【上财会计】财务报告分析课件（靳庆鲁）lecture 10

Lecture 10: 收益预测（Earnings Forecasts）,Profitability analysis and earnings forecasts,We have conducted profitability analysis, which shows the ability to generate profits given the amount of capital employedBut profitability analysis is about the PAST, Valuation is about the FUTURE!So, profitability analysis is only useful if it helps us forecast future earnings, that is what we turn to now.,The value of a firm to equity investors,V = D1/(1+r) + D2/(1+r)2 + D3/(1+r)3 .,profitability,risk,We need to predict D? D can be earnings, Dividends, free cash flow,Residual income!,Some key features of accounting numbers,Most companies operation follows a relatively smooth pattern, so dramatic changes are rare.Once a dramatic change occurred, it is difficult to maintain (regression to the mean). So accounting numbers, including ratios, change smoothly.,Forecasting tips,Only forecast recurring items, including earnings from operation, interest expense (income), tax expense, and some investment incomes.Non-recurring items, such as one-time charges, impairment loss, asset disposal gains/losses, are unpredictable and value-irrelevant. Extraordinary items, such as earthquake losses, are unpredictable and value-irrelevant.,The key steps of organized earnings forecasts,Start with current and past balance sheets and income statements;Forecast revenues;Forecast assets (combining revenues forecasting and ATO);Construct pro forma balance sheets;Forecast expense ratios to construct pro forma income statements;Forecast dividend policy and future dividends;Forecast free cash flows;Forecast residual incomes,Statistics-based earnings forecasts (reduced-form earnings forecasts),In using statistical methods to forecast accounting numbers, we do not forecast the full financial statements; instead, we observe the time-series of interested variable itself, e.g., earnings, only, and use the statistical properties of these variable to forecast itself into the future.,Random Walk model (annual data),The model: EDt+1 = DtThe random walk model assumes that the earnings process is a stationary process. If earnings follow this process, the best predictor of next years earnings is current years earnings.So if D2003 = $1, then E(D2004) = $1,Random Walk model (quarterly data),Thus far, we have concerned ourselves with annual forecasts. However, especially for security analysts forecasting is very much a quarterly game. Forecasting quarter by quarter raises a new set of questions.The model: EDt+1 = Dt-3So if D2003Q1 = $1, then E(D2004Q1) = $1,Random Walk Model versus Mean-reverting Model,Regression to the mean model (annual data),The model: EDt+1 = a + b*Dt + etWhere 0 b 1In the U.S. between 1962 and 1993, when D is earnings, empirical results show that Dt+1 = 0.015 + 0.841*Dt (t=32.5) (t=303.9)So if D2003 = $1, then E(D2004) = 0.015 + 0.841*$1 = $0.856,Random Walk model (quarterly data),The form of the Foster model confirms the importance of seasonality because it shows that the starting point for a forecast for quarter t is the earnings four quarters ago, Qt-4.,It states that, a reasonable forecast of earnings for quarter t includes the following elements:the earnings of the comparable quarter of the prior year (Qt-4);a long-run trend in year-to-year quarterly earnings increases ();a fraction () of the year-to-year increase in quarterly earnings experienced most recently (Qt-1 Qt-5).,XXXs Quarterly EPS, 19881998,More specifically, when the parameters and are estimated with the data in above Table, the Foster model predicts EPS of 1999Q1 is $0.265:E(1999q1)=Q1998q1+0.01+0.44Q1998q4-Q1997q4 =0.215+0.01+0.440.47-0.38=0.265 E(1999q2)=Q1998q2+0.01+0.44Q1999q1-Q1998q1 =0.470+0.01+0.440.265-0.215=0.502,Decomposing of earnings: Accruals and Cash Flow,Earnings = Cash Earnings + Accrued EarningsThe model: EEarnings t+1 = a + b*Cash Earnings t + c*Accrued Earnings t + etIn the U.S. between 1962 and 1993, empirical results show that Dt+1 = 0.011 + 0.855*Cash Earnings t + 0.765 *Accrued Earnings t (t=24.0) (t=304.0) (186.5) So if D2003 = $1 = $0.6 + $0.4, then E(D2004) = 0.011 + 0.855*$0.6 + 0.765*0.4 = 0.830,Forecasting tips,You need to have long history of dataThe underlying process changes, so does the models that fit the data, or the parameters of the data. Updating regularly is key,Improvements on Earnings Forecasts,The forecasts we obtained need further improvements:Adjust for earnings management;Adjust for earnings quality;Adjust for heuristic bias;Adjust for significant economic, market and company eventsEarnings forecasting is not a robot job!,Adjust for earnings management,We have a firm with one machine (cost $100) to manufacture needles; the firms annual revenue is $30; machine can be used for five years, afterwards the firm is closed.,Adjust for earnings management,What if in 2003, we detected that the firm managed earnings up by lowering depreciation expense to $16?,Adjust for earnings management,We would have been wrong if we had used random walk model to forecast earnings, or any model, if we do not adjust for the effect of previous earnings management.,Adjust for earnings quality,Even without the presence of earnings management, there is still an earnings quality issue.Earnings quality: Earnings are of GOOD quality if it can help predict future earnings more accurately.,Adjust for earnings quality: Penman and Zhang (1999),Conservative accounting creates earnings reserves (ER). That is, it lowers current earnings, but increases future earnings. E.g., take more bad debt allowance.Quality score: Qi,t = ERi,t/NOAi,t ERi,t-1/NOAi, t-1The higher the Q-score is, the larger the earnings reserve is, the higher the future earnings will be.,Adjust for earnings quality,Some firms use accounting conservatively, others less conservatively (aggressively). Conservative accounting policies generate earnings of good quality, which means future earnings (or profitability) should be higher (other things equal)Aggressive accounting policies generate earnings of bad quality, which means future earnings (or profitability) should be lower (other things equal),Adjust for heuristic bias,Analysts are human beings, and they are subject to the same psychological biases.OptimismSelf-attritionOver-/under-reactionHerdingInformation cascade,Optimism,On average, analysts forecasts are higher than the actual earnings (forecast error=actual earnings-analysts forecasts),Self-attribution,When successful, human beings attribute the success to her own capability,When unsuccessful, she attributes the failure to bad luck, or other factors.,Over-/under-reaction,When a firm reports one good quarterly earnings, analysts tend to under-react and under-forecast earnings, When a firm reports ten good quarterly earnings, analysts tend to over-react and over-forecast earnings.,Herding （羊群效应）,When the first sheep goes south, other sheep follow.When the first analyst issues her earnings forecast, other analysts will observe and issue similar forecasts.It is bad when you are wrong, but it is not so bad when everyone else is also wrong.,Information cascade,There are five similar-looking restaurants outside SUFE, you have one in mind for dinner. But when you get to there, the one you have in mind is empty, and the one next to it is almost full. Which one will you go? After you research, you go to stock market with the intention to buy A stock. You are the third in line waiting. Now you see the first person buy the stock B, and the second person buy the stock B, what will you do?,Forecasting tips,If your purpose is to get the most accurate forecast, you should be aware of the heuristics biases. The key to avoiding heuristics biases is to act independently every time, not only from others, but also from your past.,Adjust for significant economic, market and company events,The forecasts we derive so far are based on past accounting data.But past accounting data does not incorporate the implications of current events for future earnings, because accounting is historical cost-based, and financial statements are prepared only four times a year or fewer.,Adjust for significant economic events,GDP, GNP growthInflationInterest rate changeTax policy changeRegulation change,Adjust for significant industry events,Entry barrierCompetitionMain competitorsInnovationMarket boundary change,Adjust for significant company events,Management changesNew contractsLabor costsSuppliersCustomers,Combining Economy and Industry into Earnings Forecasts,A regression model that forecasts the earnings of a firm via forecasts of two independent variables related to economy (XM,t) and industry (XI,t) factors:E(Xi,t)=a+b1* E(Xi,t-1)+b2*E (XM,t) +b3* E(XI,t),Forecasting tips,Firms operate in the larger economic environment, and the environment changes have big impact on firm performance.The economic, industry, and company events, although not yet to occur, once occur, would have significant impacts on earnings.Far-sighted analysts see them coming.,Related issues on analysts and earnings forecasts,Analysts conflict of interest and independent researchNumbers gameCommunications between company and analystsValue of analysts earnings forecasts and stock recommendation,Analysts conflict of interest and independent research,Most investment banks have investment banking divisions and research divisions, and the two are supposed to be independent. Increasingly, star analysts of the research divisions can move stock market. To get investment banking business, investment banks push analysts to write favorable opinion towards the companies that the bank is pursuing investment banking business.,Some star analysts of the 1990s,索罗门美邦（Salomon Smith Barney）的Jack Grubman美林公司（Merrill Lynch）的Henry Blodget高盛公司（Goldman Sachs）的Abby CohenAll have been under investigation for issuing misleading analysts reports, the first two lifetime bans from the industry, alo