Contributions in Merlin

This chapter combines recent findings from the empirical banking literature with established insights from studies of banking competition and regulation. It starts with a concise overview and assessment of the different methodological approaches taken to address banking competition. While market structure indicators are readily available, they may not be overly informative about the competitive conditions in banking markets. The literature has focused to date on “non-market structure” indicators such as the Panzar-Rosse H-statistic, the Lerner index, and the Boone indicator. The chapter then structures a discussion on the empirical findings based upon a framework that finds its roots in the different theories of financial intermediation. Many other specific approaches to infer banking competition are discussed, in particular, the impact that regulation and information-sharing between banks may have on banking competition.

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We use a model with agency frictions to analyze the structure of a dealer market that faces competition from a crossing network. Traders are privately informed about their types (e.g. their portfolios), which is something the dealer must take into account when engaging his counterparties. Instead of participating in the dealer market, the traders may take their business to a crossing network. The dealer must take into consideration that traders have this alternative when choosing a pricing schedule. We show that the presence of a crossing network may benefit traders even if they do not trade in it. Furthermore, it results in more traders being serviced by the dealer and the book’s spread shrinking (under certain conditions). We allow for the pricing on the dealer market to determine the structure of the crossing network, which itself influences the structure of the dealer market. This results in a feedback look that, under the same conditions that lead to a reduction of the spread, yields an equilibrium book/crossing network pair.

Investor behavior was shown to be considerably different when the risk-return tradeoff is presented by experience sampling as opposed to a descriptive communication. We analyze the persistency of this difference in a setting in which investors are faced with multiple decisions over time and are consequently able to adjust the risk level they initially chose. For this we use an experimental setting with repeated investment decisions over multiple trading days, and we also test a new form of risk simulation in which wealth paths over time are presented rather than just final outcomes. After investors’ initial decisions, for which we confirm previous findings, we do not find persistent differences of simulation-based learning on investors’ risk-taking behavior. With regards to trading volume, only a simulation in which investors see wealth paths and not only final outcomes leads to lower trading frequency soon after the initial asset allocation.

In 2002, Switzerland began to adopt free movement of workers with the European Union. We study the effects of the resulting immigration wave on resident workers. We focus on the level of national skill groups and propose an Instrumental Variable approach to address the endogeneity of immigration in this setting. Mostly relying on administrative data on the 2002–2011 period, we find that immigration of foreign workers reduced unemployment of residents and had limited adverse effects on their wages and employment. One reason is that younger residents changed to more demanding jobs as a response to the arrival of immigrants.

We investigate the geographical proximity of firms to their relationship banks. We find that Islamic banks are more remote to their borrowers. We also find that the probability for a firm to connect to a bank substantially decreases in distance, but that the choice along bank characteristics determines how potent distance is in its impact. If the bank in the vicinity is an Islamic bank, distance plays a more muted role, especially in cities with a high conservative party vote and higher trust in religious institutions. Overall, these findings suggest that the presence of banks with certain characteristics in the vicinity may determine the within-firm and across-firm configurations of observable firm-bank connections.

We successfully show that it is possible to optimize both for risk and for asset allocation without compromising the optimization of individual goals by introducing the novel concept of a compensation portfolio. Therefore, we solve for the global vs. local optimization paradox by bridging Modern Portfolio Theory (MPT) and Behavioral Portfolio Theory (BPT).

We investigate if corruption impedes firm growth through limiting access to bank credit. Our estimates demonstrate that access to credit tightens when a firm is more frequently involved in bribery practices, and that bribery (most likely) causes this loss of access. We also find that the detrimental impact is mainly driven by supply-side rather than by demand-side factors, and that the loss of access is particularly strong when there are fewer foreign banks in the vicinity of the firm or if competition is either very low or very high in the local banking market. Finally, the bribery-driven increase in financing obstacle significantly impedes future firm growth.

The concept of second-order risk operationalizes the estimation risk in portfolio construction induced by model uncertainty. We study its contribution to the realized volatility of recently developed risk parity strategies. For each strategy, we derive closed-form solutions for the second-order risk, subsequently illustrated in empirical analysis based on real market data. The results suggest a relation between the contribution of second-order risk and the sensitivity of a portfolio to single eigenvectors of the covariance matrix of assets' returns. Among the strategies considered, we find the principal risk parity strategy, that invests equally in each eigenvector underlying the variance-covariance matrix, to be immune to second-order risk. For the other strategies, second-order risk can be partially mitigated by means of statistical methods.

We assess the effect of securitization activity on relative credit quality employing a uniquely detailed dataset from the euro-denominated syndicated loan market. We find that at issuance, based on observable characteristics, banks do not seem to select and securitize loans of lower credit quality. Following securitization, the credit quality of borrowers whose loans are securitized deteriorates more than those in the control group. We find that poorer performance by borrowers of securitized loans seems to be connected to banks’ reduced monitoring incentives. Our results are supported by two additional methodologies and robust to controlling for predetermined borrower-lender matching.