nep-cfn New Economics Papers
on Corporate Finance
Issue of 2019‒11‒18
eight papers chosen by
Zelia Serrasqueiro
Universidade da Beira Interior

  1. Blockholder Leverage and Payout Policy: Evidence from French Holding Companies By Anantavrasilp, Sereeparp; De Jong, Abe; DeJong, Douglas V.; Hege, Ulrich
  2. Dealer Leverage and Exchange Rates: Heterogeneity Across Intermediaries By Ricardo Correa; Laurie Pounder Demarco
  3. Market-implied systemic risk and shadow capital adequacy By Chatterjee, Somnath; Jobst, Andreas
  4. The impact of Brexit on UK firms By Bloom, Nicholas; Bunn, Philip; Chen, Scarlet; Mizen, Paul; Smietanka, Pawel; Thwaites, Gregory
  5. Cross-country differences in the size of venture capital financing rounds: a machine learning approach By Marco Taboga
  6. Debt maturity and firm performance: evidence from a quasi-natural experiment By Antonio Accetturo; Giulia Canzian; Michele Cascarano; Maria Lucia Stefani
  7. Predicting bank distress in the UK with machine learning By Suss, Joel; Treitel, Henry
  8. Real Options Analysis in Appraisal of Commercial Property Development By T. O. Ayodele; A. Olaleye

  1. By: Anantavrasilp, Sereeparp; De Jong, Abe; DeJong, Douglas V.; Hege, Ulrich
    Abstract: This paper focuses on dominant owners’ use of leverage to finance their blockholdings and its relationship to dividend policy. We postulate that blockholder leverage may impact payout policy, in particular when earnings are hit by a negative shock. We use panel data for France where blockholders have tax incentives to structure their leverage in pyramidal holding companies and study the effect of the financial crisis in 2008/2009. We find no difference in payout policy and financial behavior during the 1999 to 2008 period between firms with levered owners and other firms. However, in the years 2009 to 2011 following the crisis, dividend payouts increase in proportion to pyramidal debt of dominant owners. We inspect pyramidal entities individually and find that on average only 60% of dividends are passed through to the ultimate owners, with the rest predominantly used to meet debt service obligations of the pyramidal entities.
    Keywords: payout policy, blockholders, concentrated ownership, leverage, blockholder; private leverage, margin loans, insider pledging, pyramids, financial crisis.
    JEL: G32 G34 G35
    Date: 2019–10
  2. By: Ricardo Correa; Laurie Pounder Demarco
    Abstract: In line with a growing literature on financial intermediary asset pricing, we find that changes in the leverage of primary dealers have predictive power in forecasting exchange rates. Unlike previous studies, we find that primary dealer heterogeneity matters for their role in asset pricing. The leverage of foreign-headquartered dealers in the United States entirely drive the predictive power on exchange rates, while the same measure for domestic U.S.-headquartered dealers is insignificant. The leverage of foreign-headquartered dealers also has more predictive power for some other assets. We argue that this heterogeneity is due to foreign broker-dealers having more balance sheet capacity relative to domestic dealers during the 2000s. This result conflicts with an assumption of homogeneity among intermediaries which is implicit in most modern intermediary asset pricing models. In addition, we find that currency market positions, including derivatives positions, are likely stronger than cross-border lending as the main channel through which leverage manifests itself in exchange rate changes.
    Keywords: Exchange rates ; Intermediaries ; International finance ; Leverage cycles ; Primary dealers
    JEL: F30 F31 G12 G24
    Date: 2019–11–06
  3. By: Chatterjee, Somnath (Bank of England); Jobst, Andreas (International Monetary Fund)
    Abstract: This paper presents a forward-looking approach to measure systemic solvency risk using contingent claims analysis (CCA) as a theoretical foundation for determining an institution’s default risk based on the uncertainty in its asset value relative to promised debt payments over time. Default risk can be quantified as market-implied expected losses calculated from integrating equity market and balance sheet information in a structural default risk model. The expected losses of multiple banks and their non-parametric dependence structure define a multivariate distribution that generates portfolio-based estimates of the joint default risk using the aggregation technique of the Systemic CCA framework (Jobst and Gray, 2013). This market-implied valuation approach (‘shadow capital adequacy’) endogenises bank solvency as a probabilistic concept based on the perceived default risk (in contrast to accounting-based prudential measures of capital adequacy). The presented model adds to the literature of analytical tools estimating market-implied systemic risk by augmenting the CCA approach with a jump diffusion process of asset changes to inform a more comprehensive and flexible assessment of common vulnerabilities to tail risks of the four largest UK commercial banks.
    Keywords: Systemic risk; contingent claims analysis; jump diffusion; CoVaR; systemic expected shortfall; conditional tail expectation; capital adequacy
    JEL: C61 C63 G01 G21 G28
    Date: 2019–09–16
  4. By: Bloom, Nicholas (Stanford University); Bunn, Philip (Bank of England); Chen, Scarlet (Stanford University); Mizen, Paul (University of Nottingham); Smietanka, Pawel (Bank of England); Thwaites, Gregory (LSE Centre for Macroeconomics)
    Abstract: We use a major new survey of UK firms, the Decision Maker Panel, to assess the impact of the June 2016 Brexit referendum. We identify three key results. First, the UK’s decision to leave the EU has generated a large, broad and long-lasting increase in uncertainty. Second, anticipation of Brexit is estimated to have gradually reduced investment by about 11% over the three years following the June 2016 vote. This fall in investment took longer to occur than predicted at the time of the referendum, suggesting that the size and persistence of this uncertainty may have delayed firms’ response to the Brexit vote. Finally, the Brexit process is estimated to have reduced UK productivity by between 2% and 5% over the three years after the referendum. Much of this drop is from negative within-firm effects, in part because firms are committing several hours per week of top-management time to Brexit planning. We also find evidence for smaller negative between-firm effects as more productive, internationally exposed, first have been more negatively impacted than less productive domestic firms.
    Keywords: Brexit; economic uncertainty; policy uncertainty
    JEL: D80 E66 G18 H32
    Date: 2019–08–30
  5. By: Marco Taboga (Bank of Italy)
    Abstract: We analyze the potential determinants of the size of venture capital financing rounds. We employ stacked generalization and boosted trees, two of the most powerful machine learning tools in terms of predictive power, to examine a large dataset on start-ups, venture capital funds and financing transactions. We find that the size of financing rounds is mainly associated with the characteristics of the firms being financed and with the features of the countries in which the firms are headquartered. Cross-country differences in the degree of development of the venture capital industry, while highly correlated with the size of funding rounds, are not significant once we control for other country-level characteristics. We discuss how our findings contribute to the debate about policy interventions aimed at stimulating start-up financing.
    Keywords: venture capital, financial institutions, country characteristics, machine learning
    JEL: G24 F0 C19
    Date: 2019–11
  6. By: Antonio Accetturo (Bank of Italy); Giulia Canzian (European Commission - DG Joint Research Centre (JRC)); Michele Cascarano (Bank of Italy); Maria Lucia Stefani (Bank of Italy)
    Abstract: Asymmetric information between lenders and borrowers may lead to a suboptimal provision of long term credit by banks; this may have negative effects on firms' investments and, as a consequence, future growth. In this paper we analyze a policy intervention -- Mutuo di Riassetto (MR) -- launched by an Italian regional government, aimed at increasing firms' debt maturity. Using a combination of difference-in-differences and instrumental variable approaches, we find that the MR program had a temporary impact on debt maturity by raising firms' share of long-term debt only for the first two years after the start of the program. The policy did not have relevant effects on performance: firms registered a short-term increase in intangible assets and (to a lesser extent) profitability, but did not display any permanent rise in terms of sales, tangible assets, labor cost, or credit access. We also find that firms involved in the MR program observed a significant rise in the probability to default.
    Keywords: policy evaluation, debt maturity, firm performance
    JEL: H4 G3
    Date: 2019–11
  7. By: Suss, Joel (Bank of England); Treitel, Henry (Bank of England)
    Abstract: Using novel data and machine learning techniques, we develop an early warning system for bank distress. The main input variables come from confidential regulatory returns, and our measure of distress is derived from supervisory assessments of bank riskiness from 2006 through to 2012. We contribute to a nascent academic literature utilising new methodologies to anticipate negative firm outcomes, comparing and contrasting classic linear regression techniques with modern machine learning approaches that are able to capture complex non-linearities and interactions. We find the random forest algorithm significantly and substantively outperforms other models when utilising the AUC and Brier Score as performance metrics. We go on to vary the relative cost of false negatives (missing actual cases of distress) and false positives (wrongly predicting distress) for discrete decision thresholds, finding that the random forest again outperforms the other models. We also contribute to the literature examining drivers of bank distress, using state of the art machine learning interpretability techniques, and demonstrate the benefits of ensembling techniques in gaining additional performance benefits. Overall, this paper makes important contributions, not least of which is practical: bank supervisors can utilise our findings to anticipate firm weaknesses and take appropriate mitigating action ahead of time.
    Keywords: Machine learning; bank distress; early warning system
    JEL: C14 C33 C52 C53 G21
    Date: 2019–10–04
  8. By: T. O. Ayodele; A. Olaleye
    Abstract: Purpose: This paper examined the application of real option analysis to real estate development (RED) appraisal in an emerging African market. It examined the effects of flexibility types on RED appraisal outcomes and compared the appraisal outputs with results obtained from the traditional NPV model.Design/methods: Using data of four case studies; three commercial and one residential property development, the study compared the results of the traditional NPV appraisal outputs under three scenarios of most optimistic, most likely and most pessimistic against the results obtained from the real option analysis using the Samuelson McKean Formula. The options examined were the option to delay/defer and vertically expand development.Findings: The results showed that the use of the DCF (NPV) traditional model favours a stable and optimistic market; with positive trends and forecast. Thus, during unanticipated market downturns, investors might be exposed to the greater level of downside risk when RED investments are appraised based on the traditional models only. This implies the needs to encourage the adoption of the real option models which guarantee better appraisal of RED investment even during the period of unexpected market downturns.Practical Implication: Based on evidences from an emerging market, the paper gives a further insight on the adoption real option analysis in RED appraisal in comparison with outputs obtained from the traditional DCF appraisal models.Originality: The paper is one of the few attempts that seek to demonstrate the practical application of real option analysis in practice, particularly from an emerging African market.
    Keywords: Appraisal; Investment; NPV; Real Estate Development; Real option; Uncertainty
    JEL: R3
    Date: 2018–09–01

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