Technical traders attempt to exploit trends in market prices and the order flow. Despite this little is known about how these traders behave in a micro-structure context. We consider a model of an order book based financial market. The market contains two groups: informed traders and technical traders. A numerical technique is used to identify a Markov perfect equilibrium of the trading game and so determine the optimal strategies. We find that technical trading rules are profitable and allow traders to increase their returns. The effect of technical traders on the market, however, is ambiguous. They decrease volatility and pricing errors but also increase trading costs despite primarily acting as liquidity suppliers.

We assess systemic risk in the U.S. banking system before and after the Panic of 1873, using a combination of linear programming and computational optimization to estimate the interbank network. We impose liquidity shocks resembling those of 1873, and find the network captures the distribution of interbank deposits a year later. The network predicts banks likely to panic in the crisis, and those banks see their balance sheets weaken in the year after the crisis more than others. The results shed light on the nature and regional pattern of withdrawals in a classic 19th-century U.S. financial crisis.

[First paragraph] The worldwide financial crisis (WFC) of 2007-09 has shown the importance of cross-sectional dependencies of assets, credit exposures and volatility, which can threaten domestic and global financial stability through cascades in financial networks. A correct assessment of company-specific risk has to account for the potential risk spillover effects from other firms (Hautsch et al. 2014). This is because of the intertwined nature of financial markets, which allow the spread of risk throughout the system (Acemoglu et al., 2015). The potential impact of interconnected financial institutions on the entire financial system has been a financial stability concern for central banks and regulators. The need for economic foundations for a systemic risk measure is more than an academic concern since it involves regulators, supervisory authorities and policy-makers (Acharya et al. 2017). This special issue provides a substantial contribution to the systemic risk literature.