ESG activities and firm cash flow

I measure the influence of ESG activities on Free Cash flow to the Firm and Free Cash Flow to Equity. I find that ESG activities primarily benefit the cash flows to creditors of firms in developed markets. The ESG effect predominantly comes from the excess spending of the firm on communicating how it integrates the economic (financial), social and environmental dimensions into its day-to-day decision-making processes. For developed market firms, the additional factor of excess spending on conditions for the workforce plays a role in boosting Free Cash Flow to the Firm.     

Investment opportunities and bankruptcy prediction

A firm's mix of growth options and assets in place is an important determinant of its optimal default strategy. Our simple model shows that shareholders of a firm with valuable investment opportunities would be able/willing to wait longer before defaulting on their contractual debt obligations than shareholders of an otherwise identical firm without such opportunities. More importantly, we show empirically using a dataset of recent corporate bankruptcies that measures of investment opportunities are significantly related to the likelihood of bankruptcy. Augmenting existing bankruptcy prediction models by these measures improves their out-of-sample forecasting ability.     

Bankruptcy Prediction with Industry Effects

This paper investigates the forecasting accuracy of bankruptcy hazard rate models for U.S. companies over the time period 1962–1999 using both yearly and monthly observation intervals. The contribution of this paper is multiple-fold. One, using an expanded bankruptcy database we validate the superior forecasting performance of Shumway's (2001) model as opposed to Altman (1968) and Zmijewski (1984). Two, we demonstrate the importance of including industry effects in hazard rate estimation. Industry groupings are shown to significantly affect both the intercept and slope coefficients in the forecasting equations. Three, we extend the hazard rate model to apply to financial firms and monthly observation intervals. Due to data limitations, most of the existing literature employs only yearly observations. We show that bankruptcy prediction is markedly improved using monthly observation intervals. Fourth, consistent with the notion of market efficiency with respect to publicly available information, we demonstrate that accounting variables add little predictive power when market variables are already included in the bankruptcy model.     

Internal Finance and Corporate Investment

This paper examines Pecking Order/Free Cash Flow behavior in small ($25–$50 million), medium ($100–250 million), and large ($1000 million and over) firms. The purpose is to proffer an explanation for the important role of cash flow on the investment expenditure of firms that is more complete than the commonly given accounts. The Pecking order theory (PO) emphasizes the value‐enhancing influence of cash flow, while the free cash flow hypothesis (FCF) underscores its value‐destroying effect. Using the vector error correction model, we find that although the overall behavior of small firms support the pecking order theory, the cash flow of these firms does not have any causal effect on their investment. We further find evidence of free cash flow theory in large firms.     

Finance methodology of Free Cash Flow

Free Cash Flow (FCF) was adopted in the late 1980s as a financial tool to evaluate the firm and its individual projects. We question the procedure of calculating the FCF where a significant portion of Current Liabilities is offset against Current Assets, thereby creating the hybrid asset Net Working Capital (NWC). Borrowed from accounting methodology, that procedure distorts the FCF size, composition, volatility, and estimated value. Our empirical analysis shows that the nature and extent of those distortions can misinform the firm's stockholders, lenders and borrowers, and investors at large. We propose a revised FCF that would avoid those distortions.     

Firm Value,Information Problems and the Internal Capital Market

We examine how information problems between the firm and the investor affect the value of an internal capital market. While the extant literature finds that, on average, the diversified firm's access to an internal capital market is positively related to firm value, this paper finds that the results hold only for firms which face low levels of information problems. Firms facing the high levels of information problems realize no value from internal capital market access, consistent with the Jensen Free Cash Flow hypothesis. When information problems are large, agency costs dominate any savings that result from using an internal capital market to avoid selling under-priced securities in the external capital markets.     

Equivalent valuations in cash flow and accounting models

This paper investigates the equivalence of equity valuation between the free cash flow model and the residual income model. Two conditions are found to be jointly sufficient for Residual Income and Free Cash Flow models to produce the same equity valuation: (a) the models’ discount rates jointly satisfy the Modigliani and Miller (Am Econ Rev 48:261–297, 1958) condition which relates discount rates for levered equity, unlevered equity, tax savings and debt, and (b) forecasts of the two models’ variables jointly satisfy the income statement and balance sheet identities. Past discussions fail by ignoring or misusing (a).     

How Do Investment Banks Value Initial Public Offerings (IPOs)?

Abstract:  We investigate the valuation and the pricing of initial public offerings (IPOs) by investment banks for a unique dataset of 49 IPOs on Euronext Brussels in the 1993–2001 period. We find that for each IPO several valuation methods are used, of which Discounted Free Cash Flow (DFCF) is the most popular. The offer price is mainly based on DFCF valuation, to which a discount is applied. Our results suggest that DDM tends to underestimate value, while DFCF produces unbiased value estimates. When using multiples, investment banks rely mostly on future earnings and cash flows. Multiples based on post-IPO forecasted earnings and cash flows result in more accurate valuations.     

A NOTE ON THE RELATIONSHIP BETWEEN REPORTED CASH FLOW MEASURES,RATIOS AND THEIR ACCRUAL COUNTERPARTS

This note focuses on information redundancy of cash flow measures reported in and financial ratios derived directly from Cash Flow Statements. Previous research utilised recomputed, “traditional” and “refined”, measures to proxy for cash flow. Comovements are derived amongst various earnings and cash flow key variable measures, select financial ratios and changes in financial ratios. Key variables' results support the notion that reported cash flows are correlated with funds flow and earnings. However, reported cash flows relative to funds flow are less correlated with most of their accrual based counterparts. Cash flows thus have potential to provide new and non-redundant information relative to funds and accruals. Also, the incremental benefit of reported, relative to reconstructed cash flow measures is apparent. In light of the above, the merit of cash flow for the specific decision context of identifying suspended firms is investigated. Cash flow data in this context is found to be as useful as, but not superior to, comparable accruals data.     

The reliability of the book-to-market ratio as a risk proxy

This study examines whether the book-to-market ratio consistently explains the cross-section of stock returns through time. The results reveal that the book-to-market ratio is positively and significantly related to return in only 43% of the monthly regressions. Other value/growth variables such as Cash Flow,” “Sales Growth,” and “Size”; perform even more erratically than the book-to-market ratio, and are thus less likely to be viewed as legitimate risk proxies.     

Can machine learning approaches predict corporate bankruptcy? Evidence from a qualitative experimental design

Bankruptcy prediction has received a growing interest in corporate finance and risk management recently. Although numerous studies in the literature have dealt with various statistical and artificial intelligence classifiers, their performance in credit risk forecasting needs to be further scrutinized compared to other methods. In the spirit of Chen, Härdle and Moro (2011, Quantitative Finance), we design an empirical study to assess the effectiveness of various machine learning topologies trained with big data approaches and qualitative, rather than quantitative, information as input variables. The experimental results from a ten-fold cross-validation methodology demonstrate that a generalized regression neural topology yields an accuracy measurement of 99.96%, a sensitivity measure of 99.91% and specificity of 100%. Indeed, this specific model outperformed multi-layer back-propagation networks, probabilistic neural networks, radial basis functions and regression trees, as well as other advanced classifiers. The utilization of advanced nonlinear classifiers based on big data methodologies and machine learning training generates outperforming results compared to traditional methods for bankruptcy forecasting and risk measurement.     

《现金流量表准则》实施过程中存在的两个问题

文章就《企业会计准则———现金流量表》实施过程中存在的两个突出问题进行了分析 ,并提出了手工编制现金流量表情况下调整分录编制的基本思路及非金融企业之间的非贸易往来所引起的现金流量变化的对外报告方法     

Bankruptcy prediction for Korean firms after the 1997 financial crisis: using a multiple criteria linear programming data mining approach

The main purpose of this paper is to evaluate the data mining applications, such as classification, which have been used in previous bankruptcy prediction studies and credit rating studies. Our study proposes a multiple criteria linear programming (MCLP) method to predict bankruptcy using Korean bankruptcy data after the 1997 financial crisis. The results, of the MCLP approach in our Korean bankruptcy prediction study, show that our method performs as well as traditional multiple discriminant analysis or logit analysis using only financial data. In addition, our model??s overall prediction accuracy is comparable to those of decision tree or support vector machine approaches. However, our results are not generalizable because our data are from a special situation in Korea.     

系统性风险与企业财务危机预警——基于前沿机器学习的新视角

本文采用Logit回归模型以及随机森林模型、梯度提升模型等前沿机器学习方法,深入考察系统性风险指标对我国企业财务危机的预测能力。结果表明,系统性风险对中下游企业的财务危机具有显著的预测能力,而基于因子分析构建的系统性风险指标,结合随机森林模型可取得更好的预测效果。本文进一步区分财务危机的不同成因并发现,基于随机森林模型和Logit回归模型的预测框架能够对我国大多数财务危机事件进行有效预警。在此基础上,本文对我国上市企业监管提出相关建议,从而为完善金融风险处置机制提供一定参考。     

USING NEURAL NETS TO COMBINE INFORMATION SETS IN CORPORATE BANKRUPTCY PREDICTION

We demonstrate that the use of a neural network (NN) model to combine information from corporate financial statements and equity markets provides improved predictive estimates of the probability of corporate bankruptcy. Using performance measures, based on the receiver operating characteristic curve, the forecast combinations from the NN models are demonstrated to outperform the forecasts derived from a forecast combination generated using a logistic regression approach. This result provides support for the use of forecast combinations generated from NN models in the estimation of corporate bankruptcy probabilities as it outperforms the standard approach of forming a hybrid forecasting model which includes all the explanatory variables. Copyright © 2012 John Wiley & Sons, Ltd.     

Bankruptcy and Institutions: Theory and Empirical Evidence from Korea and the United States

Using a simple z-score bankruptcy model, this article explores the relationship between bankruptcy threshold and institutions. The z-score threshold for bankruptcy is found to be higher in countries with stronger institutions. To test this claim, a cross-section data set of 86 Korean firms and 60 US firms from 1991 to 2001, extracted from a panel data set, is used. The empirical finding that the z-score bankruptcy threshold in the United States (which has better quality of institutions than does Korea) is higher than that in Korea is consistent with the prediction of the model. Additionally, having examined bankruptcy laws of the two countries, it is found that filing a petition for bankruptcy is easier and debtors rights are better protected in the United States than in Korea, which suggests that the bankruptcy laws of Korea and the United States may be partially responsible for the difference in the z-score threshold for bankruptcy.     

A comparison of alternative bankruptcy prediction models

Early models of bankruptcy prediction employed financial ratios drawn from pre-bankruptcy financial statements and performed well both in-sample and out-of-sample. Since then there has been an ongoing effort in the literature to develop models with even greater predictive performance. A significant innovation in the literature was the introduction into bankruptcy prediction models of capital market data such as excess stock returns and stock return volatility, along with the application of the Black–Scholes–Merton option-pricing model. In this note, we test five key bankruptcy models from the literature using an up-to-date data set and find that they each contain unique information regarding the probability of bankruptcy but that their performance varies over time. We build a new model comprising key variables from each of the five models and add a new variable that proxies for the degree of diversification within the firm. The degree of diversification is shown to be negatively associated with the risk of bankruptcy. This more general model outperforms the existing models in a variety of in-sample and out-of-sample tests.     

Financial Flexibility and Opportunity Capture: Bridging the Gap Between Finance and Strategy

Logically, the practice of corporate finance and corporate strategy should be closely coordinated, but in reality there remains a massive gap between the two. This can lead strategically oriented firms to de‐emphasize or even discard NPV. Neither financial theory nor competitive strategy has been very open to the economic value of investment opportunity capture. Strategy must recognize that financial flexibility provides powerful advantages and financial theory must evaluate entire strategic programs rather than discrete, stand‐alone projects. Necessarily, the financial discussion of cost of capital and capital structure has to change. The authors offer two specific concepts to bridge the Gap between Finance and Strategy: 1) Reserve Financial Capacity is the annual sum of Free Cash Flow, Financing Flexibility and Cash Reserves over the period envisioned for strategy execution. Individual projects must belong to strategic programs in the sense that they either: 1) keep the base business running; 2) preserve an existing competitive position; or 3) form part of a program to enhance advantage or fashion a strategic breakout. 2) Strategically Sustainable Cost of Capital is the true, blended cost of capital required to complete an entire capital program. These concepts provide financial rigor to firms with well‐defined strategies and allow managements to wield Financial Flexibility as a strategic weapon, creating options on unique buying opportunities, such as at the bottom of industry cycles.     

Predicting Bankruptcy Resolution

This study examines classification and prediction of the bankruptcy resolution event. Filing of bankruptcy is resolved through one of three alternative resolutions: acquisition, emergence or liquidation. Predicting the final bankruptcy resolution has not been examined in the prior accounting and finance literature. This post-bankruptcy classification and prediction of the final resolution is harder than discriminating between healthy and bankrupt firms because all filing firms are already in financial distress. Motivation for predicting the final resolution is developed and enhanced. A sample of 237 firms filing for bankruptcy is used. Classification and prediction accuracies are determined using a logit model. A ten-variable, three-group resolution logit model, which includes five accounting and five non-accounting variables is developed. The model correctly classifies 62 percent of the firms, significantly better than a random classification. We conclude that non-accounting data add relevant information to financial accounting data for predicting post bankruptcy resolution. Further, public policy implications for investors, researchers, bankruptcy judges, claimants and other stakeholders are discussed.     

A South African Success Story: Excellence in the Corporate Use of Capital and Its Social Benefits

South African companies have made great progress in improving corporate profitability since the nation became a full democracy in 1994. Using the “Cash Flow Return on Investment” (CFROI) method, the authors demonstrate that South African listed companies have been generating world‐beating levels of inflation‐adjusted return on capital over the past decade. But not all parts of the South African economy have benefited from this corporate success. Despite the impressive corporate returns, economic growth remains lackluster, constrained by confused labor and government policies. The authors recommend that South African policy makers aim to minimize uncertainty for the private sector by refraining from interventions with agendas that have little to do with expanding output or employment growth. Using terminology borrowed from Thomas Piketty's recent book, the two authors argue that what South Africa needs is not some way to limit investors' return on capital (r) but rather sound economic approaches to liberate growth (g). The authors would like to see the country's companies continue to generate high “r” while reinvesting their profits to produce more wealth‐creating “g.”