Data vs. information: Using clustering techniques to enhance stock returns forecasting

This paper explores the use of clustering models of stocks to improve both (a) the prediction of stock prices and (b) the returns of trading algorithms.We cluster stocks using k-means and several alternative distance metrics, using as features quarterly financial ratios, prices and daily returns. Then, for each cluster, we train ARIMA and LSTM forecasting models to predict the daily price of each stock in the cluster. Finally, we employ the clustering-empowered forecasting models to analyze the returns of different trading algorithms.We obtain three key results: (i) LSTM models outperform ARIMA and benchmark models, obtaining positive investment returns in several scenarios; (ii) forecasting is improved by using the additional information provided by the clustering methods, therefore selecting relevant data is an important preprocessing task in the forecasting process; (iii) using information from the whole sample of stocks deteriorates the forecasting ability of LSTM models.These results have been validated using data of 240 companies of the Russell 3000 index spanning 2017 to 2022, training and testing with different subperiods.     

在热电联产企业中精益成本管理的评价指标及应用对策

论文从热电联产企业的特征入手,通过对精益成本管理理论的研究,总结出热电联产企业精益成本管理的评价指标,并通过对指标的分析总结出精益成本管理在热电联产企业实际应用中的管理对策。     

成都市国际化营商环境升级版战略研究--基于万博新经济研究院营商环境指数的分析

打造营商环境是促进经济的重要环节,提升营商环境是增强城市竞争力和吸引力的手段。论文通过引入万博新经济研究院发布的《后疫情时代中国城市营商环境指数评价报告(2020)》,多角度对比分析成都与国内先发城市,发现成都在营商环境方面的优势与短板,最后得出改进措施,旨在为成都打造国际化营商环境提供理论依据。     

Forecasting the volatility of asset returns: The informational gains from option prices

A new class of forecasting models is proposed that extends the realized GARCH class of models through the inclusion of option prices to forecast the variance of asset returns. The VIX is used to approximate option prices, resulting in a set of cross-equation restrictions on the model’s parameters. The full model is characterized by a nonlinear system of three equations containing asset returns, the realized variance, and the VIX, with estimation of the parameters based on maximum likelihood methods. The forecasting properties of the new class of forecasting models, as well as a number of special cases, are investigated and applied to forecasting the daily S&P500 index realized variance using intra-day and daily data from September 2001 to November 2017. The forecasting results provide strong support for including the realized variance and the VIX to improve variance forecasts, with linear conditional variance models performing well for short-term one-day-ahead forecasts, whereas log-linear conditional variance models tend to perform better for intermediate five-day-ahead forecasts.     

“Sensing” the destination: Development of the destination sensescape index

Despite the increasing academic interest in the sensory dimension of the tourist experience, the quantitative empirical research in the field is limited by a lack of measurement instruments for evaluating the sensory stimuli perceived by tourists during a destination visit. The study addresses this gap by developing a composite index to assess the sensory destination panorama, termed as “destination sensescape”. The construct is conceptualised as a formative multidimensional variable with 5 dimensions (visualscape, smellscape, tastescape, soundscape, and hapticscape). The psychometric validity and reliability of the 17 items integrating the formative index were established by a rigorous multi-step procedure based on three empirical studies. The instrument was tested with data collected from visitors of a Mediterranean urban destination. The operationalisation of the destination sensescape construct not only paves the way for future quantitative sensory studies, but also yields a useful tool for Destination Marketing Organisations (DMOs).     

Impact of state-dependent oil price on US stock returns using local projections

In this paper, we investigate the impact of oil prices on both aggregate and industry US real stock returns over the period 1973–2017. The empirical analysis contributes to the related literature introducing a state-dependent oil price (high and low) and the local projections approach. Our main finding is that, depending on the nature of the shock and industry, the negative effects of oil price shocks become exacerbated -and the positive effects get moderated- if oil prices are already high.     

市场化程度对花卉产业组织影响实证分析

以刘易斯市场规模分析框架为基础,采用2008—2014年中国各省区市花卉产业的面板数据,对市场化进程与花卉产业组织的关系进行实证分析,结果表明:市场化程度对企业数量、小企业数量和小企业比例具有正向影响作用,市场化是促进花卉产业组织演化的重要因素,有利于优化花卉产业组织的规模和结构。因此,政府应该从市场组织与制度完善角度维护好市场竞争秩序,企业应该提升核心竞争力而不是简单扩大规模。     

Price discovery and volatility spillover in spot and futures markets: evidences from steel-related commodities in China

The price discovery and spillover effect are significant indicators in futures markets. This study examines the price discovery and spillover effects using vector error correction model and generalized autoregressive conditional heteroskedastic for seven types of steel products in Chinese spot and futures markets. The results show that the price discovery exists in all of steel futures market. It is also confirmed that futures prices in all items are mainly leading spot prices via permanent-transitory and information share. In the results of spillover effects, it is found that wire rod, coking coal, coke and silico-manganese have the effects between spot and futures market. In rebar market, there is the spillover effect from spot to futures. This information about futures prices can help the market participants to make decisions when they predict the spot prices.     

Settlement procedures and stock market efficiency

This study examines why most derivatives markets that settle on the day following expiration choose the opening rather than the closing price as the final settlement price (FSP), whereas most markets that settle on the expiration day select an average rather than a single price as the FSP. Four exogenous changes in the Taiwan Futures Exchange settlement procedures provide an experimental basis for studying the settlement procedures’ impact on underlying assets. Greatest market efficiency is observed when the FSP is determined by a single rather than an average price and hypothesize that manipulation is prevented at the expense of market quality.