Financial Innovation
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Published By Springer (Biomed Central Ltd.)

2199-4730

2022 ◽  
Vol 8 (1) ◽  
Author(s):  
José Campino ◽  
Ana Brochado ◽  
Álvaro Rosa

AbstractRecent literature has addressed initial coin offering (ICO) projects, which are an innovative form of venture financing through cryptocurrencies using blockchain technology. Many features of ICOs remain unexplored, leaving much room for additional research, including the success factors of ICO projects. We investigate the success of ICO projects, with our main purpose being to identify factors that influence a project’s outcome. Following a literature review, from which several potential variables were collected, we used a database comprising 428 ICO projects in the banking/financial sector to regress several econometric models. We confirmed the impacts of several variables and obtained particularly valuable results concerning project and campaign variables. We confirmed the importance of a well-structured and informative whitepaper. The proximity to certain markets with high availability of financial and human capital is also an important determinant of the success of an ICO. We also confirm the strong dependency on cryptocurrency and the impact of cryptocurrency valuations on the success of a project. Furthermore, we confirm the importance of social media in ICO projects, as well as the importance of human capital characteristics. Our research contributes to the ICO literature by capturing most of the success factors previously identified and testing their impacts based on a large database. The current research contributes to the building of systems theory and signaling theory by adapting their frameworks to the ICO environment. Our results are also important for regulators, as ICOs are mainly unregulated and have vast future potential, and for investors, who can benefit from our analysis and use it in their due diligence.


2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Chandranath Amarasekara ◽  
Bernard Njindan Iyke ◽  
Paresh Kumar Narayan

AbstractIn this paper, we assess the role of investment in research and development (R&D) and economic policy uncertainty (EPU) in Sri Lanka’s economic growth experience. We do this by first determining which endogenous growth theories best explain the evolution of total factor productivity (TFP) in the country. Using historical time series data (1980–2018), we find that semi-endogenous growth theories best explain the evolution of TFP in Sri Lanka. This evidence suggests that R&D is critical to the country’s TFP expansion. We find that, through R&D, EPU has a crucial detrimental impact on TFP growth, although it is short-lived. Our findings are robust and have important implications for R&D investment and for moderating EPU.


2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Ikhlaas Gurrib ◽  
Mohammad Nourani ◽  
Rajesh Kumar Bhaskaran

AbstractThis paper investigates the role of Fibonacci retracements levels, a popular technical analysis indicator, in predicting stock prices of leading U.S. energy companies and energy cryptocurrencies. The study methodology focuses on applying Fibonacci retracements as a system compared with the buy-and-hold strategy. Daily crypto and stock prices were obtained from the Standard & Poor's composite 1500 energy index and CoinMarketCap between November 2017 and January 2020. This study also examined if the combined Fibonacci retracements and the price crossover strategy result in a higher return per unit of risk. Our findings revealed that Fibonacci retracement captures energy stock price changes better than cryptos. Furthermore, most price violations were frequent during price falls compared to price increases, supporting that the Fibonacci instrument does not capture price movements during up and downtrends, respectively. Also, fewer consecutive retracement breaks were observed when the price violations were examined 3 days before the current break. Furthermore, the Fibonacci-based strategy resulted in higher returns relative to the naïve buy-and-hold model. Finally, complementing Fibonacci with the price cross strategy did not improve the results and led to fewer or no trades for some constituents. This study’s overall findings elucidate that, despite significant drops in oil prices, speculators (traders) can implement profitable strategies when using technical analysis indicators, like the Fibonacci retracement tool, with or without price crossover rules.


2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Luis Lorenzo ◽  
Javier Arroyo

AbstractSince the emergence of Bitcoin, cryptocurrencies have grown significantly, not only in terms of capitalization but also in number. Consequently, the cryptocurrency market can be a conducive arena for investors, as it offers many opportunities. However, it is difficult to understand. This study aims to describe, summarize, and segment the main trends of the entire cryptocurrency market in 2018, using data analysis tools. Accordingly, we propose a new clustering-based methodology that provides complementary views of the financial behavior of cryptocurrencies, and one that looks for associations between the clustering results, and other factors that are not involved in clustering. Particularly, the methodology involves applying three different partitional clustering algorithms, where each of them use a different representation for cryptocurrencies, namely, yearly mean, and standard deviation of the returns, distribution of returns that have not been applied to financial markets previously, and the time series of returns. Because each representation provides a different outlook of the market, we also examine the integration of the three clustering results, to obtain a fine-grained analysis of the main trends of the market. In conclusion, we analyze the association of the clustering results with other descriptive features of cryptocurrencies, including the age, technological attributes, and financial ratios derived from them. This will help to enhance the profiling of the clusters with additional descriptive insights, and to find associations with other variables. Consequently, this study describes the whole market based on graphical information, and a scalable methodology that can be reproduced by investors who want to understand the main trends in the market quickly, and those that look for cryptocurrencies with different financial performance.In our analysis of the 2018 and 2019 for extended period, we found that the market can be typically segmented in few clusters (five or less), and even considering the intersections, the 6 more populations account for 75% of the market. Regarding the associations between the clusters and descriptive features, we find associations between some clusters with volume, market capitalization, and some financial ratios, which could be explored in future research.


2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Benlu Hai ◽  
Ximing Yin ◽  
Jie Xiong ◽  
Jin Chen

AbstractInnovation scholars highlight the economic benefits to firms, while research findings on the relationship between innovation output and economic returns remain mixed. In this study, we develop the profiting from innovation (PFI) framework and address the crucial role of financial constraints in the relationship between innovation output and financial performance. We argue that the liability of newness differentiates firms’ financial performance during the commercialization of innovation, leading to a U-shaped relationship between firms’ innovation output and financial performance. We further document the moderating impact of individual financial constraints (IFC) and market-based financial constraints (MFC) on this curvilinear relationship. Empirical tests based on the 142,972 firm-year observations of the multi-source dataset of Chinese manufacturing firms from 1999–2009 support our hypotheses. The additional analysis shows that non-state-owned enterprises and small and medium enterprises benefit more from the synergistic effect of reductions of IFC and MFC than state-owned enterprises and large firms. Our study enriches the literature of the PFI framework by uncovering the mechanism between innovation output and economic returns where financial constraints play an essential role. To the best of our knowledge, we are among the first to investigate the processes and mechanisms between innovation output and financial performance, generating novel insights for business practitioners and policymakers.


2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Mudassar Hasan ◽  
Muhammad Abubakr Naeem ◽  
Muhammad Arif ◽  
Syed Jawad Hussain Shahzad ◽  
Xuan Vinh Vo

AbstractWe examine the dynamics of liquidity connectedness in the cryptocurrency market. We use the connectedness models of Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012) and Baruník and Křehlík (J Financ Econom 16(2):271–296, 2018) on a sample of six major cryptocurrencies, namely, Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Ripple (XRP), Monero (XMR), and Dash. Our static analysis reveals a moderate liquidity connectedness among our sample cryptocurrencies, whereas BTC and LTC play a significant role in connectedness magnitude. A distinct liquidity cluster is observed for BTC, LTC, and XRP, and ETH, XMR, and Dash also form another distinct liquidity cluster. The frequency domain analysis reveals that liquidity connectedness is more pronounced in the short-run time horizon than the medium- and long-run time horizons. In the short run, BTC, LTC, and XRP are the leading contributor to liquidity shocks, whereas, in the long run, ETH assumes this role. Compared with the medium term, a tight liquidity clustering is found in the short and long terms. The time-varying analysis indicates that liquidity connectedness in the cryptocurrency market increases over time, pointing to the possible effect of rising demand and higher acceptability for this unique asset. Furthermore, more pronounced liquidity connectedness patterns are observed over the short and long run, reinforcing that liquidity connectedness in the cryptocurrency market is a phenomenon dependent on the time–frequency connectedness.


2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Alfred Ma

AbstractMost technical trading strategies use the official closing price for analysis. But what is the effect when the official closing price is subject to market manipulation? This paper answers this question by testing the difference of profitabilities between using the official closing price and the last tick price. The results show a significant improvement of profitability by using the last tick price over the official closing price based on a data set in Hong Kong from 2011 to 2018.


2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Francisco Javier García-Corral ◽  
José Antonio Cordero-García ◽  
Jaime de Pablo-Valenciano ◽  
Juan Uribe-Toril

AbstractWith the development of new technologies, some concepts become relevant in the economic area, as is the case with cryptocurrencies, in general, or Bitcoin and Ethereum, in particular. Due to the impact of these tools, a detailed bibliometric study that allows us to obtain all information about cryptocurrencies must be conducted. This study will help scientific production by specifying the development and lines of related research that have been followed and are currently being followed. We have used Tableau, R (Bibliometrix R Package), and VOSviewer software to analyze the information. These have been combined to create and review unified metadata from the Web of Science (WoS) and Scopus databases. The bibliometric analysis shows 771 articles on the WoS database and 648 articles on Scopus published between 2010 and early 2019. They present the most relevant articles, research areas, countries, institutions, authors, journals, and trends during the last few years. In conclusion, the number of publications has grown in the last 3 years. The analysis shows the evolution of blockchain technology used in this type of cryptocurrency. The review of this period marks a possible end to the historical part of cryptocurrencies, thereby opening the current topic to its multiple applications.


2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Donglian Ma ◽  
Hisashi Tanizaki

AbstractIn this study, an investigation is conducted into the phenomenon of price clustering in Bitcoin (BTC) denominated in the Japanese yen (JPY). It answers two questions using tick-by-tick data. The first is whether price clustering exists in BTC/JPY transactions, and the other is how the scale of price clustering varies throughout a trading day. With the assistance of statistical measures, the last two digits of BTC price were discovered to cluster at the numbers that end with ’00’. In addition, the scales of BTC/JPY clustering at ’00’ tended to decline at the specific hour intervals. This study contributes to the emerging literature on price clustering and investor behavior.


2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Yanzhao Li ◽  
Ju-e Guo ◽  
Shaolong Sun ◽  
Yongwu Li

AbstractConsidering that the assumption of time consistency does not adequately reveal the mechanisms of exit decisions of venture capital (VC), this study proposes two kinds of time-inconsistent preferences (i.e., time-flow inconsistency and time-point inconsistency) to advance research in this field. Time-flow inconsistency is in line with the previous time inconsistency literature, while time-point inconsistency is rooted in the VC fund’s finite lifespan. Based on the assumption about the strategies guiding future behaviors, we consider four types of venture capitalists: time-consistent, time-point-inconsistent, naïve, and sophisticated venture capitalists, of which the latter three are time-inconsistent. We derive and compare the exit thresholds of these four types of venture capitalists. The main results include: (1) time-inconsistent preferences accelerate the exits of venture capitalists; (2) the closer the VC funds expiry dates are, the more likely time-inconsistent venture capitalists are to accelerate their exits; and (3) future selves caused by time-flow inconsistency weaken the effect of time-point inconsistency. Our study provides a behavioral explanation for the empirical fact of young VCs’ grandstanding.


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