We analyze the resiliency of a pure limit order market by investigating the limit order book (bid and ask prices, spreads, depth and duration), order flow and transaction prices in a window of best limit updates and transactions around aggressive orders (orders that move prices). We find strong persistence in the submission of aggressive orders. Aggressive orders take place when spreads and depths are relatively low, and they induce bid and ask prices to be persistently different after the shock. Depth and spread remain also higher than just before the order, but do return to their initial level within 20 best limit updates after the shock. Relative to the sample average, depths stay around their mean before and after aggressive orders, whereas spreads return to their mean after about twenty best limit updates. The initial price impact of the aggressive order is partly reversed in the subsequent transactions. However, the aggressive order produces a long-term effect as prices show a tendency to return slowly to the price of the aggressive order. Copyright Springer 2005

We present a dynamic microstructure model where a dealer market (DM) and a crossing network (CN) interact. We consider sequentially arriving agents having different valuations for an asset. Agents maximize their profits by either trading at a DM or by submitting an order for (possibly) uncertain execution at a CN. We develop the analysis for three different informational settings: transparency, "complete" opaqueness of all order flow, and "partial" opaqueness (with observable DM trades). We find that a CN and a DM cater for different types of traders. Investors with a high eagerness to trade are more likely to prefer a DM. The introduction of a CN increases overall order flow by attracting traders who would not otherwise submit orders ("order creation"). It also diverts trades from the DM. The transparency and "partial" opaqueness settings generate systematic patterns in order flow. With transparency, the probability of observing a CN order at the same side of the market is smaller after such an order than if it was not. Buy (sell) orders at a CN are also less likely to attract subsequent sell (buy) orders at the DM.JEL Codes: G10, G20

Since the financial crisis of 2008, next to banks, insurers have received increasing attention from researchers and regulators because of their crucial role in the financial system. A key point for a stable insurer is its capital structure, i.e. the choice between equity, debt and provisions in financing its operations. Based on earlier work a quickly developing literature has directly applied capital structure theories (in particular trade-off and pecking order) from corporate finance to insurers' financing choices. Corporate finance concepts used herein however, are developed for industrial firms. In this paper we provide an overview of the literature on the capital structure of insurers, but contribute by systematically clarifying how to account for the specificities of insurers when transferring the trade-off and pecking-order logic from an industrial to an insurer context. This way, we add several new insights on an insurer's choice between equity, financial debt and provisions. In particular, we are able to explain why, as compared to industrial firms, insurers use less financial debt, and why insurers focus so strongly on self-financing. Finally, we identify multiple avenues for future research.

We present a dynamic microstructure model where a dealer market (DM) and a crossing network (CN) interact. Sequentially arriving traders with different valuations for an asset maximise their profits either by trading on a DM or by submitting an order for (possibly) uncertain execution via a CN. We develop the analysis for three different informational settings: transparency, "complete" opaqueness of all order flow, and "partial" opaqueness (with observable DM trades). A key result is that the interaction of trading systems generates systematic patterns in order flow for the transparency and partial opaqueness settings. The precise nature of these patterns depends on the degree of transparency at the CN. While unambiguous with a transparent CN, they may reverse direction if the CN is opaque. Moreover, in all three informational settings, we find that a CN and a DM cater for different types of traders. Investors with a high willingness to trade are more likely to prefer a DM. The introduction of a CN next to a DM also affects welfare as it increases total order flow by attracting traders who would otherwise not submit orders ("order creation"); in addition, it diverts trade from the DM ("trade diversion"). We find that the coexistence of a CN and DM produces more trader welfare than a DM in isolation. Also, more transparent markets lead to greater trader welfare but may reduce overall welfare.