Valuation ratios and long‐horizon stock price predictability

Using annual data for 1872–1997, this paper re‐examines the predictability of real stock prices based on price–dividend and price–earnings ratios. In line with the extant literature, we find significant evidence of increased long‐horizon predictability; that is, the hypothesis that the current value of a valuation ratio is uncorrelated with future stock price changes cannot be rejected at short horizons but can be rejected at longer horizons based on bootstrapped critical values constructed from linear representations of the data. While increased statistical power at long horizons in finite samples provides a possible explanation for the pattern of predictability in the data, we find via Monte Carlo simulations that the power to detect predictability in finite samples does not increase at long horizons in a linear framework. An alternative explanation for the pattern of predictability in the data is nonlinearities in the underlying data‐generating process. We consider exponential smooth‐transition autoregressive models of the price–dividend and price–earnings ratios and their ability to explain the pattern of stock price predictability in the data. Copyright © 2005 John Wiley & Sons, Ltd.     

The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning

Whether investor sentiment affects stock prices is an issue of long-standing interest for economists. We conduct a comprehensive study of the predictability of investor sentiment, which is measured directly by extracting expectations from online user-generated content (UGC) on the stock message board of Eastmoney.com in the Chinese stock market. We consider the influential factors in prediction, including the selections of different text classification algorithms, price forecasting models, time horizons, and information update schemes. Using comparisons of the long short-term memory (LSTM) model, logistic regression, support vector machine, and Naïve Bayes model, the results show that daily investor sentiment contains predictive information only for open prices, while the hourly sentiment has two hours of leading predictability for closing prices. Investors do update their expectations during trading hours. Moreover, our results reveal that advanced models, such as LSTM, can provide more predictive power with investor sentiment only if the inputs of a model contain predictive information.     

Forecasting commodity prices out-of-sample: Can technical indicators help?

Economic variables are often used for forecasting commodity prices, but technical indicators have received much less attention in the literature. This paper demonstrates the predictability of commodity price changes using many technical indicators. Technical indicators are stronger predictors than economic indicators, and their forecasting performances are not affected by the problems of data mining or time changes. An investor with mean–variance preference receives utility gains of between 104.4 and 185.5 basis points from using technical indicators. Further analysis shows that technical indicators also perform better than economic variables for forecasting the density of commodity price changes.     

An exploration of factors influencing the choice of commodity price risk mitigation strategies

Most firms are exposed to price volatility associated with commodities, which can significantly affect the price paid for raw materials, energy, packaging, shipping, and component purchases. Commodity price risk represents the financial, operational and informational effects of commodity price volatility (CPV). The purpose of this paper is to contribute to the supply chain risk management literature by providing a taxonomy of commodity price risk mitigation strategies and factors that may influence the adoption of these strategies. A qualitative study was conducted using a grounded theory approach, based on case studies of companies with home operations in Italy, Germany, and the US. The paper provides some initial evidence for theory and practice as to: 1) how firms can mitigate the risk from CPV by implementing various sourcing, contracting, and financing strategies; and 2) the influence of commodity/product factors, buying organization factors, supply chain factors, and external environment factors on strategy capability and choice.     

浅析房价虚高对经济的影响

近期房价过高已成为人们热点关注的一个话题。过高的房价会给经济带来一系列的负面影响。首先,人们为了还银行贷款而降低了自己的边际消费倾向,使得消费品需求不足,这样将大大抵消投资扩张对经济增长的拉动作用。其次,被归还的大量银行贷款又被用于投资。这样更会加剧经济过热,拉动生产资料的价格,从而造成国内需求结构不合理的局面。最为重要的一点是,由于投资造成的货币供应的持续增加,很容易造成通货膨胀,而且现在已经有这种倾向了。房价过高的原因在于供给需求结构不合理,高价房供应太多,经济房严重不足,应该利用税收调整使其趋向合理。     

Forecasting inflation using commodity price aggregates

This paper shows that for five small commodity-exporting countries that have adopted inflation targeting monetary policies, world commodity price aggregates have predictive power for their CPI and PPI inflation, particularly once possible structural breaks are taken into account. This conclusion is robust to using either disaggregated or aggregated commodity price indexes (although the former perform better), the currency denomination of the commodity prices, and to using mixed-frequency data. In pseudo out-of-sample forecasting, commodity indexes outperform the random walk and AR(1) processes, although the improvements over the latter are sometimes modest.     

Forecasting China's foreign exchange reserves using dynamic model averaging: The roles of macroeconomic fundamentals,financial stress and economic uncertainty

We develop models for examining possible predictors of growth of China's foreign exchange reserves that embrace Chinese and global trade, financial and risk (uncertainty) factors. Specifically, by comparing with other alternative models, we show that the dynamic model averaging (DMA) and dynamic model selection (DMS) models outperform not only linear models (such as random walk, recursive OLS-AR(1) models, recursive OLS with all predictive variables models) but also the Bayesian model averaging (BMA) model for examining possible predictors of growth of those reserves. The DMS is the best overall across all forecast horizons. While some predictors matter more than others over the forecast horizons, there are few that stand the test of time. The US–China interest rate differential has a superior predictive power among the 13 predictors considered, followed by the nominal effective exchange rate and the interest rate spread for most of the forecast horizons. The relative predictive prowess of the oil and copper prices alternates, depending on the commodity cycles. Policy implications are also provided.     

Can structural change explain the Meese-Rogoff puzzle?

This paper provides empirical evidence suggesting that fundamentals matter for stock price fluctuations once temporal instability underpinning stock price-relations is accounted for. Specifically, this study extends the out-of sample forecasting methodology of Meese and Rogoff (J Int Econ 14:3–24 (1983)) to the stock market after explicitly testing for parameter nonconstancy using recursive techniques. The predictive ability of a present value model based on Imperfect Knowledge Economics (IKE) is found to match that of the pure random walk benchmark at short forecasting horizons and to perform significantly better at medium to longer-run horizons based on conventional measures of predictability and direction of change statistics. In addition, the presence of a cointegrating relation is found only within regimes of statistical parameter constancy. Augmenting the MR methodology in a piecewise linear fashion yields empirical results in favor of a fundamentals-based account of stock price behavior overturning the recent results of Flood and Rose (2010).     

The quantilogram: With an application to evaluating directional predictability

We propose a new diagnostic tool for time series called the quantilogram. The tool can be used formally and we provide the inference tools to do this under general conditions, and it can also be used as a simple graphical device. We apply our method to measure directional predictability and to test the hypothesis that a given time series has no directional predictability. The test is based on comparing the correlogram of quantile hits to a pointwise confidence interval or on comparing the cumulated squared autocorrelations with the corresponding critical value. We provide the distribution theory needed to conduct inference, propose some model free upper bound critical values, and apply our methods to S&P500 stock index return data. The empirical results suggest some directional predictability in returns. The evidence is strongest in mid range quantiles like 5–10% and for daily data. The evidence for predictability at the median is of comparable strength to the evidence around the mean, and is strongest at the daily frequency.     

Nonparametric methods and local‐time‐based estimation for dynamic power law distributions

This paper introduces nonparametric econometric methods that characterize general power law distributions under basic stability conditions. These methods extend the literature on power laws in the social sciences in several directions. First, we show that any stationary distribution in a random growth setting is shaped entirely by two factors: the idiosyncratic volatilities and reversion rates (a measure of cross‐sectional mean reversion) for different ranks in the distribution. This result is valid regardless of how growth rates and volatilities vary across different economic agents, and hence applies to Gibrat's law and its extensions. Second, we present techniques to estimate these two factors using panel data. Third, we describe how our results imply predictability as higher‐ranked processes must on average grow more slowly than lower‐ranked processes. We employ our empirical methods using data on commodity prices and show that our techniques accurately describe the empirical distribution of relative commodity prices. We also show that rank‐based out‐of‐sample forecasts of future commodity prices outperform random‐walk forecasts at a 1‐month horizon.     

THE EMPIRICAL MERIT OF STRUCTURAL EXPLANATIONS OF COMMODITY PRICE VOLATILITY: REVIEW AND PERSPECTIVES

This paper presents both the history of and state‐of‐the‐art in empirical modeling approaches to the world commodity price volatility. The analysis builds on the storage model and key milestones in its development. Specifically, it is intended to offer a reader unfamiliar with the relevant literature an insight into the modeling issues at stake from both a historical and speculative viewpoint. The review considers primarily the empirical techniques designed to assess the merits of the storage theory; it does not address purely statistical approaches that do not rely on storage theory and that have been studied in depth in other streams of the commodity price literature. The paper concludes with some suggestions for future research to try to resolve some of the existing empirical flaws, and hopefully to increase the explanatory power of the storage model.     

The risk spillover between China’s economic policy uncertainty and commodity markets: Evidence from frequency spillover and quantile connectedness approaches

Based on the frequency spillover method extended by Baruník and Křehlík (2018), we explore the risk spillover relationship between China’s economic policy uncertainty (CNEPU) and commodity futures in different frequency domains with daily settlement price data of 14 commodity futures in China. The results show that the risk spillover relationship between CNEPU and the commodity market mainly occurs in the short term. Quantile connectedness results show that economic policy uncertainty, which mainly plays the role of risk transmitter, is more closely related to the commodity market during the market boom and recession. Soybeans, soybean meal, and corn have shown high investment value in the process of market recovery, which is exposed to less risk spillover from policy uncertainty. Finally, the economic crisis with different characteristics will have specific impacts on asymmetric risk spillovers based on certain impact mechanisms.     

Monetary general equilibrium with transaction costs

Commodity money arises endogenously in a general equilibrium model with separate budget constraints for each transaction. Transaction costs imply differing bid and ask (selling and buying) prices. The most liquid good—with the smallest proportionate bid/ask spread—becomes commodity money. General equilibrium may not be Pareto efficient. If zero-transaction-cost money is available then the equilibrium allocation is Pareto efficient. Fiat money is an intrinsically worthless instrument. Its positive price comes from acceptability in paying taxes, and its use as a medium of exchange is based on low transaction cost.     

Do house price developments spillover across euro area countries? Evidence from a global VAR

This paper empirically assesses the prospects for house price spillovers in the euro area, where co-movement in house prices across countries may be particularly relevant given a general trend with monetary union toward increasing linkages in trade, financial markets, and general economic conditions. A global VAR is estimated for three housing demand variables (real house prices, real per capita income, and the cost of borrowing, captured by a real long-term interest rate) on the basis of quarterly data for 7 euro area countries (Belgium, Germany, Ireland, Spain, France, Italy and the Netherlands), which together comprise nearly 90% of euro area GDP, over the period 1971–2009. The results suggest limited house price spillovers in the euro area, albeit with evidence of some overshooting in the first year after the shock, followed by a long run aggregate euro area impact of country-specific changes in real house prices related in part to the country’s economic weight. This contrasts with the impacts of a shock to domestic long-term interest rates, causing a permanent shift in house prices after 2–3 years. Underlying this aggregate development are rather heterogeneous house price spillovers at the country level, with a strong importance for weights – either economic or geographic – in governing their general magnitude. More generally, the impact of financing costs on house prices appears to have grown though time.     

Long-run risk-return trade-offs

Excess market returns are correlated with past market variance. This dependence is statistically mild at short horizons (thereby leading to a hard-to-detect risk-return trade-off, as in the existing literature) but increases with the horizon and is strong in the long run (i.e., between 6 and 10 years). From an econometric standpoint, we find that the long-run predictive power of past market variance is robust to the statistical properties of long-horizon stock-return predictive regressions. From an economic standpoint, we show that, when conditioning on past market variance, conditional versions of the traditional CAPM and consumption-CAPM yield considerably smaller cross-sectional pricing errors than their unconditional counterparts.     

Forecasting economic activity from yield curve factors

This paper provides clear-cut evidence that the slope and curvature factors of the term structure of interest rates (yield curve) contain more information about future changes in economic activity than the term spread itself, often used in the literature as a predictive regressor of economic activity. These two factors reflect different information about future economic activity, which is smoothed out by the term spread. The paper shows that the slope factor has predictive power on future economic activity over longer horizons ahead, and thus may be interpreted as reflecting future business cycle conditions. On the other hand, the curvature factor, which enters the term spread with opposite sign than the slope factor, has predictive power on shorter movements of future economic activity which may be associated with changes in the current stance of monetary policy. These results hold for a number of world developed economies.     

会计信息质量与市场定价分析

本文以应计质量、盈余持续性、盈余可预测性、盈余平滑度作为会计信息质量的代理变量,通过研究会计信息不同纬度的质量与权益资本成本之间的关系,为投资者的市场定价及对信息质量的关注程度提供证据。研究结果表明,除盈余的持续性不显著外,其他各项质量与权益资本成本之间均呈负相关关系;在对权益资本成本的影响程度方面,无论是单独影响还是条件影响,应计质量影响程度最大,其次是可预测性。     

北京地区与全国总体经济增长阶段性特点的比较分析

本文以GDP增长指数、消费者价格指数、商品零售价格指数等指标为对象,以全国总体为参照．研究了北京地区经济增长和经济波动的特点,以及与全国变动的同步性、相关性。其主要结论如下：（1）北京的经济增长速度高于全国;（2）在剔除1981年异常值后,北京年经济增长率分布的集中程度并不低于全国;（3）北京与全国的经济增长都表现出显著的阶段特征,北京经济增长路径可能发生了上移．而且上移的幅度可能要大于全国．上移的时间要早于全国。     

Exchange rates and monetary fundamentals: what do we learn from long-horizon regressions?

The use of a new bootstrap method for small-sample inference in long-horizon regressions is illustrated by analysing the long-horizon predictability of four major exchange rates, and the findings are reconciled with those of an earlier study by Mark ( 1995 ). While there is some evidence of exchange rate predictability, contrary to earlier studies, no evidence is found of higher predictability at longer horizons. Additional evidence is presented that the linear VEC model framework underlying the empirical study is likely to be misspecified, and that the methodology for constructing bootstrap p-values for long-horizon regression tests may be fundamentally flawed. Copyright © 1999 John Wiley & Sons, Ltd.     

COMPETITION LAW AND COMMODITY MARKETS: THE CASE OF WHOLESALE ELECTRICITY

This paper considers some of the challenges that the exercise of market power in commodity markets poses for public policy, focusing on the case of wholesale electricity. The particular economic characteristics of electricity markets can give rise to market conditions where the price elasticities of both demand and supply are very low. Under such conditions, it may not be necessary for a supplier to have control over a large share of available capacity to be able to exercise substantial market power. This paper questions whether the two principal existing forms of supervision of these markets, Competition Law and financial regulation, are sufficient to address the types of problems that can be expected to arise given these characteristics. The answer to that question is in the negative.