Evaluation of current research on stock return predictability

The results of recent replication studies suggest that false positive findings are a big problem in empirical finance. We contribute to this debate by reviewing a sample of articles dealing with the short-term directional forecasting of the prices of stocks, commodities, and currencies. Screening all relevant articles published in 2016 by one of the 96 journals covered by the Social Sciences Citation Index in the category “Business, Finance,” we select only those studies that use easily accessible data of daily or higher frequency. We examine each study in detail, from the selection of the dataset to the interpretation of the results. We also include empirical analyses to illustrate the shortcomings of certain approaches. There are three main findings from our review. First, the number of selected papers is very low, which is surprising even when the strict selection criteria are taken into account. Second, there are hardly any relevant studies that use high-frequency data—despite the hype about financial big data and machine learning. Third, the economic significance of the findings—for example, their usefulness for trading purposes—is questionable. In general, apparently good forecasting performance does not translate into profitability once realistic transaction costs and the effect of data snooping are taken into account. Other typical problems include unsuitable benchmarks, short evaluation periods, and nonoperational trading strategies.     

Examining Conditions that Influence Evaluation use within a Humanitarian Non-Governmental Organization in Burkina Faso (West Africa)

Program evaluation can support capacity building and inform practice and policy. Yet long-term efforts to ensure evaluation use (EU) in the humanitarian sector are seldom documented, leaving much uncertainty about EU conditions. This study examined conditions that influenced EU by stakeholders of a humanitarian non-governmental organization (NGO) in Burkina Faso striving to base its health care program on solid evidence. It used 36 qualitative semi-structured interviews and a single case study design to document stakeholders’ (n?=?26) perception of EU conditions. Analyses focussed on characteristics of five broad conditions of research use previously documented. Results demonstrate that EU was facilitated by intended users with proactive attitudes, research experience, and willingness to participate in program evaluations. Also helpful was an organizational culture that valued learning, feedback, and accountability, wherein leaders collaborated toward common goals. Evaluation-based knowledge that met information needs and that was actionable, contextualized, and quickly accessible enhanced EU. Knowledge transfer strategies promoting EU were diverse, participatory, adapted to needs, and regularly followed up. Evaluators who were trusted, experienced, credible, and adaptable, promoted EU most effectively. Conversely, EU was compromised when intended users felt distrusting, uninformed, or unable to engage in program evaluations. Knowledge contradicting expectations or deemed inapplicable impeded EU. Adapting knowledge transfer strategies required time and interactions. Initially, evaluations were not sufficiently adapted and put into plain language, which hampered EU. EU conditions are numerous and intricately interrelated, but interpersonal relationships, trust, and effective communication are key conditions for evaluators and stakeholders wishing to promote EU.

     

多笔画联机手写字符识别的动态时间规正算法

在单笔画符号(或字符)联机手写识别中,动态时间规正(DTW)算法遵循时间次序约束和边界约束,并具有较高的识别率.为了将此算法应用于多笔画符号识别,常用而简单的方法是按照人们的手写顺序连接多笔画符号为单笔画符号.但此方法存在一个问题:人们常使用不同的笔画顺序和笔画方向书写同一个符号,用朴素(Brute Force)方法寻找所有笔画可能性非常耗时.为了降低计算复杂度,文中提出了DTW A*算法.在部分笔画匹配时,此算法保留着次序约束,并用A*算法降低计算复杂度.文中还通过流程图数据库多笔画符号识别实验对比了DTW A*算法、DTW算法、改良Hausdorff距离3种算法的性能,结果表明DTW A*算法具有最高的识别率和最好的稳定性.     

Second‐Generation Prediction Markets for Information Aggregation: A Comparison of Payoff Mechanisms

Initial applications of prediction markets (PMs) indicate that they provide good forecasting instruments in many settings, such as elections, the box office, or product sales. One particular characteristic of these ‘first‐generation’ (G1) PMs is that they link the payoff value of a stock's share to the outcome of an event. Recently, ‘second‐generation’ (G2) PMs have introduced alternative mechanisms to determine payoff values which allow them to be used as preference markets for determining preferences for product concepts or as idea markets for generating and evaluating new product ideas. Three different G2 payoff mechanisms appear in the existing literature, but they have never been compared. This study conceptually and empirically compares the forecasting accuracy of the three G2 payoff mechanisms and investigates their influence on participants' trading behavior. We find that G2 payoff mechanisms perform almost as well as their G1 counterpart, and trading behavior is very similar in both markets (i.e. trading prices and trading volume), except during the very last trading hours of the market. These results indicate that G2 PMs are valid instruments and support their applicability shown in previous studies for developing new product ideas or evaluating new product concepts. Copyright © 2011 John Wiley & Sons, Ltd.     

Accounting for Word‐of‐Mouth Effects in Preference‐Based Market Forecasts

Consumers differ in their involvement in new product purchase decisions. Opinion leaders usually show a higher involvement in their purchase decisions than other consumers. This leads to a higher stability in their answers when being asked about their preferences. An important question that previous research has not analyzed yet is whether and how to capture this finding in preference‐based market forecasts. The authors study these aspects for a representative sample of 364 consumers in the mobile phone market of a large European country. They find that assigning higher weights to the preferences of opinion leaders in aggregate market forecasts results in estimates that are more consistent with observed market shares than forecasts in which all consumers are given equal weights. The authors further test different measures of opinion leadership and find that sociometric indicators outperform psychographic constructs to account for the outcome of opinion leadership in preference‐based market forecasts. Copyright © 2013 John Wiley & Sons, Ltd.     

Haem oxygenase is synthetically lethal with the tumour suppressor fumarate hydratase

Fumarate hydratase (FH) is an enzyme of the tricarboxylic acid cycle (TCA cycle) that catalyses the hydration of fumarate into malate. Germline mutations of FH are responsible for hereditary leiomyomatosis and renal-cell cancer (HLRCC). It has previously been demonstrated that the absence of FH leads to the accumulation of fumarate, which activates hypoxia-inducible factors (HIFs) at normal oxygen tensions. However, so far no mechanism that explains the ability of cells to survive without a functional TCA cycle has been provided. Here we use newly characterized genetically modified kidney mouse cells in which Fh1 has been deleted, and apply a newly developed computer model of the metabolism of these cells to predict and experimentally validate a linear metabolic pathway beginning with glutamine uptake and ending with bilirubin excretion from Fh1-deficient cells. This pathway, which involves the biosynthesis and degradation of haem, enables Fh1-deficient cells to use the accumulated TCA cycle metabolites and permits partial mitochondrial NADH production. We predicted and confirmed that targeting this pathway would render Fh1-deficient cells non-viable, while sparing wild-type Fh1-containing cells. This work goes beyond identifying a metabolic pathway that is induced in Fh1-deficient cells to demonstrate that inhibition of haem oxygenation is synthetically lethal when combined with Fh1 deficiency, providing a new potential target for treating HLRCC patients.     

BCL6 enables Ph+ acute lymphoblastic leukaemia cells to survive BCR-ABL1 kinase inhibition

Tyrosine kinase inhibitors (TKIs) are widely used to treat patients with leukaemia driven by BCR-ABL1 (ref. 1) and other oncogenic tyrosine kinases. Recent efforts have focused on developing more potent TKIs that also inhibit mutant tyrosine kinases. However, even effective TKIs typically fail to eradicate leukaemia-initiating cells (LICs), which often cause recurrence of leukaemia after initially successful treatment. Here we report the discovery of a novel mechanism of drug resistance, which is based on protective feedback signalling of leukaemia cells in response to treatment with TKI. We identify BCL6 as a central component of this drug-resistance pathway and demonstrate that targeted inhibition of BCL6 leads to eradication of drug-resistant and leukaemia-initiating subclones.