Research articles for the 2020-01-14
A Note on Monotone Mean-Variance Preferences for Continuous Processes
SSRN
We extend a recent result of Trybula and Zawisza [Mathematics of Operations Research, 44(3), 966-987, 2019], who investigate a continuous-time portfolio optimization problem under monotone mean-variance preferences. Their main finding is that the optimal strategies for monotone and classical mean-variance preferences coincide in a stochastic factor model for the financial market. We generalize this result to any model for the financial market where stock prices are continuous.
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We extend a recent result of Trybula and Zawisza [Mathematics of Operations Research, 44(3), 966-987, 2019], who investigate a continuous-time portfolio optimization problem under monotone mean-variance preferences. Their main finding is that the optimal strategies for monotone and classical mean-variance preferences coincide in a stochastic factor model for the financial market. We generalize this result to any model for the financial market where stock prices are continuous.
An Improved Method to Predict Assignment of Stocks into Russell Indexes
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A growing literature uses the Russell 1000/2000 reconstitution event as an identification strategy to investigate corporate finance and asset pricing questions. To implement this identification strategy, researchers need to approximate the ranking variable used to assign stocks to indexes. We develop a procedure that predicts assignment to the Russell 1000/2000 with significant improvements relative to previous approaches. We apply this methodology to extend the tests in Ben-David, Franzoni, and Moussawi (2018).
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A growing literature uses the Russell 1000/2000 reconstitution event as an identification strategy to investigate corporate finance and asset pricing questions. To implement this identification strategy, researchers need to approximate the ranking variable used to assign stocks to indexes. We develop a procedure that predicts assignment to the Russell 1000/2000 with significant improvements relative to previous approaches. We apply this methodology to extend the tests in Ben-David, Franzoni, and Moussawi (2018).
Approximating intractable short ratemodel distribution with neural network
arXiv
arXiv
We propose an algorithm which predicts each subsequent time step relative to the previous time step of intractable short rate model (when adjusted for drift and overall distribution of previous percentile result) and show that the method achieves superior outcomes to the unbiased estimate both on the trained dataset and different validation data.
Bank Mergers, Lender Concentration, and Corporate Acquisitions
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A merger between the firm’s two existing lenders increases its lender concentration, creating a new lender with more incentives and bargaining power to monitor. I show that such exogenous increases in lender concentration lower the borrower’s propensity to pursue public takeovers. This result is mainly pronounced for firms with more managerial discretion and when the merger involves a lead arranger, suggesting that lender monitoring is indeed intensified. Lender concentration not only reduces public takeovers that are value-destroying to shareholders but also value-enhancing ones. Additionally, affected firms exhibit lower credit risk during the post period. These results suggest that lender monitoring mitigates managerial agency costs and improves credit conditions, yet sometimes leads to over-conservative firm policies destroying shareholder value.
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A merger between the firm’s two existing lenders increases its lender concentration, creating a new lender with more incentives and bargaining power to monitor. I show that such exogenous increases in lender concentration lower the borrower’s propensity to pursue public takeovers. This result is mainly pronounced for firms with more managerial discretion and when the merger involves a lead arranger, suggesting that lender monitoring is indeed intensified. Lender concentration not only reduces public takeovers that are value-destroying to shareholders but also value-enhancing ones. Additionally, affected firms exhibit lower credit risk during the post period. These results suggest that lender monitoring mitigates managerial agency costs and improves credit conditions, yet sometimes leads to over-conservative firm policies destroying shareholder value.
Banking Supervision, Monetary Policy and Risk-Taking: Big Data Evidence from 15 Credit Registers
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We analyse the effects of supranational versus national banking supervision on credit supply, and its interactions with monetary policy. For identification, we exploit: (i) a new, proprietary dataset based on 15 European credit registers; (ii) the institutional change leading to the centralisation of European banking supervision; (iii) high-frequency monetary policy surprises; (iv) differences across euro area countries, also vis-Ã -vis non-euro area countries. We show that supranational supervision reduces credit supply to firms with very high ex-ante and ex-post credit risk, while stimulating credit supply to firms without loan delinquencies. Moreover, the increased risk-sensitivity of credit supply driven by centralised supervision is stronger for banks operating in stressed countries. Exploiting heterogeneity across banks, we find that the mechanism driving the results is higher quantity and quality of human resources available to the supranational supervisor rather than changes in incentives due to the reallocation of supervisory responsibility to the new institution. Finally, there are crucial complementarities between supervision and monetary policy: centralised supervision offsets excessive bank risk-taking induced by a more accommodative monetary policy stance, but does not offset more productive risk-taking. Overall, we show that using multiple credit registers - first time in the literature - is crucial for external validity.
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We analyse the effects of supranational versus national banking supervision on credit supply, and its interactions with monetary policy. For identification, we exploit: (i) a new, proprietary dataset based on 15 European credit registers; (ii) the institutional change leading to the centralisation of European banking supervision; (iii) high-frequency monetary policy surprises; (iv) differences across euro area countries, also vis-Ã -vis non-euro area countries. We show that supranational supervision reduces credit supply to firms with very high ex-ante and ex-post credit risk, while stimulating credit supply to firms without loan delinquencies. Moreover, the increased risk-sensitivity of credit supply driven by centralised supervision is stronger for banks operating in stressed countries. Exploiting heterogeneity across banks, we find that the mechanism driving the results is higher quantity and quality of human resources available to the supranational supervisor rather than changes in incentives due to the reallocation of supervisory responsibility to the new institution. Finally, there are crucial complementarities between supervision and monetary policy: centralised supervision offsets excessive bank risk-taking induced by a more accommodative monetary policy stance, but does not offset more productive risk-taking. Overall, we show that using multiple credit registers - first time in the literature - is crucial for external validity.
Bounds on Multi-asset Derivatives via Neural Networks
arXiv
arXiv
Using neural networks, we compute bounds on the prices of multi-asset derivatives given information on prices of related payoffs. As a main example, we focus on European basket options and include information on the prices of other similar options, such as spread options and/or basket options on subindices. We show that, in most cases, adding further constraints gives rise to bounds that are considerably tighter and discuss the maximizing/minimizing copulas achieving such bounds. Our approach follows the literature on constrained optimal transport and, in particular, builds on a recent paper by Eckstein and Kupper (2019, Appl. Math. Optim.).
Capital, Liquidity and Prudential Regulation (Presentation Slides)
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This presentation addresses the following issues: How does bank capital affect bank liquidity creation? How does bank capital affect bank performance during crises / bad times and normal times? What are implications for bank regulation?
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This presentation addresses the following issues: How does bank capital affect bank liquidity creation? How does bank capital affect bank performance during crises / bad times and normal times? What are implications for bank regulation?
Climate Emergency and Central Banks
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Although there are numerous tools theoretically available to central banks (depending on their current mandates) to address systemic financial risks posed by climate change and to green the financial sector, their use has been limited to predominantly emerging and developing countries most likely to be exposed to climate change. The central banks in advanced economies are increasingly likely to consider climate-related risks impacting the financial system and to support internationally consistent green disclosure standards. However, they see themselves as lacking democratic legitimacy to drive the transition to a low-carbon economy. It remains to be seen whether central banks could be the second-best solution if the governments fail to deliver on climate action. This might not be possible without expanding their mandates and ensuring they remain accountable and not overburdened with conflicting goals.
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Although there are numerous tools theoretically available to central banks (depending on their current mandates) to address systemic financial risks posed by climate change and to green the financial sector, their use has been limited to predominantly emerging and developing countries most likely to be exposed to climate change. The central banks in advanced economies are increasingly likely to consider climate-related risks impacting the financial system and to support internationally consistent green disclosure standards. However, they see themselves as lacking democratic legitimacy to drive the transition to a low-carbon economy. It remains to be seen whether central banks could be the second-best solution if the governments fail to deliver on climate action. This might not be possible without expanding their mandates and ensuring they remain accountable and not overburdened with conflicting goals.
Continuous-Time Portfolio Choice Under Monotone Mean-Variance Preferences-Stochastic Factor Case
arXiv
arXiv
We consider an incomplete market with a nontradable stochastic factor and a continuous time investment problem with an optimality criterion based on monotone mean-variance preferences. We formulate it as a stochastic differential game problem and use Hamilton-Jacobi-Bellman-Isaacs equations to find an optimal investment strategy and the value function. What is more, we show that our solution is also optimal for the classical Markowitz problem and every optimal solution for the classical Markowitz problem is optimal also for the monotone mean-variance preferences. These results are interesting because the original Markowitz functional is not monotone, and it was observed that in the case of a static one-period optimization problem the solutions for those two functionals are different. In addition, we determine explicit Markowitz strategies in the square root factor models.
Do Role Models Affect Risk-Taking Behavior? the Case of Minorities
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We show that social changes, like the success of role models, affects household financial decisions. Specifically, President Obama is a role model for minorities. Minorities historically underinvest in equity, which contributes to the widening racial wealth gap. Obama's election in 2008 is a positive social change for minorities that should encourage investing. Indeed, post-2008 and compared to White Americans, minorities, have a higher propensity to increase risk tolerance and to increase allocations to risky assets and savings, a lower propensity to exit the market, and trade more often. Overall, we show that societal factors affect the racial stock ownership gap.
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We show that social changes, like the success of role models, affects household financial decisions. Specifically, President Obama is a role model for minorities. Minorities historically underinvest in equity, which contributes to the widening racial wealth gap. Obama's election in 2008 is a positive social change for minorities that should encourage investing. Indeed, post-2008 and compared to White Americans, minorities, have a higher propensity to increase risk tolerance and to increase allocations to risky assets and savings, a lower propensity to exit the market, and trade more often. Overall, we show that societal factors affect the racial stock ownership gap.
ETF Trading and the Bifurcation of Liquidity
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Passively managed exchange traded funds (ETFs) are a financial technology that has risen dramatically in the last two decades. Over the same period liquid stocks have become more liquid while illiquid stocks have not experienced a similar improvement. We model investors shifting from trading individual stocks to trading ETFs and generate predictions consistent with the documented bifurcation in liquidity. Using daily ETF creation and redemption activity, we provide empirical evidence that closely matches the model's predictions. The results show that the effects of ETFs on underlying asset markets are driven by their index replication strategy.
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Passively managed exchange traded funds (ETFs) are a financial technology that has risen dramatically in the last two decades. Over the same period liquid stocks have become more liquid while illiquid stocks have not experienced a similar improvement. We model investors shifting from trading individual stocks to trading ETFs and generate predictions consistent with the documented bifurcation in liquidity. Using daily ETF creation and redemption activity, we provide empirical evidence that closely matches the model's predictions. The results show that the effects of ETFs on underlying asset markets are driven by their index replication strategy.
Expansionary Yet Different: Credit Supply and Real Effects of Negative Interest Rate Policy
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We show that negative interest rate policy (NIRP) has expansionary effects on bank credit supply-and the real economy-through a portfolio rebalancing channel, and that, by shifting down and flattening the yield curve, NIRP differs from rate cuts just above the zero lower bound. For identification, we exploit ECB's NIRP and matched administrative datasets-including the credit register-from Italy, severely hit by the Eurozone crisis. NIRP affects banks with higher ex-ante net short-term interbank positions or, more broadly, more liquid balance-sheets. NIRP-affected banks rebalance their portfolios from liquid assets to lending, especially to ex-ante riskier and smaller firms-without
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We show that negative interest rate policy (NIRP) has expansionary effects on bank credit supply-and the real economy-through a portfolio rebalancing channel, and that, by shifting down and flattening the yield curve, NIRP differs from rate cuts just above the zero lower bound. For identification, we exploit ECB's NIRP and matched administrative datasets-including the credit register-from Italy, severely hit by the Eurozone crisis. NIRP affects banks with higher ex-ante net short-term interbank positions or, more broadly, more liquid balance-sheets. NIRP-affected banks rebalance their portfolios from liquid assets to lending, especially to ex-ante riskier and smaller firms-without
Foreign Currency Loans and Credit Risk: Evidence from U.S. Banks
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When firms borrow in foreign currency, exchange rate changes can affect their ability to repay the debt. Loan-level data from U.S. banks' regulatory filings show that a 10 percent depreciation of the local currency quarter-to-quarter increases the probability that a firm becomes past due on its loans by 37 basis points for firms with foreign currency debt relative to those with local currency debt. Because firms do not perfectly hedge, exchange rate risk of the borrowers translates into credit risk for banks. Firms are more likely to borrow in foreign currency if they have foreign income and if a UIP deviation makes foreign currency loans cheaper. The paper establishes additional facts on large U.S. banks' international corporate loan portfolios, offering a more comprehensive perspective than syndicated loan data.
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When firms borrow in foreign currency, exchange rate changes can affect their ability to repay the debt. Loan-level data from U.S. banks' regulatory filings show that a 10 percent depreciation of the local currency quarter-to-quarter increases the probability that a firm becomes past due on its loans by 37 basis points for firms with foreign currency debt relative to those with local currency debt. Because firms do not perfectly hedge, exchange rate risk of the borrowers translates into credit risk for banks. Firms are more likely to borrow in foreign currency if they have foreign income and if a UIP deviation makes foreign currency loans cheaper. The paper establishes additional facts on large U.S. banks' international corporate loan portfolios, offering a more comprehensive perspective than syndicated loan data.
Global Market Inefficiencies
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Using point-in-time accounting data, we estimate monthly fair values of 25,000+ stocks from 36 countries. A trading strategy based on deviations from fair value earns significant risk-adjusted returns ("alpha") in most regions, especially the Asia Pacific, that are unrelated to known anomalies. The strategy's 40â??70 basis point per month alpha difference between emerging and developed markets contrast with prior research findings. A country's pre-transaction-cost alpha is positively related to its trading costs, but exceeds country-specific institutional trading costs. Thus, global equity markets are inefficient, particularly in countries with quantifiable market frictions, like trading costs, that deter arbitrageurs.
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Using point-in-time accounting data, we estimate monthly fair values of 25,000+ stocks from 36 countries. A trading strategy based on deviations from fair value earns significant risk-adjusted returns ("alpha") in most regions, especially the Asia Pacific, that are unrelated to known anomalies. The strategy's 40â??70 basis point per month alpha difference between emerging and developed markets contrast with prior research findings. A country's pre-transaction-cost alpha is positively related to its trading costs, but exceeds country-specific institutional trading costs. Thus, global equity markets are inefficient, particularly in countries with quantifiable market frictions, like trading costs, that deter arbitrageurs.
Global Risk Sharing Through Trade in Goods and Assets: Theory and Evidence
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Exporting not only provides firms with profit opportunities, but can also provide for risk diversification if demand is imperfectly correlated across countries. This paper shows that the correlation pattern of demand shocks across countries constitutes a hitherto unexplored source of comparative advantage that shapes trade flows and persists even if financial markets are complete. With exporters making market- specific choices under uncertainty, countries whose shocks are riskier, in the sense that they contribute more to aggregate volatility, are less attractive destinations for both investment and exports. A gravity-type regression lends support to the hypothesis that, conditional on trade costs and market size, exporters sell smaller quantities in riskier destinations. I develop a general equilibrium trade model, with risk-averse investors and complete asset markets, which rationalizes this novel fact. A counterfactual experiment shows that risk-based comparative advantage accounts for 4.6% of global trade. Country-level exports would grow by -13% to +10% if all diversification opportunities were eliminated, entailing welfare losses in the range of .4% to 16%.
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Exporting not only provides firms with profit opportunities, but can also provide for risk diversification if demand is imperfectly correlated across countries. This paper shows that the correlation pattern of demand shocks across countries constitutes a hitherto unexplored source of comparative advantage that shapes trade flows and persists even if financial markets are complete. With exporters making market- specific choices under uncertainty, countries whose shocks are riskier, in the sense that they contribute more to aggregate volatility, are less attractive destinations for both investment and exports. A gravity-type regression lends support to the hypothesis that, conditional on trade costs and market size, exporters sell smaller quantities in riskier destinations. I develop a general equilibrium trade model, with risk-averse investors and complete asset markets, which rationalizes this novel fact. A counterfactual experiment shows that risk-based comparative advantage accounts for 4.6% of global trade. Country-level exports would grow by -13% to +10% if all diversification opportunities were eliminated, entailing welfare losses in the range of .4% to 16%.
God Insures Those Who Pay? Formal Insurance and Religious Offerings in Ghana
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This paper provides experimental support for the hypothesis that insurance can be a motive
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This paper provides experimental support for the hypothesis that insurance can be a motive
Heterogeneity in Decentralized Asset Markets
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We study a search and bargaining model of asset markets in which investors' heterogeneous valuations for the asset are drawn from an arbitrary distribution. We present a solution technique that makes the model fully tractable, and allows us to provide a complete characterization of the unique equilibrium, in closed-form, both in and out of steady-state. Using this characterization, we derive several novel implications that highlight the important of heterogeneity. In particular, we show how some investors endogenously emerge as intermediaries, even though they have no advantage in contacting other agents or holding inventory; and we show how heterogeneity magnifies the impact of search frictions on asset prices, misallocation, and welfare.
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We study a search and bargaining model of asset markets in which investors' heterogeneous valuations for the asset are drawn from an arbitrary distribution. We present a solution technique that makes the model fully tractable, and allows us to provide a complete characterization of the unique equilibrium, in closed-form, both in and out of steady-state. Using this characterization, we derive several novel implications that highlight the important of heterogeneity. In particular, we show how some investors endogenously emerge as intermediaries, even though they have no advantage in contacting other agents or holding inventory; and we show how heterogeneity magnifies the impact of search frictions on asset prices, misallocation, and welfare.
How Do Machine Learning and Non-Traditional Data Affect Credit Scoring? New Evidence from a Chinese Fintech Firm
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This paper compares the predictive power of credit scoring models based on machine learning techniques with that of traditional loss and default models. Using proprietary transaction-level data from a leading fintech company in China for the period between May and September 2017, we test the performance of different models to predict losses and defaults both in normal times and when the economy is subject to a shock. In particular, we analyse the case of an (exogenous) change in regulation policy on shadow banking in China that caused lending to decline and credit conditions to deteriorate. We find that the model based on machine learning and non-traditional data is better able to predict losses and defaults than traditional models in the presence of a negative shock to the aggregate credit supply. One possible reason for this is that machine learning can better mine the non-linear relationship between variables in a period of stress. Finally, the comparative advantage of the model that uses the fintech credit scoring technique based on machine learning and big data tends to decline for borrowers with a longer credit history.
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This paper compares the predictive power of credit scoring models based on machine learning techniques with that of traditional loss and default models. Using proprietary transaction-level data from a leading fintech company in China for the period between May and September 2017, we test the performance of different models to predict losses and defaults both in normal times and when the economy is subject to a shock. In particular, we analyse the case of an (exogenous) change in regulation policy on shadow banking in China that caused lending to decline and credit conditions to deteriorate. We find that the model based on machine learning and non-traditional data is better able to predict losses and defaults than traditional models in the presence of a negative shock to the aggregate credit supply. One possible reason for this is that machine learning can better mine the non-linear relationship between variables in a period of stress. Finally, the comparative advantage of the model that uses the fintech credit scoring technique based on machine learning and big data tends to decline for borrowers with a longer credit history.
How Monetary Policy Shaped the Housing Boom
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Between 2003 and 2006, the Federal Reserve raised rates by 4.25%. Yet it was precisely during this period that the housing boom accelerated, fueled by rapid growth in mortgage lending. There is deep disagreement about how, or even if, monetary policy impacted the boom. Using heterogeneity in banks' exposures to the deposits channel of monetary policy, we show that Fed tightening induced a large reduction in banks' deposit funding, leading them to contract new on-balance-sheet lending for home purchases by 26%. However, an unprecedented expansion in privately-securitized loans, led by nonbanks, largely offset this contraction. Since privately-securitized loans are neither GSE-insured nor deposit-funded, they are run-prone, which made the mortgage market fragile. Consistent with our theory, the re-emergence of privately-securitized mortgages has closely tracked the recent increase in rates.
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Between 2003 and 2006, the Federal Reserve raised rates by 4.25%. Yet it was precisely during this period that the housing boom accelerated, fueled by rapid growth in mortgage lending. There is deep disagreement about how, or even if, monetary policy impacted the boom. Using heterogeneity in banks' exposures to the deposits channel of monetary policy, we show that Fed tightening induced a large reduction in banks' deposit funding, leading them to contract new on-balance-sheet lending for home purchases by 26%. However, an unprecedented expansion in privately-securitized loans, led by nonbanks, largely offset this contraction. Since privately-securitized loans are neither GSE-insured nor deposit-funded, they are run-prone, which made the mortgage market fragile. Consistent with our theory, the re-emergence of privately-securitized mortgages has closely tracked the recent increase in rates.
Liquidity Requirements and the Interbank Loan Market: An Experimental Investigation (Presentation Slides)
SSRN
This conference presentation reports on results of an experiment that illustrates costs and benefits of liquidity regulation. These costs and benefits may come out of interbank market equilibrium behavior.
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This conference presentation reports on results of an experiment that illustrates costs and benefits of liquidity regulation. These costs and benefits may come out of interbank market equilibrium behavior.
Liquidity in the Financial System Panel (Presentation Slides)
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This presentation focuses on sources of liquidity and illiquidity in financial markets, price risk and liquidity risk, crowding in financial markets and approaches to modeling crowding.
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This presentation focuses on sources of liquidity and illiquidity in financial markets, price risk and liquidity risk, crowding in financial markets and approaches to modeling crowding.
Market Efficiency in the Age of Big Data
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Modern investors face a high-dimensional prediction problem: thousands of observable variables are potentially relevant for forecasting. We reassess the conventional wisdom on market efficiency in light of this fact. In our model economy, which resembles a typical machine learning setting, N assets have cash flows that are a linear function of J firm characteristics, but with uncertain coefficients. Risk-neutral Bayesian investors impose shrinkage (ridge regression) or sparsity (Lasso) when they estimate the J coefficients of the model and use them to price assets. When J is comparable in size to N, returns appear cross-sectionally predictable using firm characteristics to an econometrician who analyzes data from the economy ex post. A factor zoo emerges even without p-hacking and data-mining. Standard in-sample tests of market efficiency reject the no-predictability null with high probability, despite the fact that investors optimally use the information available to them in real time. In contrast, out-of-sample tests retain their economic meaning.
SSRN
Modern investors face a high-dimensional prediction problem: thousands of observable variables are potentially relevant for forecasting. We reassess the conventional wisdom on market efficiency in light of this fact. In our model economy, which resembles a typical machine learning setting, N assets have cash flows that are a linear function of J firm characteristics, but with uncertain coefficients. Risk-neutral Bayesian investors impose shrinkage (ridge regression) or sparsity (Lasso) when they estimate the J coefficients of the model and use them to price assets. When J is comparable in size to N, returns appear cross-sectionally predictable using firm characteristics to an econometrician who analyzes data from the economy ex post. A factor zoo emerges even without p-hacking and data-mining. Standard in-sample tests of market efficiency reject the no-predictability null with high probability, despite the fact that investors optimally use the information available to them in real time. In contrast, out-of-sample tests retain their economic meaning.
Market Efficiency in the Age of Big Data
SSRN
Modern investors face a high-dimensional prediction problem: thousands of observable variables are potentially relevant for forecasting. We reassess the conventional wisdom on market efficiency in light of this fact. In our model economy, which resembles a typical machine learning setting, N assets have cash flows that are a linear function of J firm characteristics, but with uncertain coefficients. Risk-neutral Bayesian investors impose shrinkage (ridge regression) or sparsity (Lasso) when they estimate the J coefficients of the model and use them to price assets. When J is comparable in size to N, returns appear cross-sectionally predictable using firm characteristics to an econometrician who analyzes data from the economy ex post. A factor zoo emerges even without p-hacking and data-mining. Standard in-sample tests of market efficiency reject the no-predictability null with high probability, despite the fact that investors optimally use the information available to them in real time. In contrast, out-of-sample tests retain their economic meaning.
SSRN
Modern investors face a high-dimensional prediction problem: thousands of observable variables are potentially relevant for forecasting. We reassess the conventional wisdom on market efficiency in light of this fact. In our model economy, which resembles a typical machine learning setting, N assets have cash flows that are a linear function of J firm characteristics, but with uncertain coefficients. Risk-neutral Bayesian investors impose shrinkage (ridge regression) or sparsity (Lasso) when they estimate the J coefficients of the model and use them to price assets. When J is comparable in size to N, returns appear cross-sectionally predictable using firm characteristics to an econometrician who analyzes data from the economy ex post. A factor zoo emerges even without p-hacking and data-mining. Standard in-sample tests of market efficiency reject the no-predictability null with high probability, despite the fact that investors optimally use the information available to them in real time. In contrast, out-of-sample tests retain their economic meaning.
Nowcasting Net Asset Values: The Case of Private Equity
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We apply advances in analysis of mix frequency and sparse data to estimate "unsmoothed'' private equity (PE) Net Asset Values (NAVs) at the weekly frequency for individual funds. Using simulations and a large sample of buyout and venture funds, we show that our method yields superior estimates of fund asset values than a simple approach based on comparable public asset and as-reported NAVs. Our method easily accommodates additional data on PE fund portfolios, such as individual holdings, relevant mergers and acquisitions, secondary trades with fund stakes. The method is easily extended to other illiquid portfolios that are subject to appraisal bias while generating irregular and infrequent cash flows. We find significant variation in systematic and idiosyncratic risk exposures across PE funds and through time. In particular, the risk-return profile based on the samples from the 1990s is not representative of currently operating funds.
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We apply advances in analysis of mix frequency and sparse data to estimate "unsmoothed'' private equity (PE) Net Asset Values (NAVs) at the weekly frequency for individual funds. Using simulations and a large sample of buyout and venture funds, we show that our method yields superior estimates of fund asset values than a simple approach based on comparable public asset and as-reported NAVs. Our method easily accommodates additional data on PE fund portfolios, such as individual holdings, relevant mergers and acquisitions, secondary trades with fund stakes. The method is easily extended to other illiquid portfolios that are subject to appraisal bias while generating irregular and infrequent cash flows. We find significant variation in systematic and idiosyncratic risk exposures across PE funds and through time. In particular, the risk-return profile based on the samples from the 1990s is not representative of currently operating funds.
On Fintech and Financial Inclusion
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The cost of financial intermediation has declined in recent years thanks to technological progress and increased
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The cost of financial intermediation has declined in recent years thanks to technological progress and increased
On the Interaction of Bank Liquidity and Capital (Presentation Slides)
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This conference presentation summarizes research on the impact of liquidity shocks on banks' capital and vice versa. From a regulatory point of view the question is whether capital and liquidity are complements or substitutes? The empirical work reviewed here asks how will banks respond to tighter regulatory constraints? A distinction is made between small and large banks.
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This conference presentation summarizes research on the impact of liquidity shocks on banks' capital and vice versa. From a regulatory point of view the question is whether capital and liquidity are complements or substitutes? The empirical work reviewed here asks how will banks respond to tighter regulatory constraints? A distinction is made between small and large banks.
Optimal Forbearance of Bank Resolution
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We analyze optimal strategic delay of bank resolution ('grq forbearance') and deposit insurance coverage. After bad news on the bank's assets, depositors fear for the uninsured part of their deposit and withdraw while the regulator observes withdrawals and needs to decide when to intervene. Optimal policy maximizes the joint value of the demand deposit contract and the insurance fund to avoid inefficient risk-shifting towards the fund while also preventing inefficient runs. Under low insurance coverage, the optimal intervention policy is never to intervene (laissez-faire). Optimal deposit insurance coverage is always interior.
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We analyze optimal strategic delay of bank resolution ('grq forbearance') and deposit insurance coverage. After bad news on the bank's assets, depositors fear for the uninsured part of their deposit and withdraw while the regulator observes withdrawals and needs to decide when to intervene. Optimal policy maximizes the joint value of the demand deposit contract and the insurance fund to avoid inefficient risk-shifting towards the fund while also preventing inefficient runs. Under low insurance coverage, the optimal intervention policy is never to intervene (laissez-faire). Optimal deposit insurance coverage is always interior.
Optimal Volatility Dependent Derivatives in the Stochastic Volatility Model
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We consider derivatives that maximize an investor’s expected utility in the stochastic volatility model. We show that the optimal derivative that depends on the stock and its variance significantly outperforms the optimal derivative that depends on the stock only. Such derivatives yield a much higher certainty equivalent return. This implies that investors could benefit from structured financial products that are constructed along these ideas.
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We consider derivatives that maximize an investor’s expected utility in the stochastic volatility model. We show that the optimal derivative that depends on the stock and its variance significantly outperforms the optimal derivative that depends on the stock only. Such derivatives yield a much higher certainty equivalent return. This implies that investors could benefit from structured financial products that are constructed along these ideas.
Re-Evaluation of Capital Adequacy Ratio (CAR) in the Context of Increasing Nonpeforming Loans in Turkey (Türkiye’de Artan Sorunlu Krediler Bağlamında Sermaye Yeterliliği Rasyosunun (SYR) Yeniden Değerlendirilmesi)
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English Abstract: Banking sector restructuring program, which was applied after 2000 and 2001 crisis in Turkey, initiated a process of radical changes that occurred in the functions of Turkish Banking Sector (TBS). As a result of this, TBS has been in a growth process of which financial indicators were positive. However, the global crisis that emerged in 2008 was a new period of difficulty that slowed down the growth of TBS. With the contribution of the measures taken, 2008 crisis was overcome without heavy damage. On the other hand, the national and international environment, which were started to be deteriorated in 2018, has created new challenges recently. The slowdown in credit volume, credit/deposit ratio above 100%, and as a result of these, nonperforming loans (NPL) exceeding TL 111 billion are the most prominent ones. Therefore, the initiation and rapid implementation of a new and comprehensive credit restructuring process in TBS has become inevitable. As a matter of fact, various initiatives related to the structuring of NPLs are reflected to the public.This study aims to reconsider CAR practice in Turkey, which is targeted as 12% currently, in the context of requirement of restructuring of NPLs. In the study, the analysis has been made with using 2019 June data published by Banking Regulation and Supervision Agency.As of June 2019, there is TL 116.2 billion NPLs in total credits of which volume is TL 2.5 trillion. The ratio of NPLs/total credits is 4.6%. In the same period, liquidity surplus is TL 1.5 trillion and CAR is 17.73%. On the other hand, volume of non-performing loans in TBS is estimated to be USD 40 billion (TL 232 billion) with the addition of distressed credits which are not in legal stage. Restructuring is a necessity to provide collection to existing NPLs, prevent further new flows to NPLs and prevent increase in NPLs.ın order to increase the capability of banks in restructuring of NPL, it is recommended that the 12% target CAR implemented in TBS should be reduced to 8% which is the international standard adopted by BASEL Banking Supervision Committee. Thus, banks will be able to restructure NPL amounting to TL 116.2 billion and distressed credits TL 232 billion without approaching to 12% CAR limit. As an important point in terms of credit restructuring, TBS also has sufficient liquidity.Due to the provision allocated for NPLs currently, restructuring will not have any impact on banks in the short term, and in the medium term, profitability of banks will increase as some of the loans are converted to live loans because of reversal of some provisions. Increased profitability will provide an increase in CAR by making a positive contribution. After a transition period of 2-3 years, it can be considered again that CAR can be increased gradually.Turkish Abstract: Türkiye’de yaşanan 2000 ve 2001 krizleri sonrasında uygulanan bankacılık sektörü yeniden yapılandırma programı, Türk Bankacılık Sektörünün (TBS) aracılık işlevlerinde köklü değişimlerin yaşandığı bir süreci başlatmıştır. Bunun sonucunda ise TBS’nin finansal göstergelerinde olumlu yansımaların görüldüğü büyüme sürecine girilmiştir. Ancak 2008 yılında ortaya çıkan küresel kriz TBS’nin büyümesini yavaşlatan yeni bir zorluk dönemi olmuştur. Alınan tedbirlerin de katkısıyla birlikte 2008 krizi ağır hasar alınmadan atlatılmıştır. Diğer taraftan, 2018 yılında bozulmaya başlayan ulusal ve uluslararası ortam, son dönemde yeni zorlukların oluşmasına neden olmuştur. Kredi hacmindeki yavaşlama, kredi/mevduat oranının %100’ün üzerinde seyretmesi ve bunların bir sonucu olarak 111 milyar TL’nin üzerine çıkan sorunlu krediler bu zorluklardan en göze çarpanlarıdır. Dolayısıyla, TBS’de yeni ve kapsamlı bir kredi yapılandırma sürecinin başlatılması ve hızla uygulanması kaçınılmaz hale gelmiştir. Nitekim sorunlu kredilerin yapılandırılması ile ilgili çeşitli girişimler kamuya yansımaktadır.Bu çalışma bir zorunluluk haline gelen sorunlu kredilerin yapılandırılması bağlamında, Türkiye’de yürürlükte bulunan %12 hedef SYR uygulamasını yeniden ele almayı amaçlamaktadır. Çalışmada Bankacılık Düzenleme ve Denetleme Kurumu tarafından yayınlanan 2019 Haziran verileri kullanılarak analiz yapılmıştır.2019 Haziran itibarıyla 2,5 trilyon TL büyüklüğe ulaşan kredi hacmi içinde 116,2 milyar TL takipte kredi bulunmaktadır. Takipteki kredilerin/kredilere oranı %4,6’dır. Aynı dönemde likidite fazlası 1,5 trilyon TL, SYR ise %17,73’tür. Diğer taraftan, takibe dönüşmemiş olanların eklenmesiyle birlikte TBS’deki sorunlu kredilerin büyüklüğünün 40 milyar USD (232 milyar TL) olduğu tahmin edilmektedir. Mevcut sorunlu kredilerin tahsil edilmesinin önünü açmak, yeni sorunlu kredilerin oluşmasını ve sorunlu kredilerin daha fazla artmasını önlemek için yeniden yapılandırma bir gerekliliktir.Sorunlu kredilerin yeniden yapılandırılmasında, bankaların kabiliyetlerini artırmak için, TBS’de uygulanan %12 hedef SYR’nin, BASEL Bankacılık Gözetim Komitesi tarafından benimsenen %8 seviyesine çekilmesi önerilmektedir. Böylece, bankalar %12 SYR sınırına yaklaşmaksızın 116,2 milyar TL olan takipteki kredileri ve toplam 232 milyar TL seviyesinde olan sorunlu kredileri yapılandırabilecektir. Yapılandırma açısından önemli bir nokta olarak TBS’nin yeterli likiditesi de bulunmaktadır. Sorunlu kredilere mevcut durumda karşılık ayrılması nedeniyle, yeniden yapılandırma işlemleri kısa dönemde bankalar üzerinde etki oluşturmayacak, orta vadede ise bazı kredilerin canlı krediye dönüşmesi ile birlikte karşılıklar azalacağı için karlılıklar artacaktır. Artan karlılık ise SYR’ye pozitif katkı yaparak yükselmesini sağlayacaktır. 2-3 yıllık bir geçiş süreci sonunda SYR’nin kademeli olarak yeniden artırılabileceği değerlendirilmektedir.
SSRN
English Abstract: Banking sector restructuring program, which was applied after 2000 and 2001 crisis in Turkey, initiated a process of radical changes that occurred in the functions of Turkish Banking Sector (TBS). As a result of this, TBS has been in a growth process of which financial indicators were positive. However, the global crisis that emerged in 2008 was a new period of difficulty that slowed down the growth of TBS. With the contribution of the measures taken, 2008 crisis was overcome without heavy damage. On the other hand, the national and international environment, which were started to be deteriorated in 2018, has created new challenges recently. The slowdown in credit volume, credit/deposit ratio above 100%, and as a result of these, nonperforming loans (NPL) exceeding TL 111 billion are the most prominent ones. Therefore, the initiation and rapid implementation of a new and comprehensive credit restructuring process in TBS has become inevitable. As a matter of fact, various initiatives related to the structuring of NPLs are reflected to the public.This study aims to reconsider CAR practice in Turkey, which is targeted as 12% currently, in the context of requirement of restructuring of NPLs. In the study, the analysis has been made with using 2019 June data published by Banking Regulation and Supervision Agency.As of June 2019, there is TL 116.2 billion NPLs in total credits of which volume is TL 2.5 trillion. The ratio of NPLs/total credits is 4.6%. In the same period, liquidity surplus is TL 1.5 trillion and CAR is 17.73%. On the other hand, volume of non-performing loans in TBS is estimated to be USD 40 billion (TL 232 billion) with the addition of distressed credits which are not in legal stage. Restructuring is a necessity to provide collection to existing NPLs, prevent further new flows to NPLs and prevent increase in NPLs.ın order to increase the capability of banks in restructuring of NPL, it is recommended that the 12% target CAR implemented in TBS should be reduced to 8% which is the international standard adopted by BASEL Banking Supervision Committee. Thus, banks will be able to restructure NPL amounting to TL 116.2 billion and distressed credits TL 232 billion without approaching to 12% CAR limit. As an important point in terms of credit restructuring, TBS also has sufficient liquidity.Due to the provision allocated for NPLs currently, restructuring will not have any impact on banks in the short term, and in the medium term, profitability of banks will increase as some of the loans are converted to live loans because of reversal of some provisions. Increased profitability will provide an increase in CAR by making a positive contribution. After a transition period of 2-3 years, it can be considered again that CAR can be increased gradually.Turkish Abstract: Türkiye’de yaşanan 2000 ve 2001 krizleri sonrasında uygulanan bankacılık sektörü yeniden yapılandırma programı, Türk Bankacılık Sektörünün (TBS) aracılık işlevlerinde köklü değişimlerin yaşandığı bir süreci başlatmıştır. Bunun sonucunda ise TBS’nin finansal göstergelerinde olumlu yansımaların görüldüğü büyüme sürecine girilmiştir. Ancak 2008 yılında ortaya çıkan küresel kriz TBS’nin büyümesini yavaşlatan yeni bir zorluk dönemi olmuştur. Alınan tedbirlerin de katkısıyla birlikte 2008 krizi ağır hasar alınmadan atlatılmıştır. Diğer taraftan, 2018 yılında bozulmaya başlayan ulusal ve uluslararası ortam, son dönemde yeni zorlukların oluşmasına neden olmuştur. Kredi hacmindeki yavaşlama, kredi/mevduat oranının %100’ün üzerinde seyretmesi ve bunların bir sonucu olarak 111 milyar TL’nin üzerine çıkan sorunlu krediler bu zorluklardan en göze çarpanlarıdır. Dolayısıyla, TBS’de yeni ve kapsamlı bir kredi yapılandırma sürecinin başlatılması ve hızla uygulanması kaçınılmaz hale gelmiştir. Nitekim sorunlu kredilerin yapılandırılması ile ilgili çeşitli girişimler kamuya yansımaktadır.Bu çalışma bir zorunluluk haline gelen sorunlu kredilerin yapılandırılması bağlamında, Türkiye’de yürürlükte bulunan %12 hedef SYR uygulamasını yeniden ele almayı amaçlamaktadır. Çalışmada Bankacılık Düzenleme ve Denetleme Kurumu tarafından yayınlanan 2019 Haziran verileri kullanılarak analiz yapılmıştır.2019 Haziran itibarıyla 2,5 trilyon TL büyüklüğe ulaşan kredi hacmi içinde 116,2 milyar TL takipte kredi bulunmaktadır. Takipteki kredilerin/kredilere oranı %4,6’dır. Aynı dönemde likidite fazlası 1,5 trilyon TL, SYR ise %17,73’tür. Diğer taraftan, takibe dönüşmemiş olanların eklenmesiyle birlikte TBS’deki sorunlu kredilerin büyüklüğünün 40 milyar USD (232 milyar TL) olduğu tahmin edilmektedir. Mevcut sorunlu kredilerin tahsil edilmesinin önünü açmak, yeni sorunlu kredilerin oluşmasını ve sorunlu kredilerin daha fazla artmasını önlemek için yeniden yapılandırma bir gerekliliktir.Sorunlu kredilerin yeniden yapılandırılmasında, bankaların kabiliyetlerini artırmak için, TBS’de uygulanan %12 hedef SYR’nin, BASEL Bankacılık Gözetim Komitesi tarafından benimsenen %8 seviyesine çekilmesi önerilmektedir. Böylece, bankalar %12 SYR sınırına yaklaşmaksızın 116,2 milyar TL olan takipteki kredileri ve toplam 232 milyar TL seviyesinde olan sorunlu kredileri yapılandırabilecektir. Yapılandırma açısından önemli bir nokta olarak TBS’nin yeterli likiditesi de bulunmaktadır. Sorunlu kredilere mevcut durumda karşılık ayrılması nedeniyle, yeniden yapılandırma işlemleri kısa dönemde bankalar üzerinde etki oluşturmayacak, orta vadede ise bazı kredilerin canlı krediye dönüşmesi ile birlikte karşılıklar azalacağı için karlılıklar artacaktır. Artan karlılık ise SYR’ye pozitif katkı yaparak yükselmesini sağlayacaktır. 2-3 yıllık bir geçiş süreci sonunda SYR’nin kademeli olarak yeniden artırılabileceği değerlendirilmektedir.
Strategic Formation and Reliability of Supply Chain Networks
arXiv
arXiv
Supply chains are the backbone of the global economy. Disruptions to them can be costly. Centrally managed supply chains invest in ensuring their resilience. Decentralized supply chains, however, must rely upon the self-interest of their individual components to maintain the resilience of the entire chain.
We examine the incentives that independent self-interested agents have in forming a resilient supply chain network in the face of production disruptions and competition. In our model, competing suppliers are subject to yield uncertainty (they deliver less than ordered) and congestion (lead time uncertainty or, "soft" supply caps). Competing retailers must decide which suppliers to link to based on both price and reliability. In the presence of yield uncertainty only, the resulting supply chain networks are sparse. Retailers concentrate their links on a single supplier, counter to the idea that they should mitigate yield uncertainty by diversifying their supply base. This happens because retailers benefit from supply variance. It suggests that competition will amplify output uncertainty. When congestion is included as well, the resulting networks are denser and resemble the bipartite expander graphs that have been proposed in the supply chain literature, thereby, providing the first example of endogenous formation of resilient supply chain networks, without resilience being explicitly encoded in payoffs. Finally, we show that a supplier's investments in improved yield can make it worse off. This happens because high production output saturates the market, which, in turn lowers prices and profits for participants.
The Economics of Enlightenment: Time Value of Knowledge and the Net Present Value (NPV) of Knowledge Machines, A Proposed Approach Adapted from Finance
arXiv
arXiv
We formulate one methodology to put a value or price on knowledge using well accepted techniques from finance. We provide justifications for these finance principles based on the limitations of the physical world we live in. We start with the intuition for our method to value knowledge and then formalize this idea with a series of axioms and models. To the best of our knowledge this is the first recorded attempt to put a numerical value on knowledge. The implications of this valuation exercise, which places a high premium on any piece of knowledge, are to ensure that participants in any knowledge system are better trained to notice the knowledge available from any source. Just because someone does not see a connection does not mean that there is no connection. We need to try harder and be more open to acknowledging the smallest piece of new knowledge that might have been brought to light by anyone from anywhere about anything.
The Global Impact of Brexit Uncertainty
SSRN
Using tools from computational linguistics, we construct new measures of the impact of Brexit on listed firms in the United States and around the world; these measures are based on the proportion of discussions in quarterly earnings conference calls on the costs, benefits, and risks associated with the UK's intention to leave the EU. We identify which firms expect to gain or lose from Brexit and which are most affected by Brexit uncertainty. We then estimate effects of the different types of Brexit exposure on firm-level outcomes. We find that the impact of Brexit-related uncertainty extends far beyond British or even European firms; US and international firms most exposed to Brexit uncertainty lost a substantial fraction of their market value and have also reduced hiring and investment. In addition to Brexit uncertainty (the second moment), we find that international firms overwhelmingly expect negative direct effects from Brexit (the first moment) should it come to pass. Most prominently, firms expect difficulties from regulatory divergence, reduced labor mobility, limited trade access, and the costs of post-Brexit operational adjustments. Consistent with the predictions of canonical theory, this negative sentiment is recognized and priced in stock markets but has not yet significantly affected firm actions.
SSRN
Using tools from computational linguistics, we construct new measures of the impact of Brexit on listed firms in the United States and around the world; these measures are based on the proportion of discussions in quarterly earnings conference calls on the costs, benefits, and risks associated with the UK's intention to leave the EU. We identify which firms expect to gain or lose from Brexit and which are most affected by Brexit uncertainty. We then estimate effects of the different types of Brexit exposure on firm-level outcomes. We find that the impact of Brexit-related uncertainty extends far beyond British or even European firms; US and international firms most exposed to Brexit uncertainty lost a substantial fraction of their market value and have also reduced hiring and investment. In addition to Brexit uncertainty (the second moment), we find that international firms overwhelmingly expect negative direct effects from Brexit (the first moment) should it come to pass. Most prominently, firms expect difficulties from regulatory divergence, reduced labor mobility, limited trade access, and the costs of post-Brexit operational adjustments. Consistent with the predictions of canonical theory, this negative sentiment is recognized and priced in stock markets but has not yet significantly affected firm actions.
The Impact of JOBS Act on M&As
SSRN
Do changes in the IPO regulatory environment affect private firms’ exit choices, bargaining abilities, and valuations? Using the JOBS Act as an exogenous shock to the exit decisions among private firms, we observe that their valuations as M&A targets increase by 36% after the Act, negatively affecting acquirer wealth gains. These results are more prominent for VC-backed targets. We also find that stock (cash) deals decrease (increase) for private firms after the Act. Our results are robust to endogeneity concerns, alternative measures, placebo tests, and other robustness tests.
SSRN
Do changes in the IPO regulatory environment affect private firms’ exit choices, bargaining abilities, and valuations? Using the JOBS Act as an exogenous shock to the exit decisions among private firms, we observe that their valuations as M&A targets increase by 36% after the Act, negatively affecting acquirer wealth gains. These results are more prominent for VC-backed targets. We also find that stock (cash) deals decrease (increase) for private firms after the Act. Our results are robust to endogeneity concerns, alternative measures, placebo tests, and other robustness tests.
The Impact of the Ecb's Targeted Long-Term Refinancing Operations on Banks’ Lending Policies: The Role of Competition
SSRN
We assess the impact of the Eurosystem’s Targeted Long-Term Refinancing Operations (TLTROs) on the lending policies of euro area banks. We first build a theoretical model in which banks compete in the credit and deposit markets. We distinguish between direct and indirect effects. Direct effects take place because bidding banks expand their loan supply due to the lower marginal costs implied by the TLTROs. Indirect effects on non-bidders operate via changes in the competitive environment in banks’ credit and deposit markets. We then test these predictions with a sample of 130 banks from 13 countries focusing on the first TLTRO series. Regarding direct effects, we find an easing impact on margins on loans to relatively safe borrowers, but no impact on credit standards. Regarding indirect effects, there is a positive impact on the loan supply on non-bidders which operates via an easing of credit standards.
SSRN
We assess the impact of the Eurosystem’s Targeted Long-Term Refinancing Operations (TLTROs) on the lending policies of euro area banks. We first build a theoretical model in which banks compete in the credit and deposit markets. We distinguish between direct and indirect effects. Direct effects take place because bidding banks expand their loan supply due to the lower marginal costs implied by the TLTROs. Indirect effects on non-bidders operate via changes in the competitive environment in banks’ credit and deposit markets. We then test these predictions with a sample of 130 banks from 13 countries focusing on the first TLTRO series. Regarding direct effects, we find an easing impact on margins on loans to relatively safe borrowers, but no impact on credit standards. Regarding indirect effects, there is a positive impact on the loan supply on non-bidders which operates via an easing of credit standards.
The Natural Rate Puzzle: Global Macro Trends and the Market-Implied R
SSRN
Benchmark finance models deliver estimates of bond risk premia based on components of Treasury bond yields. Benchmark macroeconomic models deliver estimates of the natural rate of interest based on growth, inflation, and other macro factors. But estimates of the natural rate implied by the former are wildly inconsistent with those of the latter; and estimates of risk premia implied by the latter are wildly inconsistent with those of the former. This is the natural rate puzzle, and we show that it applies not only in the United States but also across several advanced economies. A unified model should not fail such consistency tests. We estimate a unified macro-finance model with long-run trend factors which delivers paths for a market-implied natural rate r* consistent with inflation expectations Ã?* and bond risk premia. These paths are plausible and our factors improve the explanatory power of yield and return regressions. Trading strategies based on signals incorporating both r* and Ã?* trends outperform both yield- only strategies like level and slope and strategies which only add trend inflation. The estimates from our unified model satisfy consistency and deliver a resolution to the puzzle. They show that most of the variation in yields has come from shifts in r* and Ã?*, not from bond risk premia. Our market-implied natural rate differs from consensus estimates, and is typically lower, intensifying concerns about secular stagnation and proximity to the effective lower-bound on monetary policy in advanced economies.
SSRN
Benchmark finance models deliver estimates of bond risk premia based on components of Treasury bond yields. Benchmark macroeconomic models deliver estimates of the natural rate of interest based on growth, inflation, and other macro factors. But estimates of the natural rate implied by the former are wildly inconsistent with those of the latter; and estimates of risk premia implied by the latter are wildly inconsistent with those of the former. This is the natural rate puzzle, and we show that it applies not only in the United States but also across several advanced economies. A unified model should not fail such consistency tests. We estimate a unified macro-finance model with long-run trend factors which delivers paths for a market-implied natural rate r* consistent with inflation expectations Ã?* and bond risk premia. These paths are plausible and our factors improve the explanatory power of yield and return regressions. Trading strategies based on signals incorporating both r* and Ã?* trends outperform both yield- only strategies like level and slope and strategies which only add trend inflation. The estimates from our unified model satisfy consistency and deliver a resolution to the puzzle. They show that most of the variation in yields has come from shifts in r* and Ã?*, not from bond risk premia. Our market-implied natural rate differs from consensus estimates, and is typically lower, intensifying concerns about secular stagnation and proximity to the effective lower-bound on monetary policy in advanced economies.
The Regulatory Observer Effect: Large-Sample Evidence from SEC Investigations
SSRN
Drawing on financial reporting, institutional, and social psychology theories, we consider whether awareness of SEC scrutiny affects the extent to which managers exercise financial reporting discretion. Because there is a higher probability that the SEC will detect misconduct and impose penalties on firms under investigation, we predict that managers will change their behavior during periods of increased scrutiny. We test our predictions using novel data on all Division of Enforcement (DoE) investigations completed during the 2000-2016 period. The evidence we present offers three insights. First, our results suggest that managers perceive the SEC will be more concerned, and potentially more punitive, with firms that employ discretion through accruals rather than real activities. Second, the actions taken by managers appear to reflect improvements in accounting misstatement risk, reductions in accounting irregularities, and increases in conservatism. Third, firms investigated by the SEC, but not ultimately subject to an enforcement action, exhibit decreased R&D and increased likelihoods of CEO turnover, comment letter receipt, earnings restatements, and class-action lawsuits. The implications of our study should be of interest to academics, investors, and regulators in understanding how heightened regulatory monitoring over financial reporting can affect both accounting practices and operating decisions.
SSRN
Drawing on financial reporting, institutional, and social psychology theories, we consider whether awareness of SEC scrutiny affects the extent to which managers exercise financial reporting discretion. Because there is a higher probability that the SEC will detect misconduct and impose penalties on firms under investigation, we predict that managers will change their behavior during periods of increased scrutiny. We test our predictions using novel data on all Division of Enforcement (DoE) investigations completed during the 2000-2016 period. The evidence we present offers three insights. First, our results suggest that managers perceive the SEC will be more concerned, and potentially more punitive, with firms that employ discretion through accruals rather than real activities. Second, the actions taken by managers appear to reflect improvements in accounting misstatement risk, reductions in accounting irregularities, and increases in conservatism. Third, firms investigated by the SEC, but not ultimately subject to an enforcement action, exhibit decreased R&D and increased likelihoods of CEO turnover, comment letter receipt, earnings restatements, and class-action lawsuits. The implications of our study should be of interest to academics, investors, and regulators in understanding how heightened regulatory monitoring over financial reporting can affect both accounting practices and operating decisions.
Too Many Voters to Fail: Influencing and Political Bargaining for Bailouts
SSRN
The paper provides a novel theory of how banks not only exploit but also cause being perceived as 'too big to fail'.
SSRN
The paper provides a novel theory of how banks not only exploit but also cause being perceived as 'too big to fail'.
Turkish Banking Sector in Terms of Concentration After Global Crisis: An Examination for The Period Of 2008-2019/3 (Küresel Kriz Sonrasında Yoğunlaşma Açısından Türk Bankacılık Sektörü: 2008-2019/3 Dönemine İlişkin Bir İnceleme)
SSRN
English Abstract: The restructuring program implemented after 2000 and 2001 crises, the structural change in the Turkish Banking Sector (TBS) started and the sector entered the growth process and reached TL 4.23 trillion total assets size as of June 2019. On the other hand, the global crisis, whose effects were felt in 2008 and 2009, was a new milestone for TBS.While crises are the beginning of a new era, the increasing effects of globalization and digitalization force all sectors to transform. In this context, it is important to be competitive of the banking sector in countries with bank-based financial systems such as Turkey. The basis of competition is concentration.Concentration in the literature is examined either structural or non-structural approaches. In this study, Herfindahl-Hirschman Index (HHI), which is one of the structural approaches, was used to address the concentration in TBS. The analysis for TBS includes the period between 2008, of which the global crisis began, and 2019/3, of which the most up-to-date data are available. The concentration is analyzed for 5 component types which are total assets, loans, deposits, equity and net profit. It is determined that TBS is an unconcentrated sector for all component types for the period 2008-2019/3. On the other hand, it was observed that there has been an increase in the concentration of some components in 2008 and 2009 and some of the following year. There was a concentration above 1,000 in deposits for the years of 2008, 2009 and 2010, in net profit for the years of 2009, 2010 and 2014.The average concentration has decreased to 804 as of 2019/3 while it was 883 in 2008. This decrease resulted from the increasing number of banks in the sector. As a matter of fact, the number of banks increased to 52 as of 2019/3 from 46 in 2008.It is determined that the HHI value of the top 5 banks in terms of components in TBS is below the HHI value calculated for TBS; the HHI value of the top 10 banks is almost the same as the HHI value calculated for TBS. Therefore, the concentration level of TBS resulted from the top 10 banks.The table emerging from 2008 to 2019/3 reveals that increasing number of the banks in TBS is very important in terms of concentration and thus competition. Therefore, the entry of new banking institutions and international banks into the sector should be encouraged by eliminating the high barriers to the entry of more new players into TBS. Concentration in TBS will further decrease with the increasing number of banks. However, there is a long way to go for TBS to reach <100 concentration level in terms of HHI, to become a sector with low concentration and high competition.Turkish Abstract: 2000 ve 2001 krizleri sonrasında uygulanan yeniden yapılandırma programı, Türk Bankacılık Sektörü (TBS)’nde yapısal değişim başlamış ve sektör büyüme sürecine girerek 2019 Haziran itibarıyla 4,23 trilyon TL aktif büyüklüğe ulaşmıştır. Diğer taraftan, 2008 ve 2009 yıllarında etkileri hissedilen küresel kriz TBS için yeni bir dönemeç olmuştur. Yaşanan krizler yeni bir dönem başlangıcı olurken küreselleşmenin ve dijitalleşmenin artan etkileri tüm sektörleri dönüşüme zorlamaktadır. Bu kapsamda, Türkiye gibi banka temelli finansal sistemlere sahip ülkelerde, bankacılık sektörünün rekabetçi olması önem taşımaktadır. Rekabetin temelinde ise yoğunlaşma bulunmaktadır. Literatürde yoğunlaşma yapısal ve yapısal olmayan yaklaşımlarla incelenmektedir. Bu çalışmada, çalışmada TBS’deki yoğunlaşmanın ele alınması amacıyla yapısal yaklaşımlardan biri olan Herfindahl-Hirschman İndeksi (HHI) kullanılmıştır. TBS’deki yoğunlaşmaya yönelik inceleme, küresel krizin başladığı 2008 ile ulaşılabilen en güncel verilerin ait olduğu 2019/3 arasındaki dönemi kapsamaktadır. Yoğunlaşma toplam aktifler, krediler, mevduatlar, özkaynaklar ve net kar olmak üzere 5 bileşen türü için incelenmiştir. Tüm bileşen türlerinde 2008-2019/3 dönemi için TBS’nin yoğunlaşmamış bir sektör olduğu belirlenmiştir. Diğer taraftan, küresel krizin yaşandığı 2008 ve 2009 yılları ile devam eden bazı yıllarda bazı bileşen türlerinde yoğunlaşmada artış yaşandığı belirlenmiştir. Mevduatlarda 2008, 2009 ve 2010 yıllarında, net karda ise 2009, 2010 ve 2014 yıllarında 1.000 seviyesinin üzerinde bir yoğunlaşma olduğu görülmüştür. Yoğunlaşma ortalaması 2008 yılında 883 seviyesindeyken 2019/3 döneminde 804 seviyesine gerilemiştir. Bu azalma, sektörde artan banka sayısından kaynaklanmaktadır. Nitekim 2008 yılında 46 olan banka sayısı 2019/3 dönemi itibarıyla 52 olmuştur. TBS’de bileşenler açısından ilk 5’te yer alan bankaların HHI değerinin TBS için hesaplanan HHI değerinin altında; ilk 10’da yer alan bankaların HHI değerinin ise neredeyse TBS için hesaplanan HHI değeri ile aynı olduğu belirlenmiştir. Dolayısıyla, TBS’nin yoğunlaşma seviyesi ilk 10’daki bankalardan kaynaklanmaktadır. 2008 yılından 2019/3 dönemine ortaya çıkan tablo, TBS’de banka sayısının artırılmasının yoğunlaşma ve dolayısıyla rekabet açısından oldukça önemli olduğunu ortaya koymaktadır. Bu nedenle, TBS’ye daha fazla sayıda yeni oyuncu girişinin önündeki yüksek engeller ortadan kaldırılarak yeni banka kuruluşları ve uluslararası bankaların sektöre girişi teşvik edilmelidir. Artan banka sayısı ile birlikte TBS’deki yoğunlaşma daha da azalacaktır. Ancak, TBS’nin HHI açısından <100 yoğunlaşma seviyesine ulaşması, düşük yoğunlaşmaya ve yüksek rekabete sahip bir sektör haline gelmesi için önümüzde uzun bir yol bulunmaktadır.
SSRN
English Abstract: The restructuring program implemented after 2000 and 2001 crises, the structural change in the Turkish Banking Sector (TBS) started and the sector entered the growth process and reached TL 4.23 trillion total assets size as of June 2019. On the other hand, the global crisis, whose effects were felt in 2008 and 2009, was a new milestone for TBS.While crises are the beginning of a new era, the increasing effects of globalization and digitalization force all sectors to transform. In this context, it is important to be competitive of the banking sector in countries with bank-based financial systems such as Turkey. The basis of competition is concentration.Concentration in the literature is examined either structural or non-structural approaches. In this study, Herfindahl-Hirschman Index (HHI), which is one of the structural approaches, was used to address the concentration in TBS. The analysis for TBS includes the period between 2008, of which the global crisis began, and 2019/3, of which the most up-to-date data are available. The concentration is analyzed for 5 component types which are total assets, loans, deposits, equity and net profit. It is determined that TBS is an unconcentrated sector for all component types for the period 2008-2019/3. On the other hand, it was observed that there has been an increase in the concentration of some components in 2008 and 2009 and some of the following year. There was a concentration above 1,000 in deposits for the years of 2008, 2009 and 2010, in net profit for the years of 2009, 2010 and 2014.The average concentration has decreased to 804 as of 2019/3 while it was 883 in 2008. This decrease resulted from the increasing number of banks in the sector. As a matter of fact, the number of banks increased to 52 as of 2019/3 from 46 in 2008.It is determined that the HHI value of the top 5 banks in terms of components in TBS is below the HHI value calculated for TBS; the HHI value of the top 10 banks is almost the same as the HHI value calculated for TBS. Therefore, the concentration level of TBS resulted from the top 10 banks.The table emerging from 2008 to 2019/3 reveals that increasing number of the banks in TBS is very important in terms of concentration and thus competition. Therefore, the entry of new banking institutions and international banks into the sector should be encouraged by eliminating the high barriers to the entry of more new players into TBS. Concentration in TBS will further decrease with the increasing number of banks. However, there is a long way to go for TBS to reach <100 concentration level in terms of HHI, to become a sector with low concentration and high competition.Turkish Abstract: 2000 ve 2001 krizleri sonrasında uygulanan yeniden yapılandırma programı, Türk Bankacılık Sektörü (TBS)’nde yapısal değişim başlamış ve sektör büyüme sürecine girerek 2019 Haziran itibarıyla 4,23 trilyon TL aktif büyüklüğe ulaşmıştır. Diğer taraftan, 2008 ve 2009 yıllarında etkileri hissedilen küresel kriz TBS için yeni bir dönemeç olmuştur. Yaşanan krizler yeni bir dönem başlangıcı olurken küreselleşmenin ve dijitalleşmenin artan etkileri tüm sektörleri dönüşüme zorlamaktadır. Bu kapsamda, Türkiye gibi banka temelli finansal sistemlere sahip ülkelerde, bankacılık sektörünün rekabetçi olması önem taşımaktadır. Rekabetin temelinde ise yoğunlaşma bulunmaktadır. Literatürde yoğunlaşma yapısal ve yapısal olmayan yaklaşımlarla incelenmektedir. Bu çalışmada, çalışmada TBS’deki yoğunlaşmanın ele alınması amacıyla yapısal yaklaşımlardan biri olan Herfindahl-Hirschman İndeksi (HHI) kullanılmıştır. TBS’deki yoğunlaşmaya yönelik inceleme, küresel krizin başladığı 2008 ile ulaşılabilen en güncel verilerin ait olduğu 2019/3 arasındaki dönemi kapsamaktadır. Yoğunlaşma toplam aktifler, krediler, mevduatlar, özkaynaklar ve net kar olmak üzere 5 bileşen türü için incelenmiştir. Tüm bileşen türlerinde 2008-2019/3 dönemi için TBS’nin yoğunlaşmamış bir sektör olduğu belirlenmiştir. Diğer taraftan, küresel krizin yaşandığı 2008 ve 2009 yılları ile devam eden bazı yıllarda bazı bileşen türlerinde yoğunlaşmada artış yaşandığı belirlenmiştir. Mevduatlarda 2008, 2009 ve 2010 yıllarında, net karda ise 2009, 2010 ve 2014 yıllarında 1.000 seviyesinin üzerinde bir yoğunlaşma olduğu görülmüştür. Yoğunlaşma ortalaması 2008 yılında 883 seviyesindeyken 2019/3 döneminde 804 seviyesine gerilemiştir. Bu azalma, sektörde artan banka sayısından kaynaklanmaktadır. Nitekim 2008 yılında 46 olan banka sayısı 2019/3 dönemi itibarıyla 52 olmuştur. TBS’de bileşenler açısından ilk 5’te yer alan bankaların HHI değerinin TBS için hesaplanan HHI değerinin altında; ilk 10’da yer alan bankaların HHI değerinin ise neredeyse TBS için hesaplanan HHI değeri ile aynı olduğu belirlenmiştir. Dolayısıyla, TBS’nin yoğunlaşma seviyesi ilk 10’daki bankalardan kaynaklanmaktadır. 2008 yılından 2019/3 dönemine ortaya çıkan tablo, TBS’de banka sayısının artırılmasının yoğunlaşma ve dolayısıyla rekabet açısından oldukça önemli olduğunu ortaya koymaktadır. Bu nedenle, TBS’ye daha fazla sayıda yeni oyuncu girişinin önündeki yüksek engeller ortadan kaldırılarak yeni banka kuruluşları ve uluslararası bankaların sektöre girişi teşvik edilmelidir. Artan banka sayısı ile birlikte TBS’deki yoğunlaşma daha da azalacaktır. Ancak, TBS’nin HHI açısından <100 yoğunlaşma seviyesine ulaşması, düşük yoğunlaşmaya ve yüksek rekabete sahip bir sektör haline gelmesi için önümüzde uzun bir yol bulunmaktadır.
U.S. Investors’ Understanding of Workplace Policies and Practices and the Need to Change Them: Progress and Future Efforts
SSRN
There have been increasing efforts by investors to spur disclosure of companies' workplace-related policies and practices. This paper provides a "case of first impression" assessment of the state of the field of such efforts among U.S. investors. Part I describes attributes of some of the important actors - investors and investor-related organizations - in the field, including their goals, their particular focus on workplace-related issues, and the standards/frameworks/criteria for what should be disclosed relevant to such an analysis. Part II offers a characterization of the success of efforts in the field to date and details challenges posed to making further progress. Part III provides suggestions and ideas about how those challenges might be might.
SSRN
There have been increasing efforts by investors to spur disclosure of companies' workplace-related policies and practices. This paper provides a "case of first impression" assessment of the state of the field of such efforts among U.S. investors. Part I describes attributes of some of the important actors - investors and investor-related organizations - in the field, including their goals, their particular focus on workplace-related issues, and the standards/frameworks/criteria for what should be disclosed relevant to such an analysis. Part II offers a characterization of the success of efforts in the field to date and details challenges posed to making further progress. Part III provides suggestions and ideas about how those challenges might be might.
Unconventional Central Bank Policies in Emerging Asia (Presentation Slides)
SSRN
Targeting Inflation is well enshrined as a principal central bank objective, but other goals are also acknowledged to be important, notably financial stability. In small and highly open (both in terms of trade in goods and financial assets) economies, capital flows and exchange rate volatility can be important sources of macroeconomic and financial instability. Central bank policy is therefore conducted not only by using a short-term interest rate as in conventional Inflation Targeting, but also by using capital flow management policies and interventions in the foreign exchange market.
SSRN
Targeting Inflation is well enshrined as a principal central bank objective, but other goals are also acknowledged to be important, notably financial stability. In small and highly open (both in terms of trade in goods and financial assets) economies, capital flows and exchange rate volatility can be important sources of macroeconomic and financial instability. Central bank policy is therefore conducted not only by using a short-term interest rate as in conventional Inflation Targeting, but also by using capital flow management policies and interventions in the foreign exchange market.
Unintended Consequences of the Global Derivatives Market Reform
SSRN
We investigate regulatory arbitrage during the G20’s global derivatives market reform. Using hand-collected data on staggered reform progress, we find that banks shift their trading towards less regulated jurisdictions. The result is driven by agenda items â€" such as the promotion of central clearing â€" that are costly, but do not directly benefit banks. We further document that subsidiaries in jurisdictions with more reform progress shift to riskier portfolios. Alleviating endogeneity concerns we show that reform progress is primarily driven by structural (time-invariant) factors.
SSRN
We investigate regulatory arbitrage during the G20’s global derivatives market reform. Using hand-collected data on staggered reform progress, we find that banks shift their trading towards less regulated jurisdictions. The result is driven by agenda items â€" such as the promotion of central clearing â€" that are costly, but do not directly benefit banks. We further document that subsidiaries in jurisdictions with more reform progress shift to riskier portfolios. Alleviating endogeneity concerns we show that reform progress is primarily driven by structural (time-invariant) factors.
Valuing Private Equity Strip by Strip
SSRN
We propose a new valuation method for private equity investments. First, we construct a cash-flow replicating portfolio for the private investment, applying Machine Learning techniques on cash-flows on various listed equity and fixed income instruments. The second step values the replicating portfolio using a flexible asset pricing model that accurately prices the systematic risk in bonds of different maturities and a broad cross-section of equity factors. The method delivers a measure of the risk-adjusted profit earned on a PE investment and a time series for the expected return on PE fund categories. We apply the method to buyout, venture capital, real estate, and infrastructure funds, among others. Accounting for horizon-dependent risk and exposure to a broad cross-section of equity factors results in negative average risk-adjusted profits. Substantial cross-sectional variation and persistence in performance suggests some funds outperform. We also find declining expected returns on PE funds in the later part of the sample.
SSRN
We propose a new valuation method for private equity investments. First, we construct a cash-flow replicating portfolio for the private investment, applying Machine Learning techniques on cash-flows on various listed equity and fixed income instruments. The second step values the replicating portfolio using a flexible asset pricing model that accurately prices the systematic risk in bonds of different maturities and a broad cross-section of equity factors. The method delivers a measure of the risk-adjusted profit earned on a PE investment and a time series for the expected return on PE fund categories. We apply the method to buyout, venture capital, real estate, and infrastructure funds, among others. Accounting for horizon-dependent risk and exposure to a broad cross-section of equity factors results in negative average risk-adjusted profits. Substantial cross-sectional variation and persistence in performance suggests some funds outperform. We also find declining expected returns on PE funds in the later part of the sample.
