Research articles for the 2020-03-08
A Capital Markets-Based Water Risk Assessment of Key Industrial Water Users in the Great Lakes Region: Indicators for Portfolio Managers
SSRN
This project explores capital markets risk exposure from water use in key industrial sectors in the Great Lakes region, represented by a subset of the region's largest companies and water users. The largest industrial water users in the Great Lakes region include (in decreasing order): thermoelectric, industrial, domestic/public supply, and commercial sectors. It is salient to make the distinction between water withdrawal and consumptive use, whereby the former is largely returned to the source reservoir after use in business operations, and the latter is removed from available supplies.Industry-specific water risks can be viewed through several lenses: watershed stewardship, impact of water as a natural resource constraint on corporate operations, and risk pricing of water in the capital markets as a result of curtailed operations and growth. The approach taken here builds on portfolio theory by integrating share price trends, with corporate accounting and voluntary disclosure data to extract a share price volatility risk metric - waterBeta - reflective of water and weather risk. The approach leverages signal processing waterBeta algorithms developed by Equarius Risk Analytics, a fintech firm, which prices water/weather risk directly into share price volatility, as a risk premium. The signal is derived from value-at-risk (VaR) models, which captures the short term ‘tail’ of extreme market volatility risks in share price behavior relative to industry and sector-specific benchmarks. Simply put, a higher waterBeta means a company is more prone to capital market volatility as a result of climate risks. Our results indicate that, by comparing nine companies across four industry sectors, the waterBeta signal is lowest for utilities, followed by health care, consumer discretionary, and industrials. Companies with high waterBeta tend to exhibit a higher degree of tail risk volatility in their short term share price, have a high percentage of facilities operating in water stressed regions, and exhibit low water intensities (WI). Interestingly, these same high waterBeta companies also tend to have high fixed asset turnover ratios, indicating high waterBeta companies are more dependent on fixed assets. Conversely, low waterBeta companies exhibit low VaR, high water intensities and a high percent of facilities in water stressed locations. However, these companies have low fixed asset turnover ratios, and are thus inefficient at generating revenue from fixed assets. Even though our subset of companies was too small for sector-wide generalizations, it appears that when an entity has higher fixed asset turnover ratios, even small changes in water intensity or exposure to high water risk areas can have a significant impact on waterBeta. This is the case with Archer Daniels Midland (ADM). However, the opposite trend can be observed, and is exemplified by the thermoelectric companies, which are the most inefficient at generating revenue from fixed assets and have the highest WI but exhibit the lowest waterBeta values. This is largely due to the fact that thermoelectric plants/companies rely almost exclusively on surface water sources, such as the Great Lakes, and tend to have corporate/industry wide water risk management strategies in place, given their high dependency on water. It should be noted that this capital markets risk at this time provides limited feedback to the companies on how to address this volatility, given that the model is multiparametric. Addressing water intensity (how much water a company uses to generate revenue) only has impact if its efficiency to generate revenue from its physical assets can be addressed. We are currently identifying factors that enable more targeted corporate risk management actions. As noted, the sample in this study was small and regionally focused. Broader universes of companies across multiple sectors such as represented in the ‘500’ index will serve to develop imputation and learning models to scale capital markets-based water risk observations.
SSRN
This project explores capital markets risk exposure from water use in key industrial sectors in the Great Lakes region, represented by a subset of the region's largest companies and water users. The largest industrial water users in the Great Lakes region include (in decreasing order): thermoelectric, industrial, domestic/public supply, and commercial sectors. It is salient to make the distinction between water withdrawal and consumptive use, whereby the former is largely returned to the source reservoir after use in business operations, and the latter is removed from available supplies.Industry-specific water risks can be viewed through several lenses: watershed stewardship, impact of water as a natural resource constraint on corporate operations, and risk pricing of water in the capital markets as a result of curtailed operations and growth. The approach taken here builds on portfolio theory by integrating share price trends, with corporate accounting and voluntary disclosure data to extract a share price volatility risk metric - waterBeta - reflective of water and weather risk. The approach leverages signal processing waterBeta algorithms developed by Equarius Risk Analytics, a fintech firm, which prices water/weather risk directly into share price volatility, as a risk premium. The signal is derived from value-at-risk (VaR) models, which captures the short term ‘tail’ of extreme market volatility risks in share price behavior relative to industry and sector-specific benchmarks. Simply put, a higher waterBeta means a company is more prone to capital market volatility as a result of climate risks. Our results indicate that, by comparing nine companies across four industry sectors, the waterBeta signal is lowest for utilities, followed by health care, consumer discretionary, and industrials. Companies with high waterBeta tend to exhibit a higher degree of tail risk volatility in their short term share price, have a high percentage of facilities operating in water stressed regions, and exhibit low water intensities (WI). Interestingly, these same high waterBeta companies also tend to have high fixed asset turnover ratios, indicating high waterBeta companies are more dependent on fixed assets. Conversely, low waterBeta companies exhibit low VaR, high water intensities and a high percent of facilities in water stressed locations. However, these companies have low fixed asset turnover ratios, and are thus inefficient at generating revenue from fixed assets. Even though our subset of companies was too small for sector-wide generalizations, it appears that when an entity has higher fixed asset turnover ratios, even small changes in water intensity or exposure to high water risk areas can have a significant impact on waterBeta. This is the case with Archer Daniels Midland (ADM). However, the opposite trend can be observed, and is exemplified by the thermoelectric companies, which are the most inefficient at generating revenue from fixed assets and have the highest WI but exhibit the lowest waterBeta values. This is largely due to the fact that thermoelectric plants/companies rely almost exclusively on surface water sources, such as the Great Lakes, and tend to have corporate/industry wide water risk management strategies in place, given their high dependency on water. It should be noted that this capital markets risk at this time provides limited feedback to the companies on how to address this volatility, given that the model is multiparametric. Addressing water intensity (how much water a company uses to generate revenue) only has impact if its efficiency to generate revenue from its physical assets can be addressed. We are currently identifying factors that enable more targeted corporate risk management actions. As noted, the sample in this study was small and regionally focused. Broader universes of companies across multiple sectors such as represented in the ‘500’ index will serve to develop imputation and learning models to scale capital markets-based water risk observations.
A Mean Field Game Approach to Equilibrium Pricing with Market Clearing Condition
arXiv
arXiv
In this work, we study an equilibrium-based continuous asset pricing problem which seeks to form a price process endogenously by requiring it to balance the flow of sales-and-purchase orders in the exchange market, where a large number of agents are interacting through the market price. Adopting a mean field game (MFG) approach, we find a special form of forward-backward stochastic differential equations of McKean-Vlasov type with common noise whose solution provides a good approximate of the market price. We show the convergence of the net order flow to zero in the large N-limit and get the order of convergence in N under some conditions. We also extend the model to a setup with multiple populations where the agents within each population share the same cost and coefficient functions but they can be different population by population.
A Revolution in Progress: Regulating P2P Lending Platforms
SSRN
Peer-to-peer (P2P) lending, defined broadly as the use of non-bank online platforms that match borrowers with lenders, is arguably one of the most important innovations in the area of alternative finance. It changes the way lenders and borrowers interact, reconstructs the credit market by driving massive disintermediation, and reshapes our general understanding of financial systems.This Article analyzes the current state of the P2P lending market with the goal of developing policy recommendations to facilitate the safe growth of this important market segment. It starts by providing an extensive overview of the P2P lending market from four different perspectives: the financial intermediary role of the platforms, the characteristics of the market, benefits and risks faced by market participants, and its regulation in leading jurisdictions. This descriptive analysis demonstrates how the P2P lending market has changed over time and identifies recent trends, risks, and challenges that require regulatory attention.In light of this analysis, the Article then proceeds to develop three policy recommendations. First, it shows that P2P lending platforms, originally designed to serve as online marketplaces that only match lenders with borrowers, have gradually evolved into new financial intermediaries that perform various brokerage activities and provide tools intended to help lenders manage their credit risks. It then argues that regulation should be modified to better suit this new financial intermediary role and discusses key considerations. Second, the Article proposes imposing consistent disclosure standards tailored to the characteristics of different types of P2P lending platforms. It presents specific examples of such disclosure requirements and provides justifications for imposing them. Finally, the article outlines key concerns related to the increasing involvement of institutional actors in P2P lending platforms â€" adverse selection among different types of lenders and growing financial stability risks â€" and discusses their regulatory implications.
SSRN
Peer-to-peer (P2P) lending, defined broadly as the use of non-bank online platforms that match borrowers with lenders, is arguably one of the most important innovations in the area of alternative finance. It changes the way lenders and borrowers interact, reconstructs the credit market by driving massive disintermediation, and reshapes our general understanding of financial systems.This Article analyzes the current state of the P2P lending market with the goal of developing policy recommendations to facilitate the safe growth of this important market segment. It starts by providing an extensive overview of the P2P lending market from four different perspectives: the financial intermediary role of the platforms, the characteristics of the market, benefits and risks faced by market participants, and its regulation in leading jurisdictions. This descriptive analysis demonstrates how the P2P lending market has changed over time and identifies recent trends, risks, and challenges that require regulatory attention.In light of this analysis, the Article then proceeds to develop three policy recommendations. First, it shows that P2P lending platforms, originally designed to serve as online marketplaces that only match lenders with borrowers, have gradually evolved into new financial intermediaries that perform various brokerage activities and provide tools intended to help lenders manage their credit risks. It then argues that regulation should be modified to better suit this new financial intermediary role and discusses key considerations. Second, the Article proposes imposing consistent disclosure standards tailored to the characteristics of different types of P2P lending platforms. It presents specific examples of such disclosure requirements and provides justifications for imposing them. Finally, the article outlines key concerns related to the increasing involvement of institutional actors in P2P lending platforms â€" adverse selection among different types of lenders and growing financial stability risks â€" and discusses their regulatory implications.
Ages of Financial Instability
SSRN
Starting from the mid-nineteenth century, this paper analyzes two periods of financial instability connected with financial globalization. The first culminates with the 1929 crisis, while the second characterizes the more recent experience starting from the 1970s. The period in between is divided into two subperiods. The first goes up to World War II and sees a retrenchment from globalization and the affirmation of a statist approach to national policy autonomy in pursuing domestic goals, for which we take as examples the New Deal, financial regulation, and the new international cooperative approach finally leading to Bretton Woods. The second subperiod, marked by the new international monetary order and limited globalization, although appearing as a relatively calm interlude, conceals the seeds of a renewed push toward financial fragility. The above periods are synthetically analyzed in terms of the development and mutual fertilization of theories, institutions, and vested public and private interests. The narrative is based on two interpretative keys: the Minskyan theory of financial fragility and changes in the public-private partnership, mainly with reference to the financial sector for which the role of the State as guarantor of last resort necessarily ensues. The lesson that can be derived is that a laissez-faire approach to globalization strengthens asymmetric powers and necessarily leads to overglobalization, as well as to financial and economic instability, rendering it extremely difficult and socially costly for the State to comply with its role of financial guarantor.
SSRN
Starting from the mid-nineteenth century, this paper analyzes two periods of financial instability connected with financial globalization. The first culminates with the 1929 crisis, while the second characterizes the more recent experience starting from the 1970s. The period in between is divided into two subperiods. The first goes up to World War II and sees a retrenchment from globalization and the affirmation of a statist approach to national policy autonomy in pursuing domestic goals, for which we take as examples the New Deal, financial regulation, and the new international cooperative approach finally leading to Bretton Woods. The second subperiod, marked by the new international monetary order and limited globalization, although appearing as a relatively calm interlude, conceals the seeds of a renewed push toward financial fragility. The above periods are synthetically analyzed in terms of the development and mutual fertilization of theories, institutions, and vested public and private interests. The narrative is based on two interpretative keys: the Minskyan theory of financial fragility and changes in the public-private partnership, mainly with reference to the financial sector for which the role of the State as guarantor of last resort necessarily ensues. The lesson that can be derived is that a laissez-faire approach to globalization strengthens asymmetric powers and necessarily leads to overglobalization, as well as to financial and economic instability, rendering it extremely difficult and socially costly for the State to comply with its role of financial guarantor.
Asymptotic distribution of the Markowitz portfolio
arXiv
arXiv
The asymptotic distribution of the Markowitz portfolio is derived, for the general case (assuming fourth moments of returns exist), and for the case of multivariate normal returns. The derivation allows for inference which is robust to heteroskedasticity and autocorrelation of moments up to order four. As a side effect, one can estimate the proportion of error in the Markowitz portfolio due to mis-estimation of the covariance matrix. A likelihood ratio test is given which generalizes Dempster's Covariance Selection test to allow inference on linear combinations of the precision matrix and the Markowitz portfolio. Extensions of the main method to deal with hedged portfolios, conditional heteroskedasticity, conditional expectation, and constrained estimation are given. It is shown that the Hotelling-Lawley statistic generalizes the (squared) Sharpe ratio under the conditional expectation model. Asymptotic distributions of all four of the common `MGLH' statistics are found, assuming random covariates. Examples are given demonstrating the possible uses of these results.
Bank Credit in Uncertain Times: Islamic vs. Conventional Banks
SSRN
This paper explores whether the impact of economic uncertainty on credit growth differs for Islamic vs. conventional banks. Using a sample of 416 banks (58 Islamic and 358 conventional) in 12 countries, the findings indicate that an increase in economic uncertainty significantly decreases the credit growth of conventional banks but does not have any significant impact on Islamic banks’ credit growth. Our results are robust to alternative specifications and addressing endogeneity concerns using GMM estimators. We further observe that our findings are stronger for the following countries: (1) countries with explicit deposit insurance protection system for Islamic banks, (2) lower foreign dominance, and (3) countries with a higher share of deposits and assets in Islamic banks.
SSRN
This paper explores whether the impact of economic uncertainty on credit growth differs for Islamic vs. conventional banks. Using a sample of 416 banks (58 Islamic and 358 conventional) in 12 countries, the findings indicate that an increase in economic uncertainty significantly decreases the credit growth of conventional banks but does not have any significant impact on Islamic banks’ credit growth. Our results are robust to alternative specifications and addressing endogeneity concerns using GMM estimators. We further observe that our findings are stronger for the following countries: (1) countries with explicit deposit insurance protection system for Islamic banks, (2) lower foreign dominance, and (3) countries with a higher share of deposits and assets in Islamic banks.
Bank Levy in Europe
SSRN
Risk-taking by financial institutions is widely regarded as the one of the causes of the financial crisis. To reduce the probability of crises and internalize the costs of financial institution distress, policymakers have introduced bank levy. However, these regulations are different in all countries. Our paper contributes to a specific strand of literature. The role of regulations in monitoring risk lies in the intervention of, for example, the tax policy. The problem lies in identifying regulatory instruments or a combination of instruments that would be most effective in reducing risk and assessing how effectively they can be applied. Our paper may be of interest to a wide range of researchers as it is call for more research on effect on bank levy introduction on risk-taking by financial institutions in Europe. First of all, we present the significance of the research on bank levy for the theory and economic practise, then we present the models of taxation of banking sector and we propose directions of future research.
SSRN
Risk-taking by financial institutions is widely regarded as the one of the causes of the financial crisis. To reduce the probability of crises and internalize the costs of financial institution distress, policymakers have introduced bank levy. However, these regulations are different in all countries. Our paper contributes to a specific strand of literature. The role of regulations in monitoring risk lies in the intervention of, for example, the tax policy. The problem lies in identifying regulatory instruments or a combination of instruments that would be most effective in reducing risk and assessing how effectively they can be applied. Our paper may be of interest to a wide range of researchers as it is call for more research on effect on bank levy introduction on risk-taking by financial institutions in Europe. First of all, we present the significance of the research on bank levy for the theory and economic practise, then we present the models of taxation of banking sector and we propose directions of future research.
Can the Leading Us Energy Stock Prices Be Predicted Using Ichimoku Clouds?
SSRN
The aim of this study is to investigate Ichimoku Clouds, as a technical analysis indicator, can serve to better predict stock prices of leading US energy companies. The methodology centers on the application of the Ichimoku clouds as a trading system. Daily stock prices from the top ten constituents of the S&P Composite 1500 Energy Index are sourced, spanning from 12th April 2012 to 31st July 2019. The performance of the Ichimoku Cloud is captured using both the Sharpe and Sortino performance measures, to adjust both for total risk and downside risk. To account for the drop in energy stock prices during the July 2014- December 2015, the analysis is broken down into pre and post oil crisis. The model is also benchmarked against the naïve buy-and-hold strategy. The capacity of the Ichimoku indicator to provide signals during strengthening trends is also captured. Despite energy stock prices drop, number of trades continued to increase, with profits opportunities. PSX ranked first, with the highest Sharpe, Sortino, and Sharpe per number of trade. While various buying signals took place during strengthening bullish periods, various selling signals also unexpectedly happened during similar strengthening bullish trends. Most buying and selling signals under the Ichimoku indicator occurred during no strengthening of bullish or bearish trends. Overall findings suggest, speculators can benefit from the use of Ichimoku Clouds over energy stock price movements, and are not susceptible to changes in energy prices.
SSRN
The aim of this study is to investigate Ichimoku Clouds, as a technical analysis indicator, can serve to better predict stock prices of leading US energy companies. The methodology centers on the application of the Ichimoku clouds as a trading system. Daily stock prices from the top ten constituents of the S&P Composite 1500 Energy Index are sourced, spanning from 12th April 2012 to 31st July 2019. The performance of the Ichimoku Cloud is captured using both the Sharpe and Sortino performance measures, to adjust both for total risk and downside risk. To account for the drop in energy stock prices during the July 2014- December 2015, the analysis is broken down into pre and post oil crisis. The model is also benchmarked against the naïve buy-and-hold strategy. The capacity of the Ichimoku indicator to provide signals during strengthening trends is also captured. Despite energy stock prices drop, number of trades continued to increase, with profits opportunities. PSX ranked first, with the highest Sharpe, Sortino, and Sharpe per number of trade. While various buying signals took place during strengthening bullish periods, various selling signals also unexpectedly happened during similar strengthening bullish trends. Most buying and selling signals under the Ichimoku indicator occurred during no strengthening of bullish or bearish trends. Overall findings suggest, speculators can benefit from the use of Ichimoku Clouds over energy stock price movements, and are not susceptible to changes in energy prices.
Catch the Thief! Fraud in the U.S. Banking Industry
SSRN
Little is known about fraud in the financial services sector. Using a rich supervisory dataset, this study dissects fraud at large U.S. banking organizations. We examine the different categories of fraud and their materiality, the recovery from fraud, the time from fraud occurrence to fraud discovery and accounting. We quantify exposure to fraud and study the determinants of fraud at the banking organization level. Lastly, we document a significant effect of fraud on bank credit intermediation. Overall, our analysis provides new, detailed evidence on fraud in the U.S. financial services industry, and its costs and consequences.
SSRN
Little is known about fraud in the financial services sector. Using a rich supervisory dataset, this study dissects fraud at large U.S. banking organizations. We examine the different categories of fraud and their materiality, the recovery from fraud, the time from fraud occurrence to fraud discovery and accounting. We quantify exposure to fraud and study the determinants of fraud at the banking organization level. Lastly, we document a significant effect of fraud on bank credit intermediation. Overall, our analysis provides new, detailed evidence on fraud in the U.S. financial services industry, and its costs and consequences.
Climate Risk Perceptions and Demand for Flood Insurance
SSRN
Using detailed micro-level data, we show that individuals' beliefs about climate change influence their choice and level of flood insurance coverage. Our empirical strategy exploits the heterogeneous impact of widening partisan polarization on climate change beliefs after the 2016 general election. We find that, in areas where flood insurance is not mandatory, a one-standard-deviation drop in the fraction of adults who believe global warming is happening leads to a 26% drop in the demand for flood insurance. In areas where flood insurance is mandatory, a similar drop in beliefs is associated with a lower propensity to carry voluntary content coverage and a higher likelihood of choosing the maximum deductible amount. As a secondary test, we exploit the flood insurance premium increases due to the Biggert-Waters Flood Insurance Reform Act of 2012. We show that homeowners who do not believe global warming is happening were more likely to terminate mandatory flood insurance coverage by prepaying mortgages.
SSRN
Using detailed micro-level data, we show that individuals' beliefs about climate change influence their choice and level of flood insurance coverage. Our empirical strategy exploits the heterogeneous impact of widening partisan polarization on climate change beliefs after the 2016 general election. We find that, in areas where flood insurance is not mandatory, a one-standard-deviation drop in the fraction of adults who believe global warming is happening leads to a 26% drop in the demand for flood insurance. In areas where flood insurance is mandatory, a similar drop in beliefs is associated with a lower propensity to carry voluntary content coverage and a higher likelihood of choosing the maximum deductible amount. As a secondary test, we exploit the flood insurance premium increases due to the Biggert-Waters Flood Insurance Reform Act of 2012. We show that homeowners who do not believe global warming is happening were more likely to terminate mandatory flood insurance coverage by prepaying mortgages.
Conflict externalization and the quest for peace: theory and case evidence from Colombia
arXiv
arXiv
I study the relationship between the likelihood of a violent domestic conflict and the risk that such a conflict "externalizes" (i.e. spreads to another country by becoming an international dispute). I consider a situation in which a domestic conflict between a government and a rebel group externalizes. I show that the risk of externalization increases the likelihood of a peaceful outcome, but only if the government is sufficiently powerful relative to the rebels, and if the risk of externalization is sufficiently high. I show how this model helps to understand the recent and successful peace process between the Colombian government and the country's most powerful rebel group, the FARC, that ended 52 years of armed conflict.
Consumer Welfare and Product Creation: The Credit Supply Channel
SSRN
I show that firms that face a reduction in credit supply reduce product creation, by using variation from US banks' exposure to the mortgage market to instrument for credit supply. The magnitude is substantial: firms facing a one-standard-deviation decrease in credit supply offered 10% fewer products. Furthermore, I show that the reduction in product offerings derives from the limited creation of new products rather than the destruction of existing ones. Motivated by these findings, I develop a model to investigate the equilibrium responses of consumers and firms. I estimate that the reduction in credit supply is responsible for a 1% drop in consumer welfare because of reduced product creation. Two types of equilibrium response are responsible for welfare loss that is smaller than a "naive" interpretation of the reduced form estimates: first, in equilibrium, consumers substitute products with other available products in the same category; and second, in equilibrium, firms' new products have lower "appeal" (quality or taste) relative to existing products.
SSRN
I show that firms that face a reduction in credit supply reduce product creation, by using variation from US banks' exposure to the mortgage market to instrument for credit supply. The magnitude is substantial: firms facing a one-standard-deviation decrease in credit supply offered 10% fewer products. Furthermore, I show that the reduction in product offerings derives from the limited creation of new products rather than the destruction of existing ones. Motivated by these findings, I develop a model to investigate the equilibrium responses of consumers and firms. I estimate that the reduction in credit supply is responsible for a 1% drop in consumer welfare because of reduced product creation. Two types of equilibrium response are responsible for welfare loss that is smaller than a "naive" interpretation of the reduced form estimates: first, in equilibrium, consumers substitute products with other available products in the same category; and second, in equilibrium, firms' new products have lower "appeal" (quality or taste) relative to existing products.
Convex Optimization Over Risk-Neutral Probabilities
arXiv
arXiv
We consider a collection of derivatives that depend on the price of an underlying asset at expiration or maturity. The absence of arbitrage is equivalent to the existence of a risk-neutral probability distribution on the price; in particular, any risk neutral distribution can be interpreted as a certificate establishing that no arbitrage exists. We are interested in the case when there are multiple risk-neutral probabilities. We describe a number of convex optimization problems over the convex set of risk neutral price probabilities. These include computation of bounds on the cumulative distribution, VaR, CVaR, and other quantities, over the set of risk-neutral probabilities. After discretizing the underlying price, these problems become finite dimensional convex or quasiconvex optimization problems, and therefore are tractable. We illustrate our approach using real options and futures pricing data for the S&P 500 index and Bitcoin.
Cross-Listings of Blockchain-Based Tokens Issued Through Initial Coin Offerings: Do Liquidity and Specific Cryptocurrency Exchanges Matter?
SSRN
Initial coin offerings (ICOs) represent a novel funding mechanism where digital tokens are issued on the blockchain and sold to investors. One major reason for the success of this financing model is the fact that the issued tokens can immediately be traded on secondary markets. This event study analyzes 250 exchange cross-listings of 135 different tokens issued through ICOs on 22 cryptocurrency exchanges. We find significant abnormal returns of 6.51% on the listing day and 9.97% over a seven-day window around the event. Further analysis shows that the results clearly differ for individual cryptocurrency exchanges, as listings on individual exchanges yield returns of up to 34% on the event day, while others are negligible. An investigation of liquidity-related metrics shows that lower prior trading volume and asset market capitalization have positive effect on listing returns. Investors use phases of high market liquidity to sell off positions around the period of cross-listing events. These first results on the cross-listing effects of ICOs may be of relevance to investors/traders, ICO projects, cryptocurrency exchanges and regulators.
SSRN
Initial coin offerings (ICOs) represent a novel funding mechanism where digital tokens are issued on the blockchain and sold to investors. One major reason for the success of this financing model is the fact that the issued tokens can immediately be traded on secondary markets. This event study analyzes 250 exchange cross-listings of 135 different tokens issued through ICOs on 22 cryptocurrency exchanges. We find significant abnormal returns of 6.51% on the listing day and 9.97% over a seven-day window around the event. Further analysis shows that the results clearly differ for individual cryptocurrency exchanges, as listings on individual exchanges yield returns of up to 34% on the event day, while others are negligible. An investigation of liquidity-related metrics shows that lower prior trading volume and asset market capitalization have positive effect on listing returns. Investors use phases of high market liquidity to sell off positions around the period of cross-listing events. These first results on the cross-listing effects of ICOs may be of relevance to investors/traders, ICO projects, cryptocurrency exchanges and regulators.
Effects of the Bank Levy Introduction on the Interbank Market
SSRN
[enter Abstract Body]One of the proposals that have been brought forward regarding ways of discouraging banks from taking unnecessary risk, widely debated these days, is the introduction of taxes in the financial sector. Although recent empirical investigations document a positive effect of the bank levies (BL), it may also reduce banks’ activity. In this paper, we aim to analyse the Polish BL on assets. Poland’s interbank market might be affected by a new BL introduced in 2016, as interbank positions of the balance sheet have been also taxed. The analysis covers the panel structure of data of 209 Polish banks with unconsolidated financial statements. To evaluate the impact of the BL on the above interbank market features, we use the OLS regression with fixed effects in relation to the bank. Data has been sourced from OrbisFocus and Central Banks’ websites and covers the period 2011-2017. The result demonstrates that the BL on assets applied in Poland has a negative impact on the interbank market. Estimation results shows that the BL on assets significantly decrease the value of 1y and increases the value of 3m interbank loans. In addition, the BL on assets in the banking sector positively affects the value of government securities and negatively affects the interest income on interbank loans. Moreover, the dispersion of 1m and 3m quotations was reduced as a result of the BL introduction. In case of short-term transactions, dispersion amplifies. Additionally, the volatility of quotation decreases due to reduced trading after the BL implementation.
SSRN
[enter Abstract Body]One of the proposals that have been brought forward regarding ways of discouraging banks from taking unnecessary risk, widely debated these days, is the introduction of taxes in the financial sector. Although recent empirical investigations document a positive effect of the bank levies (BL), it may also reduce banks’ activity. In this paper, we aim to analyse the Polish BL on assets. Poland’s interbank market might be affected by a new BL introduced in 2016, as interbank positions of the balance sheet have been also taxed. The analysis covers the panel structure of data of 209 Polish banks with unconsolidated financial statements. To evaluate the impact of the BL on the above interbank market features, we use the OLS regression with fixed effects in relation to the bank. Data has been sourced from OrbisFocus and Central Banks’ websites and covers the period 2011-2017. The result demonstrates that the BL on assets applied in Poland has a negative impact on the interbank market. Estimation results shows that the BL on assets significantly decrease the value of 1y and increases the value of 3m interbank loans. In addition, the BL on assets in the banking sector positively affects the value of government securities and negatively affects the interest income on interbank loans. Moreover, the dispersion of 1m and 3m quotations was reduced as a result of the BL introduction. In case of short-term transactions, dispersion amplifies. Additionally, the volatility of quotation decreases due to reduced trading after the BL implementation.
Epstein-Zin Utility Maximization on Random Horizons
arXiv
arXiv
This paper solves the consumption-investment problem under Epstein-Zin preferences on a random horizon. In an incomplete market, we take the random horizon to be a stopping time adapted to the market filtration, generated by all observable, but not necessarily tradable, state processes. Contrary to prior studies, we do not impose any fixed upper bound for the random horizon, allowing for truly unbounded ones. Focusing on the empirically relevant case where the risk aversion and the elasticity of intertemporal substitution are both larger than one, we characterize optimal consumption and investment strategies through backward stochastic differential equations (BSDEs). Compared with classical results on a fixed horizon, our characterization involves an additional stochastic process to account for the uncertainty of the horizon. As demonstrated in a Markovian setting, this added uncertainty drastically alters optimal strategies from the fixed-horizon case. The main results are obtained through the development of new techniques for BSDEs with superlinear growth on unbounded random horizons.
Estimating Beta: The International Evidence
SSRN
This paper examines different beta estimation methodologies for a large set of Developed and Emerging international markets. For all markets, estimators based on daily data outperform those based on monthly data. The optimal window length is surprisingly homogeneous, at roughly 12 months for Developed Markets, while tending to be somewhat longer for Emerging Markets. The best estimators include a double-shrinkage, a long memory (FI), and a simple combination approach. The FI model generally yields the best predictions for both Developed and Emerging Markets. For portfolio formation, the double-shrinkage, FI, and combination estimators also perform best.
SSRN
This paper examines different beta estimation methodologies for a large set of Developed and Emerging international markets. For all markets, estimators based on daily data outperform those based on monthly data. The optimal window length is surprisingly homogeneous, at roughly 12 months for Developed Markets, while tending to be somewhat longer for Emerging Markets. The best estimators include a double-shrinkage, a long memory (FI), and a simple combination approach. The FI model generally yields the best predictions for both Developed and Emerging Markets. For portfolio formation, the double-shrinkage, FI, and combination estimators also perform best.
Financial Inclusion and Organic Farming Practices of Kuruchya Tribe in Wayanad: An Empirical Study
SSRN
Countries, developing as well as developed are emphasising environment sustainability of agricultural production, methods and practices. The traditional wisdom of farmers on indigenous agrarian practices increasingly being called into question owing to a host of factors. This paper tries to examine the impact of financial services especially institutional credit on the organic farming practices of tribes in Kerala. It uses primary data of 384 respondents from Kuruchya tribes in Wayanad district of Kerala. It found that the extension of formal credit is one of the chief determinants of organic farming. We observed that, majority of tribes, who have access to formal credit continue their traditional or organic farming practices. The tribes being dependent on informal/non institutional credit are mostly practicing inorganic farming methods. The determinants and predictors of organic farming differ from those of inorganic farming. In our country a large number of institutions and agencies are constituted to strengthen the credit delivery system, especially in the rural areas, but still they are not germane to meet the variety of financial needs of rural agriculture sector. This study therefore contains findings which will be helpful in formulating financial inclusion policies with more stress on credit delivery system to foster organic farming practices in rural India.
SSRN
Countries, developing as well as developed are emphasising environment sustainability of agricultural production, methods and practices. The traditional wisdom of farmers on indigenous agrarian practices increasingly being called into question owing to a host of factors. This paper tries to examine the impact of financial services especially institutional credit on the organic farming practices of tribes in Kerala. It uses primary data of 384 respondents from Kuruchya tribes in Wayanad district of Kerala. It found that the extension of formal credit is one of the chief determinants of organic farming. We observed that, majority of tribes, who have access to formal credit continue their traditional or organic farming practices. The tribes being dependent on informal/non institutional credit are mostly practicing inorganic farming methods. The determinants and predictors of organic farming differ from those of inorganic farming. In our country a large number of institutions and agencies are constituted to strengthen the credit delivery system, especially in the rural areas, but still they are not germane to meet the variety of financial needs of rural agriculture sector. This study therefore contains findings which will be helpful in formulating financial inclusion policies with more stress on credit delivery system to foster organic farming practices in rural India.
How Do Star Analyst Rankings Affect Analysts’ Performance?
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We examine the impact of star analyst rankings on analysts’ forecast performance. To strengthen identification, we explore the exogenous variation in analysts’ incentives generated by the suspension of the New Fortune Star Analyst Contest in China. We find that the reduction in rankings-related incentives has a positive impact on analysts’ performance, as measured by forecast accuracy, market reaction to forecasts, and the likelihood of conducting site visits. The evidence is consistent with the view that star analyst rankings are largely popularity contests that induce analysts to allocate time and resources to attention grabbing and relationship building activities.
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We examine the impact of star analyst rankings on analysts’ forecast performance. To strengthen identification, we explore the exogenous variation in analysts’ incentives generated by the suspension of the New Fortune Star Analyst Contest in China. We find that the reduction in rankings-related incentives has a positive impact on analysts’ performance, as measured by forecast accuracy, market reaction to forecasts, and the likelihood of conducting site visits. The evidence is consistent with the view that star analyst rankings are largely popularity contests that induce analysts to allocate time and resources to attention grabbing and relationship building activities.
How Integrated Are Corporate Bond and Stock Markets?
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In this paper, I study the degree of market integration between US corporate bonds and stocks of the corresponding issuing firms, accounting for their characteristics. I find that short-selling constraints are essential restrictions to optimal Sharpe ratio portfolios that yield admissible portfolio positions and implied pricing errors within quoted bid-ask spreads. My empirical evidence suggests that markets are more integrated for larger firms, with more liquid corporate bonds and stocks. Similarly, firms that are more leveraged, have a higher asset growth and profitability feature a greater extent of integration between their debt and equity securities.
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In this paper, I study the degree of market integration between US corporate bonds and stocks of the corresponding issuing firms, accounting for their characteristics. I find that short-selling constraints are essential restrictions to optimal Sharpe ratio portfolios that yield admissible portfolio positions and implied pricing errors within quoted bid-ask spreads. My empirical evidence suggests that markets are more integrated for larger firms, with more liquid corporate bonds and stocks. Similarly, firms that are more leveraged, have a higher asset growth and profitability feature a greater extent of integration between their debt and equity securities.
Low-Carbon Transition Risk in Mutual Fund Portfolios: Managerial Involvement and Performance Effects
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Transitioning to a low-carbon economy to mitigate the effects of climate change involves risks. We investigate the effects of managerial ownership and management on the low-carbon transition risk of mutual fund portfolios and the effects of low-carbon transition risk on mutual fund performance and flows. Using a low-carbon transition risk measure based on the unmanaged carbon risk of companies included in fund portfolios, we find that managerial ownership and the socially responsible focus of the fund reduces fund portfolio exposure to carbon risk, whereas active management has the opposite effect. Furthermore, funds with low-carbon transition risk levels yield a better risk-adjusted performance, are more sensitive to tail risks and exhibit better flow performance.
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Transitioning to a low-carbon economy to mitigate the effects of climate change involves risks. We investigate the effects of managerial ownership and management on the low-carbon transition risk of mutual fund portfolios and the effects of low-carbon transition risk on mutual fund performance and flows. Using a low-carbon transition risk measure based on the unmanaged carbon risk of companies included in fund portfolios, we find that managerial ownership and the socially responsible focus of the fund reduces fund portfolio exposure to carbon risk, whereas active management has the opposite effect. Furthermore, funds with low-carbon transition risk levels yield a better risk-adjusted performance, are more sensitive to tail risks and exhibit better flow performance.
Malliavin-Mancino estimators implemented with non-uniform fast Fourier transforms
arXiv
arXiv
We implement and test kernel averaging Non-Uniform Fast-Fourier Transform (NUFFT) methods to enhance the performance of correlation and covariance estimation on asynchronously sampled event-data using the Malliavin-Mancino Fourier estimator. The methods are benchmarked for Dirichlet and Fej\'{e}r Fourier basis kernels. We consider test cases formed from Geometric Brownian motions to replicate synchronous and asynchronous data for benchmarking purposes. We consider three standard averaging kernels to convolve the event-data for synchronisation via over-sampling for use with the Fast Fourier Transform (FFT): the Gaussian kernel, the Kaiser-Bessel kernel, and the exponential of semi-circle kernel. First, this allows us to demonstrate the performance of the estimator with different combinations of basis kernels and averaging kernels. Second, we investigate and compare the impact of the averaging scales explicit in each averaging kernel and its relationship between the time-scale averaging implicit in the Malliavin-Mancino estimator. Third, we demonstrate the relationship between time-scale averaging based on the number of Fourier coefficients used in the estimator to a theoretical model of the Epps effect. We briefly demonstrate the methods on Trade-and-Quote (TAQ) data from the Johannesburg Stock Exchange to make an initial visualisation of the correlation dynamics for various time-scales under market microstructure.
Margin Trading Activists
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We examine margin trading activists that we define as activist investors that are identified by Schedule 13D filings and state therein that they can use margin borrowings to finance their holdings. We find that arrivals of margin trading activists are associated with positive target announcement returns compared to those of non-margin trading activists. Further, targets of margin trading activists seem to adjust payout policy relative to their industry peer group in a differentiated manner after activists’ arrival: If target firms have paid dividends ex ante, they raise relative dividend yields ex post whereas they reduce relative dividend yields if they have not paid dividends ex ante. Despite the short-term horizon of margin borrowings compared to equity financing, we find margin trading activists that have not been invested before their 13D filing remain invested for a longer term in their targets’ shares compared to unlevered activists.
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We examine margin trading activists that we define as activist investors that are identified by Schedule 13D filings and state therein that they can use margin borrowings to finance their holdings. We find that arrivals of margin trading activists are associated with positive target announcement returns compared to those of non-margin trading activists. Further, targets of margin trading activists seem to adjust payout policy relative to their industry peer group in a differentiated manner after activists’ arrival: If target firms have paid dividends ex ante, they raise relative dividend yields ex post whereas they reduce relative dividend yields if they have not paid dividends ex ante. Despite the short-term horizon of margin borrowings compared to equity financing, we find margin trading activists that have not been invested before their 13D filing remain invested for a longer term in their targets’ shares compared to unlevered activists.
Optimal Convergence Trading for Cross-listed Stocks
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With the intention of maximizing an investor's terminal utility, we construct a non-threshold ased trading model within which the optimal trading weights for daily rebalancing are derived analytically via stochastic optimal control. Having released the constraint that the cointegrating vector is equal to one, we propose a more practical trading strategy that applies to a much wider range of categories of cointegrated assets. We explore extensive out-of-the-sample experiments on the cross-listed stock portfolios, facilitating comparative studies among Chinese and European, UK and US stock markets. We further test the time-delay arbitrage of the strategy using the cross-listed stocks by employing two parallel trading mechanisms, respectively equity-based contracts for difference (CFD) and real shares trading. Our empirical results illustrate that the time-delay arbitrage of the cross-listed stocks strategy based on the analytical solution of weights yields relatively stable and better performance than that of the home market index. Our research is instructive for the practitioner's trading decision in cross-listed stocks and other kinds of convergence investment.
SSRN
With the intention of maximizing an investor's terminal utility, we construct a non-threshold ased trading model within which the optimal trading weights for daily rebalancing are derived analytically via stochastic optimal control. Having released the constraint that the cointegrating vector is equal to one, we propose a more practical trading strategy that applies to a much wider range of categories of cointegrated assets. We explore extensive out-of-the-sample experiments on the cross-listed stock portfolios, facilitating comparative studies among Chinese and European, UK and US stock markets. We further test the time-delay arbitrage of the strategy using the cross-listed stocks by employing two parallel trading mechanisms, respectively equity-based contracts for difference (CFD) and real shares trading. Our empirical results illustrate that the time-delay arbitrage of the cross-listed stocks strategy based on the analytical solution of weights yields relatively stable and better performance than that of the home market index. Our research is instructive for the practitioner's trading decision in cross-listed stocks and other kinds of convergence investment.
Predicting Stock Returns with Batched AROW
arXiv
arXiv
We extend the AROW regression algorithm developed by Vaits and Crammer in [VC11] to handle synchronous mini-batch updates and apply it to stock return prediction. By design, the model should be more robust to noise and adapt better to non-stationarity compared to a simple rolling regression. We empirically show that the new model outperforms more classical approaches by backtesting a strategy on S\&P500 stocks.
Quick and Dirty Patents
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The scope and timing of patents determine the size of economic rewards to inventors. We provide causal evidence on the effects of scope and timing on startups and externalities on their rivals, by leveraging the quasi-random assignment of patent applications to examiners. Using unique data on all first-time applications filed at the U.S. Patent and Trademark Office since 2001, we find that patent grant delays are harmful to the inventor, in terms of reduced growth in employment and sales and a reduced quantity and quality of follow-on innovation. In addition, delays are harmful to both the inventor and its rivals in terms of access to external capital. Broader scope, on the other hand, tends to benefit the inventor (in terms of follow-on innovation) while harming rivals (in terms of growth and follow-on innovation). Our findings suggest that “quick†patents maximize both inventor rewards and positive externalities to rivals. “Dirty†patents may benefit inventors but also impose large negative externalities on rivals.
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The scope and timing of patents determine the size of economic rewards to inventors. We provide causal evidence on the effects of scope and timing on startups and externalities on their rivals, by leveraging the quasi-random assignment of patent applications to examiners. Using unique data on all first-time applications filed at the U.S. Patent and Trademark Office since 2001, we find that patent grant delays are harmful to the inventor, in terms of reduced growth in employment and sales and a reduced quantity and quality of follow-on innovation. In addition, delays are harmful to both the inventor and its rivals in terms of access to external capital. Broader scope, on the other hand, tends to benefit the inventor (in terms of follow-on innovation) while harming rivals (in terms of growth and follow-on innovation). Our findings suggest that “quick†patents maximize both inventor rewards and positive externalities to rivals. “Dirty†patents may benefit inventors but also impose large negative externalities on rivals.
Religion and Terrorism: Evidence from Ramadan Fasting
arXiv
arXiv
We study the effect of religion and intense religious experiences on terrorism by focusing on one of the five pillars of Islam: Ramadan fasting. For identification, we exploit two facts: First, daily fasting from dawn to sunset during Ramadan is considered mandatory for most Muslims. Second, the Islamic calendar is not synchronized with the solar cycle. We find a robust negative effect of more intense Ramadan fasting on terrorist events within districts and country-years in predominantly Muslim countries. This effect seems to operate partly through decreases in public support for terrorism and the operational capabilities of terrorist groups.
Revisiting the Nexus between Oil Rents and Financial Development in Nigeria: The Threshold Regression Approach
SSRN
The study challenged the findings of Beck (2011) that resource-rich countries and oil-exporting developing countries are characterized by lower levels of financial development, and like past studies, utilized the two-stage least squares to estimate the linear impact of oil rents on financial development in Nigeria over the period 1981 to 2017. Results showed that oil rents exert negative influence on financial development in Africa’s largest oil exporting country. Also re-examined was the nexus between oil rents and financial development by accounting for nonlinearities using the threshold regression approach developed by Hansen (1999). Results revealed that the impact of oil rents on financial development is an increasing function of the level of oil rents. 14% was defined as the minimum threshold of oil rents that could help enhance financial development, thereby suggesting that the oil rents-financial development relation in Nigeria is U-shaped. One important policy implication of findings is that resource-rich countries, Nigeria inclusive, could deepen their financial sectors by properly channeling windfalls from resource rents towards the development of other sectors so as to strengthen the resilience of their economies in events of shocks to the booming resource sector.
SSRN
The study challenged the findings of Beck (2011) that resource-rich countries and oil-exporting developing countries are characterized by lower levels of financial development, and like past studies, utilized the two-stage least squares to estimate the linear impact of oil rents on financial development in Nigeria over the period 1981 to 2017. Results showed that oil rents exert negative influence on financial development in Africa’s largest oil exporting country. Also re-examined was the nexus between oil rents and financial development by accounting for nonlinearities using the threshold regression approach developed by Hansen (1999). Results revealed that the impact of oil rents on financial development is an increasing function of the level of oil rents. 14% was defined as the minimum threshold of oil rents that could help enhance financial development, thereby suggesting that the oil rents-financial development relation in Nigeria is U-shaped. One important policy implication of findings is that resource-rich countries, Nigeria inclusive, could deepen their financial sectors by properly channeling windfalls from resource rents towards the development of other sectors so as to strengthen the resilience of their economies in events of shocks to the booming resource sector.
Sensitivity to Sentiment: News vs Social Media
SSRN
We explore the rapidly changing social and news media landscape that is responsible for the dissemination of information vital to the efficient functioning of the financial markets. Using the sheer volume of social and news media activity, commonly known as buzz, we document three distinct regimes. We find that between 2011 and 2013 the news media coverage stimulates activity in social media. This is followed by a transition period of two-way causality. From 2016, however, changes in levels of social media activity seem to lead and generate news coverage volumes. We uncover similar evolution of lead-lag pattern between sentiment measures constructed from the tonality contained in textual data from social and news media posts. We discover that market variables exert stronger impact on investor sentiment than the other way around. We also find that return responses to social media sentiment almost doubled after the transition period, while return responses to news-based sentiment almost halved to its pre-transition level. The linkage between volatility and sentiment is much more persistent than that between returns and sentiment. Overall, our results suggest that social media is becoming the dominant media source.
SSRN
We explore the rapidly changing social and news media landscape that is responsible for the dissemination of information vital to the efficient functioning of the financial markets. Using the sheer volume of social and news media activity, commonly known as buzz, we document three distinct regimes. We find that between 2011 and 2013 the news media coverage stimulates activity in social media. This is followed by a transition period of two-way causality. From 2016, however, changes in levels of social media activity seem to lead and generate news coverage volumes. We uncover similar evolution of lead-lag pattern between sentiment measures constructed from the tonality contained in textual data from social and news media posts. We discover that market variables exert stronger impact on investor sentiment than the other way around. We also find that return responses to social media sentiment almost doubled after the transition period, while return responses to news-based sentiment almost halved to its pre-transition level. The linkage between volatility and sentiment is much more persistent than that between returns and sentiment. Overall, our results suggest that social media is becoming the dominant media source.
Share Pledging and Financial Constraints in China
SSRN
We investigate the relationship between the intensity of share pledging activities and the level of financial constraint. Using a sample of Chinese publicly listed firms from 2003 to 2018, our main findings are fourfold. First, we document that the high financial constraint level may motivate insiders to use share pledging as an alternative funding source and an expropriation mechanism. Second, share collateralization can cause a subsequently more constrained financing condition. Third, investors may raise more concerns about the existence of share collateralization than the proportion of pledged shares in a firm. Fourth, we find evidence that share pledging made by the controlling shareholder is likely to mitigate financial constraints in the following year. Our results are robust to alternative measures of share pledging, an alternative definition of financial constraint, and an instrumental variable for dealing with endogeneity problems. Our findings provide insights into rationales behind and consequences of share pledging activities, which have important implications for financially constrained firms and regulators in emerging markets.
SSRN
We investigate the relationship between the intensity of share pledging activities and the level of financial constraint. Using a sample of Chinese publicly listed firms from 2003 to 2018, our main findings are fourfold. First, we document that the high financial constraint level may motivate insiders to use share pledging as an alternative funding source and an expropriation mechanism. Second, share collateralization can cause a subsequently more constrained financing condition. Third, investors may raise more concerns about the existence of share collateralization than the proportion of pledged shares in a firm. Fourth, we find evidence that share pledging made by the controlling shareholder is likely to mitigate financial constraints in the following year. Our results are robust to alternative measures of share pledging, an alternative definition of financial constraint, and an instrumental variable for dealing with endogeneity problems. Our findings provide insights into rationales behind and consequences of share pledging activities, which have important implications for financially constrained firms and regulators in emerging markets.
Should Investors Choose Both the Highest-Return and Small-Variance Assets When the Mean-Variance Rule Says No? A Study of Health Care and T-Bill in the Investment
SSRN
The high-speed growth of the health care sector has given this sector an increasingly important role in the stock market. This sector however has the highest mean in our study and a low correlation with the business cycle. On the other hand, T-Bill is also an important asset in investment because of its positive return and low variance. In this paper, we examine the conjecture of whether investors should choose both the highest-return and small-variance assets even when the mean-variance rule says “NOâ€. This conjecture is explored by making a comparison of the performance of portfolios with and without health care and 6-M T-bill in the U.S. market using portfolio optimization, mean-variance and stochastic dominance approaches. Our findings imply that all risk averters prefer to invest in portfolios with both health care and 6-M T-bill, regardless of whether they buy long or sell short in the market. Our findings do not support the existence of any arbitrage opportunity in the markets we studied but do support market efficiency. We also show that risk averters as well as investors with components of both risk aversion and risk seeking will choose both the highest-return and small-variance assets even when the mean-variance rule says NO.
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The high-speed growth of the health care sector has given this sector an increasingly important role in the stock market. This sector however has the highest mean in our study and a low correlation with the business cycle. On the other hand, T-Bill is also an important asset in investment because of its positive return and low variance. In this paper, we examine the conjecture of whether investors should choose both the highest-return and small-variance assets even when the mean-variance rule says “NOâ€. This conjecture is explored by making a comparison of the performance of portfolios with and without health care and 6-M T-bill in the U.S. market using portfolio optimization, mean-variance and stochastic dominance approaches. Our findings imply that all risk averters prefer to invest in portfolios with both health care and 6-M T-bill, regardless of whether they buy long or sell short in the market. Our findings do not support the existence of any arbitrage opportunity in the markets we studied but do support market efficiency. We also show that risk averters as well as investors with components of both risk aversion and risk seeking will choose both the highest-return and small-variance assets even when the mean-variance rule says NO.
Technological Innovation and Discrimination in Household Finance
SSRN
Technology has changed how discrimination manifests itself in financial services. Replacing human discretion with algorithms in decision-making roles reduces taste-based discrimination, and new modeling techniques have expanded access to financial services to households who were previously excluded from these markets. However, algorithms can exhibit bias from human involvement in the development process, and their opacity and complexity can facilitate statistical discrimination inconsistent with antidiscrimination laws in several aspects of financial services provision, including advertising, pricing, and credit-risk assessment. In this chapter, we provide a new amalgamation and analysis of these developments, identifying five gateways whereby technology induces discrimination to creep into financial services. We also consider how these technological changes in finance intersect with existing discrimination and data privacy laws, leading to our contribution of four frontlines of regulation. Our analysis concludes that the net effect of innovation in technological finance on discrimination is ambiguous and depends on the future choices made by policymakers, the courts, and firms.
SSRN
Technology has changed how discrimination manifests itself in financial services. Replacing human discretion with algorithms in decision-making roles reduces taste-based discrimination, and new modeling techniques have expanded access to financial services to households who were previously excluded from these markets. However, algorithms can exhibit bias from human involvement in the development process, and their opacity and complexity can facilitate statistical discrimination inconsistent with antidiscrimination laws in several aspects of financial services provision, including advertising, pricing, and credit-risk assessment. In this chapter, we provide a new amalgamation and analysis of these developments, identifying five gateways whereby technology induces discrimination to creep into financial services. We also consider how these technological changes in finance intersect with existing discrimination and data privacy laws, leading to our contribution of four frontlines of regulation. Our analysis concludes that the net effect of innovation in technological finance on discrimination is ambiguous and depends on the future choices made by policymakers, the courts, and firms.
The Serial Dependence of the Commodity Futures Returns: A Machine Learning Approach
SSRN
This paper uses machine learning tools to study the serial dependence (lead-lag relations) of commodity futures returns during the post financialization period (January 2004 â€" December 2019). We use LASSO (Least Absolute Shrinkage and Selection Operator) to select the predictors as the number of predictors is large relative to the number of observations. We find significant full-sample and out-of-sample predictability. In the full sample, we find that LASSO can identify a sparse set of predictors that come from economically linked commodities or are likely driven by excessive speculative trading. The out-of-sample forecasts based on the LASSO generate statistically and economically large gains. When we separate the indexed futures from the non-indexed futures and replicate the above analysis, we find that the out-of-sample performance exists in the indexed futures but disappears in the non-indexed futures. The lead-lag relations are also more significant after the advent of ETF or ETNs that track the broad futures indices such as S&P GSCI and BCOM indices, indicating that index trading due to financialization drives the excessive comovement among the commodity futures. Overall, we find that serial dependence generates significant predictability during the sample period when the performance of the long-only commodity index futures is poor.
SSRN
This paper uses machine learning tools to study the serial dependence (lead-lag relations) of commodity futures returns during the post financialization period (January 2004 â€" December 2019). We use LASSO (Least Absolute Shrinkage and Selection Operator) to select the predictors as the number of predictors is large relative to the number of observations. We find significant full-sample and out-of-sample predictability. In the full sample, we find that LASSO can identify a sparse set of predictors that come from economically linked commodities or are likely driven by excessive speculative trading. The out-of-sample forecasts based on the LASSO generate statistically and economically large gains. When we separate the indexed futures from the non-indexed futures and replicate the above analysis, we find that the out-of-sample performance exists in the indexed futures but disappears in the non-indexed futures. The lead-lag relations are also more significant after the advent of ETF or ETNs that track the broad futures indices such as S&P GSCI and BCOM indices, indicating that index trading due to financialization drives the excessive comovement among the commodity futures. Overall, we find that serial dependence generates significant predictability during the sample period when the performance of the long-only commodity index futures is poor.
Unveiling the relation between herding and liquidity with trader lead-lag networks
arXiv
arXiv
We propose a method to infer lead-lag networks of traders from the observation of their trade record as well as to reconstruct their state of supply and demand when they do not trade. The method relies on the Kinetic Ising model to describe how information propagates among traders, assigning a positive or negative "opinion" to all agents about whether the traded asset price will go up or down. This opinion is reflected by their trading behavior, but whenever the trader is not active in a given time window, a missing value will arise. Using a recently developed inference algorithm, we are able to reconstruct a lead-lag network and to estimate the unobserved opinions, giving a clearer picture about the state of supply and demand in the market at all times.
We apply our method to a dataset of clients of a major dealer in the Foreign Exchange market at the 5 minutes time scale. We identify leading players in the market and define a herding measure based on the observed and inferred opinions. We show the causal link between herding and liquidity in the inter-dealer market used by dealers to rebalance their inventories.
What Happens When Equity Investors Disagree with the FOMC?
SSRN
This research explores an alternative explanation for the equity premium associated with Federal Open Market Committee (FOMC) announcement days that accounts for a sizable fraction of annual equity returns. My evidence shows that investor expectations formulated prior to FOMC announcements have a significant impact on equity prices, particularly when these expectations are not aligned with the FOMC decision. Furthermore, I document an even larger impact around FOMC announcements where the level of interest rates remained unchanged. When monetary policy is neutral, the observed investors’ disagreement towards the FOMC decisions represents a further layer of uncertainty in the dynamics of equity markets. My results reconcile past findings on the monetary policy surprise literature and more recent empirical findings on the effect of FOMC announcements, which are difficult to explain with standard asset pricing theories. Moreover, as I find little effects on equity returns when the FOMC decision is anticipated by the market, a practical implication of my study is that monetary policy authorities should take into account market expectations when formulating disclosure policy in order to improve alignment with financial market expectations and smooth out their economic consequences.
SSRN
This research explores an alternative explanation for the equity premium associated with Federal Open Market Committee (FOMC) announcement days that accounts for a sizable fraction of annual equity returns. My evidence shows that investor expectations formulated prior to FOMC announcements have a significant impact on equity prices, particularly when these expectations are not aligned with the FOMC decision. Furthermore, I document an even larger impact around FOMC announcements where the level of interest rates remained unchanged. When monetary policy is neutral, the observed investors’ disagreement towards the FOMC decisions represents a further layer of uncertainty in the dynamics of equity markets. My results reconcile past findings on the monetary policy surprise literature and more recent empirical findings on the effect of FOMC announcements, which are difficult to explain with standard asset pricing theories. Moreover, as I find little effects on equity returns when the FOMC decision is anticipated by the market, a practical implication of my study is that monetary policy authorities should take into account market expectations when formulating disclosure policy in order to improve alignment with financial market expectations and smooth out their economic consequences.
Why Commonality Persists?
SSRN
Studies on commonality in returns, order flows and liquidity find that the first principal component is closely aligned with the market factor. With the increasing presence of high-frequency trading, commonality in returns, order flows, and liquidity can potentially arise from the commonality in the interpretation of real-time signals. In this paper, we go beyond the first factor and show that the other dominant principal components consistently reflects investors' herding behavior, demonstrating the multi-dimensional aspect of commonality. Instead of relating the asset returns to order flows, we take both as endogenous, and provide empirical evidence showing that returns commonality is driven by investors' attention, while order flows commonality is driven by investors' sentiment. We also present a comprehensive longitudinal study of commonality and co-movement over a period in excess of two decades under a unifying market microstructure framework to demonstrate the persistence of commonality over time. Our results not only extend the knowledge about cross-sectional asset behaviors, but can also be used to develop systematic trading strategies.
SSRN
Studies on commonality in returns, order flows and liquidity find that the first principal component is closely aligned with the market factor. With the increasing presence of high-frequency trading, commonality in returns, order flows, and liquidity can potentially arise from the commonality in the interpretation of real-time signals. In this paper, we go beyond the first factor and show that the other dominant principal components consistently reflects investors' herding behavior, demonstrating the multi-dimensional aspect of commonality. Instead of relating the asset returns to order flows, we take both as endogenous, and provide empirical evidence showing that returns commonality is driven by investors' attention, while order flows commonality is driven by investors' sentiment. We also present a comprehensive longitudinal study of commonality and co-movement over a period in excess of two decades under a unifying market microstructure framework to demonstrate the persistence of commonality over time. Our results not only extend the knowledge about cross-sectional asset behaviors, but can also be used to develop systematic trading strategies.
Why do Foreign Investors Demand Comparability? Evidence from Unsponsored ADRs
SSRN
We study the sources of demand for accounting comparability. We hypothesize that U.S. investors interested in investing in a foreign firm potentially have two different types of demands for comparability: (i) comparability to U.S. firms which report under U.S. GAAP (which we label as U.S. comparability) and (ii) comparability to other foreign firms which the investor is interested in investing in (which we label as regional comparability). The findings in prior literature examining U.S. institutional investors are consistent with channel (i). We explore unsponsored ADRs as a setting where we expect channel (ii) to be particularly important. We find that regional (but not U.S.) comparability increases the ex-ante likelihood that a depository bank selects a foreign firm for the creation of unsponsored ADRs, and the ex-post trading in the unsponsored ADR by U.S. investors. Our results imply an implicit trade-off in the costs and benefits of increased comparability to a specific set of firms and suggests that future research could consider not only if comparability matters in a specific context, but also to whom it is aimed for.
SSRN
We study the sources of demand for accounting comparability. We hypothesize that U.S. investors interested in investing in a foreign firm potentially have two different types of demands for comparability: (i) comparability to U.S. firms which report under U.S. GAAP (which we label as U.S. comparability) and (ii) comparability to other foreign firms which the investor is interested in investing in (which we label as regional comparability). The findings in prior literature examining U.S. institutional investors are consistent with channel (i). We explore unsponsored ADRs as a setting where we expect channel (ii) to be particularly important. We find that regional (but not U.S.) comparability increases the ex-ante likelihood that a depository bank selects a foreign firm for the creation of unsponsored ADRs, and the ex-post trading in the unsponsored ADR by U.S. investors. Our results imply an implicit trade-off in the costs and benefits of increased comparability to a specific set of firms and suggests that future research could consider not only if comparability matters in a specific context, but also to whom it is aimed for.
Worldwide Short Selling Regulations and IPO Underpricing
SSRN
We study the impact of country-level short selling constraints on IPO underpricing. Examining 17,151 IPOs from 36 countries, we find that IPO underpricing tends to be greater in countries that ban short selling or security lending and in countries where short selling is not practiced. Non-positive first-day returns are more common in countries where short selling is allowed, security lending is allowed, and short selling is commonly practiced. Short selling constraints exacerbate the positive relation between investor sentiment and underpricing. Additional evidence suggests that higher quality information environments may partially alleviate the effects of short sale constraints on underpricing.
SSRN
We study the impact of country-level short selling constraints on IPO underpricing. Examining 17,151 IPOs from 36 countries, we find that IPO underpricing tends to be greater in countries that ban short selling or security lending and in countries where short selling is not practiced. Non-positive first-day returns are more common in countries where short selling is allowed, security lending is allowed, and short selling is commonly practiced. Short selling constraints exacerbate the positive relation between investor sentiment and underpricing. Additional evidence suggests that higher quality information environments may partially alleviate the effects of short sale constraints on underpricing.
