Research articles for the 2021-01-13
Active Technological Similarity and Mutual Fund Performance
SSRN
We examine whether superior understanding of technological innovation is a source of mutual fund managers’ ability to garner positive abnormal returns. Consistent with our hypothesis, the inter-quintile annual net Carhart alpha spread for mutual funds sorted on changes in the technological similarity of their portfolio holdings is 282 basis points. Moreover, because changes in technological similarity are largely orthogonal to other predictors of mutual fund success (e.g., industry concentration, active share, fund R2, and lag fund alpha), changes in technological similarity can be combined with other measures to help identify the best performing funds.
SSRN
We examine whether superior understanding of technological innovation is a source of mutual fund managers’ ability to garner positive abnormal returns. Consistent with our hypothesis, the inter-quintile annual net Carhart alpha spread for mutual funds sorted on changes in the technological similarity of their portfolio holdings is 282 basis points. Moreover, because changes in technological similarity are largely orthogonal to other predictors of mutual fund success (e.g., industry concentration, active share, fund R2, and lag fund alpha), changes in technological similarity can be combined with other measures to help identify the best performing funds.
An analytical perturbative solution to the Merton Garman model using symmetries
arXiv
arXiv
In this paper, we introduce an analytical perturbative solution to the Merton Garman model. It is obtained by doing perturbation theory around the exact analytical solution of a model which possesses a two-dimensional Galilean symmetry. We compare our perturbative solution of the Merton Garman model to Monte Carlo simulations and find that our solutions performs surprisingly well for a wide range of parameters. We also show how to use symmetries to build option pricing models. Our results demonstrate that the concept of symmetry is important in mathematical finance.
Analysts' Stock Views and Revision Actions
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This study analyzes the consistency between analysts’ stock views and their revisions of earnings forecasts, price targets, and recommendations. A hidden Markov model (HMM) is employed to extract analysts’ views. The results show that consistent revisions (i.e., upgrades accompanied by favorable views and downgrades accompanied by unfavorable views) more effectively trigger the stock price reactions than inconsistent revisions. The rigidity of the stock views (i.e., views are unlikely to change) negatively impacts the stock price reactions. The study highlights the importance of inferring analysts’ implicit stock views, as it influences the effectiveness of their stock research outputs.
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This study analyzes the consistency between analysts’ stock views and their revisions of earnings forecasts, price targets, and recommendations. A hidden Markov model (HMM) is employed to extract analysts’ views. The results show that consistent revisions (i.e., upgrades accompanied by favorable views and downgrades accompanied by unfavorable views) more effectively trigger the stock price reactions than inconsistent revisions. The rigidity of the stock views (i.e., views are unlikely to change) negatively impacts the stock price reactions. The study highlights the importance of inferring analysts’ implicit stock views, as it influences the effectiveness of their stock research outputs.
Are Investors Sensitive to Impact?
SSRN
The rise of sustainable investing emphasizes that many investors value sustainability. But is investors’ valuation of sustainability proportional to the impact of investments, i.e., the investment’s positive social or environmental externalities? In a framed field experiment, we assess how the willingness-to-pay (WTP) for sustainability of experienced investors and dedicated impact investors depends on the impact of investments. We confirm that investors have a substantial WTP for sustainability. However, this WTP does not depend on how much impact investments have. Further findings suggest that investors’ valuation of sustainability is mainly driven by affect. Also, we show that investors are sensitive to impact if they can compare several impactful investments. Still, the WTP per unit of impact strictly depends on the impact of other salient investments, indicating that investors’ valuation of sustainability is susceptible to superficial changes in how impact information is displayed.
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The rise of sustainable investing emphasizes that many investors value sustainability. But is investors’ valuation of sustainability proportional to the impact of investments, i.e., the investment’s positive social or environmental externalities? In a framed field experiment, we assess how the willingness-to-pay (WTP) for sustainability of experienced investors and dedicated impact investors depends on the impact of investments. We confirm that investors have a substantial WTP for sustainability. However, this WTP does not depend on how much impact investments have. Further findings suggest that investors’ valuation of sustainability is mainly driven by affect. Also, we show that investors are sensitive to impact if they can compare several impactful investments. Still, the WTP per unit of impact strictly depends on the impact of other salient investments, indicating that investors’ valuation of sustainability is susceptible to superficial changes in how impact information is displayed.
Asset Pricing Based on Micro Consumption
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Using micro data, we find that the top quantiles of consumption growth are generally positively correlated with asset returns; at low quantiles, the correlations are negative-valued for many individuals. The findings support our asset pricing model based on an S-shaped consumption utility. In this model, individuals are risk-seeking (resp. risk-averse) in certain states, and their consumption growth varies negatively (resp. positively) with risky returns. Therefore, consumption growth has a small covariance with risky returns. Applying concave utility will mistakenly lead to a positive correlation between risky returns and stochastic discount factors of risk-seeking individuals, and thus asset pricing puzzles arise.
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Using micro data, we find that the top quantiles of consumption growth are generally positively correlated with asset returns; at low quantiles, the correlations are negative-valued for many individuals. The findings support our asset pricing model based on an S-shaped consumption utility. In this model, individuals are risk-seeking (resp. risk-averse) in certain states, and their consumption growth varies negatively (resp. positively) with risky returns. Therefore, consumption growth has a small covariance with risky returns. Applying concave utility will mistakenly lead to a positive correlation between risky returns and stochastic discount factors of risk-seeking individuals, and thus asset pricing puzzles arise.
Barriers to Global Capital Allocation
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We quantify the impact of barriers to international investment, using a novel multi-country over- lapping generations model with heterogeneous investors and imperfect capital mobility. Our model yields a gravity equation for foreign asset demand. We estimate this gravity equation using recently- developed foreign investment data that has been restated to account for the presence of offshore investment and financing vehicles. We show that a parsimonious implementation of the model, with four barriers (capital controls, geographic distance, institutional distance and cultural distance) can account for a large share of the observed variation in bilateral Foreign Direct Investment (FDI) and Foreign Portfolio Investment (FPI) positions. Our model predicts a significant home bias and higher rates of return on capital in emerging markets. In our benchmark calibration, we estimate that capital misallocation induced by these barriers reduces World GDP by 8.8%, compared to a situation without barriers. We also find that barriers to global capital allocation contribute significantly to cross-country inequality: the standard deviation of log capital per employee is 70% higher than it would be in a world without barriers to international investment, while the dispersion in output per employee is 39% higher.
SSRN
We quantify the impact of barriers to international investment, using a novel multi-country over- lapping generations model with heterogeneous investors and imperfect capital mobility. Our model yields a gravity equation for foreign asset demand. We estimate this gravity equation using recently- developed foreign investment data that has been restated to account for the presence of offshore investment and financing vehicles. We show that a parsimonious implementation of the model, with four barriers (capital controls, geographic distance, institutional distance and cultural distance) can account for a large share of the observed variation in bilateral Foreign Direct Investment (FDI) and Foreign Portfolio Investment (FPI) positions. Our model predicts a significant home bias and higher rates of return on capital in emerging markets. In our benchmark calibration, we estimate that capital misallocation induced by these barriers reduces World GDP by 8.8%, compared to a situation without barriers. We also find that barriers to global capital allocation contribute significantly to cross-country inequality: the standard deviation of log capital per employee is 70% higher than it would be in a world without barriers to international investment, while the dispersion in output per employee is 39% higher.
Behavioral Finance in Investing: The Existence and Importance of 'Investment Tribes' and Risk-Preference Diversity
SSRN
Using case studies of two investment companies, this paper highlights that organizations may have “investment tribes,†i.e., groups of individuals who appear to exhibit similar risk tendencies for gambles involving gains or losses, possibly with a wide spread of risk preferences. Tribes and risk-preference diversity can influence and impact decision-making. Quantifying and making transparentthe existence of these tribes and individual preferences, using the Risktyle methodology, which extends the original Kahneman and Tversky (1979) approach to identifying risk biases, could improve decision-making, especially in market crises such as that of March 2020. The framework presented can be helpful for investment firms and investment advisors, allowing them to become aware of potential biases. It also can be useful for asset owners that delegate decisions to third parties, because it allows them to understand how the investment firms they delegate to might behave when drawdowns result during market crises.
SSRN
Using case studies of two investment companies, this paper highlights that organizations may have “investment tribes,†i.e., groups of individuals who appear to exhibit similar risk tendencies for gambles involving gains or losses, possibly with a wide spread of risk preferences. Tribes and risk-preference diversity can influence and impact decision-making. Quantifying and making transparentthe existence of these tribes and individual preferences, using the Risktyle methodology, which extends the original Kahneman and Tversky (1979) approach to identifying risk biases, could improve decision-making, especially in market crises such as that of March 2020. The framework presented can be helpful for investment firms and investment advisors, allowing them to become aware of potential biases. It also can be useful for asset owners that delegate decisions to third parties, because it allows them to understand how the investment firms they delegate to might behave when drawdowns result during market crises.
Broadband Internet and the Stock Market Investments of Individual Investors
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We study the effects of broadband internet use on the portfolio selection of individual investors. A public program in Norway provides plausibly exogenous variation in internet use. Our instrumental variables estimates show that internet use causes a substantial increase in stock market participation, driven primarily by increased fund ownership. Existing investors increase the fraction of their portfolios held in funds and do not increase their trading activity in stocks. Access to fast internet seems to induce individual investors to make better financial decisions and hence leads to a "democratization of finance".
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We study the effects of broadband internet use on the portfolio selection of individual investors. A public program in Norway provides plausibly exogenous variation in internet use. Our instrumental variables estimates show that internet use causes a substantial increase in stock market participation, driven primarily by increased fund ownership. Existing investors increase the fraction of their portfolios held in funds and do not increase their trading activity in stocks. Access to fast internet seems to induce individual investors to make better financial decisions and hence leads to a "democratization of finance".
COVID-19 Crisis, Bankruptcy Risk, and Transition Dynamics
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The COVID-19 pandemic has pushed many firms to the edge of bankruptcy and revived concerns of a prolonged/deep recession. The government has introduced various policies to mitigate its economic impact. We build a continuous time heterogeneous agent model to study (i) corporate bankruptcy risks, and (ii) the transition dynamics of the economy. This general framework is applied for understanding the implications of the COVID-19 economic crisis. The higher the bankruptcy rate, the faster the transition towards the new long run steady state. Transition speed decreases as the mass of firms in the upper tail of the net worth distribution increases. While broad fiscal policies are relatively more effective in reducing bankruptcy risks, monetary policies of providing market liquidity are more effective in generating faster transition dynamics.
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The COVID-19 pandemic has pushed many firms to the edge of bankruptcy and revived concerns of a prolonged/deep recession. The government has introduced various policies to mitigate its economic impact. We build a continuous time heterogeneous agent model to study (i) corporate bankruptcy risks, and (ii) the transition dynamics of the economy. This general framework is applied for understanding the implications of the COVID-19 economic crisis. The higher the bankruptcy rate, the faster the transition towards the new long run steady state. Transition speed decreases as the mass of firms in the upper tail of the net worth distribution increases. While broad fiscal policies are relatively more effective in reducing bankruptcy risks, monetary policies of providing market liquidity are more effective in generating faster transition dynamics.
COVID-19 Effects on the Canadian Term Structure of Interest Rates
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In Canada, COVID-19 pandemic triggered exceptional monetary policy interventions by the central bank, which in March 2020 made multiple unscheduled cuts to its target rate. We use functional data analysis techniques to assess the extent to which Bank of Canada interventions affected the determinants of the yield curve. By applying Functional Principal Component Analysis to the term structure of interest rates we find that, during the pandemic, the long-run dependence of level and slope components of the yield curve is unchanged with respect to previous months, although the shape of the mean yield curve completely changed after target rate cuts. Bank of Canada was effective in lowering the whole yield curve and correcting the inverted hump of previous months, but it was not able to reduce the exposure to already existing long-run risks.
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In Canada, COVID-19 pandemic triggered exceptional monetary policy interventions by the central bank, which in March 2020 made multiple unscheduled cuts to its target rate. We use functional data analysis techniques to assess the extent to which Bank of Canada interventions affected the determinants of the yield curve. By applying Functional Principal Component Analysis to the term structure of interest rates we find that, during the pandemic, the long-run dependence of level and slope components of the yield curve is unchanged with respect to previous months, although the shape of the mean yield curve completely changed after target rate cuts. Bank of Canada was effective in lowering the whole yield curve and correcting the inverted hump of previous months, but it was not able to reduce the exposure to already existing long-run risks.
Cash Heterogeneity and the Payout Channel of Monetary Policy
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This paper investigates the role of corporate cash heterogeneity in the transmission of monetary policy to equity payouts and cross-sectional risk premia. Compared to cash-poor firms, cash-rich firms not only pay out persistently more but also earn higher returns in response to expansionary monetary policy news surprises. I develop a heterogeneous firm New-Keynesian model with cash holdings and costly equity issuance to interpret the empirical findings. In the model, cash-rich firms have weaker cash flow and investment responses to monetary policy, however they disburse excess savings as precautionary cash demand declines due to monetary easing. Nominal rigidities endogenously produce procyclical payouts, rendering payout claims of cash-rich firms risky and generating cross-sectional risk premia. The paper supports a central role for the expected path of the monetary policy in affecting corporate outcomes and asset prices.
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This paper investigates the role of corporate cash heterogeneity in the transmission of monetary policy to equity payouts and cross-sectional risk premia. Compared to cash-poor firms, cash-rich firms not only pay out persistently more but also earn higher returns in response to expansionary monetary policy news surprises. I develop a heterogeneous firm New-Keynesian model with cash holdings and costly equity issuance to interpret the empirical findings. In the model, cash-rich firms have weaker cash flow and investment responses to monetary policy, however they disburse excess savings as precautionary cash demand declines due to monetary easing. Nominal rigidities endogenously produce procyclical payouts, rendering payout claims of cash-rich firms risky and generating cross-sectional risk premia. The paper supports a central role for the expected path of the monetary policy in affecting corporate outcomes and asset prices.
Could the 1933 Glass-Steagall Act Have Prevented the Financial Crisis?
SSRN
This paper explores the common argument according to which the repeal of the Glass-Steagall Act was at the origin of the 2008 financial crisis. By arguing successively that the Act would not have covered the failing banks and that it would not have solved the “Too-big-to-fail†problem, this paper concludes by the negative. Had the Glass-Steagall act still been in place, the global Financial crisis would not have been prevented. Mortgage policies, low capital requirements, and Basel II seem to be more convincing alternatives.
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This paper explores the common argument according to which the repeal of the Glass-Steagall Act was at the origin of the 2008 financial crisis. By arguing successively that the Act would not have covered the failing banks and that it would not have solved the “Too-big-to-fail†problem, this paper concludes by the negative. Had the Glass-Steagall act still been in place, the global Financial crisis would not have been prevented. Mortgage policies, low capital requirements, and Basel II seem to be more convincing alternatives.
Day-ahead electricity prices prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling
arXiv
arXiv
The availability of accurate day-ahead electricity price forecasts is pivotal for electricity market participants. In the context of trade liberalisation and market harmonisation in the European markets, accurate price forecasting becomes even more difficult to obtain. The increasing power market integration has complicated the forecasting process, where electricity forecasting requires considering features from both the local market and ever-growing coupling markets. In this paper, we apply state-of-the-art deep learning models, combined with feature selection algorithms for electricity price prediction under the consideration of market coupling. We propose three hybrid architectures of long-short term memory (LSTM) deep neural networks and compare the prediction performance, in terms of various feature selections. In our empirical study, we construct a broad set of features from the Nord Pool market and its six coupling countries for forecasting the Nord Pool system price. The results show that feature selection is essential to achieving accurate prediction. Superior feature selection algorithms filter meaningful information, eliminate irrelevant information, and further improve the forecasting accuracy of LSTM-based deep neural networks. The proposed models obtain considerably accurate results.
Designing the Best Solution for Retirement
SSRN
In March 2020, Robert Powell, Retirement Management Journal editor-in-chief; Zvi Bodie, PhD, president of Bodie Associates and the Norman and Adele Barron Professor Emeritus of Management at Boston University; and Stacy Schaus, founder and chief executive officer of Schaus Group LLC, spoke with Merton about retirement solutions for the twenty-first century working and middle classes, fintech, and solving for the right problems.
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In March 2020, Robert Powell, Retirement Management Journal editor-in-chief; Zvi Bodie, PhD, president of Bodie Associates and the Norman and Adele Barron Professor Emeritus of Management at Boston University; and Stacy Schaus, founder and chief executive officer of Schaus Group LLC, spoke with Merton about retirement solutions for the twenty-first century working and middle classes, fintech, and solving for the right problems.
E. Robert Fernholz, PhD: Stochastic Portfolio Theory
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In June 2020, Robert Fernholz spoke with members of the Journal of Investment Consulting’s editorial advisory board about stochastic portfolio theory, its contributions to the investment industry’s knowledge of equity markets, and its applicability to creating and monitoring investment portfolios. Taking part in the discussion were Inna Okounkova, Columbia University and editor-in-chief of the Journal; Edward Baker, Mesirow Financial; Ludwig Chincarini, University of San Francisco and United States Commodity Funds; Philip Fazio, Merrill Lynch; and Geoffrey Gerber, TWIN Capital Management.
SSRN
In June 2020, Robert Fernholz spoke with members of the Journal of Investment Consulting’s editorial advisory board about stochastic portfolio theory, its contributions to the investment industry’s knowledge of equity markets, and its applicability to creating and monitoring investment portfolios. Taking part in the discussion were Inna Okounkova, Columbia University and editor-in-chief of the Journal; Edward Baker, Mesirow Financial; Ludwig Chincarini, University of San Francisco and United States Commodity Funds; Philip Fazio, Merrill Lynch; and Geoffrey Gerber, TWIN Capital Management.
Equity Incentives and Financial Misreporting: Evidence from the Wealth Pursuit Motive of CEOs
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The incentive effect of CEO portfolio delta (i.e., the sensitivity of CEO wealth to changes in stock price) on financial misreporting is inconclusive given a complex reward-risk tradeoff faced by CEOs. As the tradeoff is associated with a CEO’s explicit focus on personal wealth, we introduce a new theoretical insight into the tradeoff and focus on the CEO’s misreporting motive for pursuing wealth when testing the net incentive effect of delta. We identify wealth-pursuing misreporting via the Accounting and Auditing Enforcement Release (AAERs) and document that such misreporting is not only widespread in our sample but also positively explained by CEO portfolio delta. This positive association between CEO portfolio delta and wealth-pursuing misreporting is robust to the use of coarsened exact matching, the firm-year-fixed-effect model, the two-stage instrumental variable method, and a battery of supplementary analyses. We also approach the prior inconclusive empirical evidence in simulation analysis. Our findings have important implications for compensation design and corporate governance policy.
SSRN
The incentive effect of CEO portfolio delta (i.e., the sensitivity of CEO wealth to changes in stock price) on financial misreporting is inconclusive given a complex reward-risk tradeoff faced by CEOs. As the tradeoff is associated with a CEO’s explicit focus on personal wealth, we introduce a new theoretical insight into the tradeoff and focus on the CEO’s misreporting motive for pursuing wealth when testing the net incentive effect of delta. We identify wealth-pursuing misreporting via the Accounting and Auditing Enforcement Release (AAERs) and document that such misreporting is not only widespread in our sample but also positively explained by CEO portfolio delta. This positive association between CEO portfolio delta and wealth-pursuing misreporting is robust to the use of coarsened exact matching, the firm-year-fixed-effect model, the two-stage instrumental variable method, and a battery of supplementary analyses. We also approach the prior inconclusive empirical evidence in simulation analysis. Our findings have important implications for compensation design and corporate governance policy.
Factor Tilts and Asset Allocation
SSRN
Factor investing has received much attention from academics and practitioners, as well as from individual and institutional investors. It has become usual for investors that aim to enhance returns to add to the core of their portfolios a factor satellite, thus tilting their portfolios toward factors that have produced a long-term risk premium. However, in most cases, investors behaving this way are not fully invested in stocks, which begs an interesting question: Should an investor with a two-asset portfolio of broadly diversified stocks and bonds tilt the stocks slice of the portfolio toward (small-cap and value) factors, or would the investor be better off simply increasing the allocation to broadly diversified stocks in the two-asset portfolio? The results discussed here, based on different samples and sample periods, support the notion of factor-tilting portfolios.
SSRN
Factor investing has received much attention from academics and practitioners, as well as from individual and institutional investors. It has become usual for investors that aim to enhance returns to add to the core of their portfolios a factor satellite, thus tilting their portfolios toward factors that have produced a long-term risk premium. However, in most cases, investors behaving this way are not fully invested in stocks, which begs an interesting question: Should an investor with a two-asset portfolio of broadly diversified stocks and bonds tilt the stocks slice of the portfolio toward (small-cap and value) factors, or would the investor be better off simply increasing the allocation to broadly diversified stocks in the two-asset portfolio? The results discussed here, based on different samples and sample periods, support the notion of factor-tilting portfolios.
Financial Crises and Labor Market Recoveries: A Bayesian Evaluation
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Average hours worked in the US recovers much faster than the unemployment rate following financial crises. Using an identified vector autoregression framework with nine quarterly US time series from 1984 to 2014, I find that an adverse financial shock leads to a fall in economic activity with a persistent increase in the unemployment rate but a transitory decrease in average hours worked. I then embed labor market frictions and financial frictions into a New Keynesian model to explain this stylized fact. The model introduces a relatively new financial shock the default cost shock, which captures the financial market’s inefficiency. I estimate the model using Bayesian methods and find that the default cost shock explains a significant portion of the variations in aggregate variables. In particular, this shock accounts for the business cycle features of a financial crisis better than the other relevant shocks do.
SSRN
Average hours worked in the US recovers much faster than the unemployment rate following financial crises. Using an identified vector autoregression framework with nine quarterly US time series from 1984 to 2014, I find that an adverse financial shock leads to a fall in economic activity with a persistent increase in the unemployment rate but a transitory decrease in average hours worked. I then embed labor market frictions and financial frictions into a New Keynesian model to explain this stylized fact. The model introduces a relatively new financial shock the default cost shock, which captures the financial market’s inefficiency. I estimate the model using Bayesian methods and find that the default cost shock explains a significant portion of the variations in aggregate variables. In particular, this shock accounts for the business cycle features of a financial crisis better than the other relevant shocks do.
Greed and Individual Trading Behavior in Experimental Asset Markets
SSRN
Greed has been shown to be an important economic motive. Both the popular press as well as scientific papers have mentioned questionable practices by greedy bankers and investors as one of the root causes of the 2008 global financial crisis. In spite of these suggestions, there is as of yet no substantive empirical evidence for a contribution of greed to individual trading behavior. This paper presents the result of 15 experimental asset markets in which we test the influence of greed on trading behavior. We do not find empirical support for the idea that greedier investors trade fundamentally different from their less greedy counterparts in markets. These findings shed light on the role of greed in trading and the emergence of asset market bubbles in specific, and of the financial crisis in general. Directions for future research are discussed.
SSRN
Greed has been shown to be an important economic motive. Both the popular press as well as scientific papers have mentioned questionable practices by greedy bankers and investors as one of the root causes of the 2008 global financial crisis. In spite of these suggestions, there is as of yet no substantive empirical evidence for a contribution of greed to individual trading behavior. This paper presents the result of 15 experimental asset markets in which we test the influence of greed on trading behavior. We do not find empirical support for the idea that greedier investors trade fundamentally different from their less greedy counterparts in markets. These findings shed light on the role of greed in trading and the emergence of asset market bubbles in specific, and of the financial crisis in general. Directions for future research are discussed.
Including Factor Investing in Portfolio Design
SSRN
In February 2020, Andrew Ang spoke with members of the Journal of Investment Consulting editorial advisory board about factor investingâ€"its fundamental economic basis, its past performance, and its role in the future. Taking part in the discussion were Inna Okounkova, Columbia University and editor-in-chief of the Journal; Mark J. P. Anson, The Commonfund; Edward Baker, Mesirow Financial; Ludwig Chincarini, University of San Francisco and United States Commodity Funds; Philip Fazio, Merrill Lynch; and Geoffrey Gerber, TWIN Capital Management.
SSRN
In February 2020, Andrew Ang spoke with members of the Journal of Investment Consulting editorial advisory board about factor investingâ€"its fundamental economic basis, its past performance, and its role in the future. Taking part in the discussion were Inna Okounkova, Columbia University and editor-in-chief of the Journal; Mark J. P. Anson, The Commonfund; Edward Baker, Mesirow Financial; Ludwig Chincarini, University of San Francisco and United States Commodity Funds; Philip Fazio, Merrill Lynch; and Geoffrey Gerber, TWIN Capital Management.
Intraday Market Predictability: A Machine Learning Approach
SSRN
This paper analyses and demonstrates the predictability of intraday market returns. Conducting, to our knowledge, the largest study ever of five-minute market returns using state-of-the-art machine learning models trained on lagged returns to forecast five-minute equity market index returns, we show that regularized linear models such as lasso and elastic nets along with nonlinear tree based models such as random forests yield significant predictability. Ensemble models that combine individual model predictions perform the best across time and their return predictability translates into economically significant profits with Sharpe ratios after transaction costs of 0.98. This strong predictability of intraday market returns provides evidence against market efficiency over short time horizons. Consistent with the hypothesis that predictability is driven by trader inefficiency, predictability decreased after decimalization, and market returns are more predictable during the middle of the day, on days with high volatility or high illiquidity, and in years of financial crisis.
SSRN
This paper analyses and demonstrates the predictability of intraday market returns. Conducting, to our knowledge, the largest study ever of five-minute market returns using state-of-the-art machine learning models trained on lagged returns to forecast five-minute equity market index returns, we show that regularized linear models such as lasso and elastic nets along with nonlinear tree based models such as random forests yield significant predictability. Ensemble models that combine individual model predictions perform the best across time and their return predictability translates into economically significant profits with Sharpe ratios after transaction costs of 0.98. This strong predictability of intraday market returns provides evidence against market efficiency over short time horizons. Consistent with the hypothesis that predictability is driven by trader inefficiency, predictability decreased after decimalization, and market returns are more predictable during the middle of the day, on days with high volatility or high illiquidity, and in years of financial crisis.
Liquidity Guided Machine Learning: The Case of the Volatility Risk Premium
SSRN
The financial industry has eagerly adopted machine learning algorithms to improve on traditional predictive models. In this paper we caution against blindly applying such techniques. We compare forecasting ability of machine learning methods in evaluating future payoffs on synthetic variance swaps. Standard machine learning methods tend to identify contracts which are illiquid, and hard to trade. The most successful strategies turn out to be those where we pair machine learning with institutional and market/traders inputs and insights. We show that liquidity guided pre-selection of inputs to machine learning results in trading strategies with improved pay-offs to the writers of variance swap contract replicating portfolio.
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The financial industry has eagerly adopted machine learning algorithms to improve on traditional predictive models. In this paper we caution against blindly applying such techniques. We compare forecasting ability of machine learning methods in evaluating future payoffs on synthetic variance swaps. Standard machine learning methods tend to identify contracts which are illiquid, and hard to trade. The most successful strategies turn out to be those where we pair machine learning with institutional and market/traders inputs and insights. We show that liquidity guided pre-selection of inputs to machine learning results in trading strategies with improved pay-offs to the writers of variance swap contract replicating portfolio.
Long-Term Investing in Triple Leveraged Exchange Traded Funds
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The phrase long-term investing in triple leveraged ETFs is somewhat of an anathema for investment academicians. As a result of daily rebalancing and so-called beta slippage or “the constant leverage trap†it is highly likely over the long term to significantly deviate from the targeted leverage and, in so doing, generate wipeout losses. In fact, the data show that many 3X leveraged ETFs have performed poorly over the long term in the period of their existence. However, there are some significant exceptions. The 3X leveraged Nasdaq ETF, TQQQ, for example has delivered a total return exceeding 10,000% (CAGR of 54.4%) over the 10+ years of its existence, more than 13 times the total return of its underlying ETF (QQQ). Similar, but less impressive numbers have been achieved with triple leveraged ETFs that target the S&P 500 and the Dow Industrials.These results, however, are accompanied by excessive volatility and very large maximum end-of-month (EOM) draw downs, in excess of 49% for TQQQ, and with maximum daily drawdown of almost 70%. Many retail investors would be unwilling to sustain such (paper) losses. Here we propose a strategy to mitigate these large draw downs while still retaining much of the upside performance of triple leveraging. We show that by simply establishing a portfolio consisting of an equal dollar amount of TQQQ and TMF (the triple leveraged ETF linked to the 20+ year treasury bond), and performing bimonthly rebalancing, a total return, after transaction costs, in excess of 5,800% (CAGR of 44.9%) would have been achieved over the 10+ years of TQQQ existence, with the maximum EOM draw down less than 25%.
SSRN
The phrase long-term investing in triple leveraged ETFs is somewhat of an anathema for investment academicians. As a result of daily rebalancing and so-called beta slippage or “the constant leverage trap†it is highly likely over the long term to significantly deviate from the targeted leverage and, in so doing, generate wipeout losses. In fact, the data show that many 3X leveraged ETFs have performed poorly over the long term in the period of their existence. However, there are some significant exceptions. The 3X leveraged Nasdaq ETF, TQQQ, for example has delivered a total return exceeding 10,000% (CAGR of 54.4%) over the 10+ years of its existence, more than 13 times the total return of its underlying ETF (QQQ). Similar, but less impressive numbers have been achieved with triple leveraged ETFs that target the S&P 500 and the Dow Industrials.These results, however, are accompanied by excessive volatility and very large maximum end-of-month (EOM) draw downs, in excess of 49% for TQQQ, and with maximum daily drawdown of almost 70%. Many retail investors would be unwilling to sustain such (paper) losses. Here we propose a strategy to mitigate these large draw downs while still retaining much of the upside performance of triple leveraging. We show that by simply establishing a portfolio consisting of an equal dollar amount of TQQQ and TMF (the triple leveraged ETF linked to the 20+ year treasury bond), and performing bimonthly rebalancing, a total return, after transaction costs, in excess of 5,800% (CAGR of 44.9%) would have been achieved over the 10+ years of TQQQ existence, with the maximum EOM draw down less than 25%.
Low Price-To-Book Ratios and Bank Dividend Payout Policies
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Banks with a low price-to-book ratio have a greater propensity to pay out dividends. This propensity is especially marked for banks with a price-to-book ratio below a threshold of 0.7. As a sector, banks also tend to have higher dividend payout ratios than non-financial firms. We demonstrate these features using data for 271 advanced economy banks in 30 jurisdictions. Dividend payouts as a proportion of profits rise in a non-linear way as the price-to-book ratio falls below 0.7. In a hypothetical exercise with fixed balance sheet ratios, we find that a complete suspension of bank dividends in 2020 during the Covid-19 pandemic would have added, under different stress scenario, an additional US$ 0.8â€"1.1 trillion of bank lending capacity in our sample, equivalent to 1.1â€"1.6% of total GDP.
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Banks with a low price-to-book ratio have a greater propensity to pay out dividends. This propensity is especially marked for banks with a price-to-book ratio below a threshold of 0.7. As a sector, banks also tend to have higher dividend payout ratios than non-financial firms. We demonstrate these features using data for 271 advanced economy banks in 30 jurisdictions. Dividend payouts as a proportion of profits rise in a non-linear way as the price-to-book ratio falls below 0.7. In a hypothetical exercise with fixed balance sheet ratios, we find that a complete suspension of bank dividends in 2020 during the Covid-19 pandemic would have added, under different stress scenario, an additional US$ 0.8â€"1.1 trillion of bank lending capacity in our sample, equivalent to 1.1â€"1.6% of total GDP.
Market Selection and the Absence of Arbitrage
SSRN
A central conjecture of behavioural finance is that arbitrage opportunities appear as a result of systematic irrational investment behaviour and persist since real-world arbitrage trades actually involve costs and risks due to market frictions and non-fundamental risk. This paper shows that the no-arbitrage condition can emerge from the market selection process even if systematic irrational trading behaviour occurs permanently and there are no strategic arbitrage trades. The model consists of two types of agents and two assets. Dividends are independently and identically distributed over time. Both types of agents invest positive amounts of wealth into each asset and keep portfolio weights constant. Arbitrage opportunities naturally occur in the short and medium term depending on how both types invest but disappear in the long run if both types survive the market selection process - regardless of both types' portfolios and initial wealth distribution. A necessary condition for arbitrage opportunities to persist is that one type of agents drives the other one out of the market.
SSRN
A central conjecture of behavioural finance is that arbitrage opportunities appear as a result of systematic irrational investment behaviour and persist since real-world arbitrage trades actually involve costs and risks due to market frictions and non-fundamental risk. This paper shows that the no-arbitrage condition can emerge from the market selection process even if systematic irrational trading behaviour occurs permanently and there are no strategic arbitrage trades. The model consists of two types of agents and two assets. Dividends are independently and identically distributed over time. Both types of agents invest positive amounts of wealth into each asset and keep portfolio weights constant. Arbitrage opportunities naturally occur in the short and medium term depending on how both types invest but disappear in the long run if both types survive the market selection process - regardless of both types' portfolios and initial wealth distribution. A necessary condition for arbitrage opportunities to persist is that one type of agents drives the other one out of the market.
Maximizing the Sharpe Ratio: A Genetic Programming Approach
SSRN
While common machine learning algorithms focus on minimizing the mean-square errors of model fit, we show that genetic programming, GP, is well-suited to maximize an economic objective, the Sharpe ratio of the usual spread portfolio in the cross-section of expected stock returns. In contrast to popular regression-based learning tools and the neural network, GP can double their performance in the US, and outperform them internationally. We find that, while the economic objective plays a role, GP captures nonlinearity in comparison with methods like the Lasso, and it requires smaller sample size than the neural network.
SSRN
While common machine learning algorithms focus on minimizing the mean-square errors of model fit, we show that genetic programming, GP, is well-suited to maximize an economic objective, the Sharpe ratio of the usual spread portfolio in the cross-section of expected stock returns. In contrast to popular regression-based learning tools and the neural network, GP can double their performance in the US, and outperform them internationally. We find that, while the economic objective plays a role, GP captures nonlinearity in comparison with methods like the Lasso, and it requires smaller sample size than the neural network.
Nonlinear Factor Attribution
SSRN
Factor attribution based on linear regression often fails to satisfactorily explain the performance of systematic investment strategies. Sizeable attribution residuals that do not average out to zero over time suggest latent exposures to nonlinearities in factor returns. Our proposed adjustment takes a portfolio manager’s perspective in attributing the impact thereof, identifying which factor tilts were most responsible for the unexplained performance. The resulting nonlinear attribution better reconciles realized returns with the investment process and is testable for statistical significance, with R code provided for evaluation purposes. We illustrate how this deeper understanding of factor interactions may guide client discussions and point to strategy enhancements.
SSRN
Factor attribution based on linear regression often fails to satisfactorily explain the performance of systematic investment strategies. Sizeable attribution residuals that do not average out to zero over time suggest latent exposures to nonlinearities in factor returns. Our proposed adjustment takes a portfolio manager’s perspective in attributing the impact thereof, identifying which factor tilts were most responsible for the unexplained performance. The resulting nonlinear attribution better reconciles realized returns with the investment process and is testable for statistical significance, with R code provided for evaluation purposes. We illustrate how this deeper understanding of factor interactions may guide client discussions and point to strategy enhancements.
Odds Are Retirees Don't Care About the Odds
SSRN
Random events are those that you cannot predict with certainty and the concept of a random event is the basis for probability. But uncertainty is aversive, so people try to mitigate the discomfort of the randomness and uncertainty of retirement-income planning with predictions based on probability theory and Monte Carlo analysis. Although ubiquitous within the financial services industry, Monte Carlo analysis is likely an ineffective tool that wastes resources and distracts most investors from the essence of the problem. It is ineffective because many people lack the numeric skills needed to accurately assess probability and because cognitive biases cause most people, including experts, to be insensitive to probabilities, neglect them completely as risk becomes more vivid or of greater magnitude, or view probability negatively. Monte Carlo is wildly inaccurate in its predictions of how long a retiree’s savings are likely to last and employs a methodology that is the opposite of what retirees want. Eliminating it from conversations should lead to safer, simpler, and more-personalized retirement-income portfolios for investors and help advisors create a brand of original thinking.
SSRN
Random events are those that you cannot predict with certainty and the concept of a random event is the basis for probability. But uncertainty is aversive, so people try to mitigate the discomfort of the randomness and uncertainty of retirement-income planning with predictions based on probability theory and Monte Carlo analysis. Although ubiquitous within the financial services industry, Monte Carlo analysis is likely an ineffective tool that wastes resources and distracts most investors from the essence of the problem. It is ineffective because many people lack the numeric skills needed to accurately assess probability and because cognitive biases cause most people, including experts, to be insensitive to probabilities, neglect them completely as risk becomes more vivid or of greater magnitude, or view probability negatively. Monte Carlo is wildly inaccurate in its predictions of how long a retiree’s savings are likely to last and employs a methodology that is the opposite of what retirees want. Eliminating it from conversations should lead to safer, simpler, and more-personalized retirement-income portfolios for investors and help advisors create a brand of original thinking.
Optimal reinsurance problem under fixed cost and exponential preferences
arXiv
arXiv
We investigate an optimal reinsurance problem for an insurance company facing a constant fixed cost when the reinsurance contract is signed. The insurer needs to optimally choose both the starting time of the reinsurance contract and the retention level in order to maximize the expected utility of terminal wealth. This leads to a mixed optimal control/optimal stopping time problem, which is solved by a two-step procedure: first considering the pure reinsurance stochastic control problem and next discussing a time-inhomogeneous optimal stopping problem with discontinuous reward. Using the classical Cram\'er-Lundberg approximation risk model, we prove that the optimal strategy is deterministic and depends on the model parameters. In particular, we show that there exists a maximum fixed cost that the insurer is willing to pay for the contract activation. Finally, we provide some economical interpretations and numerical simulations.
Outsourcing Climate Change
SSRN
This paper exploits newly available information on firms’ direct (own production) and indirect (supplier-generated) carbon emission intensities and transaction-level imports to conduct an in-depth analysis of whether and how U.S. firms address climate change. We find robust evidence that when firms increase their imports, their own emissions fall with a corresponding rise in supplier generated emissions. Several quasi-natural experiments further support this pivotal evidence that U.S. firms outsource some of their pollutions abroad. We show that firms, management, and directors with desires to maintain high environmental standings and environmentally-conscious customers and investors play a role in corporate environmental policies. Finally, firms with more imported emissions tend to have higher reputational risks and larger future stock returns but are less incentivized to develop clean technologies.
SSRN
This paper exploits newly available information on firms’ direct (own production) and indirect (supplier-generated) carbon emission intensities and transaction-level imports to conduct an in-depth analysis of whether and how U.S. firms address climate change. We find robust evidence that when firms increase their imports, their own emissions fall with a corresponding rise in supplier generated emissions. Several quasi-natural experiments further support this pivotal evidence that U.S. firms outsource some of their pollutions abroad. We show that firms, management, and directors with desires to maintain high environmental standings and environmentally-conscious customers and investors play a role in corporate environmental policies. Finally, firms with more imported emissions tend to have higher reputational risks and larger future stock returns but are less incentivized to develop clean technologies.
Prudential Regulation under CECL
SSRN
This study investigates prudential regulation under the current expected credit losses (CECL) model in accounting for loan loss provisioning. We highlight the dual role (valuation role and regulatory role) of the CECL accounting in deriving the optimal regulatory leverage ratios, which integrate (1) the dual role of banks (liquidity provision to households and credit supply to the real sector); (2) the reward and risk attributes of loan portfolio composition; and (3) procyclicality and countercyclicality.
SSRN
This study investigates prudential regulation under the current expected credit losses (CECL) model in accounting for loan loss provisioning. We highlight the dual role (valuation role and regulatory role) of the CECL accounting in deriving the optimal regulatory leverage ratios, which integrate (1) the dual role of banks (liquidity provision to households and credit supply to the real sector); (2) the reward and risk attributes of loan portfolio composition; and (3) procyclicality and countercyclicality.
Quantifying the importance of firms by means of reputation and network control
arXiv
arXiv
The reputation of firms is largely channeled through their ownership structure. We use this relation to determine reputation spillovers between transnational companies and their participated companies in an ownership network core of 1318 firms. We then apply concepts of network controllability to identify minimum sets of driver nodes (MDS) of 314 firms in this network. The importance of these driver nodes is classified regarding their control contribution, their operating revenue, and their reputation. The latter two are also taken as proxies for the access costs when utilizing firms as driver nodes. Using an enrichment analysis, we find that firms with high reputation maintain the controllability of the network, but rarely become top drivers, whereas firms with medium reputation most likely become top driver nodes. We further show that MDSs with lower access costs can be used to control the reputation dynamics in the whole network.
Ramsey Pricing: A Simple Example of a Subordinate Commodity
SSRN
We present preferences exhibiting a so-called subordinate good, namely a commodity that receives a negative price-cost margin according to Ramsey pricing. We also show that they deliver Ramsey quantities proportional to the efficient ones.
SSRN
We present preferences exhibiting a so-called subordinate good, namely a commodity that receives a negative price-cost margin according to Ramsey pricing. We also show that they deliver Ramsey quantities proportional to the efficient ones.
S-Shaped Consumption Utility: Empirical Evidence and Implications
SSRN
We find that common macro factors generate a “big bang/crunch†effect on micro consumption. Genreally speaking, when the aggregate effect of the common factors on the consumption in low consumption-growth states is negative (resp. positive), this effect in high consumption-growth states is positive (resp. negative). The big bang/crunch suggests that consumption utility functions are not concave-shaped but S-shaped. S-shaped consumption utility accounts for the unsatisfactory empirical performance of traditional consumption-based asset pricing models. Moreover, the S-shaped utility helps explain the negative elasticity of intertemporal substitution reported in the literature.
SSRN
We find that common macro factors generate a “big bang/crunch†effect on micro consumption. Genreally speaking, when the aggregate effect of the common factors on the consumption in low consumption-growth states is negative (resp. positive), this effect in high consumption-growth states is positive (resp. negative). The big bang/crunch suggests that consumption utility functions are not concave-shaped but S-shaped. S-shaped consumption utility accounts for the unsatisfactory empirical performance of traditional consumption-based asset pricing models. Moreover, the S-shaped utility helps explain the negative elasticity of intertemporal substitution reported in the literature.
Short versus Long: The Influence of Price Chart Display Horizons on Investor Behavior
SSRN
Price charts showing past asset performance are among the most salient and frequently used information items by investors. Default time horizons for which past asset performance is displayed vary greatly from a day to multiple years. We analyze the impact of the display horizon on retail investor trading volume and risk-taking behavior in a controlled experimental setting. We find that shorter display horizons are associated with more trading intensity, higher trading fees and hence welfare losses for investors. We do not find any effect of the display horizon on average risk-taking, and we thereby question the transferability of myopic loss aversion findings to real-world investment settings.
SSRN
Price charts showing past asset performance are among the most salient and frequently used information items by investors. Default time horizons for which past asset performance is displayed vary greatly from a day to multiple years. We analyze the impact of the display horizon on retail investor trading volume and risk-taking behavior in a controlled experimental setting. We find that shorter display horizons are associated with more trading intensity, higher trading fees and hence welfare losses for investors. We do not find any effect of the display horizon on average risk-taking, and we thereby question the transferability of myopic loss aversion findings to real-world investment settings.
Spain's Implementation of PSD2
SSRN
This paper analyses the implementation in Spain of Directive (EU) 2015/2366 of the European Parliament and of the Council of 25 November 2015 on payment services in the internal market (best known as ‘PSD2’). After introducing the background to payment services regulation in Spain, the paper addresses the specific transposition rules of PSD2 stated in Royal Decree-Law 19/2018 of 23 November on payment services and its regulatory development. The paper deals with national exceptions, while examining the technical nuances on legal framework for payment institutions and their transparency and information requirements, as well as on the rules applicable to the authorisation and execution of payment transactions. It also goes over the rules on data protection, risks management, authentication and case-law doctrine on liability of payment service providers, while considering the alternative dispute resolution procedures and the rules concerning penalties. The paper also reviews the rules applicable during the transition period and considers the regulatory development and the importance of Bank of Spain's criterion. Lastly, the paper provides some conclusions. Spain has opted to transcribe PSD2 without the necessary adaptation to domestic law. All that is added is a few nuances, except regarding two essential questions. On the one hand, the right to terminate the framework contract with an anti-competitive regulation that could constitute an incorrect transposition. On the other hand, there is no real alternative dispute resolution (ADR) system.
SSRN
This paper analyses the implementation in Spain of Directive (EU) 2015/2366 of the European Parliament and of the Council of 25 November 2015 on payment services in the internal market (best known as ‘PSD2’). After introducing the background to payment services regulation in Spain, the paper addresses the specific transposition rules of PSD2 stated in Royal Decree-Law 19/2018 of 23 November on payment services and its regulatory development. The paper deals with national exceptions, while examining the technical nuances on legal framework for payment institutions and their transparency and information requirements, as well as on the rules applicable to the authorisation and execution of payment transactions. It also goes over the rules on data protection, risks management, authentication and case-law doctrine on liability of payment service providers, while considering the alternative dispute resolution procedures and the rules concerning penalties. The paper also reviews the rules applicable during the transition period and considers the regulatory development and the importance of Bank of Spain's criterion. Lastly, the paper provides some conclusions. Spain has opted to transcribe PSD2 without the necessary adaptation to domestic law. All that is added is a few nuances, except regarding two essential questions. On the one hand, the right to terminate the framework contract with an anti-competitive regulation that could constitute an incorrect transposition. On the other hand, there is no real alternative dispute resolution (ADR) system.
The Achilles Heel of Reputable VCs
SSRN
This paper examines the impact of competition on the investment behavior and outcomes of venture capital (VC) firms with differing reputations. Following the introduction of investor tax credit programs that increase competition, reputable VCs decrease the number and size of their investments. The results are more pronounced in states with lower investment requirements and lower VC supply. Reputable VCs also reduce their syndicate size and shrink the time between financing rounds. They become less likely to partner with serial founders and their performance deteriorates. Our results suggest that increasing competition depresses returns for reputable VCs, hurting their incentive to invest.
SSRN
This paper examines the impact of competition on the investment behavior and outcomes of venture capital (VC) firms with differing reputations. Following the introduction of investor tax credit programs that increase competition, reputable VCs decrease the number and size of their investments. The results are more pronounced in states with lower investment requirements and lower VC supply. Reputable VCs also reduce their syndicate size and shrink the time between financing rounds. They become less likely to partner with serial founders and their performance deteriorates. Our results suggest that increasing competition depresses returns for reputable VCs, hurting their incentive to invest.
The Impact of Corporate Governance on Firm Performance During The COVID-19 Pandemic: Evidence from Malaysia
SSRN
The purpose of this study is to evaluate the effect of COVID-19 on corporate governance attributes and firm performance association. This research used a sample of 188 non-financial firms from the Malaysian market for the years 2019-2020. We found that the COVID-19 has affected all firm characteristics including firm performance, governance structure, dividend, liquidity, and leverage level, yet, the difference between prior and post COVID-19 pandemic is not significant. Also, the investigation revealed that board size exerts a significant positive impact on firm performance. After splitting the sample based on year, however, we found that board size does not matter in the uncertain time of the current crisis, while board diversity appeared to be significantly enhancing firm performance in the crisis time compared to the prior year where it has an inverse association with firm performance in both indicators. Board meetings and audit committee meetings seemed to have a significant negative influence on firm performance pre and post-COVID-19. This study contributes to the limited literature by providing the first empirical evidence on the impact of Coronavirus on the firm performance and corporate governance association.
SSRN
The purpose of this study is to evaluate the effect of COVID-19 on corporate governance attributes and firm performance association. This research used a sample of 188 non-financial firms from the Malaysian market for the years 2019-2020. We found that the COVID-19 has affected all firm characteristics including firm performance, governance structure, dividend, liquidity, and leverage level, yet, the difference between prior and post COVID-19 pandemic is not significant. Also, the investigation revealed that board size exerts a significant positive impact on firm performance. After splitting the sample based on year, however, we found that board size does not matter in the uncertain time of the current crisis, while board diversity appeared to be significantly enhancing firm performance in the crisis time compared to the prior year where it has an inverse association with firm performance in both indicators. Board meetings and audit committee meetings seemed to have a significant negative influence on firm performance pre and post-COVID-19. This study contributes to the limited literature by providing the first empirical evidence on the impact of Coronavirus on the firm performance and corporate governance association.
Using Barbells to Lift Risk-Adjusted Return
SSRN
This study demonstrates how a barbell strategy invested primarily in fixed income assets coupled with in-the-money long-term call options on various equity asset classes can achieve a significant percentage of upside appreciation and significantly reduce downside risk. An examination of exchange-traded funds (ETFs) covering S&P 500, NASDAQ 100, mid-cap, small-cap, developed international, emerging, and real estate equities shows a barbell strategy of 88-percent bonds and 12-percent long-term call options captures 70â€"124 percent of the geometric annual return of the underlying ETFs for December 2002â€"November 2019.
SSRN
This study demonstrates how a barbell strategy invested primarily in fixed income assets coupled with in-the-money long-term call options on various equity asset classes can achieve a significant percentage of upside appreciation and significantly reduce downside risk. An examination of exchange-traded funds (ETFs) covering S&P 500, NASDAQ 100, mid-cap, small-cap, developed international, emerging, and real estate equities shows a barbell strategy of 88-percent bonds and 12-percent long-term call options captures 70â€"124 percent of the geometric annual return of the underlying ETFs for December 2002â€"November 2019.
Using Personality Assessment and Situational Queries to Understand Risk Tolerance in Emerging Adults
SSRN
We extend the work of Pan and Statman (2013) by investigating correlations between personality traits and risk tolerance among emerging adults. We score respondents on the Big Five personality traits: extraversion, agreeableness, conscientiousness, neuroticism, and openness. We then analyze correlations between these traits and reported characteristics of risk tolerance: overconfidence, maximization, regret, trust, life satisfaction, and the propensity to attribute success to luck over skill. We find correlations that describe relationships between conscientiousness and the propensity to attribute success to luck over skill, as well as a lack of overconfidence; between openness and the propensity for maximization; and between neuroticism and the propensity for overconfidence. We underscore the nuanced dimensions of investor preferences. We discuss neuroticism and its effects on self-reporting in the context of risk assessment and financial consulting.
SSRN
We extend the work of Pan and Statman (2013) by investigating correlations between personality traits and risk tolerance among emerging adults. We score respondents on the Big Five personality traits: extraversion, agreeableness, conscientiousness, neuroticism, and openness. We then analyze correlations between these traits and reported characteristics of risk tolerance: overconfidence, maximization, regret, trust, life satisfaction, and the propensity to attribute success to luck over skill. We find correlations that describe relationships between conscientiousness and the propensity to attribute success to luck over skill, as well as a lack of overconfidence; between openness and the propensity for maximization; and between neuroticism and the propensity for overconfidence. We underscore the nuanced dimensions of investor preferences. We discuss neuroticism and its effects on self-reporting in the context of risk assessment and financial consulting.
Who Manipulates Data During Pandemics? Evidence from Newcomb-Benford Law
arXiv
arXiv
We use the Newcomb-Benford law to test if countries have manipulated reported data during the COVID-19 pandemic. We find that democratic countries, countries with the higher gross domestic product (GDP) per capita, higher healthcare expenditures, and better universal healthcare coverage are less likely to deviate from the Newcomb-Benford law. The relationship holds for the cumulative number of reported deaths and total cases but is more pronounced for the death toll. The findings are robust for second-digit tests, for a sub-sample of countries with regional data, and in relation to the previous swine flu (H1N1) 2009-2010 pandemic. The paper further highlights the importance of independent surveillance data verification projects.
