centers. Of course, information is also available to all traders whose firms have access to public information networks such as Reuters, Bloomberg, and similar providers. Different financial institutions, however, may still have different information processing capabilities, which may lead to differences in interpretation of publicly released information and in turn trading performance. For example, Lyons (1995) and Love and Payne (2008) show that information publicly and simultaneously released to all market participants is partially impounded into prices through order flows in exchange rate determination.[5]