Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from many limitations. HF data feature microstructure problem,...

Non-performing assets are the key factors to decide the financial health of Indian commercial banks. They affect the operational efficiency, which in turn influences the liquidity, efficiency, solvency and profitability position of the banks. The study investigates the relationships between the...

Pre-averaging is a popular strategy for mitigating microstructure in high frequency financial data. As the term suggests, transaction or quote data are averaged over short time periods ranging from 30 seconds to five minutes, and the resulting averages approximate the efficient price process...

We propose serial correlation-robust asymptotic confidence bands for the receiver operating characteristic (ROC) curve and its functional, viz. the area under ROC curve (AUC), estimated by quasi-maximum likelihood in the binormal model. Our simulation experiments confirm that this new method...

The economic development of country depends on the effective banking system. In recent years, there have been considerable pressures on the profitability of banks. The study investigates the long run equilibrium relationship between the return on assets (ROA) and nine variables over the period...

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from many limitations. HF data feature microstructure problem,...

Governments in most developing nations heavily rely on tax revenue to sponsor government expenditure, and Zimbabwe is not an exception. Tax revenue is supposed to be used to grow or develop an economy. This study seeks to analyse the relationship between value-added tax (VAT) and total tax...

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many limitations. HF data feature microstructure problem,...

High frequency financial data allows us to learn more about volatility, volatility of volatility and jumps. One of the key techniques developed in the literature in recent years has been bipower variation and its multipower extension, which estimates time-varying volatility robustly to jumps. We...

Deriving estimators from historical data is common practice in applied quantitative finance. The availability of ever larger data sets and easier access to statistical algorithms has also led to an increased usage of historical estimators. In this research note, we illustrate how to assess the...