Research articles for the 2020-03-14
A Machine Learning Efficient Frontier
SSRN
We propose a simple approach to bridge between portfolio theory and machine learning. The outcome is an out-of-sample machine learning efficient frontier based on two assets, high risk and low risk. By rotating between the two assets, we show that the proposed frontier dominates the mean-variance efficient frontier out-of-sample. Our results, therefore, shed important light on the appeal of machine learning into portfolio selection under estimation risk.
SSRN
We propose a simple approach to bridge between portfolio theory and machine learning. The outcome is an out-of-sample machine learning efficient frontier based on two assets, high risk and low risk. By rotating between the two assets, we show that the proposed frontier dominates the mean-variance efficient frontier out-of-sample. Our results, therefore, shed important light on the appeal of machine learning into portfolio selection under estimation risk.
A Model of Strategic Stock Buybacks
SSRN
This paper studies the authorization and execution of buybacks in a Kyle micro-structure setting with two informed parties: a speculator who trades on his own account and a manager who implements buybacks for the firm. Buybacks introduce two opposing economic forces. On the one hand, informed buybacks intensify the competition for trading profits, making it more difficult to profit from private information. On the other, buybacks generate gains and losses that increase the dispersion of the firm's per-share value across different payoff states, making private information more valuable. Less informative buybacks weaken the first force, while strengthening the second. The manager's incentive to manipulate the current stock price in order to increase her compensation constrains how much buybacks reflect her private information. The model generates novel predictions linking the structure of the manager's compensation, the buyback authorization decision, and trading outcomes following buybacks.
SSRN
This paper studies the authorization and execution of buybacks in a Kyle micro-structure setting with two informed parties: a speculator who trades on his own account and a manager who implements buybacks for the firm. Buybacks introduce two opposing economic forces. On the one hand, informed buybacks intensify the competition for trading profits, making it more difficult to profit from private information. On the other, buybacks generate gains and losses that increase the dispersion of the firm's per-share value across different payoff states, making private information more valuable. Less informative buybacks weaken the first force, while strengthening the second. The manager's incentive to manipulate the current stock price in order to increase her compensation constrains how much buybacks reflect her private information. The model generates novel predictions linking the structure of the manager's compensation, the buyback authorization decision, and trading outcomes following buybacks.
Bank Lending Networks and the Propagation of Natural Disasters
SSRN
We study how bank lending networks propagate natural disaster shocks. Natural disasters lead to an increase in corporate credit demand in affected regions. Banks meet the increase in credit demand in part by reducing credit to distant regions, not affected by natural disasters. Capital constraints play a key role in this effect as lower-capital banks propagate disaster shocks to distant regions to a greater extent. Shadow banks step in and provide additional credit in distant regions, but only partially offset the reduction in bank credit. As a result, corporate credit in distant regions still falls by approximately 3%.
SSRN
We study how bank lending networks propagate natural disaster shocks. Natural disasters lead to an increase in corporate credit demand in affected regions. Banks meet the increase in credit demand in part by reducing credit to distant regions, not affected by natural disasters. Capital constraints play a key role in this effect as lower-capital banks propagate disaster shocks to distant regions to a greater extent. Shadow banks step in and provide additional credit in distant regions, but only partially offset the reduction in bank credit. As a result, corporate credit in distant regions still falls by approximately 3%.
From Financial to Carbon Diversification â€" The Potential of Physical Gold
SSRN
Gold is a well-known diversifier of financial risk with a long history as a physical asset. This paper analyzes whether gold provides additional environmental benefits in the portfolio context. We show that the addition of gold to a diversified equity portfolio does not only enhance the risk-return relationship but also its sustainability by reducing the portfolio’s carbon emissions. If carbon emissions are fully accounted for at the production (firm) level, physical gold holdings have zero CO2 emissions. Even if CO2 emissions are fully assigned to physical gold holdings, gold becomes a CO2 diversifier if held over longer periods. Our study highlights the critical role of physical assets and the investment horizon in the sustainability analysis of portfolios.
SSRN
Gold is a well-known diversifier of financial risk with a long history as a physical asset. This paper analyzes whether gold provides additional environmental benefits in the portfolio context. We show that the addition of gold to a diversified equity portfolio does not only enhance the risk-return relationship but also its sustainability by reducing the portfolio’s carbon emissions. If carbon emissions are fully accounted for at the production (firm) level, physical gold holdings have zero CO2 emissions. Even if CO2 emissions are fully assigned to physical gold holdings, gold becomes a CO2 diversifier if held over longer periods. Our study highlights the critical role of physical assets and the investment horizon in the sustainability analysis of portfolios.
Microfinance and Human Development in Kerala
RePEC
This paper examines how microfinance institutions impact human development indicators using the case of Kerala in southern India. The study uses an institutional approach to understand microfinance institutions with the help of three variables - core activities, total loan portfolio and approach to microfinance. The impact of microfinance institutions on four human development variables namely education, health, income and participation are analyzed. The main conclusion of the study is that microfinance institutions that follow an integrated approach impact human development more than those that follow a minimalist approach. Furthermore, this impact of microfinance institution is due to production functions that generate income and protective function that defends against vulnerability. Therefore, an integrated approach to microfinance has income generating and risk mitigating effects that translate into better human development indicators.
RePEC
This paper examines how microfinance institutions impact human development indicators using the case of Kerala in southern India. The study uses an institutional approach to understand microfinance institutions with the help of three variables - core activities, total loan portfolio and approach to microfinance. The impact of microfinance institutions on four human development variables namely education, health, income and participation are analyzed. The main conclusion of the study is that microfinance institutions that follow an integrated approach impact human development more than those that follow a minimalist approach. Furthermore, this impact of microfinance institution is due to production functions that generate income and protective function that defends against vulnerability. Therefore, an integrated approach to microfinance has income generating and risk mitigating effects that translate into better human development indicators.
Robust Identification of Controlled Hawkes Processes
SSRN
The identification of Hawkes-like processes can pose significant challenges. Despite substantial amounts of data, standard estimation methods show significant bias or fail to converge. To overcome these issues, we propose an alternative approach based on an expectation-maximization algorithm, which instrumentalizes the internal branching-structure of the process, thus improving convergence behavior. Furthermore, we show that our method provides a tight lower-bound for maximum-likelihood estimates. The approach is discussed in the context of a practical application, namely the collection of outstanding unsecured consumer debt.
SSRN
The identification of Hawkes-like processes can pose significant challenges. Despite substantial amounts of data, standard estimation methods show significant bias or fail to converge. To overcome these issues, we propose an alternative approach based on an expectation-maximization algorithm, which instrumentalizes the internal branching-structure of the process, thus improving convergence behavior. Furthermore, we show that our method provides a tight lower-bound for maximum-likelihood estimates. The approach is discussed in the context of a practical application, namely the collection of outstanding unsecured consumer debt.
Systemic Risk in Global Volatility Spillover Networks: Evidence from Option-Implied Volatility Indices
SSRN
With option-implied volatility indices, we identify networks of global volatility spillovers and examine time-varying systemic risk across global financial markets. The US stock market is the center of the network and plays a dominant role in the spread of volatility spillover to other markets. The global systemic risks have intensified since the Federal Reserve exited from quantitative easing, hiked interest rate，and shrank its balance sheet. We further show that the US monetary tightening is an important catalyst for the intensifying global systemic risk. Our findings highlight the pernicious effects of monetary tightening after an era of cheap money.
SSRN
With option-implied volatility indices, we identify networks of global volatility spillovers and examine time-varying systemic risk across global financial markets. The US stock market is the center of the network and plays a dominant role in the spread of volatility spillover to other markets. The global systemic risks have intensified since the Federal Reserve exited from quantitative easing, hiked interest rate，and shrank its balance sheet. We further show that the US monetary tightening is an important catalyst for the intensifying global systemic risk. Our findings highlight the pernicious effects of monetary tightening after an era of cheap money.
The Impacts of Minimum Trading Units and Tick Size Changes on Bid-ask Spread, Depth, and Trading Volume: Evidence from the Indonesia Stock Exchange
SSRN
Purpose â€" This research aims to analyze the differences in the bid-ask spread, depth, and trading volume after a new tick size and minimum trading unit policy were imposed by the Indonesian Stock Exchange (IDX) on January the 6th, 2014. Design/Methodology/Approach â€" This research is exercised on the three variables of liquidity, i.e. the bid-ask spread, the depth, and the trading volume. This research used a paired difference test to measure the impact before and after the policy was imposed. Findings â€" The results showed that the smaller the tick size, the greater the average decrease of the bid-ask spread, ask depth, and bid depth, but the trading volume did not show a significant average difference. Research Implications â€" The tick size reduction was consistent and supported the previous research from different countries. The bid-ask spread, ask depth, and bid depth significantly decreased, and the trading volume had a tendency to increase as well, although it was not significant. Results are aimed at the IDX and Bapepam as additional information related to the changes that occurred as a result of the implementation of the new policy in stock trading. Investors can use the information from this study to make investment decisions.
SSRN
Purpose â€" This research aims to analyze the differences in the bid-ask spread, depth, and trading volume after a new tick size and minimum trading unit policy were imposed by the Indonesian Stock Exchange (IDX) on January the 6th, 2014. Design/Methodology/Approach â€" This research is exercised on the three variables of liquidity, i.e. the bid-ask spread, the depth, and the trading volume. This research used a paired difference test to measure the impact before and after the policy was imposed. Findings â€" The results showed that the smaller the tick size, the greater the average decrease of the bid-ask spread, ask depth, and bid depth, but the trading volume did not show a significant average difference. Research Implications â€" The tick size reduction was consistent and supported the previous research from different countries. The bid-ask spread, ask depth, and bid depth significantly decreased, and the trading volume had a tendency to increase as well, although it was not significant. Results are aimed at the IDX and Bapepam as additional information related to the changes that occurred as a result of the implementation of the new policy in stock trading. Investors can use the information from this study to make investment decisions.
The Pecking Order Theory of Capital Structure: Where Do We Stand?
SSRN
The pecking order theory of corporate capital structure states that firms finance deficits with internal resources when possible. If internal funds are inadequate, firms obtain external debt. External equity is the last resort. Some financing patterns in the data are consistent with pecking order: firms with moderate deficits favor debt issues; firms with very high deficits rely much more on equity than debt. Others are not: many equity issuing firms do not seem to have entirely used up the debt capacity; some firms with a surplus do issue equity. The theory suggests a sharp discontinuity of financing methods between surplus firms and deficit firms and another at the debt capacity. The literature provides little support for the predicted threshold effects.
SSRN
The pecking order theory of corporate capital structure states that firms finance deficits with internal resources when possible. If internal funds are inadequate, firms obtain external debt. External equity is the last resort. Some financing patterns in the data are consistent with pecking order: firms with moderate deficits favor debt issues; firms with very high deficits rely much more on equity than debt. Others are not: many equity issuing firms do not seem to have entirely used up the debt capacity; some firms with a surplus do issue equity. The theory suggests a sharp discontinuity of financing methods between surplus firms and deficit firms and another at the debt capacity. The literature provides little support for the predicted threshold effects.
The Sensitivity of Trading to the Cost of Information
SSRN
This study examines the impact of changes in data feed pricing schedules on the price discovery between competing venues, as espoused by Cespa & Foucault (2014). We utilize three exogenous events stemming from a staggered increase in the data feed price that transpired on the Chicago Mercantile Exchange and observe a decrease in the efficiency of price discovery following increases in the acquisition costs of exchange’s data feeds, in line with the theory. Our results indicate that the regulators need to closely monitor any increases in data fees since these not only redistribute income from the traders to the exchanges but also affect the quality of the market via price discovery, one of the market’s most important functions.
SSRN
This study examines the impact of changes in data feed pricing schedules on the price discovery between competing venues, as espoused by Cespa & Foucault (2014). We utilize three exogenous events stemming from a staggered increase in the data feed price that transpired on the Chicago Mercantile Exchange and observe a decrease in the efficiency of price discovery following increases in the acquisition costs of exchange’s data feeds, in line with the theory. Our results indicate that the regulators need to closely monitor any increases in data fees since these not only redistribute income from the traders to the exchanges but also affect the quality of the market via price discovery, one of the market’s most important functions.
