Sales Forecasting with Financial Indicators and Experts' Input

We present a method for forecasting sales using financial market information and test this method on annual data for US public retailers. Our method is motivated by the permanent income hypothesis in economics, which states that the amount of consumer spending and the mix of spending between discretionary and necessity items depend on the returns achieved on equity portfolios held by consumers. Taking as input forecasts from other sources, such as equity analysts or time‐series models, we construct a market‐based forecast by augmenting the input forecast with one additional variable, lagged return on an aggregate financial market index. For this, we develop and estimate a martingale model of joint evolution of sales forecasts and the market index. We show that the market‐based forecast achieves an average 15% reduction in mean absolute percentage error compared with forecasts given by equity analysts at the same time instant on out‐of‐sample data. We extensively analyze the performance improvement using alternative model specifications and statistics. We also show that equity analysts do not incorporate lagged financial market returns in their forecasts. Our model yields correlation coefficients between retail sales and market returns for all firms in the data set. Besides forecasting, these results can be applied in risk management and hedging.     

Time‐Varying Risk Premium in Large Cross‐Sectional Equity Data Sets

We develop an econometric methodology to infer the path of risk premia from a large unbalanced panel of individual stock returns. We estimate the time‐varying risk premia implied by conditional linear asset pricing models where the conditioning includes both instruments common to all assets and asset‐specific instruments. The estimator uses simple weighted two‐pass cross‐sectional regressions, and we show its consistency and asymptotic normality under increasing cross‐sectional and time series dimensions. We address consistent estimation of the asymptotic variance by hard thresholding, and testing for asset pricing restrictions induced by the no‐arbitrage assumption. We derive the restrictions given by a continuum of assets in a multi‐period economy under an approximate factor structure robust to asset repackaging. The empirical analysis on returns for about ten thousand U.S. stocks from July 1964 to December 2009 shows that risk premia are large and volatile in crisis periods. They exhibit large positive and negative strays from time‐invariant estimates, follow the macroeconomic cycles, and do not match risk premia estimates on standard sets of portfolios. The asset pricing restrictions are rejected for a conditional four‐factor model capturing market, size, value, and momentum effects.     

Returns Policy and Quality Risk in E‐Business

In this article, we investigate the interplay between returns policy, pricing strategy, and quality risk. We define quality risk as the possibility of product misfit, defect, or unconformity with the consumers’ perception. These notions of quality risks differ in return policy restriction, residual values, and whether it is possible to unambiguously reduce the probability of mismatch. Using a stylized two‐segment market setting, we demonstrate that consumer returns are offered only when the high‐segment consumers incur a higher hassle cost, and both the quality risk and the valuation of the low segment are moderate. Moreover, it is possible to wisely design the returns policy that eliminates all inappropriate returns. Furthermore, the seller with a high‐quality risk may offer a refund that exceeds the selling price, which provides a theoretical ground and specific operating regime for the satisfaction guaranteed policy used in some e‐tailers. In contrast, when the quality risk is relatively low, further improvement on mitigating the quality risk may not necessarily benefit the seller. Finally, we observe that the restocking fee may be non‐monotonic in product quality; thus, a more generous returns policy does not necessarily indicate a lower quality risk.     

Consumer Heterogeneity and Paid Search Effectiveness: A Large‐Scale Field Experiment

Internet advertising has been the fastest growing advertising channel in recent years, with paid search ads comprising the bulk of this revenue. We present results from a series of large‐scale field experiments done at eBay that were designed to measure the causal effectiveness of paid search ads. Because search clicks and purchase intent are correlated, we show that returns from paid search are a fraction of non‐experimental estimates. As an extreme case, we show that brand keyword ads have no measurable short‐term benefits. For non‐brand keywords, we find that new and infrequent users are positively influenced by ads but that more frequent users whose purchasing behavior is not influenced by ads account for most of the advertising expenses, resulting in average returns that are negative.     

Ambiguity,Learning, and Asset Returns

We propose a novel generalized recursive smooth ambiguity model which permits a three‐way separation among risk aversion, ambiguity aversion, and intertemporal substitution. We apply this utility model to a consumption‐based asset‐pricing model in which consumption and dividends follow hidden Markov regime‐switching processes. Our calibrated model can match the mean equity premium, the mean risk‐free rate, and the volatility of the equity premium observed in the data. In addition, our model can generate a variety of dynamic asset‐pricing phenomena, including the procyclical variation of price–dividend ratios, the countercyclical variation of equity premia and equity volatility, the leverage effect, and the mean reversion of excess returns. The key intuition is that an ambiguity‐averse agent behaves pessimistically by attaching more weight to the pricing kernel in bad times when his continuation values are low.     

Choosing the Number of Instruments

Properties of instrumental variable estimators are sensitive to the choice of valid instruments, even in large cross‐section applications. In this paper we address this problem by deriving simple mean‐square error criteria that can be minimized to choose the instrument set. We develop these criteria for two‐stage least squares (2SLS), limited information maximum likelihood (LIML), and a bias adjusted version of 2SLS (B2SLS). We give a theoretical derivation of the mean‐square error and show optimality. In Monte Carlo experiments we find that the instrument choice generally yields an improvement in performance. Also, in the Angrist and Krueger (1991) returns to education application, when the instrument set is chosen in the way we consider, it turns out that both 2SLS and LIML give similar (large) returns to education.     

基于VaR的多阶段金融资产配置模型

本文提出了基于VaR的多阶段金融资产配置模型。进一步以我国经济环境为依托,考虑了未来各种资产收益、工资变动及物价变动的不确定性,对这一模型进行了仿真计算,并与静态模型在最优性上进行了比较,得出了动态模型优于静态模型的结论。在期望财富相同的情况下,基于VaR的多阶段资产配置模型比静态模型的期望损失成本低,承担的风险更小。     

Lot Sizing for Optimal Collection and Use of Remanufacturable Returns over a Finite Life‐Cycle

Reverse supply chains process used product returns to recover value by re‐processing them via remanufacturing operations. When remanufacturing is feasible, the longer the return flows are delayed during the active (primary) market demand period of the product, the lower the value that can be recovered through these operations. In fact, in order to recover the highest value from remanufactured products, the collection rates, return timings, and reusability rates should be matched with the active market demand and supply. With these motivations, this paper is aimed at developing analytical models for the efficient use of returns in making production, inventory, and remanufacturing decisions during the active market. More specifically, we consider a stylistic setting where a collector collects used product returns and ships them to the manufacturer who, in turn, recovers value by remanufacturing and supplies products during the active market demand. Naturally, the manufacturer's production, inventory and remanufacturing decisions and costs are influenced by the timing and quantity of the collector's shipments of used product returns. Hence, we investigate the impact of the timing of returns on the profitability of the manufacturer‐collector pair by developing system‐wide cost optimization models. Analyzing the properties of the optimal shipment frequency, we observe that the fastest reverse supply chain may not always be the most efficient one.     

Slack free MEA and RDM with comprehensive efficiency measures

This paper extends two directional distance function models, the Multi-directional Efficiency Analysis (MEA) Model and the Range Directional Model (RDM), in order to account for any type of technical inefficiency, i.e. both directional and non-directional inefficiencies. We first focus on the variable returns to scale (VRS) case, because both VRS-MEA and RDM are translation invariant models, which mean that both models are able to deal with negative data. Our main result is the definition of a new comprehensive efficiency measure which is units invariant and translation invariant and covers both models. Secondly, we introduce the RDM model under constant returns to scale (CRS) together with a new comprehensive efficiency measure.     

Earning While Learning: When and How Student Employment is Beneficial

Although studies of student employment (‘earning while learning’) mostly find positive wage effects, they do not adequately consider the relation of the employment to the field of study. We investigate how different types of student employment during tertiary education affect short‐ and long‐term labour market returns. Beyond examining differences between non‐working and part‐time working students, we distinguish between student employment related and unrelated to the field of study. Our results show significant positive labour market returns of ‘earning while learning’ only for student employment related to the field of study. These returns consist of a lower unemployment risk, shorter job‐search duration, higher wage effects, and greater job responsibility.     

Efficient Semiparametric Estimation of the Fama–French Model and Extensions

This paper develops a new estimation procedure for characteristic‐based factor models of stock returns. We treat the factor model as a weighted additive nonparametric regression model, with the factor returns serving as time‐varying weights and a set of univariate nonparametric functions relating security characteristic to the associated factor betas. We use a time‐series and cross‐sectional pooled weighted additive nonparametric regression methodology to simultaneously estimate the factor returns and characteristic‐beta functions. By avoiding the curse of dimensionality, our methodology allows for a larger number of factors than existing semiparametric methods. We apply the technique to the three‐factor Fama–French model, Carhart's four‐factor extension of it that adds a momentum factor, and a five‐factor extension that adds an own‐volatility factor. We find that momentum and own‐volatility factors are at least as important, if not more important, than size and value in explaining equity return comovements. We test the multifactor beta pricing theory against a general alternative using a new nonparametric test.     

一种新的金融动态横截面估计方法——基于中国股票市场条件定价模型评估的应用与扩展

大多数资产定价模型常常用静态横截面回归(the static cross-sectional regression)进行定价表现评估,从而投资组合回报率的时间变化性并不能被时变的风险承载或者(和)时变的风险溢价所解释.本文从经济学的角度,运用一种新的金融动态横截面回归(the dynamic cross-sectional regression),首次考察了基于中国股票市场和美国股票市场的条件资产定价模型的定价表现:股票市场投资组合回报率的时变性是否能被时变的风险溢价所解释.本文发现,短期收益反转和流通市值加权市场换手率为条件变量的条件资本资产定价模型和基于消费的条件资本资产定价模型,能更好的解释中国股票投资组合的回报时变性,其时变性主要来自于时变的风险溢价.另外,本文发现一些拥有持续(persistence)和缓慢变化(slow-moving)特性的条件变量更能够解释横截面投资组合的时变回报.     

WHY DO EMERGING ECONOMIES BORROW SHORT TERM?

We argue that one reason why emerging economies borrow short term is that it is cheaper than borrowing long term. This is especially the case during crises, as during these episodes the relative cost of long‐term borrowing increases. We construct a unique database of sovereign bond prices, returns, and issuances at different maturities for 11 emerging economies from 1990 to 2009 and present a set of new stylized facts. On average, these countries pay a higher risk premium on long‐term than on short‐term bonds. During crises, the difference between the two risk premia increases and issuance shifts towards shorter maturities. To illustrate our argument, we present a simple model in which the maturity structure is the outcome of a risk‐sharing problem between an emerging economy subject to rollover crises and risk‐averse international investors.     

End‐of‐Life Inventory Problem with Phaseout Returns

We consider the service parts end‐of‐life inventory problem of a capital goods manufacturer in the final phase of its life cycle. The final phase starts as soon as the production of parts terminates and continues until the last service contract expires. Final order quantities are considered a popular tactic to sustain service fulfillment obligations and to mitigate the effect of obsolescence. In addition to the final order quantity, other sources to obtain serviceable parts are repairing returned defective items and retrieving parts from phaseout returns. Phaseout returns happen when a customer replaces an old system platform with a next‐generation one and returns the old product to the original equipment manufacturer (OEM). These returns can well serve the demand for service parts of other customers still using the old generation of the product. In this study, we study the decision‐making complications as well as cost‐saving opportunities stemming from phaseout occurrence. We use a finite‐horizon Markov decision process to characterize the structure of the optimal inventory control policy. We show that the optimal policy consists of a time‐varying threshold level for item repair. Furthermore, we study the value of phaseout information by extending the results to cases with an uncertain phaseout quantity or an uncertain schedule. Numerical analysis sheds light on the advantages of the optimal policy compared to some heuristic policies.     

金融资产收益非对称性的多标度分形测度及其在VaR计算中的应用

通过提炼多标度分形分析过程中所产生的对描述金融资产收益非对称特征有益的统计信息,提出了一种新的资产收益非对称测度--多标度分形非对称测度(Multifractal asymmetry measurement)Δf,并以沪深300指数长达7年左右的5分钟高频数据为实证样本,通过两种不同的VaR后验分析(Backtesting analysis)方法,实证对比了Δf测度和传统的偏度系数(Coefficient of skewness)测度在市场风险计算准确性方面的差异。实证结果表明:基于Δf测度的市场风险计算模型的VaR计算精度优于基于偏度系数测度的对应模型,Δf测度具有较偏度系数测度更为优异的对金融资产收益非对称特征的刻画能力。     

Strategic sustainability and financial performance: exploring abnormal returns

The ongoing empirical debate about whether SRI is associated, if anything, with subpar or surpassing financial performance is characterized by a somewhat indistinct focus and the infeasibility of tapping the full potential of existing models. By indistinct focus, we mean an analysis based on an aggregation of a myriad of SRI factors that potentially affect a firm’s financial performance. The inability of taking full advantage of existing models is reflected by the fact that studies with European data have not been able to comprehensively account for systematic risk tilts. This paper presents a portfolio analysis that overcomes these issues by analyzing a distinct selection of small and innovative firms. We argue that both their strategic implementation of Corporate Social Responsibility and the general growth in socially responsible investments (SRI) lend themselves to an explanation for positive abnormal returns of this portfolio. We account for the idiosyncratic investment style of SRI by introducing a comprehensive pan-European risk-adjusted portfolio analysis based on the Carhart four-factor model. A novel propensity score matching method in conjunction with the estimation of structural models completes the conventional robustness checks in the literature.     

A Profit‐Maximizing Approach to Disposition Decisions for Product Returns*

Motivated by the asset recovery process at IBM, we analyze the optimal disposition decision for product returns in electronic products industries. Returns may be either remanufactured for reselling or dismantled for spare parts. Reselling a remanufactured unit typically yields higher unit margins. However, demand is uncertain. A common policy in many firms is to rank disposition alternatives by unit margins. We propose a profit‐maximization approach that considers demand uncertainty. We develop single period and multiperiod stochastic optimization models for the disposition problem. Analyzing these models, we show that the optimal allocation balances expected marginal profits across the disposition alternatives. A detailed numerical study reveals that our approach to the disposition problem outperforms the current practice of focusing exclusively on high‐margin options, and we identify conditions under which this improvement is the highest. In addition, we show that a simple myopic heuristic in the multiperiod problem performs well.     

The Value of Quality Grading in Remanufacturing

In this paper we consider a tactical production‐planning problem for remanufacturing when returns have different quality levels. Remanufacturing cost increases as the quality level decreases, and any unused returns may be salvaged at a value that increases with their quality level. Decision variables include the amount to remanufacture each period for each return quality level and the amount of inventory to carry over for future periods for both returns (unremanufactured), and finished remanufactured products. Our model is grounded with data collected at Pitney‐Bowes from their mailing systems remanufacturing operations. We derive some analytic properties for the optimal solution in the general case, and provide a simple greedy heuristic to computing the optimal solution in the case of deterministic returns and demand. Under mild assumptions, we find that the firm always remanufactures the exact demand in each period. We also study the value of a nominal quality‐grading system in planning production. Based on common industry parameters, we analyze, via a numerical study, the increase in profits observed by the firm if it maintains separate inventories for each quality grade. The results show that a grading system increases profit by an average of 4% over a wide range of parameter values commonly found in the remanufacturing industry; this number increases as the returns volume increases. We also numerically explore the case where there are capacity constraints and find the average improvement of a grading system remains around 4%.     

An Approach to Asset Pricing Under Incomplete and Diverse Perceptions

We model a dynamic, competitive market, where in every period, risk‐neutral traders trade a one‐period bond against an infinitely lived asset, with limited short‐selling of the long‐term asset. Traders lack structural knowledge and use different “incomplete theories,” all of which give statistically correct beliefs about next period's market price of the long‐term asset. The more theories there are in the market, the higher is the equilibrium price of the long‐term asset. Investors with more complete theories do not necessarily earn higher returns than those with less complete ones, who can earn above the risk‐free rate. We provide two necessary conditions for a trader to earn above the risk‐free rate.