Research articles for the 2020-09-08
Arc-Sine Law and the Libor Reform
SSRN
The fallback spread that will be used to calculate Libor rates of a given tenor in the future is defined as the median (50%-th percentile) of five years of historical observations of the spread between this Libor and compounded OIS rates, calculated on the future date of Libor cessation announcement. Some of the observations that will enter this calculation have already occurred and some are still in the future. In this note we assert that the future realized median is a non-linear function of future, and hence yet unknown, spread observations and therefore its fair value calculation must account for spread dynamics and not just forward values. We propose a model of the future evolution of spreads and derive a very numerically-efficient algorithm for calculating the fair value of the median that incorporates both the historical observations and the future dynamics of the spread. We establish that, given our model, the market expectations of the fallback spreads are at, or somewhat beyond, the upper range of theoretically-justifiable values. The approximation method we develop is based in part on the Arc-Sine Law and should be of independent interest to math finance professionals.
SSRN
The fallback spread that will be used to calculate Libor rates of a given tenor in the future is defined as the median (50%-th percentile) of five years of historical observations of the spread between this Libor and compounded OIS rates, calculated on the future date of Libor cessation announcement. Some of the observations that will enter this calculation have already occurred and some are still in the future. In this note we assert that the future realized median is a non-linear function of future, and hence yet unknown, spread observations and therefore its fair value calculation must account for spread dynamics and not just forward values. We propose a model of the future evolution of spreads and derive a very numerically-efficient algorithm for calculating the fair value of the median that incorporates both the historical observations and the future dynamics of the spread. We establish that, given our model, the market expectations of the fallback spreads are at, or somewhat beyond, the upper range of theoretically-justifiable values. The approximation method we develop is based in part on the Arc-Sine Law and should be of independent interest to math finance professionals.
Contagion Risks and Security Investment in Directed Networks
SSRN
We develop a model for contagion risks and optimal security investment in a directed network of interconnected agents with heterogeneous degrees, loss functions and security profiles. Our model generalizes much of contagion models in the literature; in particular the independent cascade model and the linear threshold model. We state various limit theorems on the final size of infected agents in the case of random networks with given vertex degrees for finite and infinite variance degree distributions. The results allow us to derive a resilience condition of the network to the infection of a large group of agents and quantify how contagion amplifies small shocks to the network. We show that when the degree distribution has infinite variance and, highly correlated in- and out-degrees, then even when agents have high thresholds, a sub-linear fraction of initially infected agents is enough to trigger the infection of a positive fraction. We also show how these results are sensitive to vertex and edge percolation (immunization).We then study the asymptotic Nash equilibrium and socially optimal security investment. In the asymptotic limit, agents' risk depends on all other agents' investment through an aggregate quantity, that we call network vulnerability. The limit theorems allow us to capture the impact of one class of agents' decision on the overall network vulnerability. Based on our results, the vulnerability is semi-analytic allowing for a tractable Nash equilibrium.We give sufficient conditions for investment in equilibrium to be monotone in the network vulnerability. When investment is monotone, we show that the (asymptotic) Nash equilibrium is unique. In the particular example of two types core-periphery agents, we exhibit a strong effect of the cost heterogeneity and in particular non-monotonous investment as a function of costs.
SSRN
We develop a model for contagion risks and optimal security investment in a directed network of interconnected agents with heterogeneous degrees, loss functions and security profiles. Our model generalizes much of contagion models in the literature; in particular the independent cascade model and the linear threshold model. We state various limit theorems on the final size of infected agents in the case of random networks with given vertex degrees for finite and infinite variance degree distributions. The results allow us to derive a resilience condition of the network to the infection of a large group of agents and quantify how contagion amplifies small shocks to the network. We show that when the degree distribution has infinite variance and, highly correlated in- and out-degrees, then even when agents have high thresholds, a sub-linear fraction of initially infected agents is enough to trigger the infection of a positive fraction. We also show how these results are sensitive to vertex and edge percolation (immunization).We then study the asymptotic Nash equilibrium and socially optimal security investment. In the asymptotic limit, agents' risk depends on all other agents' investment through an aggregate quantity, that we call network vulnerability. The limit theorems allow us to capture the impact of one class of agents' decision on the overall network vulnerability. Based on our results, the vulnerability is semi-analytic allowing for a tractable Nash equilibrium.We give sufficient conditions for investment in equilibrium to be monotone in the network vulnerability. When investment is monotone, we show that the (asymptotic) Nash equilibrium is unique. In the particular example of two types core-periphery agents, we exhibit a strong effect of the cost heterogeneity and in particular non-monotonous investment as a function of costs.
Counterfactual and Welfare Analysis with an Approximate Model
arXiv
arXiv
We propose a conceptual framework for counterfactual and welfare analysis for approximate models. Our key assumption is that model approximation error is the same magnitude at new choices as the observed data. Applying the framework to quasilinear utility, we obtain bounds on quantities at new prices using an approximate law of demand. We then bound utility differences between bundles and welfare differences between prices. All bounds are computable as linear programs. We provide detailed analytical results describing how the data map to the bounds including shape restrictions that provide a foundation for plug-in estimation. An application to gasoline demand illustrates the methodology.
Credit Risk and Equity Returns: An Augmented Fama-French Five-Factor Model in the Chinese Market
SSRN
Whether the credit risk should be priced has been widely debated. We study this issue in the Chinese context, where the financial market has been long dominated by indirect financing. We employ the Merton’s (1974) model to measure the credit risk of firms listed on Chinese A-share market monthly. We document a positive relationship between credit risk and subsequent returns. Following a high-minus-low strategy, we construct a credit risk factor DMU, which is then incorporated into Fama-French models. By comparing the performance of 6 competing models, we find that the credit risk factor helps improve the description of portfolio returns while the investment factor makes little contribution. The conclusions are further confirmed by regression details including adjusted-R2, AIC tests and intercepts. Meanwhile, the slopes on DMU are significant for most tested portfolios and present monotonic patterns when the credit risk increases, implying that the credit risk factor can well explain the variation in the cross section of portfolio returns. Our findings show that in the Chinese context, the credit risk factor is relevant and the DMU-augmented Fama-French five-factor model is a preferred model.
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Whether the credit risk should be priced has been widely debated. We study this issue in the Chinese context, where the financial market has been long dominated by indirect financing. We employ the Merton’s (1974) model to measure the credit risk of firms listed on Chinese A-share market monthly. We document a positive relationship between credit risk and subsequent returns. Following a high-minus-low strategy, we construct a credit risk factor DMU, which is then incorporated into Fama-French models. By comparing the performance of 6 competing models, we find that the credit risk factor helps improve the description of portfolio returns while the investment factor makes little contribution. The conclusions are further confirmed by regression details including adjusted-R2, AIC tests and intercepts. Meanwhile, the slopes on DMU are significant for most tested portfolios and present monotonic patterns when the credit risk increases, implying that the credit risk factor can well explain the variation in the cross section of portfolio returns. Our findings show that in the Chinese context, the credit risk factor is relevant and the DMU-augmented Fama-French five-factor model is a preferred model.
Das Wertpapierhandelsgesetz (1994â€"2019) â€" Eine quantitative juristische Studie (The Securities Trading Act (1994â€"2019) â€" A Quantitative Legal Study)
SSRN
Deutsche Zusammenfassung: Als das Wertpapierhandelsgesetz vor 25 Jahren in Kraft trat, wurden Wertpapiere bereits elektronisch gehandelt. Gleichwohl dürfte die zunehmende Automatisierung des Handels einer der Hauptgründe sein, warum das Wertpapierhandelsgesetz in den letzten Jahren so häufig und so tiefgreifend modifiziert wurde. War es anfangs primär das Zusammenführen von Kauf- und Verkaufsaufträgen, das automatisiert erfolgte (matching), sind es heute schon die Aufträge selbst, die automatisiert erstellt und platziert werden. Während der Gesetzgeber auf die fortschreitende Automatisierung des Handels immer wieder mit Änderungen des Wertpapierhandelsgesetzes reagiert hat, wählt dieser Beitrag den umgekehrten Weg: eine computergestützte (und insoweit automatisierte) Analyse der Veränderungen, die das Wertpapierhandelsgesetz in den letzten 25 Jahren durchlaufen hat. Der Beitrag ist damit ein Beispiel für die quantitative Rechtswissenschaft â€" die statistische Auswertung zählbarer Daten zur Beantwortung juristischer Fragen.English Abstract: When the Securities Trading Act entered into force 25 years ago, securities were already being traded electronically. Nevertheless, the increasing automation of trading is likely one of the main reasons why the Securities Trading Act has been modified so frequently and so deeply in recent years. Initially, it was primarily the matching of buy and sell orders that was automated. Today, it is the orders themselves that are both generated and placed automatically. While lawmakers regularly responded to the increasing automation of trading by amending the Securities Trading Act, this paper takes the opposite route, offering a computer-aided (and in this respect automated) analysis of the changes that the Securities Trading Act has undergone in the past 25 years. The paper is thus an example of quantitative legal studies: the statistical analysis of discrete data to answer legal questions.
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Deutsche Zusammenfassung: Als das Wertpapierhandelsgesetz vor 25 Jahren in Kraft trat, wurden Wertpapiere bereits elektronisch gehandelt. Gleichwohl dürfte die zunehmende Automatisierung des Handels einer der Hauptgründe sein, warum das Wertpapierhandelsgesetz in den letzten Jahren so häufig und so tiefgreifend modifiziert wurde. War es anfangs primär das Zusammenführen von Kauf- und Verkaufsaufträgen, das automatisiert erfolgte (matching), sind es heute schon die Aufträge selbst, die automatisiert erstellt und platziert werden. Während der Gesetzgeber auf die fortschreitende Automatisierung des Handels immer wieder mit Änderungen des Wertpapierhandelsgesetzes reagiert hat, wählt dieser Beitrag den umgekehrten Weg: eine computergestützte (und insoweit automatisierte) Analyse der Veränderungen, die das Wertpapierhandelsgesetz in den letzten 25 Jahren durchlaufen hat. Der Beitrag ist damit ein Beispiel für die quantitative Rechtswissenschaft â€" die statistische Auswertung zählbarer Daten zur Beantwortung juristischer Fragen.English Abstract: When the Securities Trading Act entered into force 25 years ago, securities were already being traded electronically. Nevertheless, the increasing automation of trading is likely one of the main reasons why the Securities Trading Act has been modified so frequently and so deeply in recent years. Initially, it was primarily the matching of buy and sell orders that was automated. Today, it is the orders themselves that are both generated and placed automatically. While lawmakers regularly responded to the increasing automation of trading by amending the Securities Trading Act, this paper takes the opposite route, offering a computer-aided (and in this respect automated) analysis of the changes that the Securities Trading Act has undergone in the past 25 years. The paper is thus an example of quantitative legal studies: the statistical analysis of discrete data to answer legal questions.
Deep Learning, Predictability, and Optimal Portfolio Returns
arXiv
arXiv
We study optimal dynamic portfolio choice of a long-horizon investor who uses deep learning methods to predict equity returns when forming optimal portfolios. The results show statistically and economically significant out-of-sample portfolio benefits of deep learning as measured by high certainty equivalent returns and Sharpe ratios. Return predictability via deep learning generates substantially improved portfolio performance across different subsamples, particularly the recession periods. These gains are robust to including transaction costs, short-selling and borrowing constraints.
Dividend Payout Policies in Founder Owned Firms: Evidence From India
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In this paper, we examine the role of dividends as a corporate governance mechanism in founders’ controlled firms to mitigate agency conflicts between founders and minority shareholders in the Indian context. We show that at higher level of ownership where founders possess effective control over the firm, the minority shareholders face greater information asymmetry problem; therefore, founders are more likely to pay dividends to signal less expropriation of minority shareholders. Consistent with the extant literature, we show that this relationship is driven by the agency problem between controlling and minority shareholders. We confirm this argument by showing that the positive relationship between founder ownership and dividend policy is more pronounced for business group firms, financially mature firms, and firms having lower debt and low-growth opportunities.
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In this paper, we examine the role of dividends as a corporate governance mechanism in founders’ controlled firms to mitigate agency conflicts between founders and minority shareholders in the Indian context. We show that at higher level of ownership where founders possess effective control over the firm, the minority shareholders face greater information asymmetry problem; therefore, founders are more likely to pay dividends to signal less expropriation of minority shareholders. Consistent with the extant literature, we show that this relationship is driven by the agency problem between controlling and minority shareholders. We confirm this argument by showing that the positive relationship between founder ownership and dividend policy is more pronounced for business group firms, financially mature firms, and firms having lower debt and low-growth opportunities.
Does Business Strategy Influence Trade Credit Policies?
SSRN
This paper investigates the impact of business strategy on firms’ trade credit policies. Based on a large sample of U.S. listed firms over the period of 1962-2019, we find that firms following an innovation-oriented strategy (prospectors) offer significantly more trade credit to their customers than those following an efficiency-oriented strategy (defenders), consistent with prospectors using generous trade credit policies as a strategic tool to proactively appeal to a larger customer base and build favorable relationships with their customers. Our cross-sectional analyses suggest that such relation is more salient for firms with excessive levels of inventory and firms that are financially healthy. Furthermore, by exploiting two exogenous shocks to the supplies of high-skill employees and bank credit, we conduct triple-differences (DiDiD) analyses and find that prospectors curtail trade credit in response to the reduction of talent mobility following the adoptions of Inevitable Disclosure Doctrine (IDD), whereas defenders significantly cut the provisions of trade credit following the increase in credit supply after the enactment of Interstate banking and Branching Efficiency Act (IBBEA). Additional evidence confirms that prospectors increasing trade credit provisions enjoy higher sales generation efficiency and superior performance. Finally, we examine the trade credit provision across the supply chain and document that, relative to the defenders, prospectors also receive significantly more trade credit from their suppliers. Our results are robust to alternative measures of trade credit, the inclusion of individual business strategy components, and a propensity-score-matched (PSM) sample. Collectively, our findings highlight that business strategy is an important yet intrinsic determinant of trade credit policies.
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This paper investigates the impact of business strategy on firms’ trade credit policies. Based on a large sample of U.S. listed firms over the period of 1962-2019, we find that firms following an innovation-oriented strategy (prospectors) offer significantly more trade credit to their customers than those following an efficiency-oriented strategy (defenders), consistent with prospectors using generous trade credit policies as a strategic tool to proactively appeal to a larger customer base and build favorable relationships with their customers. Our cross-sectional analyses suggest that such relation is more salient for firms with excessive levels of inventory and firms that are financially healthy. Furthermore, by exploiting two exogenous shocks to the supplies of high-skill employees and bank credit, we conduct triple-differences (DiDiD) analyses and find that prospectors curtail trade credit in response to the reduction of talent mobility following the adoptions of Inevitable Disclosure Doctrine (IDD), whereas defenders significantly cut the provisions of trade credit following the increase in credit supply after the enactment of Interstate banking and Branching Efficiency Act (IBBEA). Additional evidence confirms that prospectors increasing trade credit provisions enjoy higher sales generation efficiency and superior performance. Finally, we examine the trade credit provision across the supply chain and document that, relative to the defenders, prospectors also receive significantly more trade credit from their suppliers. Our results are robust to alternative measures of trade credit, the inclusion of individual business strategy components, and a propensity-score-matched (PSM) sample. Collectively, our findings highlight that business strategy is an important yet intrinsic determinant of trade credit policies.
Econophysics of Asset Price, Return and Multiple Expectations
arXiv
arXiv
This paper describes asset price and return disturbances as result of relations between transactions and multiple kinds of expectations. We show that disturbances of expectations can cause fluctuations of trade volume, price and return. We model price disturbances for transactions made under all types of expectations as weighted sum of partial price and trade volume disturbances for transactions made under separate kinds of expectations. Relations on price allow present return as weighted sum of partial return and trade volume "return" for transactions made under separate expectations. Dependence of price disturbances on trade volume disturbances as well as dependence of return on trade volume "return" cause dependence of volatility and statistical distributions of price and return on statistical properties of trade volume disturbances and trade volume "return" respectively.
Efficiency Assessment of Indian Commercial Banks: A Meta-Frontier Approach
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The study examines the efficiency of the Indian Commercial Banks in the backdrop of undesirable Non-Performing Assets. The study applies Meta-Frontier approach for assessing the efficiency of banks in heterogeneous Indian banking groups, such as Indian PSU Banks, Domestic Private Banks and Foreign Banks, from managerial point of view. The study reveals that, the issue of Non-Performing Assets which is considered as alarming in case of the Indian banking sector, has not been efficiently and properly addressed by the Indian PSU banks and Domestic Private Banks. None of the Indian PSU banks is able to position as an efficient frontier in the Meta frontier matrix. Wilcoxon matched pairs signed ranks test confirms that only the Indian foreign banks are serious in managing their NPAs effectively. Mann- Whitney independent sample test also confirms that there is a significant difference in Meta efficiency scores and technological gap inefficiency scores of Foreign Banks compared to the PSU and Indian Domestic Private Banks. The Indian foreign banks outperform PSU and Domestic private banks in all respects, which may be owing to their advanced technology, global focus and global experience in banking operations.
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The study examines the efficiency of the Indian Commercial Banks in the backdrop of undesirable Non-Performing Assets. The study applies Meta-Frontier approach for assessing the efficiency of banks in heterogeneous Indian banking groups, such as Indian PSU Banks, Domestic Private Banks and Foreign Banks, from managerial point of view. The study reveals that, the issue of Non-Performing Assets which is considered as alarming in case of the Indian banking sector, has not been efficiently and properly addressed by the Indian PSU banks and Domestic Private Banks. None of the Indian PSU banks is able to position as an efficient frontier in the Meta frontier matrix. Wilcoxon matched pairs signed ranks test confirms that only the Indian foreign banks are serious in managing their NPAs effectively. Mann- Whitney independent sample test also confirms that there is a significant difference in Meta efficiency scores and technological gap inefficiency scores of Foreign Banks compared to the PSU and Indian Domestic Private Banks. The Indian foreign banks outperform PSU and Domestic private banks in all respects, which may be owing to their advanced technology, global focus and global experience in banking operations.
Expectation and Price in Incomplete Markets
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Risk-neutral pricing dictates that the discounted derivative price is a martingale in a measure equivalent to the economic measure. The residual ambiguity for incomplete markets is here resolved by minimizing the entropy of the price measure from the economic measure, subject to mark-to-market constraints, following arguments based on the optimization of portfolio risk. The approach accounts for market and funding convexities and incorporates available price information, interpolating between methodologies based on expectation and replication.
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Risk-neutral pricing dictates that the discounted derivative price is a martingale in a measure equivalent to the economic measure. The residual ambiguity for incomplete markets is here resolved by minimizing the entropy of the price measure from the economic measure, subject to mark-to-market constraints, following arguments based on the optimization of portfolio risk. The approach accounts for market and funding convexities and incorporates available price information, interpolating between methodologies based on expectation and replication.
Firm Life Stage and Earnings Announcement Reactions
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This study examines whether stock price reactions around positive or negative earnings surprises differ based on a firm’s life stage. We find that introduction and decline stage companies exhibit significantly less positive cumulative abnormal returns (CARs) around positive earnings surprises and more negative CARs around negative earnings surprises as compared with companies in growth, maturity, and shake-out stages. Among positive earnings surprises, lottery characteristics exacerbate the lower announcement reactions for introduction and decline stage firms, while such lottery features have the opposite effect on firms in growth, maturity, and shake-out stages. Our results suggest speculation from noise traders/retail investors drives the lower earnings announcement reactions to positive earnings surprises for companies in the introduction and decline stages. More broadly, our study demonstrates that Dickinson’s (2011) cash flow-based life stage classification system has real implications for financial market responses to earnings announcements.
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This study examines whether stock price reactions around positive or negative earnings surprises differ based on a firm’s life stage. We find that introduction and decline stage companies exhibit significantly less positive cumulative abnormal returns (CARs) around positive earnings surprises and more negative CARs around negative earnings surprises as compared with companies in growth, maturity, and shake-out stages. Among positive earnings surprises, lottery characteristics exacerbate the lower announcement reactions for introduction and decline stage firms, while such lottery features have the opposite effect on firms in growth, maturity, and shake-out stages. Our results suggest speculation from noise traders/retail investors drives the lower earnings announcement reactions to positive earnings surprises for companies in the introduction and decline stages. More broadly, our study demonstrates that Dickinson’s (2011) cash flow-based life stage classification system has real implications for financial market responses to earnings announcements.
Forward utilities and Mean-field games under relative performance concerns
arXiv
arXiv
We introduce the concept of mean field games for agents using Forward utilities of CARA type to study a family of portfolio management problems under relative performance concerns. Under asset specialization of the fund managers, we solve the forward-utility finite player game and the forward-utility mean-field game. We study best response and equilibrium strategies in the single common stock asset and the asset specialization with common noise. As an application, we draw on the core features of the forward utility paradigm and discuss a problem of time-consistent mean-field dynamic model selection in sequential time-horizons.
Globalization? Trade War? A Counterbalance Perspective
arXiv
arXiv
During the last few decades, globalization and protectionism have ebbed and flowed from time to time among economies. The movements demand that we develop formal analytics that can help countries make better trade policies. The movements also imply that the best trade policies are time-varying and country-specific. Economies and their imports and exports constitute a counterbalanced network where conflict and cooperation are two sides of the same coin of the global economy. A country could improve its relative strength in the interactive network by embracing globalization, protectionism, or a trade war. This paper provides necessary conditions for globalization and trade wars, evaluates their side effects, identifies the right targets for conflict, and recommends a fair resolution for a trade war. Data from 2018 show that trade wars could be an option for the USA to maintain its competitiveness. However, adverse side effects on third parties could be significant. Nevertheless, whether the USA should engage in protectionism depends on its bargaining power.
Impact of Internal Governance on a CEO’s Investment Cycle
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The investment cycle literature suggests that older CEOs with short investment horizon may be myopic and as result incur agency costs as they try to extract rents by under-investing. Acharya, Myers and Rajan (2011) theorize that internal governance may mitigate the CEO horizon problem. We find that good internal governance helps reduce older CEOs under-investing before their exit. These results are robust to: normal CEO retirements, sudden CEO deaths, while controlling for measures of board characteristics, CEO’s pay-performance sensitivity, CEO pay slice, CEO power, firm complexity and if the CEO was an outsider or not.
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The investment cycle literature suggests that older CEOs with short investment horizon may be myopic and as result incur agency costs as they try to extract rents by under-investing. Acharya, Myers and Rajan (2011) theorize that internal governance may mitigate the CEO horizon problem. We find that good internal governance helps reduce older CEOs under-investing before their exit. These results are robust to: normal CEO retirements, sudden CEO deaths, while controlling for measures of board characteristics, CEO’s pay-performance sensitivity, CEO pay slice, CEO power, firm complexity and if the CEO was an outsider or not.
Initial Public Offerings Chinese Style
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We examine various aspects of the IPO market in China â€" the policy history, IPO pricing, bids and allocation, and aftermarket trading under two lenses: IPO theories and the unique regulatory environment in China. We show that heavy-handed regulations cause inefficient IPO offer prices and high initial returns, resulting in a high cost of going public. Investors treat IPOs as lotteries with extreme short-term returns, with little incentive for long-term investment. The auction selling method, however, works in the way it is supposed to. Mutual funds bid more smartly than other investors, and their advantages are unlikely to be due to underwriters’ preferential treatment. We also discuss the direction of future regulation reforms (including the latest science and technology board, or STAR market).
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We examine various aspects of the IPO market in China â€" the policy history, IPO pricing, bids and allocation, and aftermarket trading under two lenses: IPO theories and the unique regulatory environment in China. We show that heavy-handed regulations cause inefficient IPO offer prices and high initial returns, resulting in a high cost of going public. Investors treat IPOs as lotteries with extreme short-term returns, with little incentive for long-term investment. The auction selling method, however, works in the way it is supposed to. Mutual funds bid more smartly than other investors, and their advantages are unlikely to be due to underwriters’ preferential treatment. We also discuss the direction of future regulation reforms (including the latest science and technology board, or STAR market).
Measuring Information Effects of Monetary Policy: New Evidence from the VIX Futures Market
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I provide new evidence on the information content of monetary policy announcements. I construct shocks from 30-minute changes in VIX futures prices around FOMC announcements which are orthogonal to traditional high-frequency monetary policy shocks. I find that changes in the VIX futures are well represented by a level and slope factor. After purging them from variation due to changes in the yield curve, I find that an increase in the level factor leads to a significant contraction in economic activity, whereas the increase in slope factor does not lead to size-able effects. My findings emphasize the effect of monetary policy releases on real economic activity through its information release, and beyond their impact on the yield curve.
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I provide new evidence on the information content of monetary policy announcements. I construct shocks from 30-minute changes in VIX futures prices around FOMC announcements which are orthogonal to traditional high-frequency monetary policy shocks. I find that changes in the VIX futures are well represented by a level and slope factor. After purging them from variation due to changes in the yield curve, I find that an increase in the level factor leads to a significant contraction in economic activity, whereas the increase in slope factor does not lead to size-able effects. My findings emphasize the effect of monetary policy releases on real economic activity through its information release, and beyond their impact on the yield curve.
No Fear of Discounting - How to Manage the Transition from EONIA to €STR
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An important step in the Financial Benchmarks Reform was taken on 13th September 2018, when the ECB Working Group on Euro Risk-Free Rates recommended the Euro Short-Term Rate €STR as the new benchmark rate for the euro area, to replace the Euro OverNight Index Average (EONIA) which will be discontinued at the end of 2021. This transition has a number of important consequences on financial instruments, OTC derivatives in particular. In this paper we show in detail how the switch from EONIA to €STR affects the pricing of OIS, IRS and XVAs. We conclude that the adoption of the "clean discounting" approach recommended by the ECB [2], based on €STR only, is theoretically sound and leads to very limited impacts on financial valuations. This finding ensures the possibility, for the financial industry, to switch all EUR OTC derivatives, either cleared with Central Counterparties, or subject to bilateral collateral agreements, or non-collateralised, in a safe and consistent manner. The transition to such EONIA-free pricing framework is essential for the complete elimination of EONIA before its discontinuation scheduled on 31st December 2021.
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An important step in the Financial Benchmarks Reform was taken on 13th September 2018, when the ECB Working Group on Euro Risk-Free Rates recommended the Euro Short-Term Rate €STR as the new benchmark rate for the euro area, to replace the Euro OverNight Index Average (EONIA) which will be discontinued at the end of 2021. This transition has a number of important consequences on financial instruments, OTC derivatives in particular. In this paper we show in detail how the switch from EONIA to €STR affects the pricing of OIS, IRS and XVAs. We conclude that the adoption of the "clean discounting" approach recommended by the ECB [2], based on €STR only, is theoretically sound and leads to very limited impacts on financial valuations. This finding ensures the possibility, for the financial industry, to switch all EUR OTC derivatives, either cleared with Central Counterparties, or subject to bilateral collateral agreements, or non-collateralised, in a safe and consistent manner. The transition to such EONIA-free pricing framework is essential for the complete elimination of EONIA before its discontinuation scheduled on 31st December 2021.
Odd-Lot Trading Activity and Nominal Stock Price
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We examine the rise of odd-lot trading activity and nominal stock prices in recent years. We find that odd-lot trading activity is positively associated with nominal stock price, for both time-series and cross-sectional variation. After stock splits (reverse split), the odd-lot trading activity decreases (increases) significantly. For higher priced stocks, there is a higher percentage of odd-lot trades with transaction price occurring within NBBOs. However, we show that the rise of odd-lot trading activity is not entirely due to the increase of nominal stock prices over time.
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We examine the rise of odd-lot trading activity and nominal stock prices in recent years. We find that odd-lot trading activity is positively associated with nominal stock price, for both time-series and cross-sectional variation. After stock splits (reverse split), the odd-lot trading activity decreases (increases) significantly. For higher priced stocks, there is a higher percentage of odd-lot trades with transaction price occurring within NBBOs. However, we show that the rise of odd-lot trading activity is not entirely due to the increase of nominal stock prices over time.
Ownership of Mutual Funds, Shareholder Sentiment, and Use of the Internet, 2019
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Each year, the Investment Company Institute (ICI) conducts a telephone survey of US households to track households’ ownership of mutual funds and to gather information on their demographic and financial characteristics. The most recent survey was conducted from May to July 2019 and was based on a dual-frame telephone sample of 4,000 US households. Of these, 1,800 households were from a landline random digit dial (RDD) frame and 2,200 households were from a cell phone RDD frame. Of the households contacted, 1,821 households, or 45.5 percent, owned mutual funds. This paper presents results from the survey, highlighting incidence of mutual fund ownership among US households; mutual fund shareholder sentiment; households’ willingness to take financial risk; and mutual fundâ€"owning households’ use of the internet.
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Each year, the Investment Company Institute (ICI) conducts a telephone survey of US households to track households’ ownership of mutual funds and to gather information on their demographic and financial characteristics. The most recent survey was conducted from May to July 2019 and was based on a dual-frame telephone sample of 4,000 US households. Of these, 1,800 households were from a landline random digit dial (RDD) frame and 2,200 households were from a cell phone RDD frame. Of the households contacted, 1,821 households, or 45.5 percent, owned mutual funds. This paper presents results from the survey, highlighting incidence of mutual fund ownership among US households; mutual fund shareholder sentiment; households’ willingness to take financial risk; and mutual fundâ€"owning households’ use of the internet.
Peer-to-Peer Lending: Social Marketplace, Crowdfunding or Finance 2.0?
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With each passing year the peer-to-peer lending becomes more popular. The increased numbers of users and provided loans through the P2P platforms led us to write this paper to clarify what peer-to-peer lending is and what are the benefits and the flaws of using such platforms. Are they just peer-to-peer or they have evolved in something more complexed with the participation of more “players†like institutional investors, banks and venture capital funds? We shall examine the connections between peer-to-peer lending and other widely discussed terms, such as crowdfunding, social marketplace and finance 2.0. As a conclusion we will give our prediction about the mutual future of technologies and lending.
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With each passing year the peer-to-peer lending becomes more popular. The increased numbers of users and provided loans through the P2P platforms led us to write this paper to clarify what peer-to-peer lending is and what are the benefits and the flaws of using such platforms. Are they just peer-to-peer or they have evolved in something more complexed with the participation of more “players†like institutional investors, banks and venture capital funds? We shall examine the connections between peer-to-peer lending and other widely discussed terms, such as crowdfunding, social marketplace and finance 2.0. As a conclusion we will give our prediction about the mutual future of technologies and lending.
Risk Transfer with Interest Rate Swaps
SSRN
This paper proposes Entity-Netted Notionals (ENNs) as a metric of interest rate risk transfer in the interest rate swap (IRS) market. Unlike the ubiquitous metric of notional amount, ENNs normalize for risk and account for the netting of longs and shorts within counter party relationships. Using regulatory data for U.S.-reporting entities, the size of the market measured by notional amount is $231 trillion, but, measured by ENNs, is only $13.9 trillion 5-year swap equivalents, which is the same order of magnitude as other large U.S. fixed income markets. This paper also quantifies the size and direction of IRS positions across and within various business sectors. Among the empirical findings are that 92% of entities using IRS are exclusively long or exclusively short. Hence, the vast majority of market participants are prototypical end users, and the extensive amount of netting in the market is attributable to the activity of relatively few, larger entities. Finally, some sector-specific empirical findings are inconsistent with widespread, prior beliefs. For example, pension funds and insurance companies are typically thought to be long IRS to hedge their long-term liabilities, and these sectors are indeed net long, but approximately 50% of individual entities in these sectors are actually net short.
SSRN
This paper proposes Entity-Netted Notionals (ENNs) as a metric of interest rate risk transfer in the interest rate swap (IRS) market. Unlike the ubiquitous metric of notional amount, ENNs normalize for risk and account for the netting of longs and shorts within counter party relationships. Using regulatory data for U.S.-reporting entities, the size of the market measured by notional amount is $231 trillion, but, measured by ENNs, is only $13.9 trillion 5-year swap equivalents, which is the same order of magnitude as other large U.S. fixed income markets. This paper also quantifies the size and direction of IRS positions across and within various business sectors. Among the empirical findings are that 92% of entities using IRS are exclusively long or exclusively short. Hence, the vast majority of market participants are prototypical end users, and the extensive amount of netting in the market is attributable to the activity of relatively few, larger entities. Finally, some sector-specific empirical findings are inconsistent with widespread, prior beliefs. For example, pension funds and insurance companies are typically thought to be long IRS to hedge their long-term liabilities, and these sectors are indeed net long, but approximately 50% of individual entities in these sectors are actually net short.
Simulation Methods for Robust Risk Assessment and the Distorted Mix Approach
arXiv
arXiv
Uncertainty requires suitable techniques for risk assessment. Combining stochastic approximation and stochastic average approximation, we propose an efficient algorithm to compute the worst case average value at risk in the face of tail uncertainty. Dependence is modelled by the distorted mix method that flexibly assigns different copulas to different regions of multivariate distributions. We illustrate the application of our approach in the context of financial markets and cyber risk.
Surveying the Use of Pharmaceutical Cognitive Enhancers in the Australian Financial Services Industry
SSRN
The non-medical use of pharmaceuticals such as methylphenidate and modafinil for cognitive enhancement has been explored in college students, medical students and various professions in the US and Europe. We present results of an anonymous online survey of such use among members of the Australian financial services industry. Our hypothesis was that industry sectors would report different preferences for different drugs, reflecting different workplace task demands. The survey was advertised to industry groups, online media articles, and social media outlets between September 2016 and October 2017. Industry sector, hours worked per week, and other demographic and personal health factors were also surveyed. 372 responses were received, of which 140 were valid and complete, and 69 were variously incomplete but usable. Different sectors of the financial services industry reported significantly different rates of use among colleagues. Respondents from different industry sectors also nominated different substances as most prevalent with significantly different frequencies. There was a significant difference in reported hours slept per night between those who reported workplace use and those who did not. A number of side effects were also reported, including headaches and mood swings. This is an important first step in exploring the use of attempts at pharmaceutical cognitive enhancement in competitive professional workplaces with diverse task demands.
SSRN
The non-medical use of pharmaceuticals such as methylphenidate and modafinil for cognitive enhancement has been explored in college students, medical students and various professions in the US and Europe. We present results of an anonymous online survey of such use among members of the Australian financial services industry. Our hypothesis was that industry sectors would report different preferences for different drugs, reflecting different workplace task demands. The survey was advertised to industry groups, online media articles, and social media outlets between September 2016 and October 2017. Industry sector, hours worked per week, and other demographic and personal health factors were also surveyed. 372 responses were received, of which 140 were valid and complete, and 69 were variously incomplete but usable. Different sectors of the financial services industry reported significantly different rates of use among colleagues. Respondents from different industry sectors also nominated different substances as most prevalent with significantly different frequencies. There was a significant difference in reported hours slept per night between those who reported workplace use and those who did not. A number of side effects were also reported, including headaches and mood swings. This is an important first step in exploring the use of attempts at pharmaceutical cognitive enhancement in competitive professional workplaces with diverse task demands.
The Link Between Bank Competition and Risk in the United Kingdom: Two Views for Policymaking
SSRN
We use quantile regression to examine the links between competition and firm-level solvency risk for all banks and building societies in the United Kingdom between 1994 and 2013. Quantile regression provides a finer picture of the relationship (as compared with standard regression techniques) across institutions ranked according to how close each is to insolvency. We find that for domestic banks and building societies already close to insolvency the association is favourable, suggesting that risk decreases (increases) with more (less) competition. For foreign-owned banks and for relatively healthy building societies farther from insolvency we find the opposite, indicating that risk increases (decreases) with more (less) competition. We find that regulation is effective in moderating adverse links between risk and competition. Our results highlight real differences in the links between competition and risk at the individual level that are useful for assessing the link at the system-wide level.
SSRN
We use quantile regression to examine the links between competition and firm-level solvency risk for all banks and building societies in the United Kingdom between 1994 and 2013. Quantile regression provides a finer picture of the relationship (as compared with standard regression techniques) across institutions ranked according to how close each is to insolvency. We find that for domestic banks and building societies already close to insolvency the association is favourable, suggesting that risk decreases (increases) with more (less) competition. For foreign-owned banks and for relatively healthy building societies farther from insolvency we find the opposite, indicating that risk increases (decreases) with more (less) competition. We find that regulation is effective in moderating adverse links between risk and competition. Our results highlight real differences in the links between competition and risk at the individual level that are useful for assessing the link at the system-wide level.
The Pricing of Private Assets: Mutual Fund Investments in ‘Unicorn’ Companies
SSRN
This paper analyzes valuation dynamics of ‘Unicorn’ companies, that is, privately held and venture capital-backed companies with a valuation of at least $1 billion. In recent years, Unicorns have received substantial investments from U.S. mutual funds, whose public reporting allows for rare insight into the pricing of these opaque assets. We study the pricing data for 223 investments made by 80 separate funds of 8 U.S. mutual fund managers into 98 Unicorns. In line with price 'anchoring' and 'reference' theories, our results show that external factors, such as the valuation of peer companies, are the primary driver behind Unicorn stock pricing. Analyses of the stock price patterns additionally reveal the importance of shareholder (cash flow) rights: different share classes with different cash flow rights issued by the same Unicorn are priced differently at the same point in time, even by the same shareholder. Our research creates a variety of important implications for investors and regulators, especially by highlighting the behavioral issues in the pricing of Unicorn shares, and by providing empirical evidence of the discrepancy between investors’ share class valuations and the publicly reported ‘headline’ valuations of Unicorns.
SSRN
This paper analyzes valuation dynamics of ‘Unicorn’ companies, that is, privately held and venture capital-backed companies with a valuation of at least $1 billion. In recent years, Unicorns have received substantial investments from U.S. mutual funds, whose public reporting allows for rare insight into the pricing of these opaque assets. We study the pricing data for 223 investments made by 80 separate funds of 8 U.S. mutual fund managers into 98 Unicorns. In line with price 'anchoring' and 'reference' theories, our results show that external factors, such as the valuation of peer companies, are the primary driver behind Unicorn stock pricing. Analyses of the stock price patterns additionally reveal the importance of shareholder (cash flow) rights: different share classes with different cash flow rights issued by the same Unicorn are priced differently at the same point in time, even by the same shareholder. Our research creates a variety of important implications for investors and regulators, especially by highlighting the behavioral issues in the pricing of Unicorn shares, and by providing empirical evidence of the discrepancy between investors’ share class valuations and the publicly reported ‘headline’ valuations of Unicorns.
The Role of IRAs in US Households’ Saving for Retirement, 2019
SSRN
This paper presents survey results on the incidence of IRA ownership in the United States and the activity of IRA-owning households. In mid-2019, 36 percent of US households owned individual retirement accounts (IRAs). More than eight in 10 IRA-owning households also had employer-sponsored retirement plan accumulations or had defined benefit plan coverage. All told, more than six in 10 US households had retirement plans through work or IRAs; three-quarters of near-retiree households did. In mid-2019, 28 percent of US households owned traditional IRAs. Traditional IRAs were the most common type of IRA owned, followed by Roth IRAs and employer-sponsored IRAs. Rollovers from employer-sponsored retirement plans have fueled the growth in IRAs. About six in 10 traditional IRAâ€"owning households in mid-2019 indicated their IRAs contained rollovers from employer-sponsored retirement plans. Among households with rollovers in their traditional IRAs, 86 percent indicated they had rolled over the entire retirement account balance in their most recent rollover; 43 percent also had made contributions to their traditional IRAs at some point. Traditional IRAâ€"owning households with rollovers cite multiple reasons for rolling over their retirement plan assets into traditional IRAs. The three most common primary reasons for rolling over were not wanting to leave assets behind at the former employer, wanting to preserve the tax treatment of the savings, and wanting to consolidate assets (25 percent, 17 percent, and 17 percent of traditional IRAâ€"owning households with rollovers, respectively). Another 12 percent of traditional IRAâ€"owning households with rollovers indicated their primary reason for rolling over was to access more investment options. Although most US households were eligible to make IRA contributions, few did so. Only 12 percent of US households contributed to traditional or Roth IRAs in tax year 2018. Other research finds confusion over rules or satisfying savings needs at work may explain lack of contributions. In addition, traditional IRAâ€"owning households without contributions tended to have rollovers (62 percent) or have a defined contribution (DC) plan account (69 percent). Nearly half (45 percent) of traditional IRAâ€"owning households without contributions were retired. IRA withdrawals were infrequent and mostly retirement related. The majority of traditional IRA withdrawals were made by retirees. Seventy-seven percent of traditional IRAâ€"owning households with withdrawals calculated the withdrawal using the required minimum distribution (RMD) rule â€" this was the most common amount withdrawn. Most traditional IRAâ€"owning households have a planned retirement strategy.
SSRN
This paper presents survey results on the incidence of IRA ownership in the United States and the activity of IRA-owning households. In mid-2019, 36 percent of US households owned individual retirement accounts (IRAs). More than eight in 10 IRA-owning households also had employer-sponsored retirement plan accumulations or had defined benefit plan coverage. All told, more than six in 10 US households had retirement plans through work or IRAs; three-quarters of near-retiree households did. In mid-2019, 28 percent of US households owned traditional IRAs. Traditional IRAs were the most common type of IRA owned, followed by Roth IRAs and employer-sponsored IRAs. Rollovers from employer-sponsored retirement plans have fueled the growth in IRAs. About six in 10 traditional IRAâ€"owning households in mid-2019 indicated their IRAs contained rollovers from employer-sponsored retirement plans. Among households with rollovers in their traditional IRAs, 86 percent indicated they had rolled over the entire retirement account balance in their most recent rollover; 43 percent also had made contributions to their traditional IRAs at some point. Traditional IRAâ€"owning households with rollovers cite multiple reasons for rolling over their retirement plan assets into traditional IRAs. The three most common primary reasons for rolling over were not wanting to leave assets behind at the former employer, wanting to preserve the tax treatment of the savings, and wanting to consolidate assets (25 percent, 17 percent, and 17 percent of traditional IRAâ€"owning households with rollovers, respectively). Another 12 percent of traditional IRAâ€"owning households with rollovers indicated their primary reason for rolling over was to access more investment options. Although most US households were eligible to make IRA contributions, few did so. Only 12 percent of US households contributed to traditional or Roth IRAs in tax year 2018. Other research finds confusion over rules or satisfying savings needs at work may explain lack of contributions. In addition, traditional IRAâ€"owning households without contributions tended to have rollovers (62 percent) or have a defined contribution (DC) plan account (69 percent). Nearly half (45 percent) of traditional IRAâ€"owning households without contributions were retired. IRA withdrawals were infrequent and mostly retirement related. The majority of traditional IRA withdrawals were made by retirees. Seventy-seven percent of traditional IRAâ€"owning households with withdrawals calculated the withdrawal using the required minimum distribution (RMD) rule â€" this was the most common amount withdrawn. Most traditional IRAâ€"owning households have a planned retirement strategy.
The Seven-League Scheme: Deep learning for large time step Monte Carlo simulations of stochastic differential equations
arXiv
arXiv
We propose an accurate data-driven numerical scheme to solve Stochastic Differential Equations (SDEs), by taking large time steps. The SDE discretization is built up by means of a polynomial chaos expansion method, on the basis of accurately determined stochastic collocation (SC) points. By employing an artificial neural network to learn these SC points, we can perform Monte Carlo simulations with large time steps. Error analysis confirms that this data-driven scheme results in accurate SDE solutions in the sense of strong convergence, provided the learning methodology is robust and accurate. With a variant method called the compression-decompression collocation and interpolation technique, we can drastically reduce the number of neural network functions that have to be learned, so that computational speed is enhanced. Numerical results shows the high quality strong convergence error results, when using large time steps, and the novel scheme outperforms some classical numerical SDE discretizations. Some applications, here in financial option valuation, are also presented.
Topological Data Analysis for Portfolio Management of Cryptocurrencies
arXiv
arXiv
Portfolio management is essential for any investment decision. Yet, traditional methods in the literature are ill-suited for the characteristics and dynamics of cryptocurrencies. This work presents a method to build an investment portfolio consisting of more than 1500 cryptocurrencies covering 6 years of market data. It is centred around Topological Data Analysis (TDA), a recent approach to analyze data sets from the perspective of their topological structure. This publication proposes a system combining persistence landscapes to identify suitable investment opportunities in cryptocurrencies. Using a novel and comprehensive data set of cryptocurrency prices, this research shows that the proposed system enables analysts to outperform a classic method from the literature without requiring any feature engineering or domain knowledge in TDA. This work thus introduces TDA-based portfolio management of cryptocurrencies as a viable tool for the practitioner.
When Should Retirees Tap Their Home Equity?
SSRN
This paper studies a household's optimal demand for a reverse mortgage. These contracts allow homeowners to tap their home equity to finance consumption needs. In stylized frameworks, we show that the decision to enter a reverse mortgage is mainly driven by the differential between the aggregate appreciation of the house price and principal limiting factor on the one hand and the funding costs of a household on the other hand. We also study a rich life-cycle model that can explain the low demand for reverse mortgages as observed in US data. In this model, we analyze the optimal response of a household that is confronted with a health shock or financial disaster. If an agent suffers from an unexpected health shock, she reduces the risky portfolio share and is more likely to enter a reverse mortgage. On the other hand, if there is a large drop in the stock market, she keeps the risky portfolio share almost constant by buying additional shares of stock. Besides, the probability to take out a reverse mortgage is hardly affected.
SSRN
This paper studies a household's optimal demand for a reverse mortgage. These contracts allow homeowners to tap their home equity to finance consumption needs. In stylized frameworks, we show that the decision to enter a reverse mortgage is mainly driven by the differential between the aggregate appreciation of the house price and principal limiting factor on the one hand and the funding costs of a household on the other hand. We also study a rich life-cycle model that can explain the low demand for reverse mortgages as observed in US data. In this model, we analyze the optimal response of a household that is confronted with a health shock or financial disaster. If an agent suffers from an unexpected health shock, she reduces the risky portfolio share and is more likely to enter a reverse mortgage. On the other hand, if there is a large drop in the stock market, she keeps the risky portfolio share almost constant by buying additional shares of stock. Besides, the probability to take out a reverse mortgage is hardly affected.
Win, Lose and Draw: Outcomes from the 2019 World Radio Conference
SSRN
This paper identifies the winners and losers at the 2019 meeting of the World Radio Conference, the global forum for developing harmonized spectrum allocations convened by the International Telecommunication Union (“ITUâ€). World Radio Conferences, convened in four-year cycles, seek global consensus on spectrum allocations and reallocation. At WRC-19, the 193 participating nations agreed to add 17.25 Gigahertz (“GHzâ€) in bandwidth for fifth generation (“5Gâ€) wireless services, with a total 19.14 GHz bandwidth now available for domestic assignment by individual national regulatory authorities. Despite incremental progress at the ITU, senior-level United States government officials deem the ITU unable to make timely spectrum planning decisions. Federal Communications Commissioners, from both political parties, have largely rejected ITU consensus building, despite the fact that the U.S. assumed lead responsibility for creating the ITU’s rules and heretofore has complied with them. In the last eight years, the FCC has conducted 5G spectrum auctions that have contributed over $121.2 billion to the U.S. Treasury with an additional $12.05 billion awarded to incumbent broadcast television licensees as compensation for quickly abandoning a channel assignment, or changing frequencies.This paper reports on the decisions reached at WRC-19 with an eye toward assessing whether the ITU can reach timely resolution of spectrum allocation disputes. Additionally, the paper identifies the benefits and costs in the FCC’s unilateral 5G spectrum initiatives that include market-driven resource frequency assignments instead of full compliance with longstanding ITU “rules of the road†that seek to optimize technologies and harmonize spectrum allocations globally. The paper also assesses whether the ITU can remain a trusted and effective forum even though the FCC and other government agencies justify unilateralism as necessary to address national security, trade and 5G leadership concerns for which the ITU has no basis to resolve. The paper concludes that U.S. efforts to maintain or reacquire 5G market and technology leadership will generate positive “first mover†advantages, but also unanticipated and offsetting harmful consequences.
SSRN
This paper identifies the winners and losers at the 2019 meeting of the World Radio Conference, the global forum for developing harmonized spectrum allocations convened by the International Telecommunication Union (“ITUâ€). World Radio Conferences, convened in four-year cycles, seek global consensus on spectrum allocations and reallocation. At WRC-19, the 193 participating nations agreed to add 17.25 Gigahertz (“GHzâ€) in bandwidth for fifth generation (“5Gâ€) wireless services, with a total 19.14 GHz bandwidth now available for domestic assignment by individual national regulatory authorities. Despite incremental progress at the ITU, senior-level United States government officials deem the ITU unable to make timely spectrum planning decisions. Federal Communications Commissioners, from both political parties, have largely rejected ITU consensus building, despite the fact that the U.S. assumed lead responsibility for creating the ITU’s rules and heretofore has complied with them. In the last eight years, the FCC has conducted 5G spectrum auctions that have contributed over $121.2 billion to the U.S. Treasury with an additional $12.05 billion awarded to incumbent broadcast television licensees as compensation for quickly abandoning a channel assignment, or changing frequencies.This paper reports on the decisions reached at WRC-19 with an eye toward assessing whether the ITU can reach timely resolution of spectrum allocation disputes. Additionally, the paper identifies the benefits and costs in the FCC’s unilateral 5G spectrum initiatives that include market-driven resource frequency assignments instead of full compliance with longstanding ITU “rules of the road†that seek to optimize technologies and harmonize spectrum allocations globally. The paper also assesses whether the ITU can remain a trusted and effective forum even though the FCC and other government agencies justify unilateralism as necessary to address national security, trade and 5G leadership concerns for which the ITU has no basis to resolve. The paper concludes that U.S. efforts to maintain or reacquire 5G market and technology leadership will generate positive “first mover†advantages, but also unanticipated and offsetting harmful consequences.
