Data - Raw & Transformed - Cryptocurrencies & Macro-Financial Indices

The empirical investigation of the connection between cryptocurrencies and macro-financial indices is accomplished by employing the US Dollar-dominated price time series of bitcoin, bitcoincash and monero types of cryptocurrencies; along with the following macro-financial indices, USA short-term interest rate, USA bank prime lending rate, USA tedrate and USA medium-term interest rate. Notably, considering the fact that all the available digital currencies are usually priced in US Dollar, this study considers it appropriate to use the US macro-financial variables for uniformity and simplicity. Principally, the objective of this study is to investigate the possible short-run impact of macro-financial indices on cryptocurrencies in the study sample, thereby, ascertaining if the performance of cryptocurrencies can be predicted from the trend of macro-financial variables. The choice of the macro-financial variables in this study is underpinned by the economic influence of those variables in the financial markets. The data for USA short-term interest rate, USA bank prime lending rate and tedrate is sourced from the Federal Reserve, and the Federal Reserve Statistical Release website. Additionally, the daily prices for the cryptocurrencies: bitcoin, monero and bitcoincash are sourced from an online investing company. All the daily data series in the sample covers the period 1st January 2015 through 1st October 2019. The price series for all variables in the sample are converted into continuously compounded percentage exchange rate return calculated thus, r_t=(p_t⁄p_(t-1) ), where r_t is the continuously compounded return at time t, p_t is the price at time t and p_(t-1) is the price at time t-1 (i.e. t minus one) period.本研究通过采用以美元计价的比特币（Bitcoin）、比特币现金（Bitcoincash）与门罗币（Monero）加密货币价格时间序列，以及美国短期利率、美国银行最优惠贷款利率、美国泰德价差（TED rate）和美国中期利率等宏观金融指标，开展加密货币与宏观金融指标间关联的实证探究。值得注意的是，鉴于当前所有主流数字货币通常均以美元定价，本研究为保证统一性与简洁性，选用美国宏观金融变量开展分析。本研究的核心目标为探究样本范围内宏观金融指标对加密货币的潜在短期影响，以此判断能否通过宏观金融变量的走势预测加密货币的表现。本研究选取上述宏观金融变量的依据在于其对金融市场的经济影响力。其中，美国短期利率、美国银行最优惠贷款利率与泰德价差的数据取自美联储（Federal Reserve）及其官方统计发布网站。此外，比特币、门罗币与比特币现金的每日价格数据来源于某在线投资平台。样本内所有日度数据的时间跨度均为2015年1月1日至2019年10月1日。 本研究将样本内所有变量的价格序列转换为连续复利百分比汇率收益率，计算公式为：$r_t = frac{p_t}{p_{t-1}}$，其中$r_t$为时刻$t$的连续复利收益率，$p_t$为$t$时刻的价格，$p_{t-1}$为$t-1$时刻的价格（即前一期价格）。