Cash Flow At Risk Research Articles

Risk measurement in profitability calculation of non-financial investment

In the paper a model of non-financial investment profitability calculation is presented. It is based on the concept of quantile risk measures and a real option valuation. Application of Monte Carlo simulation allows to receive probability distribution of Net Present Value (NPV) and implement risk measures like Cash Flow at Risk (CFaR), Net Present Value at Risk (NPVaR) or Expected Shortfall (ES) in relation to NPV (ES (NPV)). The main contribution of the article is implementation of ES (NPV) that shows the average of worst losses regarding NPV. ES (NPV) informs the investors what the worst result of the project may be.

Optimal foreign exchange hedge tenor with liquidity risk

We develop an optimal currency hedging strategy that allows fund managers who own foreign assets to choose the hedge tenors that will maximize their foreign exchange (FX) carry returns within a liquidity risk constraint. The strategy assumes that the offshore assets are fully hedged with FX forwards. The chosen liquidity risk metric is cashflow at risk (CFaR). The strategy involves time-dispersing the total nominal hedge value into future time buckets to maximize (minimize) the expected FX carry benefit (cost), given the constraint that the CFaRs in all the future time buckets are well managed within a liquidity budget. We show by Monte Carlo simulation and by backtesting that our hedging strategy successfully delivers good carry trade returns with little liquidity risk. We also provide practical insights on when and why fund managers should choose short-dated or long-dated tenors.

ESTIMATING THE WORST SCENARIO OF NET CASH OUTFLOW OF NON-MATURITY DEPOSITS BASED ON QUANTILE REGRESSION

The article considers models that are the most commonly used to estimate the cash outflows of nonmaturity deposits: core level of deposit balances, Geometric Brownian Motion (GBM), and Cash Flow at Risk (CFaR). These models use a one-dimensional normal distribution of the probabilities of balances or cash flows. We generalize the above-mentioned cash outflow models in linear quantile regression. The properties of quantile regression are particularly attractive for assessing the liquidity risk of non-maturity deposits. Quantile regression determines quantile directly. It does not depend on the type of distributions of deposit balances or cash flows; it is resistant to outliers that are typical of outstanding deposits; captures fat tails of the underlying distribution of variables; does not assume that variance is constant. To construct a quantile regression, we use a conditional twodimensional empirical distribution of cash outflows and deposit balances for corporate non-maturity deposits denominated in hryvnias under both normal and crisis conditions. Statistical tests confirmed the satisfactory goodness-of-fit for the model and the hypothesis of linear dependence of cash flows on the current level of deposit balances. As a result, the constructed quantile regression has no areas of the values of deposit balances in which liquidity risk would be underestimated. The developed methodology for quantile measure of depositoutflow will be useful both for banking supervision and banks.

Financial exposure and technology innovation investment

ObjetivoO objetivo deste trabalho é identificar, medir e otimizar o risco financeiro e seus efeitos sobre os resultados de projetos com inovação, tanto na perspectiva do regime contábil quanto do regime de caixa, em uma indústria de commodities.AbordagemUm estudo de caso hipotético, baseado em um caso real de uma indústria petroquímica brasileira, foi analisado com regras de precificação de commodities baseados em contratos reais. As métricas Earnings at Risk (EaR) e Cash Flow at Risk (CFaR) foram utilizadas, assim como uma métrica proposta neste trabalho, denominada Cash Balance at Risk (CBaR).ResultadosEste artigo demonstrou que a mensuração e otimização do risco financeiro são questões importantes no processo de tomada de decisão em uma indústria petroquímica. As medidas EaR, CFaR e CBaR se apresentaram como contribuições ao processo padrão de avaliação de projetos. Os resultados também demonstraram que inovações tecnológicas, em certas condições, podem funcionar como um “hedge natural”. Foi verificado que descasamentos temporais entre recebimentos e despesas geram uma exposição financeira a oscilações em preços e em valores de moedas estrangeiras. Financiamento e hedge podem ser utilizados em conjunto para aprimorar resultados de projetos.Originalidade/valorUm projeto com inovação foi comparado com um projeto de expansão em uma indústria petroquímica. Foi realizada uma analise de risco que agrega ao financiamento e ao hedge o uso de contratos de precificação de commodities. Os resultados desse projeto demonstram que é importante considerar medidas de risco financeiro nas avaliações de projetos.

Risk management for private equity funds

Although risk management has been a well-ploughed field in financial modeling for over three decades, the understanding how to correctly quantify and manage the risks of investing in private equity remains limited and continues to considerably lag that of other traditional asset classes. The objective of this paper is to fill this gap by developing the first comprehensive risk management framework for private equity fund investments. The framework captures the three main sources of risks that private equity investors face when investing in the asset class: market risk, liquidity risk, and cash flow risk. Underlying the framework is a stochastic model for the value and cash flow dynamics of private equity funds, which allows deriving three dynamic risk measures for private equity fund investments: Value-at-Risk (VaR), Liquidity-Adjusted Value-at-Risk (LVaR), and Cash-Flow-at-Risk (CFaR). The model is calibrated to historical data of buyout funds and the dynamics of the developed risk measures are illustrated using Monte-Carlo simulations. A sensitivity analysis shows the impact of changes in the main model parameters on risk measures.

Optimizing Cash-Flow-at-Risk in Construction Projects: A Cost Reduction Approach

Project managers normally are facing with difficulties behind management of project cash flow, which requires distinguished methods and appropriate tools to manage negative cash flows. Cash-Flow-at-Risk (CFaR) model is an efficient approach to predict cash flow trend. In this study, all risk factors affecting project management environment have incorporated to predict an accurate project cash flow. Then, a response surface method (RSM) is applied to determine optimal level of risk. The results have successfully implemented through a case study to demonstrate the applicability of the proposed method.

Risk Management for Private Equity Funds

Although risk management has been a well-ploughed field in financial modeling for over three decades, the understanding how to correctly quantify and manage the risks of investing in private equity remains limited and continues to considerably lag that of other traditional asset classes. The objective of this paper is to fill this gap by developing the first comprehensive risk management framework for private equity fund investments. The framework captures the three main sources of risks that private equity investors face when investing in the asset class: market risk, liquidity risk, and cash flow risk. Underlying the framework is a stochastic model for the value and cash flow dynamics of private equity funds, which allows deriving three dynamic risk measures for private equity fund investments: Value-at-Risk (VaR), Liquidity-Adjusted Value-at-Risk (LVaR), and Cash-Flow-at-Risk (CFaR). The model is calibrated to historical data of buyout funds and the dynamics of the developed risk measures are illustrated using Monte-Carlo simulations. A sensitivity analysis shows the impact of changes in the main model parameters on risk measures.

ESTIMATING LIQUIDITY RISK USING THE EXPOSURE‐BASED CASH‐FLOW‐AT‐RISK APPROACH: AN APPLICATION TO THE UK BANKING SECTOR

ABSTRACTThis paper uses a relatively new quantitative model for estimating UK banks' liquidity risk. The model is called the exposure‐based cash‐flow‐at‐risk (CFaR) model, which not only measures a bank's liquidity risk tolerance but also helps to improve liquidity risk management through the provision of additional risk exposure information. Using data for the period 1997–2010, we provide evidence that there is variable funding pressure across the UK banking industry, which is forecasted to be slightly illiquid with a small amount of expected cash outflow (i.e. £0.06 billion) in 2011. In our sample of the six biggest UK banks, only the HSBC maintains positive CFaR with 95% confidence, which means that there is only a 5% chance that HSBC's cash flow will drop below £0.67 billion by the end of 2011. RBS is expected to face the largest liquidity risk with a 5% chance that the bank will face a cash outflow that year in excess of £40.29 billion. Our estimates also suggest Lloyds TSB's cash flow is the most volatile of the six biggest UK banks, because it has the biggest deviation between its downside cash flow (i.e. CFaR) and expected cash flow. Copyright © 2014 John Wiley & Sons, Ltd.

Selective hedging in hydro-based electricity companies

We analyze risk management trends in electricity commodity markets using the production and transaction data and written hedging policies of 12 Norwegian hydropower companies. The scope of our analysis is the hedging of physical electricity production using the power derivatives available at NASDAQ OMX Commodities. In their hedging policy, these companies either use a Cashflow at Risk (C-FaR) approach or a hedge ratio approach, or follow no explicitly stated approach. We find that the derivative cashflows constitute substantial profits for these companies. Furthermore, hedging contributes to reducing the C-FaR for 10 of the companies. These findings are surprising considering that we expect hedging to yield zero expected profit and to smooth the earnings. Overall, our findings reveal that a practice of incorporating market views in hedging decisions is widespread in the sample companies, as both sanctioned in their written hedging policy and as indicated by the substantial hedging profits.

Estimating Cashflow-at-Risk (CFaR)

Of the many risks faced by restaurants, a shortage of cashflow is among the most damaging. This study introduces an effective tool to estimate the cashflow risk of restaurants, so that firms can be ready to address the potential risks. Using a comparables approach to Cashflow-at-Risk (CFaR), the study analyzes cashflow data from publicly listed U.S. restaurant firms from 1988 to 2007. The study found that estimated cashflow shortfalls were larger for small and medium-size firms than for large firms. Also, full-service restaurants’ cashflow shortfalls were larger than those of limited-service restaurants, suggesting relative cashflow risk positions for different restaurant segments. This study provides nonfinancial firms such as restaurant firms with a practical tool to estimate cashflow risk, which could mitigate the probability of financial distress and improve the financial health of firms.

Um modelo alternativo de risco para companhias não-financeiras aplicado ao setor brasileiro de papel e celulose

O Earnings at Risk (EaR) é uma medida de risco financeiro aplicável a empresas não financeiras, assim como o Cash Flow at Risk (CFaR). Esta medida se baseia numa relação que pode ser quantificada através de modelos de regressão linear múltipla, nos quais a variável resposta é a variação do resultado da empresa, e as variáveis explicativas são variações nos diversos fatores de risco. A presença de correlação entre variáveis explicativas (multicolinearidade) neste modelo pode provocar problemas nos cálculos do EaR e do CfaR. Nesse trabalho, apontaremos algumas possíveis consequências deste problema no processo de cálculo do EaR, e apresentaremos uma proposta para contorná-lo baseada na técnica de Análise de Componentes Principais. Escolhemos para análise o setor de agronegócio, especificamente o ramo de papel e celulose. Mostraremos que, na ausência de correlação significativa entre as variáveis, o modelo proposto tem desempenho equivalente ao da regressão linear múltipla usual. Na presença de correlação, encontramos evidências de que o modelo aqui proposto produz previsões mais confiáveis e precisas.

Posouzení metody částečného hedgingu na případu řízení měnového rizika nefinanční instituce

Financial risk management is an inherent part of each business activity. The analysis of available hedging strategies, theirs interconnection with efficient market and firm value theories, as well as various empirical studies are regular theme of scientific papers. In this study we focus on an alternative approach to hedging of financial risk of non-financial institutions – the partial hedging approach with shortfall acceptation. This approach initiates from Follmer and Leukert (1999) method of quantile hedging. It is also related to cashflow at risk approach of Stein et al. (2001). The approach to hedging presented in this paper is based on a combined option position, so that a substantial decrease in initial capital needs can be achieved by accepting of some probability of shortfall. The strategy is studied under various circumstances given e.g. by risk neutral and real market probabilities. Simultaneously, it is compared to more standard strategies of hedging. Finally, we present two interesting findings: (i) real world probability of shortfall significantly differs from the risk neutral one, (ii) at first sight insignificant error in simulation results can have important influence on the interpretation of partial hedging strategies.

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

ABSTRACT The current level of deregulation in electricity markets is continuing to expand. Although each of these markets has individual operational and financial structures, one common characteristic is volatility. This volatility is significant and time-varying, and the persistence of this volatility makes the management of financial risk a priority among market participants. This article considers two applications of an innovative spot price model to risk management in such a market. The first application is the empirical estimation of risk premia in the market considered here. The results support other approaches, which find the risk premia to be both significant and time-variant. In addition, this work considers the application of a Cash-Flow-at-Risk (CFaR) approach to measuring and comparing financial risk among various portfolio alternatives. These portfolios are considered from the perspective of the electricity producer, and the electricity purchaser. This approach is flexible and practical, allowing the comparison among portfolios and across seasons. The results of this analysis show that derivative instruments are significantly over-priced in this market, and that producers have the opportunity to earn significant profits, above those justified by the inherent risk in the market.

Cash-Flow-at-Risk and Debt Capacity

Value-at-Risk (VaR), which indicates the loss in value associated with a certain probability, is a widely used risk measure among financial institutions. Cash-Flow-at-Risk (CFaR) is an attempt to transfer the same ideas to the setting of a non-financial firm. In this paper I argue that at-Risk measures, in the context of corporate liquidity risk management, would benefit from an explicit and more thoughtful treatment of the firm's debt capacity. By so doing one obtains risk measures that can provide information on outcomes that are identified as costly by the risk management literature, in particular underinvestment due to financing constraints. Since assessing such outcomes requires information on the firm's presumed access to external sources of funding, what is called for is a framework in which cash flow-based measures of risk are conditional on the firm's debt capacity. The group of risk measures presented in this paper incorporates this information. They render hedgeable magnitudes that can inform risk management strategies by indicating if a hedge is likely to mitigate costly consequences of volatility by acting as a substitute for equity capital.

Exposure-Based Cash-Flow-at-Risk: An Alternative to VaR for Industrial Companies

Cash-Flow-at-Risk (CFaR) is the cash flow equivalent of Value-at-Risk (VaR), a measure widely used as the basis for risk management in financial institutions. Whereas VaR-based systems specify the maximum amount of total value a firm is expected to lose under most foreseeable conditions (for example, with a 99% confidence level), CFaR-based systems determine the maximum shortfall of cash the firm is willing to tolerate. CFaR is gaining in popularity among industrial companies for much the same reasons VaR has succeeded with financial firms: it sums up all the company's risk exposures in a single number that can be used to guide corporate risk management decisions. The authors describe a six-step process for calculating a measure they call “exposure-based CFaR” and then demonstrate its application to Norsk Hydro, the Norwegian industrial conglomerate. Exposure-based CFaR involves the estimation of a set of exposure coefficients that provide information about how various macroeconomic and market variables are expected to affect the company's cash flow, while also accounting for interdependencies among such effects. The resulting model enables management to estimate the variability in corporate cash flow as a function of various risks, and to predict how a hedging contract or a change in financial structure will alter the company's risk profile.

Zentrales und dezentrales Risikocontrolling in Industrieunternehmen

Using a formal model, the paper analyzes risk management for nonfinancial corporations. A firm is considered that produces and sells divisional products. This triggers uncertain cash flows, the risk of which is measured by the Cash Flow at Risk (CFaR)-concept. The CFaR determines the required amount of equity. Several possibilities of implementing a risk management system are discussed, with a particular focus on the required equity. A major result is that a more restrictive risk policy does not necessarily lead to an increasing demand of equity. Furthermore, for the case of several divisions the differences of centralized and decentralized risk management are analyzed.

A COMPARABLES APPROACH TO MEASURING CASHFLOW‐AT‐RISK FOR NON‐FINANCIAL FIRMS

Cashflow‐at‐Risk (C‐FaR) is an attempt to create an analogue to Value at Risk (VaR) that can be used by non‐financial firms to quantify various kinds of risk exposures, including interest rate, exchange rate, and commodity price risks. There are two basic ways to attack this problem. One is from the “bottom up,” which involves building a detailed model of all of a company's specific exposures. The C‐Far approach presented here is a “top‐down” method of comparables that looks directly at the ultimate item of interest—the companies' cashflows. The fundamental challenge facing the top‐down strategy is that, for any one company, there is not enough data on its own cashflows to make precise statements about the likelihood of rare events. To get around this problem, the authors match a target company with a large set of comparable companies that are expected to have similar cashflow volatility. The comparables are chosen to be close to the target company on four dimensions: (1) market cap; (2) profitability; (3) industry risk; and (4) stock price volatility.C‐FaR can be useful to managers addressing a variety of corporate finance decisions. For example, by providing estimates of the probability of financial distress, the C‐FaR method can be used in conjunction with capital structure data to help formulate debt‐equity tradeoffs in a more precise, quantifiable fashion. It can also be used to evaluate a firm's overall risk management strategy, including the expected benefits of using derivatives to hedge commodity‐price exposures or the purchase of insurance policies. Moreover, C‐FaR may even have a use in investor relations: by disclosing the results of a comparables‐based C‐FaR analysis ahead of time, a company may be able to cushion earnings shocks by furnishing investors or analysts with credible, objective estimates of what is likely to happen to their cash flows under different economic scenarios.