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We highlight the implications of combining underwriting services and lending for the choice of underwriters and for competition in the underwriting business. We show that cross-selling can increase underwriters’ incentives, and we explain three phenomena: first, that cross-selling is important for universal banks to enter the investment banking business; second, that cross-selling is particularly attractive for highly leveraged borrowers; third, that less-than-market rates are no prerequisite for cross-selling to benefit a bank’s clients. In our model, cross-selling reduces rents in the underwriting business.
We investigate, using the 2002 US Health and Retirement Study, the factors influencing individuals’ insecurity and expectations about terrorism, and study the effects these last have on households’ portfolio choices and spending patterns. We find that females, the religiously devout, those equipped with a better memory, the less educated, and those living close to where the events of September 2001 took place worry a lot about their safety. In addition, fear of terrorism discourages households from investing in stocks, mostly through the high levels of insecurity felt by females. Insecurity due to terrorism also makes single men less likely to own a business. Finally, we find evidence of expenditure shifting away from recreational activities that can potentially leave one exposed to a terrorist attack and towards goods that might help one cope with the consequences of terrorism materially (increased use of car and spending on the house) or psychologically (spending on personal care products by females in couples).
We document significant and robust empirical relationships in cross-country panel data between government size or social expenditure on the one hand, and trade and financial development indicators on the other. Across countries, deeper economic integration is associated with more intense government redistribution, but more developed financial markets weaken that relationship. Over time, controlling for country-specific effects, public social expenditure appears to be eroded by globalization trends where financial market development can more easily substitute for it.
The paper provides novel insights on the effect of a firm’s risk management objective on the optimal design of risk transfer instruments. I analyze the interrelation between the structure of the optimal insurance contract and the firm’s objective to minimize the required equity it has to hold to accommodate losses in the presence of multiple risks and moral hazard. In contrast to the case of risk aversion and moral hazard, the optimal insurance contract involves a joint deductible on aggregate losses in the present setting.
This paper analyzes liquidity in an order driven market. We only investigate the best limits in the limit order book, but also take into account the book behind these inside prices. When subsequent prices are close to the best ones and depth at them is substantial, larger orders can be executed without an extensive price impact and without deterring liquidity. We develop and estimate several econometric models, based on depth and prices in the book, as well as on the slopes of the limit order book. The dynamics of different dimensions of liquidity are analyzed: prices, depth at and beyond the best prices, as well as resiliency, i.e. how fast the different liquidity measures recover after a liquidity shock. Our results show a somewhat less favorable image of liquidity than often found in the literature. After a liquidity shock (in the spread or depth or in the book beyond the best limits), several dimension of liquidity deteriorate at the same time. Not only does the inside spread increase, and depth at the best prices decrease, also the difference between subsequent bid and ask prices may become larger and depth provided at them decreases. The impacts are both econometrically and economically significant. Also, our findings point to an interaction between different measures of liquidity, between liquidity at the best prices and beyond in the book, and between ask and bid side of the market.
Previous evidence suggests that less liquid stocks entail higher average returns. Using NYSE data, we present evidence that both the sensitivity of returns to liquidity and liquidity premia have significantly declined over the past four decades to levels that we cannot statistically distinguish from zero. Furthermore, the profitability of trading strategies based on buying illiquid stocks and selling illiquid stocks has declined over the past four decades, rendering such strategies virtually unprofitable. Our results are robust to several conventional liquidity measures related to volume. When using liquidity measure that is not related to volume, we find just weak evidence of a liquidity premium even in the early periods of our sample. The gradual introduction and proliferation of index funds and exchange traded funds is a possible explanation for these results.
This paper addresses and resolves the issue of microstructure noise when measuring the relative importance of home and U.S. market in the price discovery process of Canadian interlisted stocks. In order to avoid large bounds for information shares, previous studies applying the Cholesky decomposition within the Hasbrouck (1995) framework had to rely on high frequency data. However, due to the considerable amount of microstructure noise inherent in return data at very high frequencies, these estimators are distorted. We offer a modified approach that identifies unique information shares based on distributional assumptions and thereby enables us to control for microstructure noise. Our results indicate that the role of the U.S. market in the price discovery process of Canadian interlisted stocks has been underestimated so far. Moreover, we suggest that rather than stock specific factors, market characteristics determine information shares.
Innovative automated execution strategies like Algorithmic Trading gain significant market share on electronic market venues worldwide, although their impact on market outcome has not been investigated in depth yet. In order to assess the impact of such concepts, e.g. effects on the price formation or the volatility of prices, a simulation environment is presented that provides stylized implementations of algorithmic trading behavior and allows for modeling latency. As simulations allow for reproducing exactly the same basic situation, an assessment of the impact of algorithmic trading models can be conducted by comparing different simulation runs including and excluding a trader constituting an algorithmic trading model in its trading behavior. By this means the impact of Algorithmic Trading on different characteristics of market outcome can be assessed. The results indicate that large volumes to execute by the algorithmic trader have an increasing impact on market prices. On the other hand, lower latency appears to lower market volatility.
Macro announcements change the equilibrium riskfree rate. We find that treasury prices reflect part of the impact instantaneously, but intermediaries rely on their customer order flow in the 15 minutes after the announcement to discover the full impact. We show that this customer flow informativeness is strongest at times when analyst forecasts of macro variables are highly dispersed. We study 30 year treasury futures to identify the customer flow. We further show that intermediaries appear to benefit from privately recognizing informed customer flow, as, in the cross-section, their own-account trade profitability correlates with access to customer orders, controlling for volatility, competition, and the announcement surprise. These results suggest that intermediaries learn about equilibrium riskfree rates through customer orders.
We report evidence that the presence of hidden liquidity is associated with greater liquidity in the order books, greater trading volume, and smaller price impact. Limit and market order submission behavior changes when hidden liquidity is present consistent with at least some traders being able to detect hidden liquidity. We estimate a model of liquidity provision that allows us to measure variations in the marginal and total payoffs from liquidity provision in states with and without hidden liquidity. Our estimates of the expected surplus to providers of visible and hidden liquidity are positive and typically of the order of one-half to one basis points per trade. The positive liquidity provider surpluses combined with the increased trading volume when hidden liquidity is present are both consistent with liquidity externalities.
This paper considers a trading game in which sequentially arriving liquidity traders either opt for a market order or for a limit order. One class of traders is considered to have an extended trading horizon, implying their impatience is linked to their trading orientation. More specifically, sellers are considered to have a trading horizon of two periods, whereas buyers only have a single-period trading scope (the extended buyer-horizon case is completely symmetric). Clearly, as the life span of their submitted limit orders is longer, this setting implies sellers are granted a natural advantage in supplying liquidity. This benefit is hampered, however, by the direct competition arising between consecutively arriving sellers. Closed-form characterizations for the order submission strategies are obtained when solving for the equilibrium of this dynamic game. These allow to examine how these forces affect traders´ order placement decisions. Further, the analysis yields insight into the dynamic process of price formation and into the market clearing process of a non-intermediated, order driven market.
Central counterparties (CCPs) have increasingly become a cornerstone of financial markets infrastructure. We present a model where trades are time-critical, liquidity is limited and there is limited enforcement of trades. We show a CCP novating trades implements efficient trading behaviour. It is optimal for the CCP to face default losses to achieve the efficient level of trade. To cover these losses, the CCP optimally uses margin calls, and, as the default problem becomes more severe, also requires default funds and then imposes position limits.
n the last few years, many of the world’s largest financial exchanges have converted from mutual, not-for-profit organizations to publicly-traded, for-profit firms. In most cases, these exchanges have substantial responsibilities with respect to enforcing various regulations that protect investors from dishonest agents. We examine how the incentives to enforce such regulations change as an exchange converts from mutual to for-profit status. In contrast to oft-stated concerns, we find that, in many circumstances, an exchange that maximizes shareholder (rather than member) income has a greater incentive to aggressively enforce these types of regulations.
The execution, clearing, and settlement of financial transactions are all subject to substantial scale and scope economies which make each of these complementary functions a natural monopoly. Integration of trade, execution, and settlement in an exchange improves efficiency by economizing on transactions costs. When scope economies in clearing are more extensive than those in execution, integration is more costly, and efficient organization involves a trade-off of scope economies and transactions costs. A properly organized clearing cooperative can eliminate double marginalization problems and exploit scope economies, but can result in opportunism and underinvestment. Moreover, a clearing cooperative may exercise market power. Vertical integration and tying can foreclose entry, but foreclosure can be efficient because market power rents attract excessive entry. Integration of trading and post-trade services is the modal form of organization in financial markets, which is consistent with the hypothesis that transactional efficiencies explain organizational arrangements in these markets.
Central counterparties
(2008)
Central counterparties (CCPs) have increasingly become a cornerstone of financial markets infrastructure. We present a model where trades are time-critical, liquidity is limited and there is limited enforcement of trades. We show a CCP novating trades implements efficient trading behaviour. It is optimal for the CCP to face default losses to achieve the efficient level of trade. To cover these losses, the CCP optimally uses margin calls, and, as the default problem becomes more severe, also requires default funds and then imposes position limits.
Algorithmic trading has sharply increased over the past decade. Equity market liquidity has improved as well. Are the two trends related? For a recent five-year panel of New York Stock Exchange (NYSE) stocks, we use a normalized measure of electronic message traffic (order submissions, cancellations, and executions) as a proxy for algorithmic trading, and we trace the associations between liquidity and message traffic. Based on within-stock variation, we find that algorithmic trading and liquidity are positively related. To sort out causality, we use the start of autoquoting on the NYSE as an exogenous instrument for algorithmic trading. Previously, specialists were responsible for manually disseminating the inside quote. As stocks were phased in gradually during early 2003, the manual quote was replaced by a new automated quote whenever there was a change to the NYSE limit order book. This market structure change provides quicker feedback to traders and algorithms and results in more message traffic. For large-cap stocks in particular, quoted and effective spreads narrow under autoquote and adverse selection declines, indicating that algorithmic trading does causally improve liquidity.
We find and describe four futures markets where the bid-ask spread is bid down to the fixed price tick size practically all the time, and which match counterparties using a pro-rata rule. These four markets´ offered depths at the quotes on average exceed mean market order size by two orders of magnitude, and their order cancellation rates (the probability of any given offered lot being cancelled) are significantly over 96 per cent. We develop a simple theoretical model to ex- plain these facts, where strategic complementarities in the choice of limit order size cause traders to risk overtrading by submitting over-sized limit orders, most of which they expect to cancel.