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Measuring Crypto Literacy
Abstract
In this article, we present the construction and validation of a scale for measuring knowledge in the area of cryptoeconomics. As users continue to adopt digital currencies and government agencies introduce more regulatory legislation, researchers need to understand the general public’s degree of literacy in this field. Measuring financial literacy has encouraged policymakers and educators to create programs that improve financial decision-making and increase financial empowerment. However, there is no similar corresponding scale to measure crypto literacy. We address this gap by developing a robust survey instrument that covers various domains of crypto literacy, including a basic knowledge of blockchain technology. The scale's development involves a rigorous process of item generation, analysis, and criterion validity. The resultant Crypto Literacy Scale (CLS) is a standardized measurement tool that contributes to ongoing efforts in financial education and regulation in the context of digital currencies and blockchain technology. We suggest several paths for future research in the emerging field of crypto literacy.
... In light of these gaps in previous research, the current study examines the association between cryptocurrency and financial literacy and fear of cryptoeconomic victimization, as well as fear of financial fraud victimization more generally. Cryptocurrency literacy refers to knowledge relating to various aspects of cryptocurrency, including the use of blockchain, the use of cryptocurrency in facilitating economic transactions, and other aspects relating specifically to these emerging virtual currencies (Jones et al., 2024a). Conversely, cryptoeconomic victimization refers to fraud or cybercrime victimization facilitated through the use of cryptocurrencies. ...
... It remains to be seen however whether fear similarly varies across forms of cryptoeconomic and financial fraud. Given the prevalence of distrust and lack of confidence associated with cryptocurrencies in the United States, coupled with sociodemographic patterns among investment in cryptocurrencies (Faverio et al., 2024), it may be the case that the correlates of personal and altruistic fear related to cryptoeconomic victimization are inconsistent, and that certain factors which may influence one's perceived vulnerability to these crimes such as financial or cryptocurrency literacy influence fear expressed not only for oneself, but altruistically (Jones et al., 2024a). ...
... Cryptocurrencies are a form of digital currency that have emerged in recent decades as an alternative to traditional currency and financial assets (Jones et al., 2024b;Ma et al., 2020;Saha et al., 2024). Cryptocurrencies are built on cryptography and blockchain technology, a decentralized ledger system that enables peer-to-peer transactions without reliance upon intermediaries (Hassani et al., 2018;Jones et al., 2024a;Ulrich et al., 2024). The use of blockchain technologies allow for records of transactions to be replicated across multiple users who collectively operate and secure the blockchain, resulting in a decentralized record of transactions (Johnson et al., 2023). ...
The proliferation of cryptocurrency throughout society has led to widespread usage within criminal offending. Despite this, limited research has investigated fear of cryptocurrency-based victimization, or the role that financial or cryptocurrency literacy play in influencing such fears. This study examines the influence in which financial and cryptocurrency literacy plays in both personal and altruistic fear of financial and cryptoeconomic crimes. Using a sample of college undergraduates (n = 433), and employing a validated scale of cryptocurrency literacy, results indicate that cryptocurrency literacy is not significantly associated with all modalities of fear of crime investigated, with the exception of altruistic fear of non-cryptocurrency financial crimes. Conversely, general financial literacy was negatively associated with personal fear of both financial crimes and non-cryptoeconomic financial crimes. Findings are discussed in light of research and policy implication as well as limitations.
... For example, Habitat Association has outlined key topics in its blockchain literacy education programme, including infrastructure elements such as information sources, legal frameworks, economy and finance and security. In a study on cryptocurrency literacy, Jones et al. (2024) defined a "literate individual" by incorporating dimensions such as economy, politics and regulations and security risks. Similarly, Uysal et al. (2024) explored Web 3.0 awareness, developing a scale that emphasizes risks and opportunities. ...
... The development of the blockchain literacy scale (BLS) in this study followed established scale development guidelines (Carpenter, 2018;Churchill, 1979) and validation procedures (Carpenter, 2018;Crocetta et al., 2021;Hair et al., 2019). First, studies on blockchain technologies were reviewed (Albayati et al., 2020;Caliskan, 2020;De Filippi et al., 2020;Herian, 2018;Janssen et al., 2020;Jones et al., 2024;Kowalski et al., 2021;Marengo & Pagano, 2023;Marikyan et al., 2022;Morkunas et al., 2019;dePina Cesario, 2023;Staples et al., 2017;Ur-Rehman et al., 2019). When evaluating the studies, it was noted that there is limited extensive literature on blockchain. ...
... The findings suggest that Turkish participants primarily perceive blockchain literacy across five dimensions: risk literacy, legal literacy, economic awareness, information access and legal regulation awareness. These dimensions align with previous studies that conceptualize blockchain literacy as a multidimensional construct (Komulainen & Natti, 2023;Jones et al., 2024;Merkley et al., 2024;Mohammad & Vargas, 2022;Suwanposri et al., 2021;Uysal et al., 2024). Additionally, three of these dimensions (risk literacy, legal literacy and economic awareness) correspond to the blockchain-related scales developed by Jones and Flannigan (2006) and Subaveerapandiyan et al. (2024). ...
... Detailed information on the nine included publications is presented in Table 1. Two publications were authored by the same authors (14,15). The majority of identified publications used quantitative data collection methodologies (n = 5) (14,15,16,19,21). ...
... Two publications were authored by the same authors (14,15). The majority of identified publications used quantitative data collection methodologies (n = 5) (14,15,16,19,21). Additionally, two studies employed qualitative data collection approaches (14,17), whereas the remaining two centered on theoretical analysis (18,22). ...
... The majority of identified publications used quantitative data collection methodologies (n = 5) (14,15,16,19,21). Additionally, two studies employed qualitative data collection approaches (14,17), whereas the remaining two centered on theoretical analysis (18,22). ...
... The majority of the early posts were expressions of confusion and/or a lack of understanding. Elsewhere, scholars have described the possession of knowledge and skills needed to make decisions related to cryptocurrency and blockchain technology as cryptocurrency literacy or "crypto literacy" (Jones et al., 2023). Overall, about one-eighth (12%) of the total posts in the dataset expressed a lack of crypto literacy and another 10% of the posts were intended to share information (therefore enhancing the crypto literacy of their peers) by including links to webpages elsewhere that covered cryptocurrency and football. ...
Purpose – Given the rise of sport non-fungible tokens (NFTs) and sponsorships from cryptocurrency companies in the sport industry during the coronavirus disease 2019 (COVID-19) pandemic, this paper aims to critically frame the partnerships between cryptocurrency and sport by exploring the reception of fan tokens amongst supporters of three English Premier League clubs: Manchester City, Everton and Crystal Palace.
Design/methodology/approach – Drawing upon the emerging critical scholarship on cryptocurrency and the political economy of professional football, this study uses digital ethnography in an attempt to understand the major themes emanating from the online forum discussions amongst fans in response to the issuance of fan tokens by the aforementioned three clubs, among other types of partnerships with crypto companies.
Findings – The supporters’ critical deliberations revolved around the contradictions of fan tokens (as a means for supposed “fan engagement” or for financial speculation) and the utility of cryptocurrency for the public. These reactions in turn showcase a larger tension underlying the financially unstable professional football industry: the contest between the owners and the fan bases over the exchange value (for profit) and use value (for community) of the clubs.
Originality/value – This paper is one of the first studies to adopt a critical framework to examine the emerging partnerships between sports and cryptocurrency companies during the COVID-19 pandemic. It also provides one of the first in-depth analyses of the critical receptions of sport NFTs amongst sport fans. While contributing to the literature on fan activism/protest in the context of the commercialization and commodification of sport, the paper also raises new questions on the responsible use of cryptocurrency/ NFT in sport.
FİNANSAL OKURYAZARLIK DÜZEYİNİN BELİRLEYİCİ FAKTÖRLERİNİN ÜLKE EKONOMİSİNE ETKİLERİ
As cryptocurrencies become more prevalent in investor portfolios, we examine whether a greater knowledge of digital assets is connected to an understanding of broader financial concepts. We find a positive relationship between cryptocurrency (crypto) literacy and financial literacy, suggesting that a higher understanding of cryptocurrencies may lead to better financial decision-making. Our research reveals that individuals with higher levels of subjective crypto literacy are more likely to seek professional guidance and view it as complementary to their own knowledge of digital assets. We conclude by discussing the possibility of including crypto literacy in financial services.
[ Full paper text available at: https://authors.elsevier.com/a/1gTiP98SGwgpX ]
Stablecoins are a relatively recent phenomenon in the cryptocurrency market, gaining prominence particularly since 2018. These digital currencies are usually pegged to nonvolatile underlying assets, offering a solution to the problem of the high price volatility of nonstable cryptocurrencies such as Bitcoin. Therefore, stablecoins seem attractive to participants in the cryptocurrency market, especially in times of turmoil. This paper aims to measure the spillover effect of shocks in volatile cryptocurrencies (Bitcoin, Ethereum, Litecoin and the Cryptocurrencies Index) on the activity of investors in the stablecoin market (Tether, USD Coin, Binance USD, DAI, Paxos, Huobi USD, and Gemini USD). Using the spectral representation of variance decomposition, the paper measures the strength of the spillover effect and investigates whether the cryptocurrency market processes information rapidly or slowly. The results suggest that shocks in the volatile cryptocurrency market moderately drive the popularity of stablecoins. The spillover effects on stablecoin popularity are short-lived, as they are observed mostly within up to 3 days of the shock. The findings indicate that investors use stablecoins as safe haven assets after bad news in the volatile cryptocurrency market; however, they react more strongly to news related to individual cryptocurrencies and not so intensively to the general sentiment in the cryptocurrency market. Investors with larger capital are more resistant to shocks.
The Fourth industrial revolution has seen many innovative technologies that are now challenging traditional economies. The innovative and technological financial instruments are inspiring individuals and expert investors to investigate the broader investment spectrum, and consequently diversify their portfolios. Going beyond the conventional portfolios and developing state-of-the-art strategies that comply with the ever-changing financial and technological advancements are the keys to long term sustainability. Therefore, to cater to the needs of all segments of the society, the investment strategies during the fourth industrial revolution demand exposure to technological and digital financial innovations. This study investigates the impact of diversification with the addition of five cryptocurrencies from November 2015 to November 2019 on four traditional asset portfolios. The results show that the diversification increased the returns in most of the cases, and reduced the portfolio volatility in all portfolios, and also provided higher returns as compared to the traditional portfolios for the same level of risk. This study also revealed that the results might improve when short sales are allowed. Moreover, we can conclude that the addition of multiple cryptocurrencies in a portfolio provides enhanced results for diversification, and Ethereum provides a better diversification opportunity as compared to Bitcoin.
Cryptocurrencies have been broadly scrutinised in recent times for a host of concerning regulatory and cyber-criminality issues. Although steps have been taken to promote regulatory sufficiency in the near future, we examine the avenues through which this extremely high-risk industry can derive potentially devastating contagion channels, influencing both unwilling and unsuspecting investors. We focus this research on the expressions of interest by publicly traded companies across the world to utilise cryptocurrency and blockchain projects. We find evidence that there exists a substantial stock price premium and sustained increase in volatility in the aftermath of blockchain announcements, with emphasis on highly-speculative motives such as coin creation and corporate name changes. Changes in price discovery and information flows are found to be largely determined from cryptocurrency-based pricing sources in the aftermath of speculative announcements. We discuss the inherent ethical and legal issues, considering as to whether such announcements are simply an attempt to artificially manipulate share prices and take part in the current phase of crypto-exuberance.
We applied Item Response Theory (IRT) to construct and evaluate new brief and in‐depth financial literacy scales. A survey of a UK adult sample (N = 589) included 50 questions to assess knowledge about managing financial resources and competence in using personal finance‐related information – including five widely used items, on interest rates – inflation, investment diversification, mortgages and bonds. IRT applied to a scale of these items identified some limitations, overcome via further iterations to construct a new brief scale with sound psychometric properties. IRT was then applied iteratively to our pool, resulting in an in‐depth, 20‐item scale, also psychometrically sound, covering four broad financial domains: everyday money transactions; the concept of money; borrowing; and saving and investment. Parallel 10‐item sub‐scales were also evaluated. The validity of the new scales was demonstrated by regression analyses which found that, controlling for demographic variables, financial literacy predicted key indicators of financial well‐being.
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Amazon’s Mechanical Turk (MTurk) is arguably one of the most important research tools of the past decade. The ability to rapidly collect large amounts of high-quality human subjects data has advanced multiple fields, including personality and social psychology. Beginning in summer 2018, concerns arose regarding MTurk data quality leading to questions about the utility of MTurk for psychological research. We present empirical evidence of a substantial decrease in data quality using a four-wave naturalistic experimental design: pre-, during, and post-summer 2018. During and to some extent post-summer 2018, we find significant increases in participants failing response validity indicators, decreases in reliability and validity of a widely used personality measure, and failures to replicate well-established findings. However, these detrimental effects can be mitigated by using response validity indicators and screening the data. We discuss implications and offer suggestions to ensure data quality.
Who is better at detecting fraud? This paper finds that more financially knowledgeable individuals have a higher propensity to detect fraud: a one standard deviation increase in financial knowledge increases fraud detection probabilities by 3 percentage points. The result is not driven by individuals' higher financial product usage and is observed to be moderated by individuals' low subjective well-being, effectively depleting skills to detect fraud. Interestingly, prudent financial behavior relating to basic money management is found to have negligible effects for detecting fraud. The findings attest to the fact that fraud tactics are increasingly complex and it is greater financial knowledge rather than basic money management skills that provide the degree of sophistication necessary to detect fraud. The paper draws policy implications for consumer education programs to go beyond cultivating money management skills, and provide advanced financial knowledge necessary for tackling fraud.
The number of online experiments conducted with subjects recruited via online platforms has grown considerably in the recent past. While one commercial crowdworking platform - Amazon's Mechanical Turk - basically has established and since dominated this field, new alternatives offer services explicitly targeted at researchers. In this article, we present www.prolific.ac and lay out its suitability for recruiting subjects for social and economic science experiments. After briefly discussing key advantages and challenges of online experiments relative to lab experiments, we trace the platform's historical development, present its features, and contrast them with requirements for different types of social and economic experiments.
Despite the fact that validating the measures of constructs is critical to building cumulative knowledge in MIS and the behavioral sciences, the process of scale development and validation continues to be a challenging activity. Undoubtedly, part of the problem is that many of the scale development procedures advocated in the literature are limited by the fact that they (1) fail to adequately discuss how to develop appropriate conceptual definitions of the focal construct, (2) often fail to properly specify the measurement model that relates the latent construct to its indicators, and (3) underutilize techniques that provide evidence that the set of items used to represent the focal construct actually measures what it purports to measure. Therefore, the purpose of the present paper is to integrate new and existing techniques into a comprehensive set of recommendations that can be used to give researchers in MIS and the behavioral sciences a framework for developing valid measures. First, we briefly elaborate upon some of the limitations of current scale development practices. Following this, we discuss each of the steps in the scale development process while paying particular attention to the differences that are required when one is attempting to develop scales for constructs with formative indicators as opposed to constructs with reflective indicators. Finally, we discuss several things that should be done after the initial development of a scale to examine its generalizability and to enhance its usefulness.
Anonymity in Bitcoin, a peer-to-peer electronic currency system, is a
complicated issue. Within the system, users are identified by public-keys only.
An attacker wishing to de-anonymize its users will attempt to construct the
one-to-many mapping between users and public-keys and associate information
external to the system with the users. Bitcoin tries to prevent this attack by
storing the mapping of a user to his or her public-keys on that user's node
only and by allowing each user to generate as many public-keys as required. In
this chapter we consider the topological structure of two networks derived from
Bitcoin's public transaction history. We show that the two networks have a
non-trivial topological structure, provide complementary views of the Bitcoin
system and have implications for anonymity. We combine these structures with
external information and techniques such as context discovery and flow analysis
to investigate an alleged theft of Bitcoins, which, at the time of the theft,
had a market value of approximately half a million U.S. dollars.
We present a 12-item scale measuring the cognitive component of economic competence and document the psychometric properties of the scale. Using a data set with >12,000 secondary school students in Germany, the scale shows high discriminatory power and covers a wide range of ability levels. Analyses of ‘Differential Item Functioninǵ show no item bias across key demographic characteristics, and scores show meaningful associations with scores obtained from adjacent test instruments. Student-level correlates mirror estimates documented in earlier literature as well as results relying on a more extensive version of the scale with 31 items. The presented short scale enables researchers and practitioners to efficiently measure economic competence of youth.
Elon Musk, one of the richest individuals in the world, is considered a technological visionary and has a social network of over 110 million followers on social media platform Twitter. He regularly uses his social media presence to communicate on various topics, one of which is cryptocurrency, such as Bitcoin or Dogecoin. Using an event study approach, we analyze to what extent Musk's Twitter activity affects short-term cryptocurrency returns and volume. In other words, we investigate whether cryptocurrency markets exhibit a “Musk Effect”. Based on a sample of 47 cryptocurrency-related Twitter events, we identify significant positive abnormal returns and trading volume following such events. However, we discover that on average, price effects are only significant for Dogecoin-related Tweets but not for Bitcoin. This is because regarding the latter, the significant price effects of positive and negative news cancel each other out. Considered in isolation, non-negative tweets from Musk lead to significantly positive abnormal Bitcoin returns. Individual tweets do raise the price of Bitcoin by 16.9 % or reduce it by almost 11.8 %. Our study shows the significant impact that the social media activity of influential individuals can have on cryptocurrencies. This suggests a conflict between morals, risks of market manipulation and investor protection.
Financial literacy is a crucial skill for personal wealth management and economic well-being. Hence, it is important to evaluate the impact of interventions aimed at increasing financial knowledge and confidence in the most vulnerable groups of the society. We conduct an impact evaluation of a two-hour lecture targeting the elderly population. We find that the intervention does not have a significant impact on knowledge but has a significant effect on confidence and (partly) on overconfidence.
A decade after the launch of Bitcoin, cryptocurrencies are maturing from a niche phenomenon and appealing to a broader audience. However, the actual prevalence of cryptocurrency ownership and usage, the users' socio-demographics, the motives to buy, and the popularity of and knowledge about cryptocurrencies have not been sufficiently researched. Based on a representative online survey among 3864 Germans, we find that 83% of the respondents are aware of the phenomenon, yet the respondents' self-assessed knowledge about crypto-currencies and the underlying blockchain technology is limited. 9.2% of the respondents owned cryptocurrencies at the time of the survey; another 9.1% have owned cryptocurrencies in the past. Cryptocurrency users tend to be young, male, well-educated and well-off. Ownership is often associated with long-term investments, and 62% of the respondents state that their ownership is ideologically motivated. The empirical analysis discloses that a major driver of ownership is knowledge about cryptocurrencies, mediated by trust. There is some discrepancy between the actual and perceived usage domains of cryptocurrencies, which reflects the polarization of the phenomenon. The findings have implications for regulators and businesses which are potentially affected by the increasing societal relevance of cryptocurrency.
Stablecoins are digital currencies that peg to non-volatile values, most commonly a fiat currency. Unlike fiat currency, stablecoins are fully transparent—every transfer is recorded on a public blockchain. In this regard, they can serve as a valuable case study of the disruptive effect which transparent money flows could have on financial markets. We analyze how 1,587 stablecoin transfers of $1 million or more between April 2019 and March 2020 affected Bitcoin returns and trading volume. We find highly significant positive abnormal trading volume and significant abnormal returns in the hours around stablecoin transfers. The sender and receiver of each transfer are categorized as (1) unknown, (2) cryptocurrency exchange or (3) stablecoin treasury. The effects on trading volume and returns differ across the nine resulting subsamples, suggesting that market participants presume different transfer motives and varying degrees of information asymmetry for each sender-receiver combination. The findings illustrate the feedback effects between cryptocurrency markets and stablecoin usage and suggest that transparent money flows can increase market efficiency.
This study compares the key characteristics of Japanese crypto asset owners with those of nonowners. After confirming that average crypto asset owners are likely to be young and male as compared to average crypto asset nonowners, we find that average crypto asset owners tend to have a higher level of financial literacy and are more likely to use cashless payment methods and hoard cash, as compared to average crypto asset nonowners. This study also determined novel heterogeneities among crypto asset owners according to their investment experience with conventional risky financial assets in terms of cash hoarding and financial literacy. Crypto asset owners without investment experience with conventional risky financial assets do not hoard cash and their level of financial literacy is lower than that of both crypto asset owners and nonowners with investment experience with conventional risky financial assets. The results suggest that financial regulators should not treat crypto asset owners as a homogenous group of financially literate investors who are inherently good at internet transactions.
This study examines the time-series relation between Bitcoin and forward inflation expectation rates. Using a vector autoregressive process, we find that changes in Bitcoin Granger cause changes in the forward inflation rate. Furthermore, imposing an exogenous shock to Bitcoin’s price results in a persistent increase in the forward inflation rate. Our findings provide support for the notion that Bitcoin may be used as a hedge against inflation as changes in the price of Bitcoin tend to lead changes in the expected inflation.
This book develops an intuitive understanding of IRT principles through the use of graphical displays and analogies to familiar psychological principles. It surveys contemporary IRT models, estimation methods, and computer programs. Polytomous IRT models are given central coverage since many psychological tests use rating scales. Ideal for clinical, industrial, counseling, educational, and behavioral medicine professionals and students familiar with classical testing principles, exposure to material covered in first-year graduate statistics courses is helpful. All symbols and equations are thoroughly explained verbally and graphically. © 2000 by Lawrence Erlbaum Associates, Inc. All rights reserved.
Over the last years, cryptocurrencies have acquired a growing social and economic interest. The most representative features of this new phenomenon are strong price increases and high volatility. The investigations developed in this field are not excessively numerous nor unanimous. Some researches consider this phenomenon to be a bubble, since they don't agree that the price pattern of the cryptocurrencies is justified or explained by their intrinsic value. The present article aims to provide a theoretical framework for the assessment of these new realities embodied by cryptocurrencies. We have created a model which differentiates two types of cryptocurrencies: the cryptocurrencies meant to fund a specific project, and the cryptocurrencies designed for general or non-specific uses. We will also make a distinction between block chain networks designed to work only with cryptocurrencies from those which admit other tasks. Our model establishes the difference between the value of the currency and that of the network. The result of this research is a theoretical valuation model based on three fundamental categories of cryptocurrencies by purpose or finality.
We examine whether inflated perceptions of financial literacy affect financial decision making. Gaps between objective financial literacy and self-reported (perceived) financial literacy (blind spots) predict 19 financial behaviors better than age, gender, income, ethnicity, marital status, self-employment status, and general education levels. Only two predictors, perceived financial literacy and financial education, carried similar levels of predictive power on financial behaviors. Those with inflated perceptions of financial literacy are more likely to miss mortgage payments, receive a collection call, use informal debt, and have poor banking behavior. Those without blind spots make better financial decisions. The differences between those with and without blind spots are more pronounced among individuals with higher education and income.
In the context of the 4th industrial revolution, artificial intelligence (AI) and environmental challenges, this study investigates the role of AI, robotics stocks and green bonds in portfolio diversification. Using daily data from 2017 to 2020, we employ tail dependence as copulas and the Generalized Forecast Error Variance Decomposition to examine the volatility connectedness. Our results suggest that, first, portfolios consisting of these assets exhibit heavy-tail dependence which implies that in the times of economic turbulence, there will be a high probability of large joint losses. Second, volatility transmission is higher in the short term, implying that short-term shocks can cause higher volatility in the assets, but in the long run, volatility transmission decreases. Third, Bitcoin and gold are vital assets for hedging, though the Bitcoin is also affected by its past volatility, a feature it shares with green bonds and NASDAQ AI. During economic downturns, gold may act as a safe haven, as its shock transmission to NASDAQ AI is just around 1.41%. Lastly, the total volatility transmission of all financial assets is considerably high, suggesting that the portfolio has an inherent self-transmitting risk which requires careful diversification. The NASDAQ AI and general equity indexes are not good hedging instruments for each other.
Cryptocurrencies such as Bitcoin have fascinated technologists and investors alike. They have become prevalent, with over 2,000 Bitcoin-like cryptocurrencies now in use. Most jurisdictions have not regulated cryptocurrencies. Whether existing regulations apply to cryptocurrency turns ultimately on if we classify cryptocurrencies as currencies, securities, or derivatives, or a money services (transfer) vehicle. In this set of exploratory analyses we seek to classify Bitcoin. We utilize a variety of methods to compare aspects of its behavior to: currencies, asset classes such as derivatives, technology-based products and possible technology-based products such as Ether and the security SPY, and speculative financial bubbles. We find that Bitcoin's behavior more closely resembles a technology-based product, an emerging asset class, or a bubble event, rather than a currency or a security; such that it is correct that existing currency and security laws should not apply to cryptocurrencies.
This letter explores the behavior of conditional correlations among main cryptocurrencies, stock and bond indices, and gold, using a generalized DCC class model. From a portfolio management point of view, asset correlation is a key metric in order to construct efficient portfolios. We find that: (i) correlations among cryptocurrencies are positive, albeit varying across time; (ii) correlations with Monero are more stable across time; (iii) correlations between cryptocurrencies and traditional financial assets are negligible.
This study examines the influence of actual and perceived financial knowledge (i.e., financial literacy and confidence) on financial wealth. We show that consideration of gender and education as moderators helps to uncover intricate effects. Greater financial literacy leads to higher wealth, with higher education strengthening this effect considerably for women, but not so for men. Men's wealth also rises in confidence, while there is hardly any confidence effect for women. Our results are robust against the employment of different instrumental variables and confidence measures, consideration of one-time wealth effects and mode of financial decision making.
Bitcoin is a popular "cryptocurrency" that records all transactions in an distributed append-only public ledger called "blockchain". The security of Bitcoin heavily relies on the incentive-compatible distributed consensus protocol which is run by participants called "miners". In exchange of the incentive, the miners are expected to honestly maintain the blockchain. Since its launch in 2009, Bitcoin economy has grown at an enormous rate is now worth about 40 billions of dollars. This exponential growth in the market value of Bitcoin motivates adversaries to exploit weaknesses for profit, and researchers to identify vulnerabilities in the system, propose countermeasures, and predict upcoming trends. In this paper, we present a systematic survey on security and privacy aspects of Bitcoin. We start by presenting an overview of the Bitcoin protocol and discuss its major components with their functionality and interactions. We review the existing vulnerabilities in Bitcoin which leads to the execution of various security threats in Bitcoin system. We discuss the feasibility and robustness of the state-of-the-art security solutions. We present privacy and anonymity considerations, and discuss the threats to enabling user privacy along with the analysis of existing privacy preserving solutions. Finally, we summarize the critical open challenges, and suggest directions for future research towards provisioning stringent security and privacy techniques for Bitcoin.
This graduate-level textbook is a tutorial for item response theory that covers both the basics of item response theory and the use of R for preparing graphical presentation in writings about the theory. Item response theory has become one of the most powerful tools used in test construction, yet one of the barriers to learning and applying it is the considerable amount of sophisticated computational effort required to illustrate even the simplest concepts. This text provides the reader access to the basic concepts of item response theory freed of the tedious underlying calculations. It is intended for those who possess limited knowledge of educational measurement and psychometrics.
Rather than presenting the full scope of item response theory, this textbook is concise and practical and presents basic concepts without becoming enmeshed in underlying mathematical and computational complexities. Clearly written text and succinct R code allow anyone familiar with statistical concepts to explore and apply item response theory in a practical way. In addition to students of educational measurement, this text will be valuable to measurement specialists working in testing programs at any level and who need an understanding of item response theory in order to evaluate its potential in their settings.
• Combines clearly written text and succinct R code
• Utilizes a building-block approach from simple to complex, enabling readers to develop a clinical feel for item response theory and how its concepts are interrelated
• Includes downloadable R functions that implement various facets of item response theory
Frank B. Baker, Ph.D., is Professor Emeritus of the Department of Educational Psychology at the University of Wisconsin-Madison. He is author of numerous publications dealing with item response theory and statistical methodology. He received his B.S., M.S., and Ph.D. degrees from the University of Minnesota, Minneapolis.
Seock-Ho Kim, Ph.D., is Professor in the Department of Educational Psychology at the University of Georgia. He is author of numerous publications in psychometrics and applied statistics and is a member of the American Educational Research Association, the American Statistical Association, the National Council on Measurement in Education, and the Psychometric Society, among other organizations. He received his B.A. from Korea University and his M.S. and Ph.D. degrees from the University of Wisconsin-Madison.
We explore whether investors who are more financially knowledgeable earn more on their retirement plan investments compared with their less sophisticated counterparts, using a unique new dataset linking administrative data on investment performance and financial knowledge. Results show that the most financially knowledgeable investors: (a) held 18% points more stock than their least knowledgeable counterparts; (b) could anticipate earning 8 basis points per month more in excess returns; (c) had 40% higher portfolio volatility; and (d) held portfolios with about 38% less idiosyncratic risk, as compared with their least savvy counterparts. Our results are qualitatively similar after controlling on observables as well as modeling sample selection. We also examine portfolio changes to assess the potential impact of the financial literacy intervention. Controlling on other factors, those who elected to take the financial literacy survey boosted their equity allocations by 66 basis points and their monthly expected excess returns rose by 2.3 basis points; no significant difference in volatility or non-systematic risk was detected before versus after the survey. While these findings relate to only one firm, we anticipate that they may spur other efforts to enhance financial knowledge in the workplace.
This study uses a 3-Parameter Logistic item response theory (IRT) model to develop an 18-item short-form of the Situational Test of Emotion Management (STEM). In a sample of 900 people, the short form showed acceptable reliability (reliability index = .87; Cronbach’s alpha = .84) and a meaningful correlation with another indicator of emotional intelligence (i.e., r = .30 with the Situational Test of Emotional Understanding). Latent class analysis of the short-form detected two classes. For all items, participants in Class 2 had a higher probability of selecting the best option than Class 1. When response options were coded to represent different emotion regulation strategies, Class 2 had a higher probability of endorsing “situation modification” and Class 1 had a higher probability of endorsing “no regulation”. These results provide validity evidence for the STEM-B as an assessment of emotion regulation.
This study aims to develop a complementary and more comprehensive measurement to assess the nature of investment value affecting consumers’ investment behavior. Recent research suggests that consumers may desire and obtain certain outcomes from investments that have not been anticipated in mainstream finance and economics literature. These benefits might be hedonistic or altruistic, self-expressive or emotional and experiential. Yet, while an increasing amount of attention has been paid to this topic, little effort has been made to develop an appropriate measurement scale for the subjective consumer perceptions of investments. To address this gap in the literature, this study introduces the concept of Perceived Investment Value (PIV), and develops and validates a measurement scale for the concept. The ultimate 18-item PIV scale parsimoniously represents six Perceived Investment Value dimensions: Economic value—Monetary savings; Economic value—Efficiency; Functional value—Convenience; Emotional value—Emotions and Experiences; Symbolic value—Altruism; and Symbolic value—Esteem. The final measurement scale demonstrates acceptable reliability and validity. Implications related to the developed scale are discussed in terms of their potential to inform a future research agenda.
A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution. Digital signatures provide part of the solution, but the main benefits are lost if a trusted third party is still required to prevent double-spending. We propose a solution to the double-spending problem using a peer-to-peer network. The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they'll generate the longest chain and outpace attackers. The network itself requires minimal structure. Messages are broadcast on a best effort basis, and nodes can leave and rejoin the network at will, accepting the longest proof-of-work chain as proof of what happened while they were gone.
This study pursues external validation of contingent valuation by comparing survey results with the voting outcome of a Corvallis, Oregon, referendum to fund a riverfront improvement project through increased property taxes. Survey respondents hypothetically make a voting decision—with no financial consequences—on the upcoming referendum. The survey sample consists of respondents verified to have voted in the election. We use available precinct-level election data to compare the proportion of “yes” survey and referendum votes as well as estimate voting models and mean willingness to pay (WTP) based on the two sets of data. We find that survey responses match the actual voting outcome and WTP estimates based on the two are not statistically different. Contrary to similar studies, our statistical results do not depend on re-coding the majority of “undecided” survey responses to “no.” Furthermore, such a re-coding of responses may be inappropriate for our data set.
The United Nations General Assembly recognized the importance of people’s sustainability values in driving attitudes and behaviors towards the sustainable development of globalization by declaring a set of “certain fundamental values to be essential to international relations in the twenty-first century” (UN, 2000). The specific values underlying this UN declaration are freedom, equality, solidarity, tolerance, respect for nature, and shared responsibility. Despite their importance, little is known about the nature of sustainability values and much work needs to be done in developing such scales. This study develops a reliable and valid measure of values underlying sustainable development which will hopefully stimulate further research on regional, cultural, and demographic differences in sustainable development.
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