Relationship between portfolio diversification and value at risk: Empirical evidence

2011 ◽  
Vol 12 (4) ◽  
pp. 443-459 ◽  
Author(s):  
Khurshid M. Kiani
Author(s):  
Mahdi Pourrafiee ◽  
AmirHossein Nafei ◽  
Shokoufe Banihashemi ◽  
S. Pourmohammad Azizi

2019 ◽  
Vol 12 (1) ◽  
pp. 79-88
Author(s):  
T. Bazhenov ◽  
D. Fantazzini

This work proposes to forecast the Realized Volatility (RV) and the Value-at-Risk (VaR) of the most liquid Russian stocks using GARCH, ARFIMA and HAR models, including both the implied volatility computed from options prices and Google Trends data. The in-sample analysis showed that only the implied volatility had a significant effect on the realized volatility across most stocks and estimated models, whereas Google Trends did not have any significant effect. The outof-sample analysis highlighted that models including the implied volatility improved their forecasting performances, whereas models including internet search activity worsened their performances in several cases. Moreover, simple HAR and ARFIMA models without additional regressors often reported the best forecasts for the daily realized volatility and for the daily Value-at-Risk at the 1 % probability level, thus showing that efficiency gains more than compensate any possible model misspecifications and parameters biases. Our empirical evidence shows that, in the case of Russian stocks, Google Trends does not capture any additional information already included in the implied volatility.


Risks ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 112 ◽  
Author(s):  
Ngoc Phu Tran ◽  
Thang Cong Nguyen ◽  
Duc Hong Vo ◽  
Michael McAleer

The purpose of this paper is to evaluate and estimate market risk for the ten major industries in Vietnam. The focus of the empirical analysis is on the energy sector, which has been designated as one of the four key industries, together with services, food, and telecommunications, targeted for economic development by the Vietnam Government through to 2020. The oil and gas industry is a separate energy-related major industry, and it is evaluated separately from energy. The data set is from 2009 to 2017, which is decomposed into two distinct sub-periods after the Global Financial Crisis (GFC), namely the immediate post-GFC (2009–2011) period and the normal (2012–2017) period, in order to identify the behavior of market risk for Vietnam’s major industries. For the stock market in Vietnam, the website used in this paper provided complete and detailed data for each stock, as classified by industry. Two widely used approaches to measure and analyze risk are used in the empirical analysis, namely Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR). The empirical findings indicate that Energy and Pharmaceuticals are the least risky industries, whereas oil and gas and securities have the greatest risk. In general, there is strong empirical evidence that the four key industries display relatively low risk. For public policy, the Vietnam Government’s proactive emphasis on the targeted industries, including energy, to achieve sustainable economic growth and national economic development, seems to be working effectively. This paper presents striking empirical evidence that Vietnam’s industries have substantially improved their economic performance over the full sample, moving from relatively higher levels of market risk in the immediate post-GFC period to a lower risk environment in a normal period several years after the end of the calamitous GFC.


2017 ◽  
Vol 30 (1) ◽  
pp. 477-498 ◽  
Author(s):  
Julija Cerović Smolović ◽  
Milena Lipovina-Božović ◽  
Saša Vujošević

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