技术创业型企业孵化资本投入的风险管控——来自多案例对比

待孵化的技术创业型企业同时具有概念性技术向差异化产品转化的高风险与产品异质性被认同后溢价评估的高收益特点，导致其投资者多处于隔岸观火却欲罢不能的的孵化投资矛盾中。对孵化资本实施有效的风险管控，成为吸引外部资本投入的关键。基于此，选择在可创概念选育与技术创业孵化领域探索出高成功率路径的概念证明中心、YCombinator和创新工场为研究案例，分析其在创业项目筛选、孵化资金运营等关键环节的风险管控方式，以期完善我国孵化资本管控理论、助力我国商业孵化器提高资金风险管控能力、促进外部资本投入。     

Situating the Asian Infrastructure Investment Bank in the context of global economic governance

The creation of the Asian Infrastructure Investment Bank (AIIB)was welcomed by the World Bank but opposed by the Obamaadministration. The paper explains China’s positive relationshipwith the Bank and the Organization for Economic Cooperation andDevelopment (OECD) in terms of the mission of the Bank, sharedby the OECD, to develop and deepen the global economy. The AIIBand the related Belt and Road initiative promise to do this throughinvestment in infrastructure and connectivity in and around thepoorly integrated Eurasian landmass. But while the current Chineseleadership has supported an inclusive global economy based uponfree trade and supported by multilateral institutions, China’s controlof resources outside the multilateral framework and adherence topractices that challenge liberal principles prompt suspicions thatthese commitments are either disingenuous or anyway subjectto reversal. In itself, therefore, the AIIB provides no conclusiveevidence either way on China’s future course.     

家族控制与企业创新投入

家族企业对社会情感财富目标的追求是其区别于非家族企业的重要特性，社会情感财富目标与企业经济利益间冲突对企业R&D投入的影响不容忽视。以社会情感财富为理论基础，基于573家上市家族企业2011-2015年的面板数据，分析受市场化程度影响时，家族涉入情境下信息透明度对企业R&D投入的影响。结果显示：信息透明度可以有效缓解信息不对称和代理冲突，促进企业R&D投入；家族控制对R&D投入有消极影响；当企业信息透明度较高时，会抑制家族所有者为个人谋取私利的动机，进而增强其对企业R&D投资的积极作用。在市场化程度更高、产权保护力度较大的地区，信息透明度会缓解家族控制权对R&D投入的消极作用。     

Large agricultural investments in Kenya’s Nanyuki Area: Inventory and analysis of business models

Many experts agree that more agricultural investment is needed in the global South to improve local food security and reduce poverty. However, there is a lack of consensus about the types of investment needed to achieve these goals. This paper contributes to the literature on large agricultural investments and corresponding business models by inventorying and analysing such investments in Kenya’s Nanyuki area. We identify four clusters of business models that differ primarily by type of production and other distinct determinants, namely: demand from markets; access to land; land tenure regime and colonial history; actors involved; biophysical context; labour availability; and governance of the value chain via private standards. The study results shed light on the factors that help or hinder implementation of large agricultural investments and shape their impacts in the context of African land use systems. The way land is accessed represents one of the most-decisive factors determining the risks and opportunities associated with such projects. We find that most investments in the Nanyuki area occur on land bought or leased from private owners.     

The angel investment decision: insights from Australian business angels

While much has been written about the investment criteria of business angels, few studies explore why these particular criteria are important to them. The Australian context has a diverse range of actors along with complex jurisdictional arrangements, making for an interesting background for investigation of the angel finance phenomenon. We examine 12 business angels in the rapidly changing Australian context and use nine corroborating participants to validate responses and identify four key drivers – personal experience, trust, the need to contribute and realistic expectations – that influence business angels during the initial investment process.     

Institutional quality,investment efficiency,and the choice of public–private partnerships

We examine a sample of 625 public–private partnership (PPP) firms from 1980 to 2015 that straddle nine countries with varying degrees of economic development and PPP markets. We find that the motivations of the firms that undertake PPP investments vary. While private sector firms in economies with low institutional quality choose to engage in PPPs to alleviate capital constraints attributed to underinvestment, those in economies with high institutional quality participate in PPPs to solve the problem of overinvestment due to an abundant cash flow. In the long run, the benefits of lower capital constraints through PPP investments are more pronounced in economies with high institutional quality.     

Do news shocks increase capital utilization?

Using the workweek of capital as a measure of capital utilization, we empirically test whether news shocks actually increase capital utilization. To this end, by estimating a panel VAR on two-digit manufacturing data identifying news shocks as innovations to stock returns orthogonal to the variations in current-period TFP growth, we find the positive response of capital utilization to news shocks. Moreover, to explain the positive response of capital utilization to news shocks in terms of plant-level investment behavior, we propose a heterogeneous plant model that combines the fixed cost of capital adjustment and an endogenous capital utilization choice. With the presence of fixed costs, except for the plants that have recently adjusted capital stock, news shock shortens the effective time horizon of currently installed capital stock and increases capital utilization. When the model economy is calibrated to match the salient features of the plant-level investment rate distribution, the economy generates a news-driven positive response of capital utilization.     

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.     

经济政策不确定性与企业投资趋同行为

文章以2003-2017年A股非金融类上市公司为研究样本,考察经济政策不确定性对企业投资趋同行为的影响。研究发现,经济政策不确定性的升高会显著增强企业投资趋同行为,该影响效应在信息优势企业有所减弱,在资产不可逆程度较高企业有所增强。分行业检验发现,在管制性行业以及景气度较低行业中,经济政策不确定性对企业投资趋同行为的影响减弱。进一步研究发现,在经济政策不确定性不断攀升的背景下,实体投资趋同性会带来更为严重的金融化,特别是在行业实体投资总体趋于放缓的情况下,企业金融化现象更加严重。该研究为宏观经济波动下企业投资趋同行为提供了经验证据。