We study the effects of goal-setting on saving behavior, exploiting the exogenous introduction of goal-setting features for saving in a FinTech app. We establish that setting goals increases individuals' saving rate, and show that the effect is causal using two distinct identification strategies that control for individuals' endogenous decision to adopt goal-setting. Our results vary along several dimensions. Individuals save more for goals with shorter horizon and larger amounts. They also save more when they use another feature of the app that allows them to divide their overall saving into small amounts (5 Euros) throughout the month. The nature of the goal, on the other hand, does not matter. Only one third of the goals are achieved before the deadline, with general goals having higher probability to be achieved than specific ones. Taken together, our findings indicate that goal-setting has a positive effect on saving, but there is considerable scope to increase its effectiveness by helping individuals set well-calibrated goals, possibly using robo-advising tools.
{"title":"Goal Setting and Saving in the FinTech Era","authors":"Antonio Gargano, Alberto G. Rossi","doi":"10.2139/ssrn.3579275","DOIUrl":"https://doi.org/10.2139/ssrn.3579275","url":null,"abstract":"We study the effects of goal-setting on saving behavior, exploiting the exogenous introduction of goal-setting features for saving in a FinTech app. We establish that setting goals increases individuals' saving rate, and show that the effect is causal using two distinct identification strategies that control for individuals' endogenous decision to adopt goal-setting. Our results vary along several dimensions. Individuals save more for goals with shorter horizon and larger amounts. They also save more when they use another feature of the app that allows them to divide their overall saving into small amounts (5 Euros) throughout the month. The nature of the goal, on the other hand, does not matter. Only one third of the goals are achieved before the deadline, with general goals having higher probability to be achieved than specific ones. Taken together, our findings indicate that goal-setting has a positive effect on saving, but there is considerable scope to increase its effectiveness by helping individuals set well-calibrated goals, possibly using robo-advising tools.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129641554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Social infrastructure has endured a long period of neglect in most developed and emerging countries, with chronic underinvestment exposed by the coronavirus crisis 2020. Private sector investment in social infrastructure has widely fallen back over the last decade - this in contrast to economic infrastructure. One of the outcomes of the last global (financial) crisis 2007/08 was a slow revival of economic infrastructure policies, and a growing involvement of institutional investors. This is the first, more systematic account of social infrastructure investment from an international perspective, leading to several key conclusions. The public sector will remain the dominant funding and financing source. Nonetheless, much more private capital could flow with greater clarity on social assets and projects, given their very diverse specific characteristics. There are various investment strategies that can realistically be improved and expanded. Sustainability, impact and SDG investing open a new door for asset owners.
{"title":"Social Infrastructure Finance and Institutional Investors. A Global Perspective","authors":"Georg Inderst","doi":"10.2139/ssrn.3556473","DOIUrl":"https://doi.org/10.2139/ssrn.3556473","url":null,"abstract":"Social infrastructure has endured a long period of neglect in most developed and emerging countries, with chronic underinvestment exposed by the coronavirus crisis 2020. Private sector investment in social infrastructure has widely fallen back over the last decade - this in contrast to economic infrastructure. One of the outcomes of the last global (financial) crisis 2007/08 was a slow revival of economic infrastructure policies, and a growing involvement of institutional investors. This is the first, more systematic account of social infrastructure investment from an international perspective, leading to several key conclusions. The public sector will remain the dominant funding and financing source. Nonetheless, much more private capital could flow with greater clarity on social assets and projects, given their very diverse specific characteristics. There are various investment strategies that can realistically be improved and expanded. Sustainability, impact and SDG investing open a new door for asset owners.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"8 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116777168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper studies long-run trends in the expected return on risky wealth and its relationship with the safe rate. We combine new data and time-varying return predictability regressions to estimate expected returns on two major risky asset classes – equity and housing – across 17 countries and 145 years. We show that the expected risky return has been in steady long-run decline, falling by more than one-third between 1870 and 2015. Much of this decline is driven by a fall in the risk premium – from 6% in 1870 to 3% in 1990 – which can in turn be traced back to secular declines in the price of risk and macro-financial volatility. We further show that movements in expected returns are largely unrelated to safe rates, and hence safe rates and risk premia are strongly negatively correlated. This suggests that relative supply and demand factors – such as safe asset shortages and investor risk appetite – play a key role in determining the prices of risky and safe assets in the economy.
{"title":"The Expected Return on Risky Assets: International Long-run Evidence","authors":"D. Kuvshinov, Kaspar Zimmermann","doi":"10.2139/ssrn.3546005","DOIUrl":"https://doi.org/10.2139/ssrn.3546005","url":null,"abstract":"This paper studies long-run trends in the expected return on risky wealth and its relationship with the safe rate. We combine new data and time-varying return predictability regressions to estimate expected returns on two major risky asset classes – equity and housing – across 17 countries and 145 years. We show that the expected risky return has been in steady long-run decline, falling by more than one-third between 1870 and 2015. Much of this decline is driven by a fall in the risk premium – from 6% in 1870 to 3% in 1990 – which can in turn be traced back to secular declines in the price of risk and macro-financial volatility. We further show that movements in expected returns are largely unrelated to safe rates, and hence safe rates and risk premia are strongly negatively correlated. This suggests that relative supply and demand factors – such as safe asset shortages and investor risk appetite – play a key role in determining the prices of risky and safe assets in the economy.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127681917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wealth taxes have been adopted or considered as an adjunct to existing tax systems such as income taxes, property taxes, and consumption taxes. Discussions about a wealth tax are usually a mixture of political, social, and economic issues, with many of the published papers designed to serve an author’s agenda. The purpose of this note is to leave many of these issues behind and to focus on the effects of a wealth tax on capital markets.
{"title":"Wealth Taxes and Capital Markets","authors":"J. Stowe","doi":"10.2139/ssrn.3542463","DOIUrl":"https://doi.org/10.2139/ssrn.3542463","url":null,"abstract":"Wealth taxes have been adopted or considered as an adjunct to existing tax systems such as income taxes, property taxes, and consumption taxes. Discussions about a wealth tax are usually a mixture of political, social, and economic issues, with many of the published papers designed to serve an author’s agenda. The purpose of this note is to leave many of these issues behind and to focus on the effects of a wealth tax on capital markets.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133317282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Today, all financial services aspect seems to be touched by technological forces. Fintech development is in its early stages; many researchers and practitioners believe that it will shape and define the future of the financial industry. The researcher intends to examine the determinant of Fintech services adoption among bank consumers. In line with the literature, the study purposed applies theoretical framework which been developed from existing literature by applying variables associated with the Technology Acceptance Model (TAM), and Diffusion of Innovation Theory (DOI) to test the critical factors that impact the intention to adopt fintech services. The researcher intends to use a quantitative approach to be empirically investigated. Structural Equation Modelling (SEM) will be utilized to determine the relative importance of associations and interactions between the factors.
{"title":"Investigation of Fintech Services Adoption in the Banking Industry","authors":"Noofa Bureshaid, Kevin J. Lu, A. Sarea","doi":"10.2139/ssrn.3659074","DOIUrl":"https://doi.org/10.2139/ssrn.3659074","url":null,"abstract":"Today, all financial services aspect seems to be touched by technological forces. Fintech development is in its early stages; many researchers and practitioners believe that it will shape and define the future of the financial industry. The researcher intends to examine the determinant of Fintech services adoption among bank consumers. In line with the literature, the study purposed applies theoretical framework which been developed from existing literature by applying variables associated with the Technology Acceptance Model (TAM), and Diffusion of Innovation Theory (DOI) to test the critical factors that impact the intention to adopt fintech services. The researcher intends to use a quantitative approach to be empirically investigated. Structural Equation Modelling (SEM) will be utilized to determine the relative importance of associations and interactions between the factors.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129597600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper examines whether deep/machine learning can help find any statistical and/or economic evidence of out-of-sample bond return predictability when real-time, instead of fully-revised, macro variables are taken as predictors. First, we find some statistical evidence for forecasting short-term non-overlapping excess bond returns using deep learning models. Second, for forecasting overlapping excess bond returns, more statistical evidence derives from using deep learning models and other machine learning models. However, all statistical evidence is much weaker than that found from using fully-revised macro data and generates minimal economic gains for a mean-variance investor, regardless of her level of risk aversion and whether she can take short positions.
{"title":"Real-Time Macro Information and Bond Return Predictability: Does Deep Learning Help?","authors":"Guanhao Feng, Andras Fulop, Junye Li","doi":"10.2139/ssrn.3517081","DOIUrl":"https://doi.org/10.2139/ssrn.3517081","url":null,"abstract":"This paper examines whether deep/machine learning can help find any statistical and/or economic evidence of out-of-sample bond return predictability when real-time, instead of fully-revised, macro variables are taken as predictors. First, we find some statistical evidence for forecasting short-term non-overlapping excess bond returns using deep learning models. Second, for forecasting overlapping excess bond returns, more statistical evidence derives from using deep learning models and other machine learning models. However, all statistical evidence is much weaker than that found from using fully-revised macro data and generates minimal economic gains for a mean-variance investor, regardless of her level of risk aversion and whether she can take short positions.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133192303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper approaches some simple methods for the calendar anomalies identification. Taking the TOY Effect as an example, we show how the t tests or the OLS regressions could be used to detect a seasonal component of the financial assets’ returns.
{"title":"Introducere în analiza anomaliilor calendaristice, Partea a doua (An Introduction to the Analysis of the Calendar Anomalies, Part 2)","authors":"R. Stefanescu, Ramona Dumitriu","doi":"10.2139/ssrn.3513768","DOIUrl":"https://doi.org/10.2139/ssrn.3513768","url":null,"abstract":"This paper approaches some simple methods for the calendar anomalies identification. Taking the TOY Effect as an example, we show how the t tests or the OLS regressions could be used to detect a seasonal component of the financial assets’ returns.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115348799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Optimal asset allocation and consumption policies have been important issues in finance in the past decades. We study these issues under constant relative risk aversion (CRRA) utility functions in a general setting: stochastic volatility, incomplete markets and finite investment horizons. So far, numerical computation has been the main method for obtaining solutions in this general setting. We present a closed-form approximate solution for this dynamic optimization problem. We show that our theoretical predictions are in good agreement with numerical results and our approximation error is even smaller than the parameter-estimation errors in underlying dynamics.
{"title":"Optimal Portfolio and Consumption Policies with Stochastic Volatility","authors":"Lei Ge, Qiang Zhang","doi":"10.2139/ssrn.3513403","DOIUrl":"https://doi.org/10.2139/ssrn.3513403","url":null,"abstract":"Optimal asset allocation and consumption policies have been important issues in finance in the past decades. We study these issues under constant relative risk aversion (CRRA) utility functions in a general setting: stochastic volatility, incomplete markets and finite investment horizons. So far, numerical computation has been the main method for obtaining solutions in this general setting. We present a closed-form approximate solution for this dynamic optimization problem. We show that our theoretical predictions are in good agreement with numerical results and our approximation error is even smaller than the parameter-estimation errors in underlying dynamics.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129648622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We employ and examine vine copulas in modeling symmetric and asymmetric dependency structures and forecasting financial returns. We analyze the asset allocations performed during the 2008-2009 financial crisis and test different portfolio strategies such as maximum Sharpe ratio, minimum variance, and minimum conditional Value-at-Risk. We then specify the regular, drawable, and canonical vine copulas, such as the Student-t, Clayton, Frank, Joe, Gumbel, and mixed copulas, and analyze both in-sample and out-of-sample portfolio performances. Out-of-sample portfolio back-testing shows that vine copulas reduce portfolio risk better than simple copulas. Our econometric analysis of the outcomes of the various models shows that in terms of reducing conditional Value-at-Risk, D-vines appear to be better than R- and C-vines. Overall, we find that the Student-t drawable vine copula models perform best with regard to risk reduction, both for the entire period 2005-2012 as well as during the financial crisis.
{"title":"Portfolio Optimization Based on Forecasting Models Using Vine Copulas: An Empirical Assessment for the Financial Crisis","authors":"Maziar Sahamkhadam, Andreas Stephan","doi":"10.2139/ssrn.3507936","DOIUrl":"https://doi.org/10.2139/ssrn.3507936","url":null,"abstract":"We employ and examine vine copulas in modeling symmetric and asymmetric dependency structures and forecasting financial returns. We analyze the asset allocations performed during the 2008-2009 financial crisis and test different portfolio strategies such as maximum Sharpe ratio, minimum variance, and minimum conditional Value-at-Risk. We then specify the regular, drawable, and canonical vine copulas, such as the Student-t, Clayton, Frank, Joe, Gumbel, and mixed copulas, and analyze both in-sample and out-of-sample portfolio performances. Out-of-sample portfolio back-testing shows that vine copulas reduce portfolio risk better than simple copulas. Our econometric analysis of the outcomes of the various models shows that in terms of reducing conditional Value-at-Risk, D-vines appear to be better than R- and C-vines. Overall, we find that the Student-t drawable vine copula models perform best with regard to risk reduction, both for the entire period 2005-2012 as well as during the financial crisis.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126364878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In most blockchain based cryptocurrencies majority of verification power is required for facilitating a successful double spending attack, i.e. using the same funds multiple times. Because possibility to double spend sharply deteriorates trust and value, concentration is traditionally considered to be a significant problem. We model agents’ incentives to facilitate double spending attacks under opportunity costs. Contrary to a host of previous literature, our main findings indicate that under meager economic profits large pools have higher incentives to act honestly than outsiders, our results hold for 13 major proof-of-work cryptocurrencies. Intuitively, this stems from the fact that mining pools holding more power in a cryptocurrency have stronger vested interest in it.
{"title":"Too Big to Cheat: Mining Pools' Incentives to Double Spend in Blockchain Based Cryptocurrencies","authors":"V. Savolainen, Jorge Soria","doi":"10.2139/ssrn.3506748","DOIUrl":"https://doi.org/10.2139/ssrn.3506748","url":null,"abstract":"In most blockchain based cryptocurrencies majority of verification power is required for facilitating a successful double spending attack, i.e. using the same funds multiple times. Because possibility to double spend sharply deteriorates trust and value, concentration is traditionally considered to be a significant problem. We model agents’ incentives to facilitate double spending attacks under opportunity costs. Contrary to a host of previous literature, our main findings indicate that under meager economic profits large pools have higher incentives to act honestly than outsiders, our results hold for 13 major proof-of-work cryptocurrencies. Intuitively, this stems from the fact that mining pools holding more power in a cryptocurrency have stronger vested interest in it.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128141944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：