Prediction and control under uncertainty: Outcomes in angel investing

Venture investing plays an important role in entrepreneurship not only because financial resources are important to new ventures, but also because early investors help shape the ventures' managerial and strategic destiny. In this study of 121 angel investors who had made 1038 new venture investments, we empirically investigate angel investors' differential use of predictive versus non-predictive control strategies. We show how the use of these strategies affects the outcomes of angel investors. Results show that angels who emphasize prediction make significantly larger venture investments, while those who emphasize non-predictive control experience a reduction in investment failures without a reduction in their number of successes.     

The Predictive Power of Credit Spread for Macroeconomic Changes

在以前学者研究的基础上,本文对信用价差对宏观经济变量的预测模型进行了改进,首次将不同信用等级企业债的信用价差引入模型,并利用国内银行间债券市场的交易数据进行了实证检验,结果表明较之基于利率期限结构和基于信用价差的宏观经济模型,该模型对宏观经济变量的变动有更好的解释和预测能力。本文同时构建了基于协整理论的长期均衡模型,进行了脉冲响应分析,结果表明长期企业债信用价差对宏观经济变量变动的解释和预测能力较稳定。在此研究基础上,本文提出了一定的政策建议。     

链路预测视角下京津冀现代制造业产业转移路径研究

产业转移是经济发展到一定程度的必然趋势。在我国经济新常态下,提出了通过产业转移提升产业结构、消除区域间经济发展不平衡的命题。传统产业转移理论主要利用局部数据和还原论研究方法,而区域产业转移机理和路径研究具有高度非线性系统特征,因而适用性不佳。因此,基于投入-产出数据构建区域产业复杂网络,利用网络特征值反映产业部门在价值链上的影响力和脆弱性,并根据链路预测理论对京津冀地区现代制造业产业转移路径进行分析。仿真结果表明,适合京津冀协同发展的产业转移路径包括优化配置路径、产业融合路径和产能淘汰路径。     

建设深圳iDEN数字集群专网一期工程的无线覆盖预测

iDEN是数字集群通信系统，属蜂窝通信体制，测算好其无线覆盖，对完成通信网规划和保证通信质量至关重要。本文给出深圳iDEN数字集群专网无线覆盖的预测，对同类通信网建设与工程规划有参考价值。     

A two-stage segment and prediction model for mortgage prepayment prediction and management

Predicting the risk of mortgage prepayments has been the focus of many studies over the past three decades. Most of these works have used single prediction models, such as logistic regressions and survival models, to seek the key influencing factors. From the point of view of customer relationship management (CRM), a two-stage model (i.e., the segment and prediction model) is proposed for analyzing the risk of mortgage prepayment in this research. In the first stage, random forests are used to segment mortgagors into different groups; then, a proportional hazard model is constructed to predict the prepayment time of the mortgagors in the second stage. The results indicate that the two-stage model predicts mortgage prepayment more accurately than the single-stage model (non-segmentation model).     

Treating and Pruning: New approaches to forecasting model selection and combination using prediction intervals

We propose a new way of selecting among model forms in automated exponential smoothing routines, consequently enhancing their predictive power. The procedure, here addressed as treating, operates by selectively subsetting the ensemble of competing models based on information from their prediction intervals. By the same token, we set forth a pruning strategy to improve the accuracy of both point forecasts and prediction intervals in forecast combination methods. The proposed approaches are respectively applied to automated exponential smoothing routines and Bagging algorithms, to demonstrate their potential. An empirical experiment is conducted on a wide range of series from the M-Competitions. The results attest that the proposed approaches are simple, without requiring much additional computational cost, but capable of substantially improving forecasting accuracy for both point forecasts and prediction intervals, outperforming important benchmarks and recently developed forecast combination methods.     

Prediction market prices under risk aversion and heterogeneous beliefs

In this paper, we examine the properties of prediction market prices when risk averse traders have heterogeneous beliefs in state probabilities. We show that the equilibrium state prices equal the mean beliefs of traders about that state if and only if the traders’ common utility function is logarithmic. We also provide a necessary and sufficient condition ensuring that the state prices are systematically below or above the mean beliefs of traders, thus providing a rational explanation to the favorite-longshot bias in prediction markets.     

Prediction after IV estimation

In the context of a single equation in a system of simultaneous equations there is evidently some confusion in the literature as to the correct approach to the problem of prediction. Here we explore this problem and compare three different approaches to it. We also relate this discussion to current practice.     

EVALUATING ALTERNATIVE REPRESENTATIONS OF THE CHOICE SETS IN MODELS OF LABOR SUPPLY

Abstract.  During the last two decades, the discrete choice modeling of labor supply decisions has become increasingly popular. Within the literature adopting this approach, however, there are two potentially important issues that so far have not been given the attention they might deserve. A first issue concerns the procedure by which the discrete alternatives are selected to enter the choice set. Most authors choose (not probabilistically) a set of fixed points identical for every individual. Some authors adopt instead a sampling procedure and also assume that the choice set may differ across households. A second issue concerns the availability of the alternatives. Most authors assume all the values of hours of work within some range are equally available. At the other extreme, some authors assume only two or three alternatives (for example, nonparticipation, part-time and full-time) are available for everyone. Some studies account instead for the fact that not all the hour opportunities are equally available to everyone specifying a probability density function of opportunities for each individual. In this paper we explore by simulation the implications of (i) the procedure used to build the choice set (fixed alternatives versus sampled alternatives); (ii) accounting or not accounting for a different availability of alternatives. The results of the evaluation performed in this paper show that the way the choice set is represented has little impact on the fitting of observed values, but a more significant and important impact on the out-of-sample prediction performance. Thus, the treatment of the choice sets might have a crucial effect on the result of policy evaluations.     

可转移发展权对于土地开发量影响研究——以武汉市洪山区为例

根据可转移发展权项目供给区(sending zone)与需求区(receiving zone)的选取原则,以武汉市洪山区为实证区域,选择具体的可转移发展权项目供给区与需求区,基于博弈思想建立可转移发展权供给区与需求区的开发量预测模型,分别求取未设置可转移发展权和设置可转移发展权后的土地开发量,并进行比较,得出可转移发展权项目的设置不一定会导致开发量的增加的结论,而开发量的变化则受到供给区与需求区面积比,供给区与需求区的土地收益情况,土地的开发建筑成本等因素的影响。