Browsing by Author "Aaltonen, Aleksi"
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- Cryptocurrencies’ Internal and External Relations: a Descriptive Analysis of Cryptocurrency Dynamics and Relations to the US Equity Market
School of Business | Bachelor's thesis(2017) Aaltonen, AleksiThis thesis is a descriptive statistical analysis of cryptocurrency market and its relation within cryptocurrencies and across asset classes, using correlation functions, orthogonalized impulse response functions and OLS regressions. Consistent with Wang (2014), bitcoin does not suffer from a liquidity trap, even though bitcoin is a decentralized system. This thesis concludes that bitcoin has a lead effect on only 2 out of 8 of the top cryptocurrencies, endowing diversification benefits within cryptocurrency market. This paper provides evidence on cryptocurrency market’s and US equity market’s impulse response dynamics which are insignificant, consistent with Gangwal’s (2016) results that adding cryptocurrencies to a diversified portfolio will yield to a higher Sharpe ratio. Lastly, the study reports bitcoin momentum factor having an impact on banking and financial industries’ excess returns. - Mutual relationships and value drivers of cryptocurrencies
School of Business | Master's thesis(2022) Aaltonen, Aleksi; Hakkarainen, Elina - Mutual relationships and value drivers of cryptocurrencies
School of Business | Master's thesis(2022) Hakkarainen, Elina; Aaltonen, Aleksi - What makes data possible? A sociotechnical view on structured data innovations
A4 Artikkeli konferenssijulkaisussa(2021) Aaltonen, Aleksi; Penttinen, EskoDrawing from the theory of digital objects, this paper examines the distinction between structured and unstructured data as carriers of facts. We argue that data do not 'have' a structure but are made by a structure that confers data their capacity to represent contextual facts. We employ a case vignette involving XBRL (eXtensible Business Reporting Language) and its use in statutory financial reporting to illustrate and explore the sociotechnical nature of data and to describe what we call data innovations: new valuable ways to render phenomena as data. We find that data structure is best viewed as a matter that is relative to a purpose in a context. Theorizing data from a sociotechnical perspective could evolve to provide, in effect, the material science of digital economy.