CFS working paper series
https://gfk-cfs.de/working-papers/
Refine
Year of publication
- 2014 (50) (remove)
Document Type
- Working Paper (50)
Language
- English (50)
Has Fulltext
- yes (50)
Is part of the Bibliography
- no (50)
Keywords
- financial crisis (4)
- monetary policy (3)
- Alternative investments (2)
- G-SIFIs (2)
- Household finance (2)
- OTC markets (2)
- Progressive Taxation (2)
- asset pricing (2)
- limited attention (2)
- simulated method of moments (2)
Institute
458
We examine trust and trustworthiness of individuals with varying professional preferences and experiences. Our subjects study business and economics in Frankfurt, the financial center of Germany and continental Europe. In the trust game, subjects with a high interest in working in the financial industry return 25 percent less than subjects with a low interest. We find no evidence that the extent of professional experience in the financial industry has a negative impact on trustworthiness. We also do not find any evidence that the financial industry screens out less trustworthy individuals in the hiring process. In a prediction game that is strategically equivalent to the trust game, the amount sent by first-movers was significantly smaller when the second-mover indicated a high interest in working in finance. These results suggest that the financial industry attracts less trustworthy individuals, which may contribute to the current lack of trust in its employees.
468
We develop a model of an order-driven exchange competing for order flow with off-exchange trading mechanisms. Liquidity suppliers face a trade-off between benefits and costs of order exposure. If they display trading intentions, they attract additional trade demand. We show, in equilibrium, hiding trade intentions can induce mis-coordination between liquidity supply and demand, generate excess price fluctuations and harm price efficiency. Econometric high-frequency analysis based on unique data on hidden orders from NASDAQ reveals strong empirical support for these predictions: We find abnormal reactions in prices and order flow after periods of high excess-supply of hidden liquidity.
450
We propose an iterative procedure to efficiently estimate models with complex log-likelihood functions and the number of parameters relative to the observations being potentially high. Given consistent but inefficient estimates of sub-vectors of the parameter vector, the procedure yields computationally tractable, consistent and asymptotic efficient estimates of all parameters. We show the asymptotic normality and derive the estimator's asymptotic covariance in dependence of the number of iteration steps. To mitigate the curse of dimensionality in high-parameterized models, we combine the procedure with a penalization approach yielding sparsity and reducing model complexity. Small sample properties of the estimator are illustrated for two time series models in a simulation study. In an empirical application, we use the proposed method to estimate the connectedness between companies by extending the approach by Diebold and Yilmaz (2014) to a high-dimensional non-Gaussian setting.
477
We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semi-martingale log asset price process which is subject to noise and non-synchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance estimates. The latter originate from a local method of moments (LMM) which recently has been introduced by Bibinger et al. (2014). We extend the LMM estimator to allow for autocorrelated noise and propose a method to adaptively infer the autocorrelations from the data. We prove the consistency and asymptotic normality of the proposed spot covariance estimator. Based on extensive simulations we provide empirical guidance on the optimal implementation of the estimator and apply it to high-frequency data of a cross-section of NASDAQ blue chip stocks. Employing the estimator to estimate spot covariances, correlations and betas in normal but also extreme-event periods yields novel insights into intraday covariance and correlation dynamics. We show that intraday (co-)variations (i) follow underlying periodicity patterns, (ii) reveal substantial intraday variability associated with (co-)variation risk, (iii) are strongly serially correlated, and (iv) can increase strongly and nearly instantaneously if new information arrives.
463
We develop a methodology to identify and rank “systemically important financial institutions” (SIFIs). Our approach is consistent with that followed by the Financial Stability Board (FSB) but, unlike the latter, it is free of judgment and it is based entirely on publicly available data, thus filling the gap between the official views of the regulator and those that market participants can form with their own information set. We apply the methodology to annual data on three samples of banks (global, EU and euro area) for the years 2007-2012. We examine the evolution of the SIFIs over time and document the shifs in the relative weights of the major geographic areas. We also discuss the implication of the 2013 update of the identification methodology proposed by the FSB.
454
We analyze the risk premium on bank bonds at origination with a special focus on the role of implicit and explicit public guarantees and the systemic relevance of the issuing institutions. By looking at the asset swap spread on 5,500 bonds, we find that explicit guarantees and sovereign creditworthiness have a substantial effect on the risk premium. In addition, while large institutions still enjoy lower issuance costs linked to the TBTF framework, we find evidence of enhanced market disciple for systemically important banks which face, since the onset of the financial crisis, an increased premium on bond placements.
453
We examine the impact of so-called "Crisis Contracts" on bank managers' risk-taking incentives and on the probability of banking crises. Under a Crisis Contract, managers are required to contribute a pre-specified share of their past earnings to finance public rescue funds when a crisis occurs. This can be viewed as a retroactive tax that is levied only when a crisis occurs and that leads to a form of collective liability for bank managers. We develop a game-theoretic model of a banking sector whose shareholders have limited liability, so that society at large will suffer losses if a crisis occurs. Without Crisis Contracts, the managers' and shareholders' interests are aligned, and managers take more than the socially optimal level of risk. We investigate how the introduction of Crisis Contracts changes the equilibrium level of risk-taking and the remuneration of bank managers. We establish conditions under which the introduction of Crisis Contracts will reduce the probability of a banking crisis and improve social welfare. We explore how Crisis Contracts and capital requirements can supplement each other and we show that the efficacy of Crisis Contracts is not undermined by attempts to hedge.
467
We propose a framework for estimating network-driven time-varying systemic risk contributions that is applicable to a high-dimensional financial system. Tail risk dependencies and contributions are estimated based on a penalized two-stage fixed-effects quantile approach, which explicitly links bank interconnectedness to systemic risk contributions. The framework is applied to a system of 51 large European banks and 17 sovereigns through the period 2006 to 2013, utilizing both equity and CDS prices. We provide new evidence on how banking sector fragmentation and sovereign-bank linkages evolved over the European sovereign debt crisis and how it is reflected in network statistics and systemic risk measures. Illustrating the usefulness of the framework as a monitoring tool, we provide indication for the fragmentation of the European financial system having peaked and that recovery has started.
494
This chapter analyzes the risk and return characteristics of investments in artists from the Middle East and Northern Africa (MENA) region over the sample period 2000 to 2012. With hedonic regression modeling we create an annual index that is based on 3,544 paintings created by 663 MENA artists. Our empirical results prove that investing in such a hypothetical index provides strong financial returns. While the results show an exponential growth in sales since 2006, the geometric annual return of the MENA art index is a stable13.9 percent over the whole period. We conclude that investing in MENA paintings would have been profitable but also note that we examined the performance of an emerging art market that has only seen an upward trend without any correction, yet.
484
Most simulated micro-founded macro models use solely consumer-demand aggregates in order to estimate deep economy-wide preference parameters, which are useful for policy evaluation. The underlying demand-aggregation properties that this approach requires, should be easy to empirically disprove: since household-consumption choices differ for households with more members, aggregation can be rejected if appropriate data violate an affine equation regarding how much individuals benefit from within-household sharing of goods. We develop a survey method that tests the validity of this equation, without utility-estimation restrictions via models. Surprisingly, in six countries, this equation is not rejected, lending support to using consumer-demand aggregates.