This paper examines the meaningfulness of fine wine as an alternative investment, with particular focus on the costs of investing in fine wine. Is fine wine suitable for further diversifying and thus improving the risk-return profile of portfolios invested in global equities and bonds? This analysis takes place in an initial stage on an index basis and in a second stage on the basis of real investment opportunities. The reference currencies are the US dollar and the euro. In order to observe stock indexes, the MSCI World Index is used, and for bonds the JPM World Government-Bond Index is deployed. Regarding the data for investment in fine wine, the main focus is on the Liv-ex-50 Index. The time period is defined by the availability of the data. For the observation of indices, the period is from the beginning of 2004 to May 2018. For observation on the basis of a real investment the period is from March 2010 to May 2018. In the case of the real investment, index funds are used for the data analysis of equities and bonds. As there is no index fund for fine wine, the Liv-ex-50 index is used including all of the costs of a real investment. Various portfolio compositions are used for the periods indicated. On the one hand, a portfolio of 50% equities and 50% bonds is compared to a portfolio of 45% equities, 45% bonds and 10% fine wine. On the other hand, a portfolio of 25% equities and 75% bonds is compared to a portfolio of 20% equities, 70% bonds and 10% fine wine. As benchmarks, the annualised return, the standard deviation and the Sharpe ratio of the respective portfolios are calculated. The results for the periods indicated are sobering. The inclusion of fine wine leads - at an index level - to only a slight improvement of the annualised return, but to a marked increase in risk. When considering the real investment, the considerable costs of an investment in fine wine come to bear. The annualised return is lower and at the same time the risk is higher than that of portfolios which do not include fine wine. It is only when the index is viewed in euros that a slight improvement of the Sharpe ratio in one portfolio can be recorded. When costs are considered, the inclusion of fine wine leads to a worsening of the Sharpe ratio in all cases. This results is a significantly more critical verdict on this diversification opportunity than was noted in the previous studies by Masset and Weisskopf (2010), Masset and Henderson (2010), Bouri (2014), Bouri et al. (2016) and Aytac et al. (2016). By contrast, our results confirm the studies which point out the high costs of investment in fine wine and which reach largely negative findings when analysing real investments in wine investment funds (Burton and Jacobsen, 2001, Masset and Weisskopf, 2015).
本文考察了精品葡萄酒作为一种另类投资的意义，特别关注投资精品葡萄酒的成本。优质葡萄酒是否适合进一步分散投资，从而改善投资于全球股票和债券的投资组合的风险回报状况?这种分析在初始阶段以指数为基础，在第二阶段以实际投资机会为基础。参考货币是美元和欧元。为了观察股票指数，我们使用摩根士丹利资本国际世界指数，对于债券，我们使用摩根大通世界政府债券指数。关于投资精品葡萄酒的数据，主要关注的是Liv-ex-50指数。时间段由数据的可用性定义。指数观测时间为2004年初至2018年5月。以实际投资为基础的观察期为2010年3月至2018年5月就实物投资而言，指数基金用于股票和债券的数据分析。由于没有针对优质葡萄酒的指数基金，我们使用的Liv-ex-50指数包含了实际投资的所有成本。不同的投资组合组合用于指定的时期。一方面，50%的股票和50%的债券的投资组合与45%的股票、45%的债券和10%的优质葡萄酒的投资组合相比。另一方面，25%的股票和75%的债券的投资组合与20%的股票、70%的债券和10%的优质葡萄酒的投资组合相比。作为基准，计算各自投资组合的年化回报率、标准差和夏普比率。这些时期的结果发人深省。从指数水平来看，纳入精品葡萄酒只会略微提高年化回报率，但风险会显著增加。当考虑到真正的投资时，投资优质葡萄酒的可观成本就会显现出来。年化回报率较低，同时风险也高于不含精品葡萄酒的投资组合。只有当指数以欧元衡量时，一个投资组合中的夏普比率才会略有改善。如果考虑到成本，在所有情况下，包括优质葡萄酒都会导致夏普比率的恶化。与Masset and Weisskopf(2010)、Masset and Henderson(2010)、Bouri(2014)、Bouri et al.(2016)和Aytac et al.(2016)等人之前的研究相比，这一结果对这一多元化机会的判断要重要得多。相比之下，我们的结果证实了一些研究，这些研究指出了投资优质葡萄酒的高成本，并且在分析葡萄酒投资基金的实际投资时，得出了很大程度上负面的结果(Burton和Jacobsen, 2001, Masset和Weisskopf, 2015)。
{"title":"Investing in Fine Wine from the Perspectives of Diversification and Costs","authors":"Thomas Nahmer","doi":"10.3905/JAI.V22I4.5585","DOIUrl":"https://doi.org/10.3905/JAI.V22I4.5585","url":null,"abstract":"This paper examines the meaningfulness of fine wine as an alternative investment, with particular focus on the costs of investing in fine wine. Is fine wine suitable for further diversifying and thus improving the risk-return profile of portfolios invested in global equities and bonds? This analysis takes place in an initial stage on an index basis and in a second stage on the basis of real investment opportunities. The reference currencies are the US dollar and the euro. In order to observe stock indexes, the MSCI World Index is used, and for bonds the JPM World Government-Bond Index is deployed. Regarding the data for investment in fine wine, the main focus is on the Liv-ex-50 Index. The time period is defined by the availability of the data. For the observation of indices, the period is from the beginning of 2004 to May 2018. For observation on the basis of a real investment the period is from March 2010 to May 2018. In the case of the real investment, index funds are used for the data analysis of equities and bonds. As there is no index fund for fine wine, the Liv-ex-50 index is used including all of the costs of a real investment. Various portfolio compositions are used for the periods indicated. On the one hand, a portfolio of 50% equities and 50% bonds is compared to a portfolio of 45% equities, 45% bonds and 10% fine wine. On the other hand, a portfolio of 25% equities and 75% bonds is compared to a portfolio of 20% equities, 70% bonds and 10% fine wine. As benchmarks, the annualised return, the standard deviation and the Sharpe ratio of the respective portfolios are calculated. The results for the periods indicated are sobering. The inclusion of fine wine leads - at an index level - to only a slight improvement of the annualised return, but to a marked increase in risk. When considering the real investment, the considerable costs of an investment in fine wine come to bear. The annualised return is lower and at the same time the risk is higher than that of portfolios which do not include fine wine. It is only when the index is viewed in euros that a slight improvement of the Sharpe ratio in one portfolio can be recorded. When costs are considered, the inclusion of fine wine leads to a worsening of the Sharpe ratio in all cases. This results is a significantly more critical verdict on this diversification opportunity than was noted in the previous studies by Masset and Weisskopf (2010), Masset and Henderson (2010), Bouri (2014), Bouri et al. (2016) and Aytac et al. (2016). By contrast, our results confirm the studies which point out the high costs of investment in fine wine and which reach largely negative findings when analysing real investments in wine investment funds (Burton and Jacobsen, 2001, Masset and Weisskopf, 2015).","PeriodicalId":45142,"journal":{"name":"Journal of Alternative Investments","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2020-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47093526","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}
M. Czasonis, W. Kinlaw, M. Kritzman, D. Turkington
Investors have traditionally relied on mean–variance analysis to determine a portfolio’s optimal asset mix, but they have struggled to incorporate private equity into this framework because they do not know how to estimate its risk. The observed volatility of private equity returns is unrealistically low because the recorded returns of private equity are based on appraised values, which are serially linked to each other. These linked appraisals, therefore, significantly dampen the observed volatility. As an alternative to observed volatility, some investors have argued that private equity volatility should be estimated as leveraged public equity volatility, because private equity companies are more highly levered than publicly traded companies. However, this approach yields unrealistically high values for private equity volatility, which invites the following question: Why isn’t the appropriately leveraged volatility of public companies a reasonable approximation of private equity volatility? This article offers an answer to this puzzle. TOPICS: Private equity, volatility measures Key Findings ▪ Why isn’t the appropriately leveraged volatility of public companies a reasonable approximation of private equity volatility? The authors look for clues in the public markets where they find no association between volatility and leverage, counter to what financial theory would suggest. ▪ The evidence suggests that the relationship between leverage and volatility is hopelessly obscured by a variety of confounding effects in both public and private markets. ▪ This article arrives at the counterintuitive conclusion that private equity volatility is similar to public equity volatility despite its higher leverage. The likely explanation is that privately held companies are inherently less risky and thus able to bear greater leverage.
{"title":"Private Equity and the Leverage Myth","authors":"M. Czasonis, W. Kinlaw, M. Kritzman, D. Turkington","doi":"10.2139/ssrn.3540545","DOIUrl":"https://doi.org/10.2139/ssrn.3540545","url":null,"abstract":"Investors have traditionally relied on mean–variance analysis to determine a portfolio’s optimal asset mix, but they have struggled to incorporate private equity into this framework because they do not know how to estimate its risk. The observed volatility of private equity returns is unrealistically low because the recorded returns of private equity are based on appraised values, which are serially linked to each other. These linked appraisals, therefore, significantly dampen the observed volatility. As an alternative to observed volatility, some investors have argued that private equity volatility should be estimated as leveraged public equity volatility, because private equity companies are more highly levered than publicly traded companies. However, this approach yields unrealistically high values for private equity volatility, which invites the following question: Why isn’t the appropriately leveraged volatility of public companies a reasonable approximation of private equity volatility? This article offers an answer to this puzzle. TOPICS: Private equity, volatility measures Key Findings ▪ Why isn’t the appropriately leveraged volatility of public companies a reasonable approximation of private equity volatility? The authors look for clues in the public markets where they find no association between volatility and leverage, counter to what financial theory would suggest. ▪ The evidence suggests that the relationship between leverage and volatility is hopelessly obscured by a variety of confounding effects in both public and private markets. ▪ This article arrives at the counterintuitive conclusion that private equity volatility is similar to public equity volatility despite its higher leverage. The likely explanation is that privately held companies are inherently less risky and thus able to bear greater leverage.","PeriodicalId":45142,"journal":{"name":"Journal of Alternative Investments","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2020-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47112290","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}
Practical Applications Summary In Private Equity Investment and Local Employment Growth: A County-Level Analysis, from the Winter 2020 issue of The Journal of Alternative Investments, Joshua Cox (of Control Risks) and Bronwyn Bailey (of BB-Advisors) use a new approach to answer the question of whether private equity investment increases employment. Previous studies have been inconclusive or contradictory. Sometimes past results indicated a loss of employment due to increased efficiencies from private equity investment, while other results indicated an increase in employment, albeit a statistically insignificant one. These studies focused on company-level employment growth, however. In contrast, Cox and Bailey examine countywide data and look for spillover effects: employment growth beyond that in the company receiving the private equity investment. The authors examine a host of control variables that might otherwise explain employment growth. In each statistical test, the association between lagged, countywide employment growth and private equity investment is positive and statistically significant.
{"title":"Practical Applications of Private Equity Investment and Local Employment Growth: A County-Level Analysis","authors":"Joshua Cox, Bronwyn Bailey","doi":"10.3905/jai.22.s2.015","DOIUrl":"https://doi.org/10.3905/jai.22.s2.015","url":null,"abstract":"Practical Applications Summary In Private Equity Investment and Local Employment Growth: A County-Level Analysis, from the Winter 2020 issue of The Journal of Alternative Investments, Joshua Cox (of Control Risks) and Bronwyn Bailey (of BB-Advisors) use a new approach to answer the question of whether private equity investment increases employment. Previous studies have been inconclusive or contradictory. Sometimes past results indicated a loss of employment due to increased efficiencies from private equity investment, while other results indicated an increase in employment, albeit a statistically insignificant one. These studies focused on company-level employment growth, however. In contrast, Cox and Bailey examine countywide data and look for spillover effects: employment growth beyond that in the company receiving the private equity investment. The authors examine a host of control variables that might otherwise explain employment growth. In each statistical test, the association between lagged, countywide employment growth and private equity investment is positive and statistically significant.","PeriodicalId":45142,"journal":{"name":"Journal of Alternative Investments","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2020-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46029888","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 case study provides new information about alternative asset fees to many institutional investors by tapping a relatively unknown data source: state pension fund annual reports. Examining the few state pension funds annual reports that track both fixed fees and carried interest fees of private equity funds and hedge funds, we find that average alternative asset fees were 2.48% of the relevant pension fund assets for the fiscal year ended June 30, 2017. In addition, as New Jersey provides the most detailed alternative asset data, this study discusses New Jersey pension fund’s private equity and hedge fund (a) returns, (b) fees, and (c) volatility, compared to verifiable and public benchmarks for the five years ended June 30, 2017. Both private equity and hedge fund portfolios underperformed the benchmarks, and the alternative asset industries’ claim of higher returns and lower risks than traditional assets is not supported in this study. To the degree that other state pension funds follow the same investment policies and controls as the state of New Jersey, this study concludes that state pension funds should reduce their holdings of alternative asset substantially. TOPICS: Wealth management, retirement, pension funds, private equity Key Findings • The New Jersey pension plan’s private equity fund and hedge fund portfolios (i) are reasonable proxies for both asset classes and (ii) are similar to those of other state pension funds. • PE five-year annualized returns (net of fees) were the same as the S&P 500. Hedge fund returns were significantly below the 60–40 index and equivalent to LIBOR+5%. • PE return volatility was similar to the S&P 500. HF volatility was greater than the 60-40 and LIBOR+5%. Average annual PE and HF fees were 3.29% and 3.08% respectively.
{"title":"Alternative Asset Fees, Returns, and Volatility of State Pension Funds: A Case Study of the New Jersey Pension Fund","authors":"Jeff Hooke, Carol Park, Ken Yook","doi":"10.3905/jai.2019.1.083","DOIUrl":"https://doi.org/10.3905/jai.2019.1.083","url":null,"abstract":"This case study provides new information about alternative asset fees to many institutional investors by tapping a relatively unknown data source: state pension fund annual reports. Examining the few state pension funds annual reports that track both fixed fees and carried interest fees of private equity funds and hedge funds, we find that average alternative asset fees were 2.48% of the relevant pension fund assets for the fiscal year ended June 30, 2017. In addition, as New Jersey provides the most detailed alternative asset data, this study discusses New Jersey pension fund’s private equity and hedge fund (a) returns, (b) fees, and (c) volatility, compared to verifiable and public benchmarks for the five years ended June 30, 2017. Both private equity and hedge fund portfolios underperformed the benchmarks, and the alternative asset industries’ claim of higher returns and lower risks than traditional assets is not supported in this study. To the degree that other state pension funds follow the same investment policies and controls as the state of New Jersey, this study concludes that state pension funds should reduce their holdings of alternative asset substantially. TOPICS: Wealth management, retirement, pension funds, private equity Key Findings • The New Jersey pension plan’s private equity fund and hedge fund portfolios (i) are reasonable proxies for both asset classes and (ii) are similar to those of other state pension funds. • PE five-year annualized returns (net of fees) were the same as the S&P 500. Hedge fund returns were significantly below the 60–40 index and equivalent to LIBOR+5%. • PE return volatility was similar to the S&P 500. HF volatility was greater than the 60-40 and LIBOR+5%. Average annual PE and HF fees were 3.29% and 3.08% respectively.","PeriodicalId":45142,"journal":{"name":"Journal of Alternative Investments","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45262228","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 article analyzes three key trends that have emerged among investors performing operational due diligence (ODD) reviews on third-party fund managers. The first trend is an increase in the scope of ODD reviews. The second trend is an expansion of the depth of ODD reviews. The third trend is a movement toward integration of ODD and investigative due diligence processes. Key Findings • Operational due diligence continues to receive more resources and attention from both investors and fund managers. • Investors are increasingly integrating the operational due diligence and investigative due diligence processes. • Investors are increasingly performing more frequent and rigorous operational due diligence reviews as fund operations have increased in complexity. TOPIC: Legal/regulatory/public policy
{"title":"Analysis of Three Emerging Trends in Limited Partner Operational Due Diligence","authors":"Jason A. Scharfman","doi":"10.3905/jai.2019.1.085","DOIUrl":"https://doi.org/10.3905/jai.2019.1.085","url":null,"abstract":"This article analyzes three key trends that have emerged among investors performing operational due diligence (ODD) reviews on third-party fund managers. The first trend is an increase in the scope of ODD reviews. The second trend is an expansion of the depth of ODD reviews. The third trend is a movement toward integration of ODD and investigative due diligence processes. Key Findings • Operational due diligence continues to receive more resources and attention from both investors and fund managers. • Investors are increasingly integrating the operational due diligence and investigative due diligence processes. • Investors are increasingly performing more frequent and rigorous operational due diligence reviews as fund operations have increased in complexity. TOPIC: Legal/regulatory/public policy","PeriodicalId":45142,"journal":{"name":"Journal of Alternative Investments","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45436837","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 article investigates the socio-demographic characteristics that individual cryptocurrency investors exhibit and the factors that go into their investment decisions in different Initial Coin Offerings (ICOs). We conducted a web-based revealed preference survey among Australian and Chinese blockchain and cryptocurrency followers, and applied a Multinomial Logit model to inferentially analyze the characteristics of cryptocurrency investors and the determinants of their choice of investment in “cryptocurrency coins” versus other types of ICO tokens. The results showed differences in the determinant of these two choices among Australian and Chinese cryptocurrency folks. The significant factors of these two choices included age, gender, education, occupation, and investment experience, and they aligned well with the behavioral literature. Furthermore, in addition to differences in how they ranked the attributes of ICOs, there was further variance between how Chinese and Australian investors ranked deterrence factors and investment strategies. TOPICS: Currency, emerging markets Key Findings • The significant factors of the choice of investment in cryptocurrency include age, gender, education, occupation, and previous investment experience. • Chinese and Australian investors rank the ICO attributes differently. • The deterrence factors and investment strategies vary between Chinese and Australians investors.
{"title":"Investigating the Investment Behaviors in Cryptocurrency","authors":"Dingli Xi, Timothy O'Brien, E. Irannezhad","doi":"10.3905/jai.2020.1.108","DOIUrl":"https://doi.org/10.3905/jai.2020.1.108","url":null,"abstract":"This article investigates the socio-demographic characteristics that individual cryptocurrency investors exhibit and the factors that go into their investment decisions in different Initial Coin Offerings (ICOs). We conducted a web-based revealed preference survey among Australian and Chinese blockchain and cryptocurrency followers, and applied a Multinomial Logit model to inferentially analyze the characteristics of cryptocurrency investors and the determinants of their choice of investment in “cryptocurrency coins” versus other types of ICO tokens. The results showed differences in the determinant of these two choices among Australian and Chinese cryptocurrency folks. The significant factors of these two choices included age, gender, education, occupation, and investment experience, and they aligned well with the behavioral literature. Furthermore, in addition to differences in how they ranked the attributes of ICOs, there was further variance between how Chinese and Australian investors ranked deterrence factors and investment strategies. TOPICS: Currency, emerging markets Key Findings • The significant factors of the choice of investment in cryptocurrency include age, gender, education, occupation, and previous investment experience. • Chinese and Australian investors rank the ICO attributes differently. • The deterrence factors and investment strategies vary between Chinese and Australians investors.","PeriodicalId":45142,"journal":{"name":"Journal of Alternative Investments","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2019-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41636012","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}
The VIX premium, the difference between VIX futures and VIX Index levels, has been shown to have predictive power over volatility returns and investment risk. This article examines a conditional strategy applied within a portfolio construct allocating equally to market and volatility risk. Although it is predominantly short volatility, the strategy owns volatility during much of the financial crisis. Both long and short volatility allocations prove to be profitable over the sample period. They produce a portfolio with more consistent profits than the S&P 500 Index and several related volatility strategies developed in previous literature and those available as volatility-based strategy indexes. TOPICS: Derivatives, futures and forward contracts, portfolio construction, financial crises and financial market history, performance measurement Key Findings ▪ From April 2007–2018, a portfolio that invests in the S&P 500 Index and VIX futures earns 1.79%, on average, each month, with a 1.02 Sharpe ratio, more than doubling the absolute and risk-adjusted returns of the S&P 500 Index. ▪ The VIX premium, the difference between VIX futures and VIX Index levels, foretells investment risk and VIX futures returns. Conditioning a long or short VIX futures allocation on the VIX premium enables the portfolio to hold short VIX futures positions for most of the time and long VIX futures positions during turbulent periods. Both long and short VIX futures investments earned positive returns, and the portfolio outperformed related strategies over the entire period and each subsample. ▪ The portfolio posts positive returns during the financial crisis by holding long VIX futures positions. In 2008, the portfolio earns 39.87%, while the S&P 500 Index lost 37.00%.
{"title":"Portfolio Strategies for Volatility Investing","authors":"Jim Campasano","doi":"10.2139/ssrn.3490978","DOIUrl":"https://doi.org/10.2139/ssrn.3490978","url":null,"abstract":"The VIX premium, the difference between VIX futures and VIX Index levels, has been shown to have predictive power over volatility returns and investment risk. This article examines a conditional strategy applied within a portfolio construct allocating equally to market and volatility risk. Although it is predominantly short volatility, the strategy owns volatility during much of the financial crisis. Both long and short volatility allocations prove to be profitable over the sample period. They produce a portfolio with more consistent profits than the S&P 500 Index and several related volatility strategies developed in previous literature and those available as volatility-based strategy indexes. TOPICS: Derivatives, futures and forward contracts, portfolio construction, financial crises and financial market history, performance measurement Key Findings ▪ From April 2007–2018, a portfolio that invests in the S&P 500 Index and VIX futures earns 1.79%, on average, each month, with a 1.02 Sharpe ratio, more than doubling the absolute and risk-adjusted returns of the S&P 500 Index. ▪ The VIX premium, the difference between VIX futures and VIX Index levels, foretells investment risk and VIX futures returns. Conditioning a long or short VIX futures allocation on the VIX premium enables the portfolio to hold short VIX futures positions for most of the time and long VIX futures positions during turbulent periods. Both long and short VIX futures investments earned positive returns, and the portfolio outperformed related strategies over the entire period and each subsample. ▪ The portfolio posts positive returns during the financial crisis by holding long VIX futures positions. In 2008, the portfolio earns 39.87%, while the S&P 500 Index lost 37.00%.","PeriodicalId":45142,"journal":{"name":"Journal of Alternative Investments","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2019-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45629180","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}
Cryptocurrencies are one of the greatest technological innovations. Cryptocurrencies are decentralized payment systems in which ownership is demonstrated cryptographically. An overview of ownership of payment units is stored in a data structure called blockchain. Of the thousands of cryptocurrencies, the best known are Bitcoin, Ethereum, Ripple, Litecoin, EOS, Cardano, NEO, Dash, and Monero. In the past, new cryptocurrencies were most often created by modifying the parameters of another cryptocurrency and by launching a new blockchain. Nowadays, new cryptocurrencies are most commonly created as applications on another existing cryptocurrency. Such cryptocurrencies are called tokens. Creating a new cryptocurrency is easy, but its value depends on users’ willingness to pay for its units. If a cryptocurrency loses its users, it becomes worthless. In this article, we analyze over 2,500 cryptocurrencies that are or were previously traded on cryptocurrency exchanges. We have explored the probability that a cryptocurrency will not survive and will be delisted from exchanges. For the different categories of cryptocurrencies according to their previous trading time on exchanges, we have determined the conditional probability of delisting within 1 to 5 years. We found out that the new cryptocurrencies are the riskiest. With the increasing age of the cryptocurrency, the probability of its delisting decreases. TOPIC: Currency Key Findings • Cryptocurrencies constitute an expanding area for potential participation and investment. Since the first cryptocurrency was created in 2009 (Bitcoin) more than 2,500 cryptocurrencies have been listed on exchanges. • Consider waiting at least a year before buying a new cryptocurrency. More than 70% of cryptocurrencies that become delisted do so in the first year. • Consider waiting five years before buying a new cryptocurrency. Cryptocurrencies that have been trading for five years have a 9% chance of being delisted within one year..
{"title":"Cryptocurrency Survival Analysis","authors":"J. Lánský","doi":"10.3905/jai.2019.1.084","DOIUrl":"https://doi.org/10.3905/jai.2019.1.084","url":null,"abstract":"Cryptocurrencies are one of the greatest technological innovations. Cryptocurrencies are decentralized payment systems in which ownership is demonstrated cryptographically. An overview of ownership of payment units is stored in a data structure called blockchain. Of the thousands of cryptocurrencies, the best known are Bitcoin, Ethereum, Ripple, Litecoin, EOS, Cardano, NEO, Dash, and Monero. In the past, new cryptocurrencies were most often created by modifying the parameters of another cryptocurrency and by launching a new blockchain. Nowadays, new cryptocurrencies are most commonly created as applications on another existing cryptocurrency. Such cryptocurrencies are called tokens. Creating a new cryptocurrency is easy, but its value depends on users’ willingness to pay for its units. If a cryptocurrency loses its users, it becomes worthless. In this article, we analyze over 2,500 cryptocurrencies that are or were previously traded on cryptocurrency exchanges. We have explored the probability that a cryptocurrency will not survive and will be delisted from exchanges. For the different categories of cryptocurrencies according to their previous trading time on exchanges, we have determined the conditional probability of delisting within 1 to 5 years. We found out that the new cryptocurrencies are the riskiest. With the increasing age of the cryptocurrency, the probability of its delisting decreases. TOPIC: Currency Key Findings • Cryptocurrencies constitute an expanding area for potential participation and investment. Since the first cryptocurrency was created in 2009 (Bitcoin) more than 2,500 cryptocurrencies have been listed on exchanges. • Consider waiting at least a year before buying a new cryptocurrency. More than 70% of cryptocurrencies that become delisted do so in the first year. • Consider waiting five years before buying a new cryptocurrency. Cryptocurrencies that have been trading for five years have a 9% chance of being delisted within one year..","PeriodicalId":45142,"journal":{"name":"Journal of Alternative Investments","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48022261","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 examines the relationship between private equity investment and local employment growth. Using a sample of over 3,000 US counties, we estimate the effect of private equity investment volume and demographic determinants of employment growth (labor supply, labor quality, labor cost, unionization, agglomeration, industry concentration, and regional geography) on employment changes from 2011 to 2014. Controlling for these demographic factors, private equity investment shows a positive correlation with employment changes. TOPIC: Private equity Key Findings • The study finds a positive association between private equity investment and employment growth. Results indicate that for each $1 million in additional private equity investment, a little more than 1.3 new jobs are created. • Results imply that private equity investment could create positive externalities. Statistical tests using countywide employment data suggest that company specific private equity investment job-creation effects spill over from the company receiving financing to the local economy.
{"title":"Private Equity Investment and Local Employment Growth: A County-Level Analysis","authors":"Joshua Cox, Bronwyn Bailey","doi":"10.3905/jai.2019.1.082","DOIUrl":"https://doi.org/10.3905/jai.2019.1.082","url":null,"abstract":"This study examines the relationship between private equity investment and local employment growth. Using a sample of over 3,000 US counties, we estimate the effect of private equity investment volume and demographic determinants of employment growth (labor supply, labor quality, labor cost, unionization, agglomeration, industry concentration, and regional geography) on employment changes from 2011 to 2014. Controlling for these demographic factors, private equity investment shows a positive correlation with employment changes. TOPIC: Private equity Key Findings • The study finds a positive association between private equity investment and employment growth. Results indicate that for each $1 million in additional private equity investment, a little more than 1.3 new jobs are created. • Results imply that private equity investment could create positive externalities. Statistical tests using countywide employment data suggest that company specific private equity investment job-creation effects spill over from the company receiving financing to the local economy.","PeriodicalId":45142,"journal":{"name":"Journal of Alternative Investments","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2019-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46043042","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}
Savva Shanaev, Arina Shuraeva, Mikhail Vasenin, M. Kuznetsov
In this article, an event studies approach is utilized to assess the influence of 51% attacks on proof-of-work (PoW) cryptocurrency prices. The study uses an exhaustive sample of 14 individual attacks on 13 cryptocurrencies. Across multiple event studies techniques, majority attacks on blockchains are consistently shown to immediately decrease corresponding coin prices by 12% to 15%. Significantly negative price response is robust in various event windows. Coin prices do not recover to pre-attack levels one week after the event. There is evidence of pump-and-dump schemes prior to the 51% attack, however the market demonstrates high efficiency after the attacks. 51% attacks are suggested to be a fundamental risk factor for cryptocurrency investments, primarily characteristic of small PoW coins with low hash rates. TOPIC: Currency Key Findings • 51% attacks on Proof-of-Work cryptocurrencies decrease their market prices by 12.60% on average. • The effect is robust to different measurement techniques and in various event windows. • There is evidence of insider trading and “pump-and-dump” schemes prior to the attacks.
{"title":"Cryptocurrency Value and 51% Attacks: Evidence from Event Studies","authors":"Savva Shanaev, Arina Shuraeva, Mikhail Vasenin, M. Kuznetsov","doi":"10.3905/jai.2019.1.081","DOIUrl":"https://doi.org/10.3905/jai.2019.1.081","url":null,"abstract":"In this article, an event studies approach is utilized to assess the influence of 51% attacks on proof-of-work (PoW) cryptocurrency prices. The study uses an exhaustive sample of 14 individual attacks on 13 cryptocurrencies. Across multiple event studies techniques, majority attacks on blockchains are consistently shown to immediately decrease corresponding coin prices by 12% to 15%. Significantly negative price response is robust in various event windows. Coin prices do not recover to pre-attack levels one week after the event. There is evidence of pump-and-dump schemes prior to the 51% attack, however the market demonstrates high efficiency after the attacks. 51% attacks are suggested to be a fundamental risk factor for cryptocurrency investments, primarily characteristic of small PoW coins with low hash rates. TOPIC: Currency Key Findings • 51% attacks on Proof-of-Work cryptocurrencies decrease their market prices by 12.60% on average. • The effect is robust to different measurement techniques and in various event windows. • There is evidence of insider trading and “pump-and-dump” schemes prior to the attacks.","PeriodicalId":45142,"journal":{"name":"Journal of Alternative Investments","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2019-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45394205","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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