2 research outputs found
BTC price volatility: Fundamentals versus information
This paper offers a plausible response to “what explains the sporadic volatility in the price of Bitcoin?” We hypothesized that market “fundamentals” and “information demands” are key drivers of Bitcoin’s unpredictable price fluctuation. We adopt the transfer-function [Autoregressive Distributed Lag, ARDL] model and its Bounds testing approach to verify how the volatility of the price of Bitcoin responds to its transaction volume, cryptocurrency market capitalisation, world market equity index and Google search. We found the existence of long-run cointegration relation and observed that all the variables except the equity index positively explain the volatility of Bitcoin price. The result established evidence that market fundamentals drive erratic swing in Bitcoin price than information. Keywords: Bitcoin price volatility Bitcoin market fundamentals information demand ARD
Signalling Behaviour and Bank Provisioning Policies in Nigeria: The Conditional Effect of the IFRS Adoption and Solvency Risk
Purpose of the article: Based on the propositions of the signalling hypothesis and prospect theory, this study examined the extent of attempt by Nigerian deposit money banks (DMBs) to solve the issue of adverse selection via signalling their financial prospects using loan loss provisions (LLPs). The empirical test was subject to the DMBs’ riskiness and changes in the accounting rule given failure of a number DMBs and the adoption of the International Financial Reporting Standards (IFRSs) respectively in Nigeria in the recent past. Methodology: Bank-level unbalanced panel datasets of a sample 16 DMBs, which are related to the variables of the study, were hand-extracted from their annual reports and account between 2007 and 2017. The analysis was conducted using the Prais-Winsten regression correlated with panel corrected standard errors (PCSE-PW) owing to the presence of heteroscedastic and autocorrelated residuals in the study’s regression models. Scientific aim: The study examined the relationship between LLPs and one-year-ahead changes in earnings before taxes and LLPs to establish whether Nigerian DMBs signal their financial strength via LLPs. Findings: The study largely found that Nigerian DMBs, regardless of accounting regime and risk of insolvency, do not use LLPs to signal their financial strength. However, where the evidence of signalling via LLPs was evident the coefficient of earnings signalling was insignificant, where it was significant signalling was achievable via discretionary LLPs (DLLP) rather than actual LLPs (TLLP) suggesting manipulative provisioning in the use of LLPs to signal. Conclusions: The study’s findings included empirical communication alerts to the regulators and Nigerian DMBs on the need for improvement in earnings signalling, as the present scenario may be interpreted as a sign of a non-going concern by analytical stakeholders. Limits of research: The generalisation of the study’s findings may be limited by the focus on one regime (IAS 39) of IFRS loan loss reporting but mitigated by the partial implementation of the second regime (IFRS 9) for the first four years in the country