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

To date, most attempts at modelling implied volatility rely on a priori assumptions about its dynamics. Machine learning methods, however, are not constrained to a pre-determined functional form. In this paper, machine learning methods are employed to forecast changes in the implied volatility of options written on S&P 500 futures. These models outperform naive predictions assessed on both standardised volatility surfaces and market quoted options, obtaining comparable performance with a benchmark deterministic model. The XGBoost model shows particularly promising results when incorporated into a minimum variance hedging strategy. In addition, the paper presents a robust adaption of the anchored eSSVI volatility surface parameterisation.

This thesis proposes an modified Dividend Growth Model by Balschun and Schindler as an alternative to the standard Dividend Growth Model, also known as Gordon Growth Model by Gordon (1962). The modified Dividend Growth model uses a linear instead of an exponential growth rate. The model was not able to find significant alpha generation in the European stock market.

Diese Arbeit prüft die Anwendung des modifizierten Dividendenwachstumsmodells nach Balschun und Schindler (2015) zur Portfoliokonstruktion innerhalb nordischer Aktienmärkte. Dabei werden die Portfolios auf risikobereinigte Überschussrenditen untersucht, um den Nutzen des neuartigen Modells für das Portfoliomanagement zu analysieren. Das Modell unterscheidet sich durch die zugrundeliegende lineare Wachstumsannahme von dem traditionellen Dividendenwachstumsmodell (Gordon Growth Model). Die Ergebnisse zeigen, dass die Portfolios des modifizierten Dividendenwachstumsmodells, nach Abzug berechneter Transaktionskosten, über 14% annualisierte Alphas erzielen können. Auch bei einem Anstieg der Transaktionskosten oder der Portfoliogrösse bleiben die beobachteten Ergebnisse robust, jedoch zeigen sich signifikante Veränderungen bei einem abweichendem Stichprobenzeitraum oder einer Anpassung von Variablenmassen.

Die Praxis der Unternehmensbewertung umfasst viele Anlässe und dementsprechend existieren eine Vielzahl von Methoden und Theorien, die in diesem Bereich Anwendung finden. Doch welche dieser Verfahren werden in der Schweizer Wirtschaft tatsächlich angewendet und was sind die Herausforderungen? Ziel dieser Arbeit ist es, einen Blick auf die praktische Anwendung der Unternehmensbewertung zu werfen und die verwendeten Bewertungsmethoden zu analysieren. Um dieses Ziel zu erreichen, wurden Fairness Opinions der letzten 15 Jahre in der Schweiz analysiert. Zusätzlich wurden drei Experteninterviews durchgeführt, um Einblicke in die Herausforderungen der praktischen Umsetzung zu erhalten.

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Die vorliegende Bachelorarbeit untersuchte die Aussagekraft des UBS Swiss Real Estate Bubble Index als Indikator für Schweizer Wohneigentumspreise, welche mittels eines Backtests überprüft wurde. Die daraus folgende Fragestellung lautete: «Ist der Real Estate Bubble Index der UBS indikativ für Schweizer Wohneigentumspreise?». Der UBS Swiss Real Estate Bubble Index stellt einen wichtigen Referenzwert für Immobilienmarktteilnehmer zur Messung von Risiken dar und wird zur Einschätzung eines potenziellen Überbewertungs- sowie Blasen- risikos auf dem schweizerischen Wohneigentumsmarkt verwendet. Der Bubble Index wird quartalsweise von der UBS herausgegeben und besteht aus sechs gleich- gewichteten Subindizes, welche sich aus makro- ökonomischen, wohneigentumsmarkt- und finanzierungs- bezogenen Daten zusammensetzen. Die Standardab- weichungen des historischen Mittelwertes der gleich- gewichteten Subindizes bilden die Werte des UBS Swiss Real Estate Bubble Index. Bei einer stark positiven Abweichung der Subindikatoren vom historischen Mittel können die Preise als überbewertet betrachtet werden. Dabei versucht der Index mit den Subindizes den fundamentalen, verhaltensbezogenen sowie charttechnischen Aspekt der Blasenidentifizierung zu verbinden (Holzhey, 2013). Verschiedene Studien beschäftigten sich bereits mit Analysen, welche potenzielle indikative Faktoren für Schweizer Wohneigentumspreise identifizieren sollten. Dabei stehen vor allem demografische und ökonomische Faktoren im Zentrum. Die vorliegende Arbeit stellt sich die Aufgabe, ob und wie sich die Veränderungen des Index auf schweizerische Wohneigentumspreise auswirkte. In einem effizienten Markt würden rationale Marktakteure auf Veränderungen von Überbewertungs- oder Unterbewertungseinschätzungen des Index reagieren, indem sie Kauf- oder Verkaufs- entscheidungen treffen, die zu einer Anpassung der Preise führen. Diese Anpassungen sollten dazu führen, dass sich die Preise ihrem fundamentalen Wert angleichen (Wienkamp, 2019).

This study explores the concept of breakeven volatility (BEV) as an unbiased estimator of an option’s fair implied volatility and its applicability in option pricing. Historical BEVs are computed for 230,000 S&P 500 index option contracts, and a predictive model is built to produce contemporaneous estimates. The model is compared to a similar implementation based on implied volatility instead of BEV, by testing both models’ pricing ability in an out-of-sample trading environment. The findings consistently demonstrate that the BEV model outperforms the implied volatility model, illustrating the unique value of using BEV as a measure of an option’s fair volatility level to price options. This research contributes to the limited literature on empirical option pricing using BEV, emphasizing its potential as a tool for accurate option pricing. Keywords: breakeven volatility, implied volatility, option pricing, SPX index options

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This study investigates the relationship between Environmental, Social, and Governance (ESG) practices and Outward Foreign Direct Investment (OFDI) in China. Utilizing a comprehensive dataset, the paper explores the conducive effect of ESG practices on OFDI deals, highlighting that firms with higher ESG scores are more likely to engage in OFDI activities. The analysis also reveals that the negative impact of COVID-19 on OFDI and private companies are more inclined to participate in OFDI compared to state-owned enterprises. The study’s findings contribute to the understanding of the interplay between responsible investment, ESG factors, and FDI, offering insights into the Chinese market.

Volatility in equity markets, in particular its excess over the volatility derived from changes in a company’s fundamentals, is a phenomenon that has plagued markets since their inception. In this study we investigate the influence of news sentiment on volatility in equity markets in an attempt to decipher whether this may be the driver of excess volatility. This is achieved by aggregating and then manipulating news sentiment scores from the TRNA dataset into various different formats regressed against volatility data at an index level, across a variety of geographical locations. What we find is that news sentiment is indeed an explanatory variable of volatility. Nevertheless, there remains a significant gap in explaining the rest of the dynamics of volatility. We attempt to fill said gap by developing a multivariate model which additionally includes volume and an auto-regressive element. This model performs significantly better and lends itself to the creation of a successful trading strategy.

I conduct a longitude study of the carry trade with 2008 as the cutting point. Employing a sample with 17 currencies and over 30 years since 1993, I find that the basic carry trade strategy with G10 currencies does underperform after 2008 relative to itself before 2008 and relative to the market. I demonstrate that refined carry strategies including basic carry with an extended currency basket, carry momentum, and volatility-adjusted carry can avoid this downturn. I observe that overall traditional risk factors fail to explain the excess return of the carry trade. However, I show that during certain periods more significance can be observed, and higher returns are associated with a lower and more negative correlation with the market. Keywords: Carry, Momentum, Investment Strategy, Factor Model

This thesis compares GARCH models, Stochastic Volatility (SV) models, and Markov-switching GARCH (MSGARCH) models in terms of forecasting one-day-ahead Value-at-Risk (VaR) for industrial metals futures. GARCH and MSGARCH models are estimated with three innovation distributions: normal, student-t, and generalized error distributions (GED). For in-sample analysis, we implement these models to compare the Akaike information criterion (AIC) as well as their in-sample conditional volatility. Out-of-sample VaR forecasting performance is evaluated based on conditional coverage test. The results show MSGARCH models outperform the other models in predicting a one-day-ahead VaR for both long and short trading positions.

Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models have gained considerable attention since the contributions of Engle (1982) and Bollerslev (1986). These pioneers showed the time-varying volatility in financial asset returns. Building upon this, Duan (1995) further expanded the applicability of GARCH models by elucidating the framework and conditions necessary for integrating them into option pricing. In 2000, the well-know affine GARCH model (HN-GARCH), which was elaborated by S. L. Heston and Nandi (2000), brought an innovation by introducing closedform option pricing formulas, while capturing several stylized fact such as the price of risk, leverage effect (Black (1976) and Christie (1982)), news effect (Campbell and Hentschel (1992) and Bekaert and G. Wu (2000)), and time-varying conditional variances as expressed by a discrete-time GARCHtype process. As a consequence, many extensions have been emerged, which are called the affine GARCH family of models. Some examples : the GARCH(p,q) of Bollerslev (1986), the aysmmetric GARCH of Engle and Ng (1993) and the threshold GARCH of Glosten et al. (1993); for the empirical application into option pricing see Christoffersen, Jacobs, and Ornthanalai (2013); for comparisons between affine and non-affine GARCH models, see Hsieh and Ritchken (2006), Christoffersen, Jacobs, and Mimouni (2006) and Christoffersen, Dorion, et al. (2010). These affine GARCH extensions incorporate non-Gaussianity by Gaussian innovations (Christoffersen, Steve Heston, et al., 2006) or Levy jumps (Ornthanalai, 2014); and multivariate extensions which allows fast and accurate pricing of multi-asset options see Escobar-Anel, Rastegari, et al. (2020). Recently, the literature indicate the importance to include the stochastic jump into the stochastic volatility structure (see Chernov et al. (2003), Eraker et al. (2003), Eraker (2004) and Todorov and Tauchen (2011)) but is missing in GARCH models except for the model proposed by Chan and J. Maheu (2002) and J. M. Maheu and McCurdy (2004). The multivariate model combining GARCH and Stochastic Volatility by introducing a latent component is proposed by Paolella and Polak (2015) : A common market factor non-Gaussian returns model (COMFORT).

This paper examines the effectiveness of environmental, social, and governance (ESG) momentum in trading Brazilian securities. It tests several trading strategies employ ing both top-decile and time-series momentum, including long-only, long-short, and reverse strategies, which invest in stocks with low ESG momentum. Brazilian results are then compared with those in Chinese, Indian, and South African markets, with overperformance seen in the Brazilian and South African markets and underperformance in Chinese and Indian markets. These results of this paper highlight the complex relationship between ESG momentum and stock returns, contributing insights to the ongoing debate on ESG investing efficacy.

This study investigates the relationship between the motive of greed and various asset market indicators, such as trading activity and bubble formation (i.e., mispricing, overpricing, and price amplitude). We ran experimental asset markets that allowed us to measure individuals’ greed in order to create markets populated with greedy individuals and markets with non-greedy individuals. Regarding trading activity, we found that greedier individuals had higher trading activity on the individual level but not on the market level. On the market level, high-greed markets exhibited less frequent and smaller price bubbles than markets with less greedy traders. If our findings translate to actual markets, greed itself might not contribute to asset market bubbles.

Non-convexities and discrete choices have become important modeling tools in modern macroeconomics. Unfortunately, the existence of competitive equilibria in the presence of such non-convexities is not always ensured, and most results on the existence of equilibrium that can be found in the literature do not directly apply to models used in applications. In this paper, we explain the three main difficulties one encounters when proving the existence and give simple sufficient conditions for the existence of competitive equilibria in stochastic OLG models with non-convex budget sets. We also give sufficient conditions for the existence of approximate equilibria that are recursive in the natural state.

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Using all loans granted to firms recorded in the Italian credit register, we estimate correlations between risk-transfer and default probabilities to gauge the severity of informational asymmetries in the loan securitization market. First, the analysis confirms the presence of information frictions in the SME loan securitisation market. Second, the unconditional quality of securitized loans remains significantly better than that of non-securitized ones, in line with the notion that markets anticipate the presence of information frictions and lead to a selection of loans which offsets the detrimental effects of asymmetric information. Third, using data for firms that maintain multiple bank relationships, we obtain indications of the relative importance played by two forms of information friction, adverse selection and moral hazard. While the former is widespread, the latter is present in weak relationships only, in line with the notion that such loans are characterised by a limited commitment to exert costly monitoring by the bank.

Investors in equities tend to follow well-defined investment strategies based on characteristics such as market capitalization and dividend yield or factors such as size, value, momentum and quality which capture the cross-section of asset returns. In this paper, we explore the interaction of such investment strategies in a demand-driven framework. The aim is to quantify the impact of a reallocation of capital between strategies on the cross-section of their performance. The main finding is that self- and cross-impact caused by the reallocation of capital can explain capacity of strategies, correlation of returns and the cyclical nature of investment strategies’ risk premia.

Minimizing the adverse social and economic consequences of the energy transition is an important social aspiration. It is the essence of the “just transition,” the connective tissue that binds together climate goals with social outcomes centered around jobs. This policy note proposes the first iteration of a just transition policy framework built around three interrelated and mutually reinforcing pillars. These include: (i) a system for determining a hierarchy of priorities for activities, sectors, or groups that are to be compensated for the negative impacts they suffer from the transition to a low-carbon economy or supported because they contribute directly to a more equitable sharing of the costs and opportunities from the transition; (ii) a fiscal transfer mechanism to allocate public funds consistent with these priorities; and (iii) financial flows enablers, a set of instruments or policy interventions to facilitate private financial flows to activities or projects that are deemed to contribute to a more just transition. The assessment provides seven key takeaways for consideration by competent authorities to strengthen further the EU just transition policy framework going forward. These are: (i) narrowing the scope of the framework by focusing on social support and/or land restoration, while encouraging private sector funding for economic revitalization projects; (ii) enhancing data collection on social impact assessment to better understand the negative effects of climate transition initiatives and prevent "social washing"; (iii) embedding just transition considerations in sustainability regulations by including relevant indicators and metrics; (iv) providing guidance on assessing just transition-related risks for financial firms in prioritized regions and sectors; (v) clarifying supervisory expectations for financial firms regarding just transition-related litigation and liability risk; (vi) encouraging the development of financial instruments for the just transition; and (vii) maximizing the role of multilateral development banks in de-risking just transition projects, especially in member countries with limited resources and capacity.