Collateral, Cash Flow & Earnings at Risk
Time to update your risk metrics and policies? By Carlos Blanco
potential variability of collateral, cash flow and earnings. In particular, we explore an evolving area where risk groups
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can conduct regular risk ‘cat scans’ on material risks arising from the normal course of operations; debt and dividend policy decisions, as well as hedging and trading strategy. Firms with that ability to identify material risks can prepare contingency as well as mitigation plans to reduce exposure to unwanted risks. Even though it may seem a relatively easy question to answer,
the calculation of ‘at-Risk’ measures for collateral, cash flow and earnings is riddled with complexities. For example, the need to integrate portfolio, counterparty, and market data from multiple sources as well as the need to ‘leap forward’ in time and measure the collateral or cash inflows or outflows for multiple states of the world, brings several computational and modelling challenges.
his article provides an overview of risk metrics that can help trading and marketing groups, as well as the CFO and treasury departments, gain insights into the
scattered sources of information residing in different systems with poor or non-existent credit, collateral and liquidity risk management tools. Those risk managers and traders often rely on spreadsheets to bridge the gaps. Financial risk management and technology advances in
recent years have made it possible to integrate data from multiple sources to have a firm-wide perspective required to forecast multiple liquidity risk dimensions such as the probability that the firm may not have enough funds to meet its cash needs.
Trade & Portfolio Level Cashflow at Risk (CFaR) & Earnings at Risk (EaR) The current financial crisis has proven again that cash
Figure 1: An Integrated Simulation Framework for Market Collateral & Counterparty Risk
is king. Even though cashflow related issues are often an essential component at the time of making hedging and other critical decisions, very few firms have forward looking measures of potential cash inflows and outflows and are particularly vulnerable to face liquidity mismatching problems. Some of the most publicised risk management failures in the energy markets, such as Constellation, Semgroup, Amaranth, Metallgesellschaft, or China Aviation Oil, resulted from their inability to continue funding their derivative positions with their limited capital. Given the high volatility and extreme
Source: NQuantX LLC
System & Data Integration Requirements Many Energy Trading and Risk Management Systems (ETRM) excel at performing tasks such as scheduling and the nomination or accounting of physical trades but offer limited risk functionality and lag behind the state of the practice of systems developed by financial institutions. As a result, energy risk managers and traders often find
themselves having to conduct a piece-meal analysis of the various risks involved in trading and hedging strategies (e.g. credit, collateral and liquidity risk management) from
worldPower 2010
moves in energy markets, proactive risk managers regularly calculate potential cashflow shortfalls and also update their liquidity contingency plans based on evolving conditions. Some hedging strategies may reduce the economic risk of a portfolio, but may have conflicting effects for other key risks indicators such as earnings, cashflow or regret. An integrated framework is needed to
measure and optimise the various risk dimensions involved (Figure 1). Some of the key elements behind each metric and the key differences are shown in Table 1. EaR and CFaR share many attributes, and the framework to calculate them is similar and differs substantially to the one used to calculate VaR (Table 1). For firms with exposures to power and gas markets, CFaR usually requires modelling costs and revenues related to the operation of physical assets (e.g. generation, storage, etc.), spot purchases and sales, as well as profit and losses from the hedging and trading portfolio.
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