Experimental evidence on coverage choices and contract prices in the market for corporate insurance

In this paper, we present experimental evidence on the effect adverse selection has on coverage choices and pricing in corporate insurance markets. Two sets of experimental data, each generated by experiments utilizing a specific parameterization of a corporate insurance decision, are presented to gauge these effects. In the first, subject behavior conforms to a unique equilibrium in which high risk firms choose higher coverage and contracts are priced accordingly. Insurers act competitively and convergence to equilibrium behavior is marked. In the second set, there is little evidence that subject behavior is consistent with either of the two equilibrium outcomes supported by the experimental setting—pooling by fully insuring losses and pooling by self insuring. JEL Classification C90, G14, G22 Electronic Supplementary Material Supplementary material is available in the online version of this article at http://dx.doi.org/10.1007/s10683-006-9152-y.     

Impact of MiFID II tick-size regime on equity markets—Evidence from the LSE

This study investigates the impact of MiFID II on the London Stock Exchange. We find that a tick-size reduction leads to lower bid–ask spreads, lower trade values, reduced cost of trading at and beyond the best bid-offer, an acceleration of quote updates, an increase in aggressive trades and a reduction in price impact. Increased tick size widens spreads and increases trading costs. Step functions reveal that liquidity adjusts opposite to the tick change. To determine if impacts are proportional, we identify potential functions that predict cost changes with tick updates, implying that traders adjust their trade sizes according to the new tick levels.     

Loss ratio dynamics

Many studies of the insurance profit cycle use industry-level annual data and focus on the existence of an AR(2) process. We take a different approach by adopting the idea of possible hard and soft markets, but they are not necessarily cyclical in the classic sense. In addition to aggregated data, we use quarterly firm-level data to examine loss ratio behavior over time. This approach allows one to assess the firm-level heterogeneity in the insurance market. We further use a Markov switching model to assess the heterogeneity of response to economic variables. Using a K-means cluster approach, we examine the different clusters of firms and their different behavior over 2001q1−2020q4.