Correlation Scenarios and Correlation Stress Testing
Natalie Packham, Fabian Wöbbeking
Journal of Economic Behavior and Organization,
January
2023
Abstract
We develop a general approach for stress testing correlations of financial asset portfolios. The correlation matrix of asset returns is specified in a parametric form, where correlations are represented as a function of risk factors, such as country and industry factors. A sparse factor structure linking assets and risk factors is built using Bayesian variable selection methods. Regular calibration yields a joint distribution of economically meaningful stress scenarios of the factors. As such, the method also lends itself as a reverse stress testing framework: using the Mahalanobis distance or Highest Density Regions (HDR) on the joint risk factor distribution allows to infer worst-case correlation scenarios. We give examples of stress tests on a large portfolio of European and North American stocks.
Artikel Lesen
Corporate Governance Benefits of Mutual Fund Cooperation
Rex Wang Renji, Patrick Verwijmeren, Shuo Xia
IWH Discussion Papers,
Nr. 21,
2022
Abstract
Mutual fund families increasingly hold bonds and stocks from the same firm. We study the implications of such dual holdings for corporate governance and firm decision-making. We present evidence that dual ownership allows financially distressed firms to increase investments and to refinance by issuing bonds with lower yields and fewer restrictive covenants. As such, dual ownership reduces shareholder-creditor conflicts, especially when families encourage cooperation among their managers. Overall, our results suggest that mutual fund families internalize the shareholder-creditor agency conflicts of their portfolio companies, highlighting the positive governance externalities of intra-family cooperation.
Artikel Lesen
Identifying Rent-sharing Using Firms' Energy Input Mix
Matthias Mertens, Steffen Müller, Georg Neuschäffer
IWH Discussion Papers,
Nr. 19,
2022
Abstract
We present causal evidence on the rent-sharing elasticity of German manufacturing firms. We develop a new firm-level Bartik instrument for firm rents that combines the firms‘ predetermined energy input mix with national energy carrier price changes. Reduced-form evidence shows that higher energy prices depress wages. Instrumental variable estimation yields a rent-sharing elasticity of approximately 0.20. Rent-sharing induced by energy price variation is asymmetric and driven by energy price increases, implying that workers do not benefit from energy price reductions but are harmed by price increases. The rent-sharing elasticity is substantially larger in small (0.26) than in large (0.17) firms.
Artikel Lesen
On the Employment Consequences of Automation and Offshoring: A Labor Market Sorting View
Ester Faia, Sébastien Laffitte, Maximilian Mayer, Gianmarco Ottaviano
Lili Yan Ing, Gene M. Grossman (eds), Robots and AI: A New Economic Era. Routledge: London,
2022
Abstract
We argue that automation may make workers and firms more selective in matching their specialized skills and tasks. We call this phenomenon “core-biased technological change”, and wonder whether something similar could be relevant also for offshoring. Looking for evidence in occupational data for European industries, we find that automation increases workers’ and firms’ selectivity as captured by longer unemployment duration, less skill-task mismatch, and more concentration of specialized knowledge in specific tasks. This does not happen in the case of offshoring, though offshoring reinforces the effects of automation. We show that a labor market model with two-sided heterogeneity and search frictions can rationalize these empirical findings if automation strengthens while offshoring weakens the assortativity between workers’ skills and firms’ tasks in the production process, and automation and offshoring complement each other. Under these conditions, automation decreases employment and increases wage inequality whereas offshoring has opposite effects.
Artikel Lesen
Political Ties and Raising Capital in Global Markets: Evidence from Yankee Bonds
Gene Ambrocio, Xian Gu, Iftekhar Hasan
Journal of Corporate Finance,
June
2022
Abstract
This paper examines whether state-to-state political ties help firms obtain better terms when raising funds in global capital markets. Focusing on the Yankee bonds market, we find that issuances by firms from countries with close political ties with the US feature lower yield spreads, higher issuance amounts, and longer maturities. Such an association is more pronounced for firms located in low income and highly indebted countries as well as firms in government-related industries, first-time issuers, and relatively smaller firms. Our study provides evidence supporting the notion that country-level political relationship is an important factor when raising capital in international markets.
Artikel Lesen
The Impact of Active Aggregate Demand on Utilisation-adjusted TFP
Konstantin Gantert
IWH Discussion Papers,
Nr. 9,
2022
Abstract
Non-clearing goods markets are an important driver of capacity utilisation and total factor productivity (TFP). The trade-off between goods prices and household search effort is central to goods market matching and therefore drives TFP over the business cycle. In this paper, I develop a New-Keynesian DSGE model with capital utilisation, worker effort, and expand it with goods market search-and-matching (SaM) to model non-clearing goods markets. I conduct a horse-race between the different capacity utilisation channels using Bayesian estimation and capacity utilisation survey data. Models that include goods market SaM improve the data fit, while the capital utilisation and worker effort channels are rendered less important compared to the literature. It follows that TFP fluctuations increase for demand and goods market mismatch shocks, while they decrease for technology shocks. This pattern increases as goods market frictions increase and as prices become stickier. The paper shows the importance of non-clearing goods markets in explaining the difference between technology and TFP over the business cycle.
Artikel Lesen
The Effects of Sovereign Risk: A High Frequency Identification Based on News Ticker Data
Ruben Staffa
IWH Discussion Papers,
Nr. 8,
2022
Abstract
This paper uses novel news ticker data to evaluate the effect of sovereign risk on economic and financial outcomes. The use of intraday news enables me to derive policy events and respective timestamps that potentially alter investors’ beliefs about a sovereign’s willingness to service its debt and thereby sovereign risk. Following the high frequency identification literature, in the tradition of Kuttner (2001) and Guerkaynak et al. (2005), associated variation in sovereign risk is then obtained by capturing bond price movements within narrowly defined time windows around the event time. I conduct the outlined identification for Italy since its large bond market and its frequent coverage in the news render it a suitable candidate country. Using the identified shocks in an instrumental variable local projection setting yields a strong instrument and robust results in line with theoretical predictions. I document a dampening effect of sovereign risk on output. Also, borrowing costs for the private sector increase and inflation rises in response to higher sovereign risk.
Artikel Lesen
Cryptocurrency Volatility Markets
Fabian Wöbbeking
Digital Finance,
Nr. 3,
2021
Abstract
By computing a volatility index (CVX) from cryptocurrency option prices, we analyze this market’s expectation of future volatility. Our method addresses the challenging liquidity environment of this young asset class and allows us to extract stable market implied volatilities. Two alternative methods are considered to compute volatilities from granular intra-day cryptocurrency options data, which spans over the COVID-19 pandemic period. CVX data therefore capture ‘normal’ market dynamics as well as distress and recovery periods. The methods yield two cointegrated index series, where the corresponding error correction model can be used as an indicator for market implied tail-risk. Comparing our CVX to existing volatility benchmarks for traditional asset classes, such as VIX (equity) or GVX (gold), confirms that cryptocurrency volatility dynamics are often disconnected from traditional markets, yet, share common shocks.
Artikel Lesen
A Comparison of Monthly Global Indicators for Forecasting Growth
Christiane Baumeister, Pierre Guérin
International Journal of Forecasting,
Nr. 3,
2021
Abstract
This paper evaluates the predictive content of a set of alternative monthly indicators of global economic activity for nowcasting and forecasting quarterly world real GDP growth using mixed-frequency models. It shows that a recently proposed indicator that covers multiple dimensions of the global economy consistently produces substantial improvements in forecasting accuracy, while other monthly measures have more mixed success. Specifically, the best-performing model yields impressive gains with MSPE reductions of up to 34% at short horizons and up to 13% at long horizons relative to an autoregressive benchmark. The global economic conditions indicator also contains valuable information for assessing the current and future state of the economy for a set of individual countries and groups of countries. This indicator is used to track the evolution of the nowcasts for the U.S., the OECD area, and the world economy during the COVID-19 pandemic and the main factors that drive the nowcasts are quantified.
Artikel Lesen