Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

新发展格局视野中的消费券发放问题与重构研究

2020年面对新冠肺炎疫情冲击,各地纷纷发放消费券刺激消费。本轮发放消费券的省市和规模远超以往。考察当前各地消费券的实践,其存在三方面的问题:短期刺激消费与构建发展新格局缺乏衔接、地方各自为政与顶层设计阙如、财政补贴与财政约束的张力。针对这些问题,本文从新发展格局视野提出将当前消费券重构为财政和金融融合的消费金融券,使之成为构建新发展格局中扩大内需的长期政策和重要的宏观调控工具。消费金融券的制度设计要与社会结构新特征和新趋势相契合。针对低收入群体的消费金融券,应以财政补贴为主、以重大生活项目消费的利息补贴与信用担保为辅。针对中等收入群体的消费金融券,应以利息补贴为主,通过消费金融的方式扩大消费。加大消费金融券的全国顶层设计,明确中央和地方财政支持产业的范围和力度。     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

Financial scandals: a historical overview

I examine the incidence of fraud from c.1720 to 2009 and relate it to the occurrence of significant financial scandals. Focusing on the UK, and US prior to Enron, and using a detailed dataset of significant events and news content, underpinned by examination of specific watershed scandals, the paper highlights the regulatory response to scandals and the implications for accounting and financial reporting. The evidence reveals the incidence of fraud and financial scandal to be historically contingent and skewed towards certain sectors, particularly banking and finance, facilitated by complex group structures and international capital mobility, and mediated by managerial incentives and ownership concentration. Financial reporting and auditing can mitigate fraud opportunities in all sectors and businesses without complex group structures, and the accounting profession achieved some success in this respect up to the mid-1970s. Since then, the profession has been increasingly challenged by, and to some degree implicated in, the development of interconnected and international business networks, which, combined with wider financial deregulation, has led to a resurgence of fraud and financial scandal not previously experienced since the mid-nineteenth century.     

Cross-border exchanges and volatility forecasting

We test for the performance of a series of volatility forecasting models (GARCH 1,1; EGARCH 1,1; CGARCH) in the context of several indices from the two oldest cross-border exchanges (Euronext; OMX). Our findings overall indicate that the EGARCH (1,1) model outperforms the other two, both before and after the outbreak of the global financial crisis. Controlling for the presence of feedback traders, the accuracy of the EGARCH (1,1) model is not affected, something further confirmed for both the pre and post crisis periods. Overall, ARCH effects can be found in the Euronext and OMX indices, with our results further indicating the presence of significant positive feedback trading in several of our tests.     

Lend me your wallets: the effect of charismatic leadership on external support for an organization

We argue that charismatic leadership can influence external support for the organization, particularly in making the company more attractive to outside investors. Two studies were conducted to test this general hypothesis. First, an archival study demonstrated that the stock of companies headed by charismatic leaders appreciated more than the stock of comparable companies, even after differences in corporate performance were controlled. It was also found that the effect of charismatic leadership was heightened under more difficult economic conditions. Second, an experiment was conducted in which the salience of charismatic leadership was manipulated, along with information about the prospects for an organization's turnaround. Results showed that appeals from a charismatic leader led to increased investment in the firm, and the leader's influence was greater when the prospects for an organizational turnaround were more difficult. It was also found that an endowment of stock enhanced the influence of charismatic appeals and that charismatic leadership may have affected the general risk propensities of followers. These findings were interpreted in terms of an external perspective on leadership, illustrating how leaders can manage the firm's economic and social environment. Copyright © 2004 John Wiley & Sons, Ltd.     

公司业绩与财务杠杆

本文从实证角度分析了我国上市公司的财务杠杆对公司业绩的影响。结果表明,往年财务杠杆和当年财务杠杆对当年公司业绩的影响截然相反。财务杠杆对公司的息税后收益和息税前收益均有影响。长期负债率和长期借款率对公司业绩的影响分别比同年的流动负债率和短期借款率对公司业