Risk estimation or volatility estimation at financial markets, particularly stock exchange markets, is complex issue of … pricing of stocks and better risk management. The aim of this research is to test applicability of simple models like Simple … Moving Average (SMA) and Exponentially Weighted Moving Average (EWMA) to estimate risk. The performance of SMA and EWMA with …

loss risk. This study uses geometric Brownian motion (GBM) and Value at Risk (VaR; with the Monte Carlo Simulation approach …) on the daily closing price of JKII from 1 August 2020-13 August 2021 to predict the price and loss risk of JKII at 16 … 2.03%. Then, using VaR with a Monte Carlo Simulation approach, the loss risk prediction for 16 August 2021 (one …

mandatory hedging requirements and for projects located in higher political risk jurisdictions. Results are robust to …

This is the first study to investigate the profitability of Barroso and Santa-Clara's (2015) risk-managing approach for … George and Hwang's (2004) 52-week high momentum strategy in an industrial portfolio setting. The findings indicate that risk …-managing adds value as the Sharpe ratio increases, and the downside risk decreases notably. Even after controlling for the spread of …

–making that requires a trade-off between expected return and risk, as well as for applications in asset pricing and risk …–regime and Markov-switching GARCH (MSGARCH) models, from a risk management perspective. I find that, for daily, weekly, and ten …-day equity log-returns, MSGARCH models yield more accurate Value-at-Risk, Expected Shortfall, and left–tail distribution …