Understanding machine learning-based forecasting methods: A decomposition framework and research opportunities

Machine learning (ML) methods are gaining popularity in the forecasting field, as they have shown strong empirical performance in the recent M4 and M5 competitions, as well as in several Kaggle competitions. However, understanding why and how these methods work well for forecasting is still at a very early stage, partly due to their complexity. In this paper, I present a framework for regression-based ML that provides researchers with a common language and abstraction to aid in their study. To demonstrate the utility of the framework, I show how it can be used to map and compare ML methods used in the M5 Uncertainty competition. I then describe how the framework can be used together with ablation testing to systematically study their performance. Lastly, I use the framework to provide an overview of the solution space in regression-based ML forecasting, identifying areas for further research.     

Understanding the trend to mobile-only internet connections:A decomposition analysis

A growing portion of internet users rely solely on mobile devices such as smartphones for their online access. The percentage of “mobile-only” households increased from 9% in 2011 to 20% in 2015, more than doubling in only four years. As this shift continues, it leads to the question of what factors are driving the rise in mobile-only adoption. Using nationally representative data, this study uses logistic regressions and a decomposition technique to understand the trend. The decomposition reveals that a significant portion (65%) of the growth was due to an increase in the download speeds of mobile networks. An increased acceptance of mobile-only access by households aged 55 and older was also partly responsible. Understanding (and developing a response to) the trend towards mobile-only adoption will be important as organizations and governments continue to work to close the digital divide.     

Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis

This paper proposes a quantile variance decomposition framework for measuring extreme risk spillover effects across international stock markets. The framework extends the spillover index approach suggested by Diebold and Yilmaz (2009) using a quantile regression analysis instead of the ordinary least squares estimation. Thus, the framework provides a new tool for further study into the extreme risk spillover effects. The model is applied to G7 and BRICS stock markets, from which new insights emerged as to the extreme risk spillovers across G7 and BRICS stock markets, and revealed how extreme risk spillover across developed and emerging stock markets. These findings have important implications for market regulators.     

The dynamics of ex-ante weighted spread: an empirical analysis

We model the evolution of the ex-ante weighted spread (EWS) embedded in an open Limit Order Book (LOB) and investigate the impact of observed market-related variables on the spread. Our modeling involves decomposing the joint distribution of the weighted spread into simple and interpretable distributions. Our main results have several implications: (i) EWS features high persistence in autocorrelation; (ii) lower-level LOB remains liquid even after a high trade imbalance; (iii) lower- and higher-level LOB react to temporal spread change and trade imbalance in different ways; and (iv) both trade durations and quote durations have seasonality effects. We also show, through a simple high frequency trading exercise, that the use of the model can be economically important. Further, our model provides an estimation of market resilience.     

Business Cycles Synchronisation and Symmetries in the Transition to East African Monetary Union

Our paper explores the prospects for the proposed East African Monetary Union (EAMU) by employing rigorous empirical tools to analyse business cycles synchronisation, structural cross-correlations, spectral decomposition and regional clusters to identify different cyclical episodes, periodicities and characterise the economic cycles of East African countries. We find that cyclical movements reflect various idiosyncratic, common, historical and external shocks in the region. Secondly, all countries appear to be structurally correlated with each other except for South Sudan and Burundi. Our results also observe that the contemporaneous co-movements of East African Community (EAC) cycles with those of Kenya and Tanzaniaare procyclical with coincidental path shift, while the same EAC cycles appear to be acyclical with those of Burundi. Additionally, from the spectral decomposition, Kenyan cycles take 10 years to complete, while those of Tanzania and Rwanda take 8 years. Ugandan and Burundian cycles take approximately 5 years, while the cyclical frequency for South Sudan corresponds to 3.3 years. Finally, the cluster characterisation of countries reveals that South Sudan, Burundi and Rwanda form a group, while Kenya and Tanzania from a group distinct from the rest. We urge the member countries to prioritise policies on regional risk-sharing and adjustment mechanisms, in addition to establishing credible institutional infrastructure that ensures surveillance and enforcement of convergence conditions adopted in EAMU protocol.     

The impact of the introduction and use of an informational website on offline customer buying behavior

Do customers increase or decrease their spending in response to the introduction of an informational website? To answer this question, this study considers the effects of the introduction and use of an informational website by a large national retailer on offline customer buying behavior. More specifically, we study a website's effects on the number of shopping trips and the amount spent per category per shopping trip. The model is calibrated through the estimation of a Poisson model (shopping trips) and a type-II tobit model (the amount spent per category per shopping trip), with effect parameters that vary across customers. For the focal retailer, an informational website creates more bad than good news; most website visitors engage in fewer shopping trips and spend less in all product categories. The authors also compare the characteristics of shoppers who exhibit negative website effects with those few shoppers who show positive effects and thus derive key implications for research and practice.     

中美双边工业品增加值贸易隐含碳福利核算与分配问题研究

现代贸易方式不仅导致贸易利益在全球价值链上进行分配,还带来了贸易隐含污染排放在全球贸易网络中的分布。两国之间的贸易利益分配除了表现为贸易经济福利的分配,还表现为贸易隐含碳福利的分配。本文将贸易增加值分解法结合MRIO模型对2000—2014年中美双边工业品贸易增加值所隐含的碳福利分配及影响机制展开深入分析。研究结果表明:(1)在中美双边工业品增加值贸易隐含碳福利分配中,碳福利逆差在中国,碳福利顺差在美国;(2)中美工业品贸易碳福利级差经历了“先扩大,后收窄”的过程,美国次贷危机之后双边碳福利不平衡状况重新呈现扩大趋势;(3)中国碳排放强度下降、价值链地位提升以及对美进口规模扩大都有助于改善碳福利逆差的局面,但美国对中国不断扩大的中间品和最终品需求以及双边复杂的技术关联结构仍是中国碳福利逆差的主导因素;(4)全球价值链的深化可能将导致对出口国加征关税会通过降低进口消费侧排放的方式恶化加征国的贸易隐含碳福利。本文研究的时间范围同时覆盖中国加入WTO以及美国次贷危机两个重要节点,这对于重新审视中美经贸关系新格局下双边贸易隐含碳福利分配构建了一个新的分析视角,为中美未来贸易谈判以及全球碳排放责任认定提供了一个新的解读方向。     

Limited information-processing capacity and asymmetric stock correlations

Through an orthogonalized impulse-response analysis, I studied the relationship between the variance risk premium, market variance and stock correlations in the French stock market from September 2002 through September 2006, using high-frequency data-based measures. Variance risk premium is estimated using realized variances and index options-implied variances and used as a state vector to proxy investors perceived uncertainty. I found that a shock to variance risk premium causes long-lasting increases in the market variance pointing to the limitedness of investors information-processing capacity. At the same time, the shock generates consecutive increases in realized correlations between individual stocks and the market portfolio. I propose this as a possible explanation for the asymmetric/counter-cyclic behaviour of stock correlations.     

技术差距视角下我国不同性质企业创新效率研究

本文利用共同前沿理论和DEA模型测算分析2005~2010年我国不同性质企业技术创新效率差异、损失来源以及影响机制。结果表明：考察期内我国企业创新效率整体水平偏低,还有42.1%的提升空间,纯技术效率和规模效率均不高。共同前沿下效率值均不超过群组前沿下效率值,TGR值显示,外资、港澳台资与内资企业的技术差距均位于0.2~0.4,且存在差距继续扩大的风险。不同性质企业效率损失根源存在显著差异,港澳台资和外资企业效率缺失主要受制于落后的企业管理水平;内资企业则因生产技术差距和管理不当所造成的效率损失均占有一定比例。企业性质、企业规模、市场竞争程度和政府金融支持对效率提升具有积极影响,企业规模在政府金融支持与效率关系中起负向调节作用。     

An effective hybrid variance reduction method for pricing the Asian options and its variants

In this paper, we propose a variance reduction method that combines importance sampling and control variates to price European Arithmetic Asian options and its variants (i.e., Asian options plus knock-in or knock-out options) under the Black-Scholes model. The numerical results show that the proposed methods are especially efficient under the following scenarios: in the money, low volatility, more sampling dates, and higher barrier thresholds.