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J.Lawrenz ist Professor für Risikomanagement am Institut für Banken und Finanzen. Er ist aktuell stv. Institutsvorstand sowie Sprecher der Gruppe der Professorinnen und Professoren an der Fakultät für Betriebswirtschaft. Von 2020-22 war er Vorstand der Deutschen Gesellschaft für Finanzwirschaft (DGF). J.Lawrenz promovierte im Jahr 2005; war Gastforscher an der HEC Lausanne (Schweiz), hielt eine Vertretungsprofessur an der Leibniz-Universität Hannover (2012) und ist seit 2015 Univ.Prof. an der Universität Innsbruck. Seine Forschungsinteressen liegen an der Schnittstelle zwischen Asset Pricing und Risk Management. Im Bereich des Asset Pricing beschäftigt er sich mit Prognosemodellen, internationaler Asset allocation und der Rolle von Faktormodellen. Im Bereich des finanzwirtschaftlichen Risikomanagements kommen von ihm Arbeiten über die Finanzierungsbedingungen und Finanzierungsentscheidungen von Unternehmen. Seine Arbeiten wurden publiziert im Journal of Empirical Finance, Journal of Banking & Finance, Journal of Corporate Finance, Schmalenbach Business Review, u.a.

  Lehre

Aktuelle Lehrveranstaltungen finden Sie im Online LV-Verzeichnig

  Forschung

- Forschungsprojekt

OeNB Jubiläumsfonds-Projekt: "Factors versus Characteristics in Empirical Asset Pricing: Investigating Institutional
Demand" See: https://www.oenb.at/Ueber-Uns/Forschungsfoerderung/Jubilaeumsfonds.html

- Publikationen

Working Papers

• Decay of cay (2023) with M.Dauber,
  Working paper.
  SSRN
  _{Comprehensive empirical assessment of the forecasting ability of the consumption-to-wealth ratio cay. We show that during the last 15-20 years, cay appears to have lost its alleged predictability altogether. We find neither in-sample, out-of-sample, nor economic predictability from the perspective of most recent data. The behavior of wealth is increasingly detached from consumption since at least 2000.}
  
  
• Can crowd-sourced employee ratings improve default prediction? Empirical evidence from a peer group approach (2023) with M.Strauss, M.Strauss and J.Walde,
  Working paper.
   
  _{We use the ratings of employees on kununu and investigate if this information has incremental predictive value for financial default. We construct a sample from hand-collected restructuring reports to address endogeneity and group-level effects. We find significant improvements beyond classical financial predictor variables.}
  
  
• Does investor-specific attention explain investor-specific trading? (2023) with M.Bank, F.Kunz, A.Kupfer, and M.Schmidt
  Working paper.
   
  _{We revisit the evidence that Google search volume is indicative of retail buying preassure and complement it by more recent evidence that Bloomberg usage is linked to institutional trading behavior. Using most recent identification techniques, we find some support for the institutional investor channel, but only limited support for retail trading.}
  
  
• The anatomy of the low-risk anomaly (2022) with M.Bank and F.Kunz,
  Working paper.
   
  _{We provide demand-based evidence from institutional holdings for the low-risk anomaly. We find strong evidence that institutional investors have a positive taste for high systematic risk and skewness and a negative taste for high idiosyncratic risk.}
  
  
• A sceptical appraisal of industry-specific return predictability (2022) with M.Praxmarer and N.Richtmann,
  Working paper.
   
  _{We investigate return predictability in more and more fine-grained industry portfolios from various predictor variables.}
  
  
• Taste for Characteristics or Risk Factor Aversion? Evidence from Institutional Demand (2022) with M.Bank and F.Insam,
  Working paper.
  (SSRN)
  _{Is it risk factors or stock characteristics? We argue that due to an identification dilemma, the question will most likely not be settled only on the basis of return data only. We therefore propose to use institutional investor holdings data. We find strong support that characteristics drive (institutional) demand, which in turn is reflected in the cross-section of returns.}
  
  
• Contingent Convertible Bonds in a General Equilibrium Model (2017),
  Working paper. EFA 2015 meeting paper
  (SSRN)
  _{Model of CoCo bonds with a feedback loop of capital structure on asset quality. Shows that CoCo bonds can mitigate debt overhang problems. However, a pure private sector restructuring is not sustainable. Furthermore, a CoCo bond program creates incentives for high risk banks to overinvest and induces higher redistributions as equivalent programs.}
  
  
• Evidence on the empirical relationship between forecast accuracy and recommendation profitability (2017), with Klaus Schredelseker and Alex Weissensteiner
  Working paper.
  (SSRN)
  _{Empirical follow-up paper to Lawrenz/Weissensteiner (2012) where we show that contrary to conventional intuition, the most succesful financial analysts (in terms of recommendation profitability) are not the most accurate ones (in terms of earnings forecast accuracy).}
  
  

Publikationen in Refereed Journals

• What drives negative investment-cash flow sensitivities? Revenue effect versus corporate life-cycle dynamics (2023) with J. Oberndorfer,
  Schmalenbach Journal of Business Research, 75, 483–518.
  (https://doi.org/10.1007/s41471-023-00164-0)
  _{We investigate if the evidence of negative ICFS (investment-cash flow sensitivities) is due to the revenue effect (i.e.debtholder anticipate investment returns if close to distress) or due to the fact that younger firms tend to have high investment and at the same time low cash flows (i.e. life-cycle dyanmics). We find that it's rather the latter.}
  
  
• Firm size effects in trade credit supply and demand (2018) with J. Oberndorfer,
  Journal of Banking & Finance, 93, 1-20.
  (https://doi.org/10.1016/j.bankfin.2018.05.014)
  _{Using a large dataset of German companies, we identify a genuine firm size effect with respect to the role of trade credit as inter-firm liquidity redistribution as well as substitute to bank financing. We show that the size effect is not entirely explained by either financial constraints, external finance dependence or creditworthiness.}
  
  
• Decomposing the predictive power of local and global financial valuation ratios (2018) with J.Zorn,
  Quarterly Review of Economics and Finance, 70, 137-149.
  (https://doi.org/10.1016/j.qref.2018.04.012)
  _{Empirical stock return predictability paper. We orthogonalize valuation ratios on the global and local level and decompose them into discount-rate and cash-flow driven components. We show that global information is much stronger related to discount-rate news and that this explains the weaker predictive power of local ratios.}
  
  
• Predicting international stock returns with conditional price-to-fundamental ratios (2017) with J.Zorn,
  Journal of Empirical Finance, 43, 159-184
  (https://doi.org/10.1016/j.jempfin.2017.06.003)
  _{Empirical stock return predictability paper. We show that combining cross-sectional and time-series information in international asset allocation improves in-sample as well as out-of-sample evidence substantially and can be exploited in a Bayesian investment strategy.}
  
  
• The Issuance of German SME Bonds and its Impact on Operating Performance (2017) with P.Freihle,
  Schmalenbach Business Review, 18, 3, 227-259
  (https://link.springer.com/article/10.1007/s41464-017-0036-9)
  _{Empirical analysis of Post-Issuance Operating Performance. Using propensity score matching to avoid hindsight bias, we document a decline in operating performance for companies after having issued SME Bonds.}
  
  
• Time-series properties of the dividend-price ratio with social dynamics (2013)
  Applied Economics, 45, 5, 569-579
  (https://doi.org/10.1080/00036846.2011.607134)
  _{Follow-up paper to 'Return predictability and social dynamics' (Lawrenz/Hule, 2013), which focuses on the cointegration relationship between simulated price and dividend time series. We show that the simulated economy with locally interacting agents produces a persistent pd-ratio which closely resembles empirical data.}
  
  
• Deposit Finance as a Commitment Device and the Optimal Debt Structure of Commercial Banks (2013) with M. Bank,
  European Financial Management, 19, 1, 14-44
  (https://doi.org/10.1111/j.1468-036X.2010.00566.x)
  _{Theoretical corporate finance capital structure model applied to the debt structure (bonds vs deposits) of commercial banks. In the spirit of Diamond/Rajan (2000), we show that the mix between bond and deposit financing balances off
  the benefit from the commitment feature against the threat from regulatory interventions.}
  
  
• Return predictability and social dynamics (2013) with R. Hule,
  Review of Managerial Science, 7, 159-189
  (https://doi.org/10.1007/s11846-013-0099-z)
  _{Asset pricing. We simulate an economy with a finite number of agents which have heterogenous beliefs and which interact locally in the sense of social dynamics. We determine prices from a Lucas tree environment and run predictive regressions on lagged pd ratios. The simulated economy matches a variety of empirical facts.}
  
  
• Contingent Convertibles. Solving or Seeding the Next Banking Crisis? (2012) with C. Koziol,
  Journal of Banking and Finance, 35, 1, 90-104
  (https://doi.org/10.1016/j.jbankfin.2011.06.009)
  _{One of the first papers to analyze CoCo bonds in a theoretical corporate finance capital structure model. We show that CoCo bonds provide risk-shifting incentives. Although CoCo bond issues increase the bank value, the probability of financial distress rises, implying that CoCos are not unambiguously beneficial for banking stability.}
  
  
• Correlated Errors. Why a monoton relationship between forecast precision and trading profitability may not hold (2012) with A. Weissensteiner,
  Journal of Business Finance and Accounting, 39, 5, 675-699
  (https://doi.org/10.1111/j.1468-5957.2012.02291.x)
  _{Theoretical model which suggests that better forecasting abilities do not necessarily translate into better trading profitability. In a market environment, the key is to recognize the commonality (or correlation) of forecasting errors made by all market participants.}
  
  
• Optimal Design of Rating-Trigger Step-Up Bonds: Agency Conflicts Versus Asymmetric Information (2010) with C. Koziol,
  Journal of Corporate Finance, 16, 2, 182-204
  (https://doi.org/10.1016/j.jcorpfin.2009.12.002)
  _{Theoretical corporate finance capital structure model applied to rating-trigger step-up bonds. We analyze two competing economic explanations for this bond design: Signalling and Asset substitution. We solve the optimal contract under both scenarios and show that only asset substition is consistent with empirical data.}
  
  
• What makes a bank risky? Insights from the optimal capital structure of banks (2009) with C.Koziol,
  Journal of Banking & Finance, 33, 5, 861-873
  (https://doi.org/10.1016/j.jbankfin.2008.09.022)
  _{Theoretical corporate finance capital structure model applied to commercial banks. By modelling the asset value as a jump-diffusion process, we show that the risk coming from the diffusion part can be accommodated by endogenous financing decisions while the jump component exposes banks to the possibility of sudden defaults.}
  
  
• Assessing the estimation uncertainty in default probabilities (2008)
  Kredit und Kapital, 41, 2
  
  
• Why Simple, When It Can Be Difficult. Some Remarks on the Basel IRB Approach (2003) with M.Bank,
  Kredit und Kapital, 4/2003
  
  
• Sind Ratingurteile kulturell beeinflusst? (2003) with M. Bank,
  Kredit&Rating Praxis, 3/2003
  
  
• Basel II: Quantitative Impact Study für Österreich (2002) with W. Schwaiger,
  Zeitschrift für das gesamte Bank- und Börsewesen, 50, Februar 2002
  
  
• Bank Deutschland: Aktualisierung der Quantitative Impact Study (QIS2) von Basel II (2002) with W. Schwaiger,
  RiskNews, www.risknews.de, 02.2002
  
  
• Standard- versus IRB-Ansatz. Auswirkungen auf die Bank Deutschland (2002) with W. Schwaiger,
  Zeitschrift für das gesamte Kreditwesen, Februar 2002

Buchbeiträge

• Local interaction, incomplete information and properties of asset prices. (2008) with R.Hule,
  in: Schredelseker, K. and F.Hauser (2008) "Complexity and Artificial Markets", Lecture Notes in Economics and Mathematical Systems, Springer Verlag, Berlin
  
  
• Understanding the non-monotonic payoffs for heterogenously informed agents. (2008) in: Hanke, M. and J.Huber,
  "Information, Interaction and (In)Efficiency in Financial Markets", Linde Verlag, Wien
  
  
• The value of information. Some clarifications and some new results for the Schredelseker-Game. (2008) with R.Hule,
  in: Hanke, M. and J.Huber (2008) "Information, Interaction and (In)Efficiency in Financial Markets", Linde Verlag, Wien