The Application of Cash-Flow-at-Risk to Risk Management in a Deregulated Electricity Market

2009 ◽  
Vol 15 (2) ◽  
pp. 253-269 ◽  
Author(s):  
C. L. Anderson ◽  
Matt Davison
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Cash Flow ◽  
Electricity Market ◽  
Deregulated Electricity Market

scholarly journals How Much Cash Is At Risk In U.S. Non-Financial Firms? A VaR-Type Measurement

2015 ◽  
Vol 31 (4) ◽  
pp. 1579
Author(s):  
Frantz Maurer
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Cash Flow ◽  
Management Practices ◽  
Risk Measures ◽  
Risk Measure ◽  
Empirical Studies ◽  
Firm Level ◽  
Level Data ◽  
Corporate Risk

<p>Risk management techniques first developed by, and for, banks are now being adopted by non-financial corporations. However, while firms are already engaged in activities intended to develop their risk management practices, they often do not possess risk measures focused on key corporate financial results such as earnings or cash flow. The main contribution of this paper is to develop a cash flow-based risk measure conditional on specific company-level factors. With U.S. firm-level data, we present evidence that Cash Flow-at-Risk and Expected shortfall differ across main non-financial industries. Our results call for renewed attention to the role that VaR-type measures for cash flow can play in empirical studies dedicated to corporate risk analysis, and with respect to corporate-level risk management purposes.</p>

scholarly journals Risk Management Maturity Model for Logistic Processes

2021 ◽  
Vol 13 (2) ◽  
pp. 659
Author(s):  
Agnieszka A. Tubis ◽  
Sylwia Werbińska-Wojciechowska
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Development Strategy ◽  
Assessment Method ◽  
Assessment Process ◽  
Strategy Development ◽  
Maturity Model ◽  
Maturity Level ◽  
Two Stage ◽  
Risk Maturity

Recently, the maturity models for risk management are attracting growing attention. The obtained maturity level defines an assessment of an organization’s management competence. Therefore, as a set of various tools and practices, the maturity model is critical for a company’s overall risk maintenance strategy development and implementation. Thus, the purpose of this article is to present a model for risk management maturity for logistic processes. We investigated the main defined assessment areas for risk maturity model implementation in logistic systems. Based on research findings, we introduced a new risk maturity assessment area based on participation in the supply chain—cooperation at risk. The proposed model constitutes the base for a two-stage assessment method implementation, where the global maturity index is introduced. Finally, we implement the proposed two-stage assessment method to verify the proposed model’s diagnostic function and determine its labor intensity. The study confirmed that the five defined maturity areas (knowledge, risk assessment, process risk management, cooperation at risk, and risk monitoring) provide a complex diagnostic tool for risk maturity level identification and, based on the obtained results, allows to define an appropriate development strategy for a given decision-making environment.

Stochastic control for risk under deregulated electricity market — a case study using a new formulation

2005 ◽  
Vol 32 (4) ◽  
pp. 719-725 ◽  
Author(s):  
Joyce Li Zhang ◽  
K Ponnambalam
Keyword(s):  
Electricity Market ◽  
Explicit Method ◽  
State Variables ◽  
Risk Minimization ◽  
Solution Approach ◽  
Second Moments ◽  
Deregulated Electricity Market ◽  
New Formulation ◽  
Dual Dynamic Programming

This paper describes the implementation of a new solution approach — Fletcher-Ponnambalam model (FP) — for risk management in hydropower system under deregulated electricity market. The FP model is an explicit method developed for the first and second moments of the storage state distributions in terms of moments of the inflow distributions. This method provides statistical information on the nature of random behaviour of the system state variables without any discretization and hence suitable for multi-reservoir problems. Also avoiding a scenario-based optimization makes it computationally inexpensive, as there is little growth to the size of the original problem. In this paper, the price uncertainty was introduced into the FP model in addition to the inflow uncertainty. Lake Nipigon reservoir system is chosen as the case study and FP results are compared with the stochastic dual dynamic programming (SDDP). Our studies indicate that the method could achieve optimum operations, considering risk minimization as one of the objectives in optimization.Key words: reservoir operations, explicit method, uncertainty, stochastic programming, risk.

Volatility Forecast by Volatility Index and Its Use as a Risk Management Tool Under a Value-at-Risk Approach

2018 ◽  
Vol 21 (02) ◽  
pp. 1850010 ◽  
Author(s):  
Yam Wing Siu
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Risk Premium ◽  
Value At Risk ◽  
Realized Volatility ◽  
Management Tool ◽  
Spot Price ◽  
Pricing Options ◽  
Significance Levels ◽  
Risk Approach

This paper examines the predicting power of the volatility indexes of VIX and VHSI on the future volatilities (or called realized volatility, [Formula: see text] of their respective underlying indexes of S&P500 Index, SPX and Hang Seng Index, HSI. It is found that volatilities indexes of VIX and VHSI, on average, are numerically greater than the realized volatilities of SPX and HSI, respectively. Further analysis indicates that realized volatility, if used for pricing options, would, on some occasions, result in greatest losses of 2.21% and 1.91% of the spot price of SPX and HSI, respectively while the greatest profits are 2.56% and 2.93% of the spot price of SPX and HSI, respectively, making it not an ideal benchmark for validating volatility forecasting techniques in relation to option pricing. Hence, a new benchmark (fair volatility, [Formula: see text] that considers the premium of option and the cost of dynamic hedging the position is proposed accordingly. It reveals that, on average, options priced by volatility indexes contain a risk premium demanded by the option sellers. However, the options could, on some occasions, result in greatest losses of 4.85% and 3.60% of the spot price of SPX and HSI, respectively while the greatest profits are 4.60% and 5.49% of the spot price of SPX and HSI, respectively. Nevertheless, it can still be a valuable tool for risk management. [Formula: see text]-values of various significance levels for value-at-risk and conditional value-at-value have been statistically determined for US, Hong Kong, Australia, India, Japan and Korea markets.

Deregulated electricity market, a stochastic variational approach

2021 ◽  
Vol 103 ◽  
pp. 105493
Author(s):  
Michele Limosani ◽  
Monica Milasi ◽  
Domenico Scopelliti
Keyword(s):  
Electricity Market ◽  
Variational Approach ◽  
Deregulated Electricity Market
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