Data on daily Log returns of the NIFTY 50 index in the National Stock Exchange India

Abstract: India is one of the major emerging markets. We report daily log return percentages of the NIFTY 50 index in the National Stock Exchange in India, from the index base date of 3rd November 1995 to 31st March 2018. The NIFTY 50 index is a diversified fifty stock index accounting for twelve sectors of the Indian economy. It is used for a variety of purposes such as bench-marking fund portfolios, index based derivatives and index funds. The daily log returns of an index are the natural logarithms of the ratios of the closing values of the index on consecutive trading days over a certain period of time. The daily log return percentages are simply the log return values multiplied by hundred. The log return data are widely used in empirical finance to assess risk and return on investments, for estimation market risk, back testing of market risk measurement procedures, for modelling volatility and testing efficiency of financial markets. Data Format: The data are reported in twenty three csv spreadsheet files. The first csv file contains log return percentage data from 3rd November 1995 to 31st March 1996 from. The remaining twenty two csv files contain log return percentages from 1st April 1996 to 31st March 2018. Each of the csv files contains date, closing value and log return percentages of the NIFTY 50 during a financial year. The name of the csv file indicates the financial year. Value of the data • To assess risk and return on investments in the Indian equity market. • To estimate and forecast market risk in terms of Value at Risk, Expected Shortfall, Median Shortfall of the NIFTY50 index. • Modelling volatility using GARCH type models. • Testing efficiency of the Indian equity market. • Benchmarking the performance of a portfolio with the NIFTY 50 index. • Estimating the chance of extreme daily returns of the NIFTY 50 index. Some observed empirical properties of the NIFTY 50 log return data. 1. Absence of autocorrelations: (linear) autocorrelations of the daily log returns seem to be insignificant beyond a time lag of one day. i.e. the linear correlation between log returns of the t th and t+h th trading days seems insignificant, for h exceeding 1. 2. Slow decay of autocorrelation in absolute returns: the autocorrelation function of the absolute values of the daily log returns remain positive for time lag upto 30 days. This suggests non linear dependence among the NIFTY 50 daily log return values. 3. The data is Leptokurtic, with extreme daily log returns (exceeding 5 percent in absolute value) present 4. Heavy tails: the (unconditional) distribution of returns seems to display a power-law or Pareto-like tail, with a tail index which is finite, higher than two. However the precise form of the tails is difficult to determine.摘要：印度是全球主要新兴市场之一。本数据集收录印度国家证券交易所NIFTY 50指数（NIFTY 50）的每日对数收益率百分比数据，时间跨度为该指数基准日1995年11月3日至2018年3月31日。NIFTY 50指数为覆盖印度经济12个行业的多元化50只股票指数，可用于基金组合业绩基准比对、指数类衍生品及指数基金等多种场景。指数的每日对数收益率，指某一时间段内连续交易日指数收盘价比值的自然对数；每日对数收益率百分比则是将对数收益率数值乘以100所得的结果。此类对数收益率数据在实证金融领域应用广泛，可用于评估投资风险与收益、估算市场风险、回溯检验市场风险计量方法、构建波动率模型以及检验金融市场有效性等。 数据格式：本数据集包含23个CSV电子表格文件。首个CSV文件收录1995年11月3日至1996年3月31日的对数收益率百分比数据；剩余22个CSV文件覆盖1996年4月1日至2018年3月31日的相关数据。每个CSV文件均包含对应财年内NIFTY 50指数的日期、收盘价及对数收益率百分比，文件名可指示其所对应的财年。 数据集应用价值： 1. 评估印度股票市场的投资风险与收益 2. 基于NIFTY 50指数，以风险价值（Value at Risk, VaR）、预期缺口（Expected Shortfall）、中位数缺口（Median Shortfall）为指标估算并预测市场风险 3. 采用广义自回归条件异方差（GARCH）类模型构建波动率模型 4. 检验印度股票市场的有效性 5. 以NIFTY 50指数为基准比对投资组合的业绩表现 6. 估算NIFTY 50指数出现极端单日收益率的概率 NIFTY 50指数对数收益率数据的部分观测经验特性： 1. 无自相关性：单日对数收益率的（线性）自相关性在滞后超过1个交易日时均不显著，即第t交易日与第t+h交易日的对数收益率之间的线性相关性在h>1时可视为无统计学意义。 2. 绝对收益率自相关衰减缓慢：单日对数收益率绝对值的自相关函数在滞后至多30个交易日时仍保持正值，这表明NIFTY 50指数的每日对数收益率之间存在非线性依赖关系。 3. 尖峰厚尾特性：数据集存在绝对值超过5%的极端单日对数收益率。 4. 厚尾分布特征：收益率的（无条件）分布呈现类幂律或类帕累托分布的尾部形态，其尾部指数有限且大于2，但具体的尾部分布形式仍难以精准确定。