Contributions published at Department of Banking and Finance (Pablo Koch Medina)

"Zombie lending" remains a widespread practice by banks around the world. In this paper, we exploit a series of large-scale on-site inspections made on the credit portfolios of several Portuguese banks to investigate how these inspections affect banks’ future lending decisions. We find that an inspected bank becomes 20% less likely to refinance zombie firms, immediately spurring their default. Overall, banks seemingly reduce zombie lending because the incentives to hold these loans disappear once they are forced to recognize losses.

In this thesis, the impact of recent armed conflicts on worldwide stock market indices is examined. The aim is to provide additional support to the findings of Schneider and Troeger (2006). This study focuses on two current conflicts, the Russian-Ukraine conflict and the ChinaTaiwan conflict. Using a one-year rolling GARCH(1,1) model, the reactions of 14 stock market indices to key events in these conflicts are analyzed. The findings indicate that conflict-related news tends to frequently impact North American markets, with European markets showing strong reactions to the developments of the Russia-Ukraine conflict. Asian markets appear to be less sensitive to geopolitical signals. While international stock markets are generally adversely affected by conflict situations, certain industry indices manage to thrive. Overall, the findings of this thesis support the idea of rational expectations in recent armed conflicts.

In this thesis, we examine 25 zero-investment long-short strategies derived from factors constructed using price, market capitalization, and trading volume of cryptocurrency assets to identify significant alpha generation. We employ various parsimonious factor models, incorporating market return, size, momentum, and market cycle to explain the observed alphas. Our findings reveal that a model encompassing all four factors can account for six out of the seven significant strategies. Additionally, we utilize a Fama-MacBeth Regression to demonstrate that the risk premia associated with market, size, and momentum exposures are not only significant over time but also exhibit greater strength and volatility during bullish market cycles.

Inspired by the celebrated Joint SPX & VIX Calibration problem, this study delves into the technical derivation of two prominent rough stochastic volatility models from the ground up, with the aim of consolidating and extending previous empirical findings as well as shining a new light on critical details that might have gone unnoticed. A systematic analysis of the latest Deep Learning interpretations of the rough Bergomi and rough Heston models reveals a series of eloquent properties with regards to stylised facts observed in SPX and VIX volatility time series.

In 2021 more than half of U.S. IPOs were SPACs, and more than a third of the companies that went public had chosen a de-SPAC transaction over a traditional IPO. However, the hot Wall Street trend ended soon after its emergence. Investors burnt their fingers, and sponsors walked away with huge profits. The SEC intervened with restrictive regulatory scrutiny to protect the investors. However, increasing the liability, improving disclosure, and ultimately enhancing the SPAC’s structure will not eliminate the risk of SPACs as an investment vehicle.

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Various studies have shown that being on top of an alphabetical listing provides an advantage. Very little research has been done on the implications of this alphabetic bias in financial markets. This master’s thesis explores whether a better alphabetical ranking is associated with greater trading activity and liquidity. Contrary to findings for the US stock market, stocks that appear early on an alphabetically ordered list do not experience higher turnover or liquidity than stocks positioned later on the list in the Swiss stock market. All robustness tests provide support for this finding. The Swiss stock universe seems too small for the alphabetic bias to manifest. Keywords: behavioral finance, alphabetic bias, trading activity, liquidity.

This thesis aims to determine the influence of energy and fertilizer prices on the food basket components within the Swiss consumer price index (CPI). The study builds upon official data released by the World Bank, the administration of Switzerland, and the Food and Agriculture Organization of the United Nations. A Vector Autoregressive Model determines the influence of energy and fertilizer prices and forecasts resulting values. The study’s primary focus is whether a vector autoregressive model can quantify external shocks in the main variables of interest and their effects on the Swiss economy. The analysis finds that energy and fertilizer prices neither Granger cause Swiss food prices’ CPI level nor add benefit to a VAR model presented by the Swiss National Bank to predict Swiss inflation.

Is deficit finance, explicit or implicit, free when borrowing rates are routinely lower than growth rates? Specifically, can the government make all generations better off by perpetually taking from the young and giving to the old? We study this question in simple closed and open economies and show that achieving Pareto gains requires implausible calibrations. Even then, the gains reflect, depending on the economy's openness, improved intergenerational risk-sharing, improved international risk-sharing, and beggaring thy neighbor – not intergenerational redistribution per se. Low government borrowing rates, including borrowing rates running far below growth rates, justify improved risk-sharing between generations and countries. They provide no convincing basis for using deficit finance to redistribute from young and future generations or other countries.

This paper is an interview with a Large Language Model (LLM), namely GPT-3, on the issues of climate change. The interview should give some insights into the current capabilities of these large models which are deep neural networks with generally more than 100 billion parameters. In particular, it shows how eloquent and convincing the answers of such LLMs can be. However, it should be noted that LLMs can suffer from hallucination and their responses may not be grounded on facts. These deficiencies offer an interesting avenue for future research.

A multivariate normal mean-variance heterogeneous tails mixture distribution is proposed for the joint distribution of financial factors and asset returns (referred to as Factor-HGH). The proposed latent variable model incorporates a Cholesky decomposition of the dispersion matrix to ensure a rich dependency structure for capturing the stylized facts of the data. It generalizes several existing model structures, with or without financial factors. It is further applicable in large dimensions due to a fast ECME estimation algorithm of all the model parameters. The advantages of modelling financial factors and asset returns jointly under non-Gaussian errors are illustrated in an empirical comparison study between the proposed Factor-HGH model and classical financial factor models. While the results for the Fama-French 49 industry portfolios are in line with Gaussian-based models, in the case of highly tail heterogeneous cryptocurrencies, the portfolio based on the Factor HGH model doubles the average return while keeping the volatility, the maximum drawdown, the turnover, and the expected-shortfall at a low level.

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Using administrative data on deposits and loans of every Norwegian resident with any Norwegian bank, we show that an existing deposit account makes a household more likely to hold deposits at the same bank later despite better alternatives and more likely to borrow there. Cross-selling potential varies by household and banks pay higher deposit rates to those more likely to become borrowers. Then they charge depositors higher risk-adjusted loan rates than new clients, suggesting that cross-selling is driven by demand rather than supply. Discounting future cross selling profits motivates lower deposit spreads in times of lower policy rates, transmitting monetary policy.

Shortseller haben unter Firmenlenkern oft keinen sehr guten Ruf - und auch viele Anleger dürften ihnen gegenüber eher negativ eingestellt sein. Denn die Leerverkäufer verdienen ihr Geld mit der Wette auf fallende Aktienkurse und sorgen mitunter selbst dafür, dass sich der Anteilsschein eines Unternehmens in die gewünschte Richtung bewegt. Doch laut Experten erfüllen sie mit ihrem Vorgehen eine wichtige Funktion am Markt.

We assess how investors’ willingness-to-pay (WTP) for sustainable investments responds to the social impact of those investments, using a framed field experiment. While investors have a substantial WTP for sustainable investments, they do not pay significantly more for more impact. This also holds for dedicated impact investors. When investors compare several sustainable investments, their WTP responds to relative, but not to absolute, levels of impact. Regardless of investments’ impact, investors experience positive emotions when choosing sustainable investments. Our findings suggest that the WTP for sustainable investments is primarily driven by an emotional, rather than a calculative, valuation of impact.

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Professeur de finances mathématiques à l’Université de Zurich et auteur du livre «La crise permanente», l’économiste Marc Chesney ne fait pas vraiment confiance aux banques systémiques. La faute, selon lui, à la Finma, à la BNS et à la majorité de l’élite politique qui, après l’effondrement d’UBS en 2008, ont pudiquement fermé les yeux sur les dérives des grandes banques.

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