When was the U.S. housing downturn predictable? A comparison of univariate forecasting methods

This paper uses three classes of univariate time series techniques (ARIMA type models, switching regression models, and state-space/structural time series models) to forecast, on an ex post basis, the downturn in U.S. housing prices starting around 2006. The performance of the techniques is compared within each class and across classes by out-of-sample forecasts for a number of different forecast points prior to and during the downturn. Most forecasting models are able to predict a downturn in future home prices by mid 2006. Some state-space models can predict an impending downturn as early as June 2005. State-space/structural time series models tend to produce the most accurate forecasts, although they are not necessarily the models with the best in-sample fit.     

Is momentum really momentum?

Momentum is primarily driven by firms' performance 12 to seven months prior to portfolio formation, not by a tendency of rising and falling stocks to keep rising and falling. Strategies based on recent past performance generate positive returns but are less profitable than those based on intermediate horizon past performance, especially among the largest, most liquid stocks. These facts are not particular to the momentum observed in the cross section of US equities. Similar results hold for momentum strategies trading international equity indices, commodities, and currencies.     

A management orientated approach to combination forecasting of tourism demand

Volatility, exponential smoothing, regression and Naïve 2 models are considered singly and in combination in terms of forecasting demand for international tourism. These models generate accurate predictions of tourism flows, but their prime utility is when combined with other models. Usually, models are combined by means of purely statistical criteria. We show that goal programming (GP) offers an alternative, flexible approach to model combination. GP offers planners a practical solution to tourism forecasting problems, since the method is more adaptable than conventional minimisation of prediction error, by permitting practitioners to prioritise a series of management related goals. Forecasters can focus on longer- and short-term goals, minimising forecast under- and over-estimation and/or concentrate on prediction errors in tourism flows at various times of the year.     

The roles of multiple channels in predicting website visits and purchases: Engagers versus closers

In today’s online environment, consumers and sellers interact through multiple channels such as email, search engines, banner ads, affiliate websites and comparison-shopping websites. In this paper, we investigate whether knowing the history of channels the consumer has used until a point of time is predictive of their future visit patterns and purchase conversions. We propose a model in which future visits and conversions are stochastically dependent on the channels a consumer used on their path up to a point. Salient features of our model are: (1) visits by consumers are allowed to be clustered, which enables separation of their visits into intra- and inter-session components, (2) interaction effects between channels where prior visits and conversions from channels impact future inter-session visits, intra-session visits and conversions through a latent variable reflecting the cumulative weighted inventory of prior visits, (3) each channel attracts inter-session and intra-session visits differently, (4) each channel has different association with conversion conditional on a customer’s arrival to the website through that channel, (5) each channel engages customers differently (i.e., keeps the customer alive for a next session or for a next visit within a session), (6) the channel from which there was an arrival in the previous session can have an enhanced ability to generate an arrival for the same channel in the current session (channel persistence), and (7) parsimonious specification for high dimensionality in a low-velocity, sparse-data environment. We estimate the model on easy-to-collect first-party data obtained from an online retailer selling a durable good and find that information on the identities of channels and incorporation of inter- and intra-session visits have significant predictive power for future visitation and conversion behavior. We find that some channels act as “closers” and others as “engagers”—consumers arriving through the former are more likely to make a purchase, while consumers arriving through the latter, even if they do not make a purchase, are more likely to visit again in the future or extend the current session. We also find that some channels engage customers more than others, and that there are interaction effects between the channels visited. Our estimates show that the effect of prior inventory of visits is different from the immediate prior visit, and that visit and purchase probabilities can increase or decrease based on the history of channels used. We discuss several managerial implications of the model including using the predictions of the model to aid in selecting customers for marketing actions and using the model to evaluate a policy change regarding the obscuring of channel information.     

信贷、保险、“信贷+保险”的扶贫效果比较研究

农村金融是农村经济发展的重要内生动力,创新金融扶贫体制对我国农村深度贫困地区的脱贫攻坚工作具有重要意义。本文基于多重均衡模型,对比研究信贷、保险、"信贷+保险"三类金融产品的扶贫效果,在不同的信贷和保险产品结构下得出陷贫概率,进而得出金融扶贫产品的精准设计,以创新金融扶贫体制,从而解决我国深度贫困的问题。研究表明:单独信贷产品扶贫无效;保险能够帮助阈值以上人群摆脱潜在贫困,但对深度贫困无效;"信贷+保险"能解决一定程度的深度贫困问题,比单独信贷或单独保险的扶贫效果更好。     

Volatility Relationship between Crude Oil and Petroleum Products

This paper utilizes calculated historical volatility and GARCH models to compare the historical price volatility behavior of crude oil, motor gasoline and heating oil in U.S. markets since 1990. We incorporate a shift variable in the GARCH/TARCH models to capture the response of price volatility to a change in OPEC’s pricing behavior. This study has three major conclusions. First, there was an increase in volatility as a result of a structural shift to higher crude oil prices after April 1999. Second, volatility shocks from current news are not important since GARCH effects dominate ARCH effects in the variance equation. Third, persistence of volatility in all commodity markets is quite transitory, with half-lives normally being a few weeks.

西北地区发展减灾农业的问题与对策

西北地区自然灾害频发,生态环境日益脆弱,水资源极度缺乏,农业生产受干旱威胁日益加深,发展减灾农业是当务之急。在发展减灾农业的方式上,要突出重点,以抗旱防灾为主,又要根据不同区域灾害特征,探索发展特色减灾模式。文章针对西北地区如何发展减灾农业提出了相关对策。     

行为金融学的研究现状与展望

由心理学家和金融学家共同发展起来的行为金融学越来越引人注目,它以前景理论和各种行为金融模型为代表性成果,能有效分析金融市场中由于心理因素引起的投资者失误偏差和市场异象,是现代金融学理论的有益补充。未来的行为金融学如想成为现代金融理论体系的中心,或作为一门单独学科而存在,必须形成统一的理论基础、严密的分析范式、明确的研究主线、研究对象和研究方法以及建立新的基于行为的核心模型。