The paper investigates quadratic hedging in a semimartingale market that does not necessarily contain a risk-free asset. An equivalence result for hedging with and without numeraire change is established. This permits direct computation of the optimal strategy without choosing a reference asset and/or performing a numeraire change. New explicit expressions for optimal strategies are obtained, featuring the use of oblique projections that provide unified treatment of the case with and without a risk-free asset. The analysis yields a streamlined computation of the efficient frontier for the pure investment problem in terms of three easily interpreted processes. The main result advances our understanding of the efficient frontier formation in the most general case in which a risk-free asset may not be present. Several illustrations of the numeraire-invariant approach are given.
{"title":"Numeraire-Invariant Quadratic Hedging and Mean-Variance Portfolio Allocation","authors":"A. Černý, Christoph Czichowsky, J. Kallsen","doi":"10.2139/ssrn.3944947","DOIUrl":"https://doi.org/10.2139/ssrn.3944947","url":null,"abstract":"The paper investigates quadratic hedging in a semimartingale market that does not necessarily contain a risk-free asset. An equivalence result for hedging with and without numeraire change is established. This permits direct computation of the optimal strategy without choosing a reference asset and/or performing a numeraire change. New explicit expressions for optimal strategies are obtained, featuring the use of oblique projections that provide unified treatment of the case with and without a risk-free asset. The analysis yields a streamlined computation of the efficient frontier for the pure investment problem in terms of three easily interpreted processes. The main result advances our understanding of the efficient frontier formation in the most general case in which a risk-free asset may not be present. Several illustrations of the numeraire-invariant approach are given.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121397182","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 examine the pricing performance of out-of-sample pricing factors in the broad cross-section of currency returns. To this end, we develop a methodology for estimating empirical minimum-entropy stochastic discount factors (SDFs) under economically-motivated constraints on position leverage. Our empirical SDFs deliver superior out-of-sample fit and smaller pricing errors than existing factor models in the cross-section of currency portfolio returns, and are priced in individual currency and hedge fund cross-sections. After transaction costs, an investable SDF portfolio delivers a Sharpe ratio of around 0.8 and positively skewed returns. These empirical SDFs offer tractable benchmarks for candidate currency pricing models.
{"title":"Benchmark Currency Stochastic Discount Factors","authors":"Piotr Orłowski, V. Sokolovski, Erik Sverdrup","doi":"10.2139/ssrn.3945075","DOIUrl":"https://doi.org/10.2139/ssrn.3945075","url":null,"abstract":"We examine the pricing performance of out-of-sample pricing factors in the broad cross-section of currency returns. To this end, we develop a methodology for estimating empirical minimum-entropy stochastic discount factors (SDFs) under economically-motivated constraints on position leverage. Our empirical SDFs deliver superior out-of-sample fit and smaller pricing errors than existing factor models in the cross-section of currency portfolio returns, and are priced in individual currency and hedge fund cross-sections. After transaction costs, an investable SDF portfolio delivers a Sharpe ratio of around 0.8 and positively skewed returns. These empirical SDFs offer tractable benchmarks for candidate currency pricing models.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125513315","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 study discrete-time predictable forward processes when trading times do not coincide with performance evaluation times in the binomial tree model for the financial market. The key step in the construction of these processes is to solve a linear functional equation of higher order associated with the inverse problem driving the evolution of the predictable forward process. We provide sufficient conditions for the existence and uniqueness and an explicit construction of the predictable forward process under these conditions. Furthermore, we show that these processes are time-monotone in the evaluation period. Finally, we argue that predictable forward preferences are a viable framework to model preferences for robo-advising applications and determine an optimal interaction schedule between client and robo-advisor that balances a tradeoff between increasing uncertainty about the client's beliefs on the financial market and an interaction cost.
{"title":"Predictable Forward Performance Processes: Infrequent Evaluation and Robo-Advising Applications","authors":"Gechun Liang, Moris S. Strub, Yuwei Wang","doi":"10.2139/ssrn.3944223","DOIUrl":"https://doi.org/10.2139/ssrn.3944223","url":null,"abstract":"We study discrete-time predictable forward processes when trading times do not coincide with performance evaluation times in the binomial tree model for the financial market. The key step in the construction of these processes is to solve a linear functional equation of higher order associated with the inverse problem driving the evolution of the predictable forward process. We provide sufficient conditions for the existence and uniqueness and an explicit construction of the predictable forward process under these conditions. Furthermore, we show that these processes are time-monotone in the evaluation period. Finally, we argue that predictable forward preferences are a viable framework to model preferences for robo-advising applications and determine an optimal interaction schedule between client and robo-advisor that balances a tradeoff between increasing uncertainty about the client's beliefs on the financial market and an interaction cost.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126540101","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 show an inverse relationship between elevated valuations (high CAPE) and forward real-returns over 1, 3, 5, and 10 years in India, similar to other international studies. There is a reasonable probability (38%) that 1-year returns are negative when CAPE is in its highest quintile. While “time in the market” reduces the chance of negative forward real-returns, these returns are still lower than entering at lower quintiles of CAPE. Even in the longer term, forward real-returns have significant variability. Thus, CAPE on its own has limited use for market timing. However, the inverse relationship implies investors should lower their forward real return expectations and consider longer investment time horizons when starting CAPE is high without sound economic rationale.
{"title":"Shiller's CAPE and Forward Real Returns in India","authors":"Rajan Raju","doi":"10.2139/ssrn.3939671","DOIUrl":"https://doi.org/10.2139/ssrn.3939671","url":null,"abstract":"We show an inverse relationship between elevated valuations (high CAPE) and forward real-returns over 1, 3, 5, and 10 years in India, similar to other international studies. There is a reasonable probability (38%) that 1-year returns are negative when CAPE is in its highest quintile. While “time in the market” reduces the chance of negative forward real-returns, these returns are still lower than entering at lower quintiles of CAPE. Even in the longer term, forward real-returns have significant variability. Thus, CAPE on its own has limited use for market timing. However, the inverse relationship implies investors should lower their forward real return expectations and consider longer investment time horizons when starting CAPE is high without sound economic rationale.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128897787","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}
H. Cordes, Hannes Mohrschladt, Sven Nolte, Judith C. Schneider
We introduce a simple and highly portable measure capturing the impact of price path visualizations on investor behavior, beliefs, and financial market outcomes: the visual shape score (VSS). The score reflects the degree of convexity of a price path. Although VSS is only a single metric, it captures four aspects of price path visualizations: bottom-up visual salience, top-down effects like evoked emotions, visual pattern recognition, and simplifications due to visualisation. Experimental findings suggest that more convex shapes positively explain investors' return expectations, their stated stock attractiveness, and investments. We augment the experimental results with field data. We find that VSS can help to better understand beliefs elicited from survey data and that VSS exhibits return predictability among individual stocks beyond a large range of cross-sectional return predictors.
{"title":"The Visual Shape Score: On its Predictability in the Lab, the Aggregated Stock Market, and the Cross-Section of Stock Returns","authors":"H. Cordes, Hannes Mohrschladt, Sven Nolte, Judith C. Schneider","doi":"10.2139/ssrn.3927479","DOIUrl":"https://doi.org/10.2139/ssrn.3927479","url":null,"abstract":"We introduce a simple and highly portable measure capturing the impact of price path visualizations on investor behavior, beliefs, and financial market outcomes: the visual shape score (VSS). The score reflects the degree of convexity of a price path. Although VSS is only a single metric, it captures four aspects of price path visualizations: bottom-up visual salience, top-down effects like evoked emotions, visual pattern recognition, and simplifications due to visualisation. Experimental findings suggest that more convex shapes positively explain investors' return expectations, their stated stock attractiveness, and investments. We augment the experimental results with field data. We find that VSS can help to better understand beliefs elicited from survey data and that VSS exhibits return predictability among individual stocks beyond a large range of cross-sectional return predictors.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133374795","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}
One of the ongoing debates in asset pricing is whether investors are rational to use the CAPM alpha to direct their fund flow. We seek to settle the debate in two steps. First, we attribute, by using the Shapley value approach, fund-level net flow to different determinants (which alpha drives fund flows?). Second, we assess how future fund performance is related to the different types of fund flow from the first step (which fund flow predicts future performance?). We show that the CAPM-alpha flow is the most consistent predictor of short term performance. However, we also show investors do not only use the CAPM-alpha as a skill measure and chase performance but that they dynamically switch between momentum and contrarian strategies when using CAPM-alpha as a signal. Overall, our evidence suggests that CAPM has been a useful model for fund investors but this success needs to be attributed to the smartness of the fund investors in their use of CAPM.
{"title":"Which Fund Flow?","authors":"You Zhou, Peng Li, Charlie X. Cai, K. Keasey","doi":"10.2139/ssrn.2839798","DOIUrl":"https://doi.org/10.2139/ssrn.2839798","url":null,"abstract":"One of the ongoing debates in asset pricing is whether investors are rational to use the CAPM alpha to direct their fund flow. We seek to settle the debate in two steps. First, we attribute, by using the Shapley value approach, fund-level net flow to different determinants (which alpha drives fund flows?). Second, we assess how future fund performance is related to the different types of fund flow from the first step (which fund flow predicts future performance?). We show that the CAPM-alpha flow is the most consistent predictor of short term performance. However, we also show investors do not only use the CAPM-alpha as a skill measure and chase performance but that they dynamically switch between momentum and contrarian strategies when using CAPM-alpha as a signal. Overall, our evidence suggests that CAPM has been a useful model for fund investors but this success needs to be attributed to the smartness of the fund investors in their use of CAPM.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121537084","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 the distributional properties of cryptocurrency realized variation measures (RVM) and the predictability of RVM on future returns. We show the cryptocurrency volatility persistence and the importance of the asymmetry on volatility forecasting. Signed jumps variations contribute around 18% of the cryptocurrency return quadratic variations. The realized signed jump (RSJ) strongly predicts the cross-sectional future excess returns. Sorting the cryptocurrencies into portfolios sorted by RSJ yields statistically and economically significant differences in future excess returns. This jump risk premium remains significant after controlling for cryptocurrency market characteristics and existing risk factors. The standard cross-sectional regression convinces the cryptocurrency return predictability from RSJ by controlling multiple cryptocurrency characteristics. The investor attention explains the predictability of realized jump risk in future cryptocurrency returns.
{"title":"Good Volatility, Bad Volatility, and the Cross Section of Cryptocurrency Returns","authors":"Zehua Zhang, Ran Zhao","doi":"10.2139/ssrn.3910202","DOIUrl":"https://doi.org/10.2139/ssrn.3910202","url":null,"abstract":"This paper examines the distributional properties of cryptocurrency realized variation measures (RVM) and the predictability of RVM on future returns. We show the cryptocurrency volatility persistence and the importance of the asymmetry on volatility forecasting. Signed jumps variations contribute around 18% of the cryptocurrency return quadratic variations. The realized signed jump (RSJ) strongly predicts the cross-sectional future excess returns. Sorting the cryptocurrencies into portfolios sorted by RSJ yields statistically and economically significant differences in future excess returns. This jump risk premium remains significant after controlling for cryptocurrency market characteristics and existing risk factors. The standard cross-sectional regression convinces the cryptocurrency return predictability from RSJ by controlling multiple cryptocurrency characteristics. The investor attention explains the predictability of realized jump risk in future cryptocurrency returns.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129234340","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}
Uniswap is one of the largest decentralized exchanges with a liquidity balance of over 3 billion USD and daily trading volume of over 700 million USD. It is designed as a system of smart contracts on the Ethereum blockchain, and is a new model of liquidity provision, so called automated market making. We collect and analyze data on all 19 million Uniswap interactions from 2018 to the current time. For this new market, we characterize equilibrium liquidity pools and provide evidence that they are stable. We compare this automated market maker to Binance and establish absence of arbitrage and show conditions under which the AMM dominates a limit order market.
{"title":"Decentralized Exchanges","authors":"Alfred Lehar, Christine A. Parlour","doi":"10.2139/ssrn.3905316","DOIUrl":"https://doi.org/10.2139/ssrn.3905316","url":null,"abstract":"Uniswap is one of the largest decentralized exchanges with a liquidity balance of over 3 billion USD and daily trading volume of over 700 million USD. It is designed as a system of smart contracts on the Ethereum blockchain, and is a new model of liquidity provision, so called automated market making. We collect and analyze data on all 19 million Uniswap interactions from 2018 to the current time. For this new market, we characterize equilibrium liquidity pools and provide evidence that they are stable. We compare this automated market maker to Binance and establish absence of arbitrage and show conditions under which the AMM dominates a limit order market.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129697804","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 study shows that changes in bitcoin exchange reserves are negatively related to contemporaneous and future bitcoin returns, consistent with the hypothesis that the transfer of bitcoin on exchanges implies increased price pressure and vice versa. We further identify an asymmetry between positive and negative reserve changes on bitcoin returns and volatility which in turn also affect exchange reserves in extreme market conditions. The results indicate that a significant fraction of bitcoin investors store their wealth off exchanges and only use exchanges to trade. This highlights a special feature of cryptocurrency trading that does not exist in traditional markets.
{"title":"Effects of Bitcoin Exchange Reserves on Bitcoin Returns and Volatility","authors":"Lai T. Hoang, D. Baur","doi":"10.2139/ssrn.3902504","DOIUrl":"https://doi.org/10.2139/ssrn.3902504","url":null,"abstract":"This study shows that changes in bitcoin exchange reserves are negatively related to contemporaneous and future bitcoin returns, consistent with the hypothesis that the transfer of bitcoin on exchanges implies increased price pressure and vice versa. We further identify an asymmetry between positive and negative reserve changes on bitcoin returns and volatility which in turn also affect exchange reserves in extreme market conditions. The results indicate that a significant fraction of bitcoin investors store their wealth off exchanges and only use exchanges to trade. This highlights a special feature of cryptocurrency trading that does not exist in traditional markets.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114942079","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}
Compared to a Chinese investor, the U.S. investors invest in Fin-Tech evergreen fund is not astrange financial activity. In the fast-developing of different technology nowadays, the US. Fin-Techevergreen investors are always attempting to catch the wave of the opportunity to invest in new financialtechnology companies that will almost like investing in Apple, Microsoft, SpaceX, or Teslar twenty yearsago. This article intends to introduce, compare, and analyst the fin-tech evergreen development in boththe USA and China. Fin-Tech Evergreen financing is a concept used to describe the gradual infusion offunds into a fin-tech company. It is feasible to organize for the receipt of venture capital money inadvance. Nevertheless, with FinTech's evergreen investment, investors provide cash in incrementalpayments throughout the company's or product's development phase. It is a perpetual fund architecturewith no set end date. It frequently provides investors with the ability to exit their commitment and allowsthe fund manager to acquire additional cash. Investors are allowed to reinvest cash generated by realizedreturns, thus the term "evergreen." With a thorough explanation of the two most powerful economicpowers' investment direction of the evergreen fund, the general public will learn more about the evergreenfund's future and destiny.
{"title":"Comparison of the Fin-tech Evergreen Fund in China and U.S.A","authors":"Antonia Tong","doi":"10.2139/ssrn.3904647","DOIUrl":"https://doi.org/10.2139/ssrn.3904647","url":null,"abstract":"Compared to a Chinese investor, the U.S. investors invest in Fin-Tech evergreen fund is not astrange financial activity. In the fast-developing of different technology nowadays, the US. Fin-Techevergreen investors are always attempting to catch the wave of the opportunity to invest in new financialtechnology companies that will almost like investing in Apple, Microsoft, SpaceX, or Teslar twenty yearsago. This article intends to introduce, compare, and analyst the fin-tech evergreen development in boththe USA and China. Fin-Tech Evergreen financing is a concept used to describe the gradual infusion offunds into a fin-tech company. It is feasible to organize for the receipt of venture capital money inadvance. Nevertheless, with FinTech's evergreen investment, investors provide cash in incrementalpayments throughout the company's or product's development phase. It is a perpetual fund architecturewith no set end date. It frequently provides investors with the ability to exit their commitment and allowsthe fund manager to acquire additional cash. Investors are allowed to reinvest cash generated by realizedreturns, thus the term \"evergreen.\" With a thorough explanation of the two most powerful economicpowers' investment direction of the evergreen fund, the general public will learn more about the evergreenfund's future and destiny.","PeriodicalId":377322,"journal":{"name":"Investments eJournal","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128695534","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}
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