Tarzan and chain: exploring the ICO jungle and evaluating design archetypes

AbstractThe phenomenon of a blockchain use case called initial coin offering (ICO) is drawing increasing attention as a novel funding mechanism. ICO is a crowdfunding type that utilizes blockchain tokens to allow for truly peer-to-peer investments. Although more than $7bn has been raised globally via ICOs as at 2018, the concept and its implications are not yet entirely understood. The research lags behind in providing in-depth analyses of ICO designs and their long-term success. We address this research gap by developing an ICO taxonomy, applying a cluster analysis to identify prevailing ICO archetypes, and providing an outlook on the token value market performance for individual archetypes. We identify five ICO design archetypes and display their secondary market development from both a short-term and a long-term perspective. We contribute to an in-depth understanding of ICOs and their implications. Further, we offer practitioners tangible design and success indications for future ICOs.

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An Approach toward the Development of a Functional Encoding Model of Short Term Memory during Reading

Journal of Reading Behavior ◽

10.1080/10862967809547263 ◽

1978 ◽

Vol 10 (2) ◽

pp. 141-148

Author(s):

Mary Anne Herndon

Keyword(s):

Cluster Analysis ◽

Storage Capacity ◽

Short Term Memory ◽

Long Term Memory ◽

Short Term ◽

Processing Efficiency ◽

Term Memory ◽

Information Unit ◽

Subsequent Storage

In a model of the functioning of short term memory, the encoding of information for subsequent storage in long term memory is simulated. In the encoding process, semantically equivalent paragraphs are detected for recombination into a macro information unit. This recombination process can be used to relieve the limited storage capacity constraint of short term memory and subsequently increase processing efficiency. The results of the simulation give a favorable indication of the success for the use of cluster analysis as a tool to simulate the encoding function in the detection of semantically similar paragraphs.

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Influence of involuntary automated motor activity upon voluntary attention and memory

SHS Web of Conferences ◽

10.1051/shsconf/20208700072 ◽

2020 ◽

Vol 87 ◽

pp. 00072

Author(s):

Eugene Brunner ◽

Denis Mokrentsov

Keyword(s):

Working Memory ◽

Cluster Analysis ◽

Information Processing ◽

Motor Activity ◽

Considerable Increase ◽

Chewing Gum ◽

Attention And Memory ◽

Voluntary Attention ◽

Short Term

The article deals with the changes and interaction of different attention and memory parameters under the influence of involuntary (automated) motor activity. Methodology. To simulate automated motor activity, we used chewing gum. To study attention, we used proofreading. We also tested short-term, long-term and working memory. 66 people at the age from 17 to 24 took part in the research. Conclusions. The conclusion is that automatic motor activity leads to considerable increase of attention and memory. This is expressed in the significant increase in the values of just about all the studied parameters, the change in the structure and strength of correlation relationships, and also (according to the cluster analysis) in the restructuring of the hierarchy of the information processing. The possible mechanisms of the phenomena under observation are discussed.

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Analisis pengaruh informasi laba terhadap perilaku investor di pasar sekunder

Jurnal Akuntansi ◽

10.24912/ja.v22i1.327 ◽

2018 ◽

Vol 22 (1) ◽

Author(s):

Farichah Farichah

Keyword(s):

Stock Returns ◽

Initial Public Offering ◽

Trading Volume ◽

Stock Exchange ◽

Investment Decision ◽

Secondary Market ◽

Short Term ◽

Stock Trading ◽

Earnings Information

After going through initial public offering process, the company must trade its shares in the secondary market. Companies should conduct signaling to users, such as investors and potential investors by providing information that can be utilized as a basis for investment decision making. The information announced (which includes earnings information) is expected to have a quality that allows investors and potential investors to predict company performance in the future. This study was conducting to investigate investors behaviour by observing trading volume, stock returns and earnings response coeffesient (ERC) in the short and long term. This study uses data and samples from the Indonesia Stock Exchange from 2006 to 2015. Hypothesis testing is done by using multiple linear regression and independent sample t test. The result showed that earnings information give effect to trading volume, stock returns, and ERC in short term (one year after IPO) and long term (for 5 years or more after IPO). The next result in the short term the stock trading volume, stock returns, and ERC is greater when compared with the volume of stock trading, stock returns, and ERC in the long term.

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The Thought Worlds of Marketing and Sales: Which Differences Make a Difference?

Journal of Marketing ◽

10.1509/jmkg.71.3.124 ◽

2007 ◽

Vol 71 (3) ◽

pp. 124-142 ◽

Cited By ~ 209

Author(s):

Christian Homburg ◽

Ove Jensen

Keyword(s):

Interpersonal Skills ◽

Market Performance ◽

The Other ◽

Product Knowledge ◽

Business Unit ◽

Short Term ◽

Negative Effect ◽

Thought Worlds

The literature is divided on whether differences between the thought worlds of marketing and sales are deleterious or beneficial. This article empirically investigates various facets of thought-world differences and their effects on various outcomes. It confirms that, in general, differences hamper the cooperation between marketing and sales, which leads to a lower market performance of the business unit. However, some facets of thought-world differences enhance the market performance of the business unit through a direct effect that outweighs the negative effect mediated by the quality of cooperation between marketing and sales. Market performance is enhanced if one side plays the customers' advocate while the other plays the products' advocate. Market performance is also enhanced if one side plays the advocate of short-term considerations while the other plays the advocate of long-term considerations. In contrast, differences between marketing and sales in regard to product knowledge and interpersonal skills are deleterious to market performance. Thus, the kind of difference makes a difference.

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Market States and Momentum: Evidence from the Dhaka Stock Exchange

Review of Pacific Basin Financial Markets and Policies ◽

10.1142/s0219091517500114 ◽

2017 ◽

Vol 20 (02) ◽

pp. 1750011 ◽

Cited By ~ 1

Author(s):

Mostafa Saidur Rahim Khan

Keyword(s):

Stock Returns ◽

Stock Exchange ◽

Market Performance ◽

Regression Coefficients ◽

Nonlinear Relationship ◽

Momentum Effect ◽

Short Term ◽

Momentum Profits

This study examines the momentum effect in the Dhaka Stock Exchange (DSE) listed stock returns on the basis of market states. Momentum profits are found to be significantly positive in UP market states but insignificant in DOWN market states. Momentum profits evident in UP market states are also found to revert in the long term. The evidence of short term momentum and long term reversal hold true even after adjusting for risks. In addition to short-term momentum and long-term reversal, regression coefficients also provide evidence for a positive but nonlinear relationship between momentum profits and market states. Maximum momentum profits are found at the median market performance not at the peak. Findings of this study suggest that investors’ overreaction causes momentum profits in the DSE.

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Crossing the agent technology chasm: Lessons, experiences and challenges in commercial applications of agents

The Knowledge Engineering Review ◽

10.1017/s0269888906001020 ◽

2006 ◽

Vol 21 (4) ◽

pp. 345-392 ◽

Cited By ~ 29

Author(s):

STEVE MUNROE ◽

TIM MILLER ◽

ROXANA A. BELECHEANU ◽

MICHAL PĚCHOUČEK ◽

PETER MCBURNEY ◽

...

Keyword(s):

Decision Making ◽

Early Stage ◽

Agent Technology ◽

Market Development ◽

Costs And Benefits ◽

Short Term ◽

Agent Systems ◽

Key Issues ◽

Commercial Applications

Agent software technologies are currently still in an early stage of market development, where, arguably, the majority of users adopting the technology are visionaries who have recognized the long-term potential of agent systems. Some current adopters also see short-term net commercial benefits from the technology, and more potential users will need to perceive such benefits if agent technologies are to become widely used. One way to assist potential adopters to assess the costs and benefits of agent technologies is through the sharing of actual deployment histories of these technologies. Working in collaboration with several companies and organizations in Europe and North America, we have studied deployed applications of agent technologies, and we present these case studies in detail in this paper. We also review the lessons learnt, and the key issues arising from the deployments, to guide decision-making in research, in development and in implementation of agent software technologies.

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The airification of cities. Making sense of the impact of peer to peer short term letting on urban functions and economy

10.31235/osf.io/vs8w3 ◽

2019 ◽

Author(s):

Stefano Picascia ◽

Antonello Romano ◽

Michela Teobaldi

Keyword(s):

Spatial Patterns ◽

Supply And Demand ◽

Sharing Economy ◽

Peer To Peer ◽

Economic Advantage ◽

Short Term ◽

Making Sense ◽

The Impact ◽

The Way

An in-depth look into the mechanics of short term rentals in Italy. The study is based on a vast dataset comprising of all the properties listed on the Airbnb website in 10 major cities in the years 2015, 2016 and 2017. We discuss the spatial patterns of Airbnb supply and demand within and between cities, we then hypothesize on the possible drivers of the Airbnb offer and suggest a possible way to assess whether Airbnb supply could be driven by an economic advantage of short-term over long term letting. We also discuss the way the benefits of this particular incarnation of the sharing economy are shared among participants. Finally, we conclude by presenting a possible alternative way of regulating Airbnb.

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Taxes, Debts, and Institutions

10.23943/princeton/9780691151496.003.0004 ◽

2017 ◽

Author(s):

Mauricio Drelichman ◽

Hans-Joachim Voth

Keyword(s):

Secondary Market ◽

Financial Instruments ◽

Short Term ◽

Fiscal Institutions

This chapter describes the fiscal institutions and borrowing instruments available to the Crown. The Castilian portfolio of fiscal and financial instruments was remarkably complete for its time. The revenue technology was a mix of useful adaptations of medieval legacy taxes combined with newer excises and trade duties. On the financing side, the Crown had both long- and short-term debt instruments at its disposal. Although the long-term juros (annuities and perpetuities) were technically nominative, they were widely traded in the secondary market, supplying a key element for the correct pricing of debt. On the short-term front, asientos—which refer to a wide variety of agreements—allowed the Crown to smooth the volatile silver revenues, leverage income outside the purview of the Cortes—Castile's representative assembly—and quickly shift resources throughout the empire.

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Long-term course of severe depression: late remission and recurrence may be found in a follow-up after 38-53 years

Mental Illness ◽

10.4081/mi.2012.e17 ◽

2012 ◽

Vol 4 (2) ◽

pp. 84-90 ◽

Cited By ~ 5

Author(s):

Lisa Crona ◽

Louise Brådvik

Keyword(s):

Cluster Analysis ◽

Telephone Interview ◽

Severe Depression ◽

Late Recurrence ◽

University Hospital ◽

Short Term ◽

Chronic Course ◽

Course Of Depression

This study is a follow-up of inpatients diagnosed with severe depression/melancholia between 1956 and 1969. During this period, all inpatients at the Department of Psychiatry, University Hospital, Lund, were rated on a multidimensional diagnostic schedule on discharge. There were 471 patients born from 1920 onward. In the present follow-up, 2006 to 2010, 169 survivors could be traced. They were asked to participate in the study involving a telephone interview, in which a structured life chart was used. Of the patients contacted, 16 were ill or confused and 3 did not remember ever being depressed, leaving 150 who could participate. Seventy-five of these agreed to participate in the study. Long-term course of depression was evaluated by cluster analysis and compared to background variables, such as heredity for depression, perceived parental rearing behaviour, and treatment of index depressive episode. Using a cluster analysis the patients could be separated into six clusters describing the course: i) single or few episodes followed by long-lasting remission; ii) single or few episodes followed by long-lasting remission, although shorter; iii) single or few episodes followed by late recurrence; iv) single or few episodes, but more frequently ill, followed by late recurrence; v) several episodes followed by lasting remission; vi) chronic course of episodes. Remission or recurrence could therefore occur even after more than a decade. In summary, there was a short-term course with or without recurrence or a chronic course with or without late remission. Heredity for depression was significantly related to a chronic course with or without late remission.

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Automatic P2P Energy Trading Model Based on Reinforcement Learning Using Long Short-Term Delayed Reward

Energies ◽

10.3390/en13205359 ◽

2020 ◽

Vol 13 (20) ◽

pp. 5359

Author(s):

Jin-Gyeom Kim ◽

Bowon Lee

Keyword(s):

Storage System ◽

Electric Energy ◽

Energy Storage System ◽

Peer To Peer ◽

Short Term ◽

Stock Trading ◽

Energy Trading ◽

Delayed Reward ◽

Trading Model

Automatic peer-to-peer energy trading can be defined as a Markov decision process and designed using deep reinforcement learning. We consider prosumer as an entity that consumes and produces electric energy with an energy storage system, and define the prosumer’s objective as maximizing the profit through participation in peer-to-peer energy trading, similar to that of the agents in stock trading. In this paper, we propose an automatic peer-to-peer energy trading model by adopting a deep Q-network-based automatic trading algorithm originally designed for stock trading. Unlike in stock trading, the assets held by a prosumer may change owing to factors such as the consumption and generation of energy by the prosumer in addition to the changes from trading activities. Therefore, we propose a new trading evaluation criterion that considers these factors by defining profit as the sum of the gains from four components: electricity bill, trading, electric energy stored in the energy storage system, and virtual loss. For the proposed automatic peer-to-peer energy trading algorithm, we adopt a long-term delayed reward method that evaluates the delayed reward that occurs once per month by generating the termination point of an episode at each month and propose a long short-term delayed reward method that compensates for the issue with the long-term delayed reward method having only a single evaluation per month. This long short-term delayed reward method enables effective learning of the monthly long-term trading patterns and the short-term trading patterns at the same time, leading to a better trading strategy. The experimental results showed that the long short-term delayed reward method-based energy trading model achieves higher profits every month both in the progressive and fixed rate systems throughout the year and that prosumer participating in the trading not only earns profits every month but also reduces loss from over-generation of electric energy in the case of South Korea. Further experiments with various progressive rate systems of Japan, Taiwan, and the United States as well as in different prosumer environments indicate the general applicability of the proposed method.

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