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Extreme value theory (EVT) is useful for modeling the impact of crashes or situations of extreme stress on investor portfolios. EVT is mostly utilized in financial modeling, risk management, insurance, and hydrology. The price of gold fluctuates considerably over time, and this introduces a risk on its own. The goal of this study is to analyze the risk of gold investment by applying the EVT to historical daily data for extreme daily losses and gains in the price of gold. We used daily gold prices in the Pakistan Bullion Market from August 1, 2011 to July 30, 2021. This paper covers two methods such as Block Maxima (BM) and Peak Over Threshold (POT) modeling. The risk measures which are adopted in this paper are Value at Risk (VaR) and Expected Shortfall (ES). The point and interval estimates of VaR and ES are obtained by fitting the Generalized Pareto (GPA) distribution. Moreover, in this paper, return-level forecasting is also included for the next 5 and 10 years by analyzing the Generalized Extreme Value (GEV) distribution. [ABSTRACT FROM AUTHOR]

The extreme value theory (EVT) has been used to model and measure the distribution of extreme minima of Byco Petroleum in the Pakistan stock market over the period from 2005 to 2012. This paper covers the investigation of distributions that are mostly used in finance including the generalized extreme value (GEV), generalized logistics (GL), and generalized Pareto (GPA) distribution. L-moment ratio diagram is being used to find the appropriate distributions among the distributions. L-moment diagram depicts that GEV and GL distributions are suitable to represent the extremes of Byco Petroleum Pakistan Limited. Thereafter, the probability weighted moment (PWM) method has been used in order to estimate the parameters of probability distributions. Furthermore, Anderson–Darling (AD) goodness-of-fit test is employed to test the goodness of fit among GEV and GL distributions, and it is clear from the results that the GL distribution is more reliable and applicable for extreme minima of Byco Petroleum Company in the Pakistan stock exchange market. EVT and traditional methods are used for value-at-risk (VaR) analysis. The analysis indicates that EVT methods are more suitable for risk measurement in comparison with traditional methods. [ABSTRACT FROM AUTHOR]

Ensuring international transport corridors' safety is essential for countries along the routes. For the sustainable development of international transport channels, this paper discusses how to evaluate the operational risks and how to alleviate the adverse effects caused by emergencies. First, an indicator system of international transport corridors' operational risks was constructed, which consists of 30 indicators from five dimensions of politics, economy, society, safety, and technology. Secondly, a comprehensive scoring approach combined with a network analysis method was applied to examine the effects caused by operational hazards. On this basis, the quantitative method and rigorous statistical analysis were used to evaluate the China-Pakistan-Iran-Turkey International Transport Corridor in the south line of the Silk Road Economic Belt, whose operational risks from 2010 to 2019 were analyzed. Finally, the operational risk index was discussed in detail. Results demonstrate the following. (1) During the China-Pakistan-Iran-Turkey International Transport Corridor, the Pakistan section has the highest operational risk index, and the next culprit is Turkey, followed by Iran. The Chinese section has the lowest operational risk index. (2) Pakistan has been trapped in severe political risks and security risks in recent years. Turkey suffers from severe security risks due to the Kurdish problem. Iran ranks first in terms of economic risk and social risk. Special attention should be paid to the natural risks for China. (3) Pakistan's operational risks will exhibit consistently high in the future, while China appears downwards in long-term trend. The operational risk index in Iran is on the rise. Turkey shows a flattening of and then a slight decline in the foreseeable future. [ABSTRACT FROM AUTHOR]