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on Banking |
By: | Roy Havemann |
Abstract: | Following the failure of Saambou bank in February 2002, another seven South African banks failed within a month, including the ï¬ fth-largest, and a further ï¬ ve within a year. In total, twenty-two small and mid-sized banks deregistered over two years: half the total number of banks, and nearly 10 per cent of the deposit base. South Africa is one of the few jurisdictions that does not have a explicit deposit insurance scheme. While such a scheme may have prevented the ï¬ rst failure, I show that it would not have prevented contagion. The banks that failed were all well capitalised and solvent, but had relatively high levels of short-term funding from non-bank ï¬ nancial institutions. They would not have qualiï¬ ed for a retail deposit insurance scheme, and would still have experienced a run of non-bank funding. This highlights that deposit insurance is best seen as a tool that should be used for its stated purposes (protecting vulnerable depositors), and not as a general ï¬ nancial stability tool that can prevent contagion. Indeed, if agents expect that the authorities will use deposit insurance to ‘bail-out’ a bank, this would introduce moral hazard. |
Keywords: | bank failures, contagion, Financial Regulation |
JEL: | G01 G21 G28 |
Date: | 2020–06 |
URL: | http://d.repec.org/n?u=RePEc:rza:wpaper:823&r=all |
By: | Ricardo Correa; Linda S. Goldberg |
Abstract: | Bank holding companies (BHCs) can be complex organizations, conducting multiple lines of business through many distinct legal entities and across a range of geographies. While such complexity raises the the costs of bank resolution when organizations fail, the effect of complexity on BHCs' broader risk profiles is less well understood. Business, organizational, and geographic complexity can engender explicit trade-offs between the agency problems that increase risk and the diversification, liquidity management, and synergy improvements that reduce risk. The outcomes of such trade-offs may depend on bank governance arrangements. We test these conjectures using data on large U.S. BHCs for the 1996-2018 period. Organizational complexity and geographic scope tend to provide diversification gains and reduce idiosyncratic and liquidity risks while also increasing BHCs' exposure to systematic and systemic risks. Regulatory changes focused on organizational complexity have significantly reduced this type of complexity, leading to a decrease in systemic risk and an increase in liquidity risk among BHCs. While bank governance structures have, in some cases, significantly affected the buildup of BHC complexity, better governance arrangements have not moderated the effects of complexity on risk outcomes. |
Keywords: | Bank complexity; Risk taking; Regulation; Too big to fail; Liquidity; Corporate governance; Agency problem; Global banks; Diversification |
JEL: | G21 G28 G32 |
Date: | 2020–07–02 |
URL: | http://d.repec.org/n?u=RePEc:fip:fedgif:1287&r=all |
By: | Michael Kumhof (Bank of England); Xuan Wang (Vrije Universiteit Amsterdam) |
Abstract: | We develop a New Keynesian model where all payments between agents require bank deposits through deposits-in-advance constraints, bank deposits are created through disbursement of bank loans, and banks face a convex lending cost. At the zero lower bound on deposit rates (ZLBD), changes in policy rates affect activity through both real interest rates and banks’ net interest margins (NIM). At estimated credit supply elasticities, the Phillips curve is very flat at the ZLBD, because inflationary pressures increase NIM. This strongly increases credit and thereby output, but it dampens inflation by relaxing price setters’ credit rationing constraint. At the ZLBD, monetary policy has far larger effects on output relative to inflation, and Taylor rules stabilize output less effectively than rules that also respond to credit. For post-COVID-19 policy, this suggests urgency in returning inflation to targets, avoidance of negative policy rates, and a strong influence of credit conditions on rate setting. |
Keywords: | Banks, money creation, inside money, money demand, deposits-in-advance, Phillips curve, zero lower bound, monetary policy rules, Taylor rules, post-COVID-19 reforms |
JEL: | E41 E44 E51 G21 |
Date: | 2020–08–20 |
URL: | http://d.repec.org/n?u=RePEc:tin:wpaper:20200050&r=all |
By: | W. Scott Frame; Ping McLemore; Atanas Mihov |
Abstract: | This study shows that banking organization growth is associated with higher operational losses per dollar of total assets and incidence of tail risks. Event studies using M&A activity and instrumental variable regressions provide consistent evidence. The relationship between banking organization growth and operational risk varies by loss event types and balance sheet categories. We demonstrate that higher growth predicts worse operational risk realizations during the global financial crisis. These findings have implications for bank performance, risk management and supervision in a continually consolidating banking industry. |
Keywords: | Banking organizations; Operational risk; Mergers & acquisitions; Growth |
JEL: | G20 G21 |
Date: | 2020–08–14 |
URL: | http://d.repec.org/n?u=RePEc:fip:feddwp:88596&r=all |
By: | Yiwei Dou; Julapa Jagtiani; Ramain Quinn Maingi; Joshua Ronen |
Abstract: | We investigate whether the Credit Card Accountability, Responsibility, and Disclosure (CARD) Act of 2009 influenced the debt structure of consumers. By debt structure, we mean the proportion of total available credit from credit cards for each consumer.The act enhances disclosures of contractual and related information and restricts card issuers’ ability to raise interest rates or charge late or over-limit fees, primarily affecting non-prime borrowers. Using the credit history via the Federal Reserve Bank of New York/Equifax Consumer Credit Panel during 2006–2016, we find that the average ratio of credit limit on cards to total consumer debt declined for non-prime borrowers in comparison to prime borrowers after the introduction of the CARD Act. The decline did not occur before the bill was first introduced in Congress; it took place afterward and continued through the end of our sample period. The results suggest that the CARD Act likely had an adverse effect on non-prime borrowers. |
Keywords: | CARD Act; credit cards; credit limits; consumer debt |
JEL: | G21 G28 G18 L21 |
Date: | 2020–08–05 |
URL: | http://d.repec.org/n?u=RePEc:fip:fedpwp:88546&r=all |
By: | Mathias Drehmann; James Yetman |
Abstract: | The credit gap, defined as the deviation of the credit-to-GDP ratio from a one-sided HP-filtered trend, is a useful indicator for predicting financial crises. Basel III therefore suggests that policymakers use it as part of their countercyclical capital buffer frameworks. Hamilton (2018), however, argues that you should never use an HP filter as it results in spurious dynamics, has end-point problems and its typical implementation is at odds with its statistical foundations. Instead he proposes the use of linear projections. Some have also criticised the normalisation by GDP, since gaps will be negatively correlated with output. We agree with these criticisms. Yet, in the absence of clear theoretical foundations, all proposed gaps are but indicators. It is therefore an empirical question which measure performs best as an early warning indicator for crises. We run a horse race using expanding samples on quarterly data from 1970 to 2017 for 41 economies. We find that credit gaps based on linear projections in real time perform poorly when based on country-by-country estimation, and are subject to their own end-point problem. But when we estimate as a panel, and impose the same coefficients on all economies, linear projections perform marginally better than the baseline credit-to-GDP gap, with somewhat larger improvements concentrated in the post-2000 period and for emerging market economies. The practical relevance of the improvement is limited, though. Over a ten year horizon policy makers could expect one less wrong call on average. |
Keywords: | early warning indicators, credit gaps, HP filter, linear projection |
JEL: | E44 G01 |
Date: | 2020–08 |
URL: | http://d.repec.org/n?u=RePEc:bis:biswps:878&r=all |
By: | Sumit Agarwal; Ricardo Correa; Bernardo Morais; Jessica Roldán; Claudia Ruiz |
Abstract: | How does a bank react when a substantial share of its borrowers suffer a large negative shock? To answer this question we exploit the 2014 collapse of energy prices using the universe of Mexican commercial bank loans. We show that, after the drop in energy prices, banks exposed to the energy sector increased their exposure to these borrowers even more, relaxing credit margins to their larger debtors in the sector. An increase of one standard deviation in a bank's ex-ante exposure to the energy sector increased the loan volume to borrowers in the sector by 18 percent and reduced interest rates by 6 percent, even though borrower's credit default swap spreads were widening. Highly exposed banks amplified this sector-specific shock to the rest of the economy by contracting lending to other sectors, with important real effects, as the borrowers could not switch credit suppliers. Finally, the energy price shock had a large negative impact on macro outcomes, especially in the capital-intensive secondary sector. Quantitatively, a one standard deviation increase in the exposure of a state's banks to the energy sector reduced its GDP by 1.8 percent. |
Keywords: | Credit exposure; Bank lending; Financial stability; Commodity prices; Emerging markets |
JEL: | E52 E58 G01 G21 G28 |
Date: | 2020–07–07 |
URL: | http://d.repec.org/n?u=RePEc:fip:fedgif:1288&r=all |
By: | Gabriel Garber; Atif Mian; Jacopo Ponticelli; Amir Sufi |
Abstract: | After the global financial crisis, government banks in Brazil boosted credit provision to households, generating a sharp increase in household debt which was followed by the most severe recession in recent Brazilian history in 2015-2016. Using a novel individual-level data set including matched credit registry and employer-employee information, we show that individuals with higher debt-to-income growth during the boom experienced lower subsequent credit card expenditure during the recession. To identify the credit-supply effect, we exploit individuals borrowing from both government-controlled and private banks. We show that, during the late stages of the boom period, government banks increased their lending more than private banks to the same individual. To study the effect of this credit supply shock on individual consumption, we exploit variation in the sector of employment of each borrower. Individuals employed by the public sector were disproportionately targeted by payroll loans offered by government banks and experienced larger decline in credit card spending during the subsequent recession. |
Keywords: | credit booms, household credit, payroll loans, credit card expenditure |
JEL: | D14 E21 G21 G28 |
Date: | 2020–08 |
URL: | http://d.repec.org/n?u=RePEc:bis:biswps:876&r=all |
By: | Dong Beom Choi; Michael R. Holcomb; Donald P. Morgan |
Abstract: | Leverage limits as a form of capital regulation have a well-known, potential bug: If banks can’t lever returns as desired, they can boost returns on equity by shifting toward riskier, higher yielding assets. That reach for yield is the leverage rule “arbitrage.” But would banks do that? In a previous post, we discussed evidence from our working paper that banks did do just that in response to the new leverage rule that took effect in 2018. This post discusses new findings in our revised paper on when and how banks arbitraged. |
Keywords: | leverage rule; reguatory arbitrage; risk; banks |
JEL: | G21 E5 G28 |
Date: | 2020–06–30 |
URL: | http://d.repec.org/n?u=RePEc:fip:fednls:88260&r=all |
By: | Houben, Aerdt; Kakes, Jan; Petersen, Annelie |
Abstract: | This article describes how the institutional set-up of central bank tasls policies differs across Europe and discusses central bank involvement. In some jurisdictions (like Austria) the central bank continues to focus on its core monetary tasks, whereas in other jurisdictions (like the Netherlands) the central bank also plays a prominent role in non-monetary financial policy fields. The purpose of this article is to i) map out how traditional and new policy tools are organized across Europe, ii) discuss how these policy instruments interact, iii) review the pros and cons of central bank involvement, and iv) discuss how the organization of policies – particularly the role of the central bank – may be related to country-specific features (like the importance of large, systemic banks). |
Keywords: | Central banks, monetary policy, lender of last resort, macroprudential policy, supervision, resolution |
JEL: | E52 E58 G28 G38 |
Date: | 2020–08 |
URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:102291&r=all |
By: | Jérôme Creel (OFCE - Observatoire français des conjonctures économiques - Sciences Po - Sciences Po); Paul Hubert (OFCE - Observatoire français des conjonctures économiques - Sciences Po - Sciences Po); Fabien Labondance (OFCE - Observatoire français des conjonctures économiques - Sciences Po - Sciences Po, CRESE - Centre de REcherches sur les Stratégies Economiques (EA 3190) - UBFC - Université Bourgogne Franche-Comté [COMUE] - UFC - Université de Franche-Comté) |
Abstract: | Although the literature has provided evidence of the predictive power of credit for financial and banking crises, this article aims to investigate the grounds of this link by assessing the interrelationships between credit and banking fragility. The main identification assumption represents credit and banking fragility as a system of simultaneous joint data generating processes whose error terms are correlated. We test the null hypotheses that credit positively affects banking fragility—a vulnerability effect—and that banking fragility has a negative effect on credit—a trauma effect. We use seemingly unrelated regressions and 3SLS on a panel of European Union (EU) countries from 1998 to 2012 and control for the financial and macroeconomic environment. We find a positive effect of credit on banking fragility in the EU as a whole, in the Eurozone, in the core of the EU but not at its periphery, and a negative effect of banking fragility on credit in all samples. |
Keywords: | Banking fragility,Credit growth,Nonperforming loans,SUR model |
Date: | 2019–12 |
URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-02894259&r=all |
By: | Okahara, Naoto |
Abstract: | This study proposes a model that describes banks' decisions about how much liquidity they hold and analyzes how liquidity regulations affect the amount of their lending. In literature, it is pointed out that banks are likely to hold ex-post excess liquidity under a liquidity regulation when some depositors make decisions based on the banks' soundness. This result implies that the regulation forces banks to suffer an unnecessary decrease of their lending, and thus, they would try to mitigate the loss by adjusting their portfolio. The aim of this study is to investigate whether banks' lending decreases or not when there exist multiple sets of assets that satisfy a liquidity regulation. In addition, we analyze two types of liquidity regulation; one focuses on banks' survivability, and the other focuses on continuity of their liquidity holding. The model shows that, even when there exist other ways to satisfy the regulations besides holding only reserves, banks still hold an ex-post excess amount of liquidity under either type of liquidity regulation. However, the model also shows that the amount of banks' lending varies according to how they satisfy the liquidity regulation and the probability that a severe reduction of lending happens depends partly on the regulation's type. These results implies that banks' decisions for mitigating losses caused by liquidity regulations lead to an undesired outcome, and thus, we consider more carefully banks' decisions under liquidity regulations. |
Keywords: | Bank, Liquidity regulation, Excess liquidity |
JEL: | E02 G21 G28 |
Date: | 2020–01–20 |
URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:101816&r=all |
By: | Nathan Blascak; Julia S. Cheney; Robert M. Hunt; Vyacheslav Mikhed; Dubravka Ritter; Michael Vogan |
Abstract: | We examine how a negative shock from identity theft affects consumer credit market behavior. We show that the immediate effects of fraud on credit files are typically negative, small, and transitory. After those immediate effects fade, identity theft victims experience persistent increases in credit scores and declines in reported delinquencies, with a significant proportion of affected consumers transitioning from subprime-to-prime credit scores. Those consumers take advantage of their improved creditworthiness to obtain additional credit, including auto loans and mortgages. Despite having larger balances, these individuals default on their loans less than prior to identity theft. |
Keywords: | identity theft; fraud alert; consumer credit; credit performance; limited attention |
JEL: | D14 D18 |
Date: | 2020–08–13 |
URL: | http://d.repec.org/n?u=RePEc:fip:fedpwp:88554&r=all |
By: | Adolfo Barajas; Andrea Deghi; Claudio Raddatz; Dulani Seneviratne; Peichu Xie; Yizhi Xu |
Abstract: | Leading up to the global financial crisis, US dollar activity by global banks headquartered outside the United States played a crucial role in transmitting shocks originating in funding markets. Although post-crisis regulation has improved banking systems’ resilience, US dollar funding remains a global vulnerability, as evidenced by strains that reemerged in March 2020 in the midst of the COVID-19 crisis. We show that shocks to US dollar funding costs lead to financial stress in the home economies of these global non-US banks, and to spillovers to borrowers, especially emerging economies. US dollar funding vulnerability amplifies these negative effects, while some policy-related factors act as mitigators, such as swap line arrangements between central banks and international reserve holdings. Thus, these vulnerabilities should be monitored and, to the extent possible, controlled. |
Date: | 2020–07–03 |
URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:20/113&r=all |
By: | Konstantinos Loizos (University of Athens (GR)) |
Abstract: | The link between banks’ liquidity and solvency is not adequately addressed in the literature, despite the central role of the interbank market in the spread of the recent crisis. This paper proposes a possible way by which the interbank rate and the required return on equity capital are determined, and are related to each other. Thereby, a link between liquidity and insolvency risk is derived on the grounds of Keynes's concept of ‘degree of confidence’ on held expectations about economic prospects. High degree of confidence and trust prevailing in the interbank market makes risk sharing possible at prices which render bank capital regulation ineffective in the rising phase of the cycle, and overly restricted in the downswing. Basel’s III higher capital, liquidity and leverage ratios might not be enough if measures, in the sense of Minsky’s Big Government-Big Bank, targeting overconfidence in booms and redressing the lack of confidence in the downturns are not taken into account. |
Keywords: | Degree of confidence, Interbank market, Liquidity preference, Insolvency risk, Financial cycles |
JEL: | E12 E32 G21 |
Date: | 2020–08 |
URL: | http://d.repec.org/n?u=RePEc:pke:wpaper:pkwp2017&r=all |
By: | Chwieroth, Jeffrey; Walter, Andrew |
Abstract: | Households face two politically salient risks associated with financial instability. The first risk, which has existed for perhaps centuries, is associated with the indirect effect of systemic banking crises on employment and income flows. The second risk arises from the direct effects of crises on asset prices and thus household wealth stocks. Historically, the second risk mainly affected only a small wealthy elite. We argue that the rapid expansion and financialization of middle class wealth since the mid-twentieth century mean that many voters now have “great expectations” regarding government responsibility to protect their wealth. The political risks of financial instability for incumbent governments have thus increased sharply, especially when institutional constraints hamper their ability to respond to voters’ new expectations. We show that the probability of incumbent governments facing significant institutional constraints retaining office after systemic banking crises has indeed fallen sharply in recent decades compared to the pre-1945 period. |
Keywords: | financial crisis; wealth; financialization; Political Economy; democracy; inequality |
JEL: | F50 P10 O50 |
Date: | 2020–06–08 |
URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:103759&r=all |
By: | Hao Tang; Anurag Pal; Lu-Feng Qiao; Tian-Yu Wang; Jun Gao; Xian-Min Jin |
Abstract: | Collateral debt obligation (CDO) has been one of the most commonly used structured financial products and is intensively studied in quantitative finance. By setting the asset pool into different tranches, it effectively works out and redistributes credit risks and returns to meet the risk preferences for different tranche investors. The copula models of various kinds are normally used for pricing CDOs, and the Monte Carlo simulations are required to get their numerical solution. Here we implement two typical CDO models, the single-factor Gaussian copula model and Normal Inverse Gaussian copula model, and by applying the conditional independence approach, we manage to load each model of distribution in quantum circuits. We then apply quantum amplitude estimation as an alternative to Monte Carlo simulation for CDO pricing. We demonstrate the quantum computation results using IBM Qiskit. Our work addresses a useful task in finance instrument pricing, significantly broadening the application scope for quantum computing in finance. |
Date: | 2020–08 |
URL: | http://d.repec.org/n?u=RePEc:arx:papers:2008.04110&r=all |
By: | Linwei Hu; Jie Chen; Joel Vaughan; Hanyu Yang; Kelly Wang; Agus Sudjianto; Vijayan N. Nair |
Abstract: | This article provides an overview of Supervised Machine Learning (SML) with a focus on applications to banking. The SML techniques covered include Bagging (Random Forest or RF), Boosting (Gradient Boosting Machine or GBM) and Neural Networks (NNs). We begin with an introduction to ML tasks and techniques. This is followed by a description of: i) tree-based ensemble algorithms including Bagging with RF and Boosting with GBMs, ii) Feedforward NNs, iii) a discussion of hyper-parameter optimization techniques, and iv) machine learning interpretability. The paper concludes with a comparison of the features of different ML algorithms. Examples taken from credit risk modeling in banking are used throughout the paper to illustrate the techniques and interpret the results of the algorithms. |
Date: | 2020–07 |
URL: | http://d.repec.org/n?u=RePEc:arx:papers:2008.04059&r=all |
By: | Berentsen, Aleksander; Markheim, Marina |
Abstract: | Peer-to-peer lending platforms are increasingly important alternatives to traditional forms of credit intermediation for small value loans. There are high hopes that they improve financial inclusion and provide better terms for borrowers. To study these hopes, we introduce altruistic investors into a peer- to-peer model of credit intermediation. We find that altruistic investors do not improve financial inclusion but that the borrowing rates are lower than the ones obtained with self-interested investors. Furthermore, investors with strong altruistic preferences are willing to finance projects which generate an expected loss to them. For a certain range of parameters, the model's allocation is observationally equivalent to a model with self-interested investors with low bargaining power. Outside of this range, the model generates allocations that are not incentive feasible in a model with self-interested investors. |
Keywords: | altruistic preferences, financial intermediation, financial inclusion, peer-to-peer platforms |
JEL: | D11 D14 D2 D40 O1 O12 O16 |
Date: | 2020–08–04 |
URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:102277&r=all |
By: | Charles Yuji HORIOKA (Research Institute for Economics and Business Administration, Kobe University, Institute of Social and Economic Research, Osaka University, Asian Growth Research Institute); Yoko NIIMI (Doshisha University and Asian Growth Research Institute) |
Abstract: | In this paper, we show that there was a rapid expansion of housing credit in Japan after 1970 and then consider what benefits and costs the rapid expansion of housing credit conferred on Japanese households and whether it was, on balance, a good thing or a bad thing for them. On the one hand, the rapid expansion of housing credit made it easier for households to purchase housing, which in turn enabled them to purchase housing at a younger age and enabled them to avoid the need to pay rent. On the other hand, the rapid expansion of housing credit increased the housing loan repayment burden of households, which in turn forced them to cut back on non-housing consumption and weakened their ability to accumulate financial assets in preparation for retirement. We conclude that, until now, the benefits of the expansion of housing credit seems to have outweighed the costs thereof, as a result of which it has increased the welfare of households but that there are some areas of concern and that the government should take the necessary steps to alleviate these concerns. |
Keywords: | Homeownership rate; Housing finance; Housing loans; Housing purchase; Mortgages; Rent |
JEL: | D14 E21 R21 |
Date: | 2020–08 |
URL: | http://d.repec.org/n?u=RePEc:kob:dpaper:dp2020-j12&r=all |
By: | Supriya Kapoor; Oana Peia |
Abstract: | We study the effects of the US Federal Reserve's large-scale asset purchase programs during 2008-2014 on bank liquidity creation. Banks create liquidity when they transform the liquid reserves resulted from quantitative easing into illiquid assets. As the composition of banks' loan portfolio affects the amount of liquidity it creates, the impact of quantitative easing on liquidity creation is not a priori clear. Using a difference-in-difference identification strategy, we find that banks that were more exposed to the policy increased lending relative to a control group. However, while the increase in lending was present across all three rounds of quantitative easing, we only find a strong effect on liquidity creation during the last round. This points to a weaker impact of quantitative easing on the real economy during the first two rounds, when affected banks transformed the reserves created through the asset purchase program into less illiquid assets, such as real estate mortgages. |
Keywords: | Large-scale asset purchases; Quantitative easing; Liquidity creation; Bank lending |
JEL: | E52 E58 G21 |
Date: | 2020–04 |
URL: | http://d.repec.org/n?u=RePEc:ucn:wpaper:202009&r=all |
By: | Bobasu, Alina; Venditti, Fabrizio; Arrigoni, Simone |
Abstract: | In this paper we assess the merits of financial condition indices constructed using simple averages versus a more sophisticated alternative that uses factor models with time varying parameters. Our analysis is based on data for 18 advanced and emerging economies at a monthly frequency covering about 70% of the world’s GDP. We use four criteria to assess the performance of these indicators, namely quantile regressions, Structural Vector Autoregressions, the ability of the indices to predict banking crises and their response to US monetary policy shocks. We find that averaging across the indicators of interest, using judgemental but intuitive weights, produces financial condition indices that are not inferior to, and actually perform better than, those constructed with more sophisticated statistical methods. JEL Classification: E32, E44, C11, C55 |
Keywords: | banking crises, financial conditions, quantile regressions, spillovers, SVARs |
Date: | 2020–08 |
URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20202451&r=all |
By: | Runshan Fu; Yan Huang; Param Vir Singh |
Abstract: | Big data and machine learning (ML) algorithms are key drivers of many fintech innovations. While it may be obvious that replacing humans with machine would increase efficiency, it is not clear whether and where machines can make better decisions than humans. We answer this question in the context of crowd lending, where decisions are traditionally made by a crowd of investors. Using data from Prosper.com, we show that a reasonably sophisticated ML algorithm predicts listing default probability more accurately than crowd investors. The dominance of the machine over the crowd is more pronounced for highly risky listings. We then use the machine to make investment decisions, and find that the machine benefits not only the lenders but also the borrowers. When machine prediction is used to select loans, it leads to a higher rate of return for investors and more funding opportunities for borrowers with few alternative funding options. We also find suggestive evidence that the machine is biased in gender and race even when it does not use gender and race information as input. We propose a general and effective "debasing" method that can be applied to any prediction focused ML applications, and demonstrate its use in our context. We show that the debiased ML algorithm, which suffers from lower prediction accuracy, still leads to better investment decisions compared with the crowd. These results indicate that ML can help crowd lending platforms better fulfill the promise of providing access to financial resources to otherwise underserved individuals and ensure fairness in the allocation of these resources. |
Date: | 2020–07 |
URL: | http://d.repec.org/n?u=RePEc:arx:papers:2008.04068&r=all |
By: | International Monetary Fund |
Abstract: | This technical note describes the financial stability analysis undertaken as part of the Financial Sector Assessment Program that primarily focuses on assessing the resilience of the banking system. Bank solvency appears relatively resilient to stress, although liquidity stress tests reveal some vulnerabilities given continued reliance on wholesale funding. The systemic risk analysis reveals a low degree of interconnectedness between the largest Australian banks and their global counterparts. However, the cross-border and interbank exposures data corroborates the systemic importance of the four largest banks and the view that the Australian banks are particularly vulnerable to external funding shocks. Cross-border analysis using country-level and individual bank-level supervisory data corroborates the view that the Australian banks are particularly vulnerable to external funding shocks given their dependence on wholesale funding from overseas. Policy recommendations made in the note include that additional investment in data and analytical tools would strengthen financial supervision and systemic risk oversight. |
Keywords: | Bank credit;Central banks;Bank liquidity;Financial soundness indicators;Systemically important financial institutions;Australian bank,liquidity,fund cost,GFC,solvency |
Date: | 2019–02–21 |
URL: | http://d.repec.org/n?u=RePEc:imf:imfscr:2019/051&r=all |
By: | Muñoz, Manuel A. |
Abstract: | Since the onset of the Global Financial Crisis, the presence of institutional investors in housing markets has steadily increased over time. Real estate funds (REIFs) and other housing investment firms leverage large-scale buy-to-rent investments in real estate assets that enable them to set prices in rental housing markets. A significant fraction of this funding is being provided in the form of non-bank lending (i.e., lending that is not subject to regulatory LTV limits). I develop a quantitative two-sector DSGE model that incorporates the main features of the real estate fund industry in the current context to study the effectiveness of dynamic LTV ratios as a macroprudential tool. Despite the comparatively low fraction of total property and debt held by REIFs, optimized LTV rules limiting the borrowing capacity of such funds are more effective in smoothing property prices, credit and business cycles than those affecting (indebted) households – borrowing limit. This finding is remarkably robust across alternative calibrations (of key parameters) and specifications of the model. The underlying reason behind such an important and unexpectedly robust finding relates to the strong interconnectedness of REIFs with various sectors of the economy. JEL Classification: E44, G23, G28 |
Keywords: | leverage, loan-to-value ratios, real estate funds, rental housing |
Date: | 2020–08 |
URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20202454&r=all |
By: | Mustapha Achibane (UIT - Université Ibn Tofaïl); Imane Allam (UIT - Université Ibn Tofaïl) |
Date: | 2019–09–28 |
URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-02901066&r=all |
By: | Sanna, Dario |
Abstract: | I propose a fast and parsimonious way to estimate the implied rate of return of common equity of single stocks and indexes, resulting from the combination of two easily computable ratios. |
Keywords: | Earnings Yield, Implied Cost of Equity, Price Earnings Ratio, Quadratic Roe Ratio, Roe Discount Model |
JEL: | G12 G32 G35 |
Date: | 2020–07–01 |
URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:102003&r=all |
By: | Dao, Kieu Oanh; Kieu, Le; Tu, Pham Thuy; Nguyen, V.C. |
Abstract: | This research was conducted to investigate the factors influencing the commercial bank’s competitive capacity in an emerging country. Data were collected from the domestic-owned commercial banks and foreign-owned commercial banks listed on Vietnam’s Stock Exchange over the period of nine years from 2010 to 2018. Three statistic approaches were employed to address econometrics issues and to improve the accuracy of the regression coefficients: Pooled Ordinary Least Square (Pooled OLS), Random Effects Model (REM), and Fixed Effects Model (FEM). To correct the diagnostics and endogeneity in the model, the study uses Generalized Least Square (GLS) and Generalized Method of Moments (GMM). In order to account for the degree of competitive capacity we use Lerner index. Results demonstrate that the impact of bank-specific characteristics on market power in banks is statistically significant, and there are substantial distinguishments of economic consideration among these factors. In addition, a bank with a higher level of competitive capacity in the previous year will outstandingly generate competitive capacity in the current year. Another possibility, a greater level foreign investment into the banks in the host country could further encourage competitive capacity in the banking system. Finally, economic growth rate has no impact on competitive capacity at a significant level of 5% while a positive effect from inflation on bank’s market power could be found. |
Date: | 2020–07–06 |
URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:8mz2y&r=all |