Conditional Mandates on Management Earnings Forecasts: The Impact on the Cost of Debt

Exploiting a unique conditional disclosure mandate on management earnings forecasts (MEFs) in China, we examine the differential effects of voluntary and mandatory MEFs on the cost of debt. We find that firms providing voluntary MEFs have lower cost of debt than do mandatory forecasters and nonforecasters. The results of the channel analyses reveal that voluntary forecasters have greater commitment to voluntary MEFs in future periods than do mandatory forecasters and nonforecasters, and the precision, accuracy, and timeliness of MEFs are higher for voluntary forecasters than for mandatory forecasters. Additional analyses show that the differential effects of voluntary and mandatory MEFs on cost of debt are stronger for voluntary forecasters operating in opaque information environments, issuing high-quality and confirming forecasts, controlled by private shareholders, and operating in highly competitive product markets. Overall, our results indicate that, compared with mandatory MEFs, voluntary MEFs are more informative for credit investors, particularly for firms facing greater information risk and operating uncertainty.     

Size and information revelation in securities trading

We examine differences in information content between order submission sizes and trade sizes by U.S. equity traders. Increasing (decreasing) order submission (trade) size is reflective of information. The result suggests that better-informed traders want to trade in a large size, but that they engage in stealth trading practices or break larger orders into smaller sizes in order to conceal information. While prior studies tend to narrowly focus on trade executions at the market-centre level, our findings indicate that order submission size varies significantly from trade size and that both sizes are informative about future prices, albeit in an inverse manner.     

Persistence of Price–Cost Margin and Technical Efficiency in the Indonesian Food and Beverage Industry

Abstract

This research investigates the persistence of price–cost margin (PCM) and technical efficiency (TE) of firms and the relation between these two factors in 44 subsectors of the Indonesian food and beverage industry in the period 1980–2014. Data envelopment analysis with a bootstrapping approach is applied to estimate TE. An autoregressive model, accounting for endogeneity, is applied to estimate the persistence coefficients of PCM and TE. A cross-sectional regression model is also applied to estimate the relation between the persistence of the PCM and the persistence of TE. The results show that for these food and beverage firms, high PCM and low TE persist. Furthermore, the persistence of PCM negatively affects the persistence of TE in the industry.     

Operating cash flow asymmetric timeliness in Australia

Operating cash flow (CFO) asymmetric timeliness occurs when CFO reflects bad news more quickly than good news. We examine the presence and determinants of CFO asymmetric timeliness in Australia, where substantial differences in reporting requirements of cash flow components, in characteristics of listed companies and in the degree of conservative financial reporting produce contrasting findings to those in the United States. We find supportive evidence for the novel ‘sticky cost behaviour’ explanation and also the product-pricing strategy, but not the life cycle hypothesis. These findings are useful for investors and analysts concerned with forecasting the future values of companies.     

Politically connected boards,family and business group affiliations,and cost of capital: Evidence from Indonesia

We investigate the effect of politically connected boards (both supervisory boards [SBs] and boards of directors [BODs]) on cost of debt and equity capital of listed companies in Indonesia which has established a two-tier corporate governance system. The results, based on 250 firms, suggest that companies with politically connected SBs experience lower cost of debt and equity capital, whereas politically connected BODs have no association with cost of either debt or equity. Furthermore, we find that family firms and firms belonging to business groups with politically connected SBs enjoy lower cost of debt and equity capital. Our main results are robust to alternative measures and to tests for endogeneity.     

Beta and firm age

We document a robust pattern of beta declining over the age of a firm. We find that changes in systematic risk via firm characteristics and life-cycle stages are insufficient to explain this pattern. Moreover, standard proxies for the quantity and quality of information also explain this pattern only partially. To fully explain this pattern we rely on the increasingly important role of familiarity in financial decision making: familiarity is a determinant of beta and firm age is a proxy for the degree of familiarity that investors feel toward individual stocks. To illustrate the implication of our findings, we document that when we control for firm age there is support for the CAPM and its use as an input for the cost of equity capital calculation.     

High frequency momentum trading with cryptocurrencies

Over the past few years, cryptocurrencies have increasingly been discussed as alternatives to traditional fiat currencies. These digital currencies have garnered significant interest from investment banks and portfolio managers as a potential option to diversify the financial risk from investing in other assets. This interest has also extended to the general public who have seen cryptocurrencies as a way of making a quick profit. This paper provides a first insight into the applicability of high frequency momentum trading strategies for cryptocurrencies. We implemented two variations of a signal-based momentum trading strategy: (i) a time series method; (ii) a cross sectional method. These strategies were tested on a selection of seven of the largest cryptocurrencies ranked by market capitalization. The results show that there exists potential for the momentum strategy to be used successfully for cryptocurrency trading in a high frequency setting. A comparison with a passive portfolio strategy is proposed, which shows abnormal returns when compared with the momentum strategies. Furthermore, the robustness of our results are checked through the application of the momentum strategies other sample periods. We also compare the performances of the signal-based momentum strategies with returns-based versions of the strategies. It is shown that the signal-based strategy outperforms the returns-based strategy. However, there appears to be no single parameterization of the signal-based strategies that can generate the greatest cumulative return over all sample periods.     

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.     

复杂山区铁路客运站自动选址研究

无备选站址条件下的客运站自动选址是线站协同优化的前提和基础,而不局限于车站选址的代价最小化,同时考虑连接车站间区间线路的代价具有重要意义。构建复杂山区铁路客运站自动选址模型,首先,建立综合地理信息模型,基于线站一体化的设计理念,实现单个车站选址,确定站心位置及站坪方向;其次,以公路线形优化模型的改进算法完成站—站间自动选线设计;最后,将车站选址代价与区间线路代价紧密结合起来,计算综合代价,实现站址方案的优选。以山区铁路为例对该方法进行验证,结果表明,该方法能高效生成山区铁路车站方案集,并辅助设计人员进行方案优化。     

基于库存理论的铁路始发直达运输产品设计

将库存理论运用到铁路始发直达运输产品设计,能够有效实现运输服务组织成本与库存成本的有机统一。为实现库存成本在铁路始发直达运输中的加载,在考虑周期非完整情况下的库存成本的同时,将铁路运输和库存成本纳入同一目标函数,在装卸车地库存能力约束下,构建基于库存理论的铁路始发直达运输产品设计模型,确定成本最小的铁路始发直达运输产品设计方案。以赤峰地区至山东省煤炭运输网络为例,设计方案有效降低了成本,有助于吸引客户选择铁路运输,以及辅助铁路运营单位研究调整始发直达运输产品方案。