New entry and strategic group emergence in the soccer betting market: pricing behaviours, group interaction and efficiency implications

The arrival of online trading in European football betting markets has brought significant structural change to the sector in recent years, with the emergence of two strategic groups of bookmakers, characterised by distinctive operating behaviours. We examine the impact on market efficiency of interactions between these two groups, by comparing 51,000 individual odds offered by leading bookmakers at nine separate points on game outcomes, across 2,132 games in six European leagues. This longitudinal analysis reveals that interactions between these groups enable information to be transmitted from informed bettors to market prices, thereby increasing market efficiency

Towards a better understanding of the full impact of the left digit effect on individual trading behaviour: unearthing a trading profit effect

Investors’ perceptions of price have been shown to be disproportionately affected by the left-most digit(s). However, a similar left digit effect (LDE) in relation to another important determinant of investors’ behaviour (i.e. trading profit) has not been explored. We examine over 7,314,570 million trades made by 25,766 individuals and find a LDE in profit that is 1.71 times stronger than that related to closing price; suggesting that individuals focus more on left digits in profit than price when deciding when to close a trade. In addition, we observe a positive synergistic relationship between the LDE related to profit and price, suggesting that its total influence may result in losses of billions of dollars per financial year for investors. We suggest that these results make a strong case for educating investors against this bias

Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting

The paper examines the potential of deep learning to support decisions in financial risk management. We develop a deep learning model for predicting whether individual spread traders secure profits from future trades. This task embodies typical modeling challenges faced in risk and behavior forecasting. Conventional machine learning requires data that is representative of the feature-target relationship and relies on the often costly development, maintenance, and revision of handcrafted features. Consequently, modeling highly variable, heterogeneous patterns such as trader behavior is challenging. Deep learning promises a remedy. Learning hierarchical distributed representations of the data in an automatic manner (e.g. risk taking behavior), it uncovers generative features that determine the target (e.g., trader’s profitability), avoids manual feature engineering, and is more robust toward change (e.g. dynamic market conditions). The results of employing a deep network for operational risk forecasting confirm the feature learning capability of deep learning, provide guidance on designing a suitable network architecture and demonstrate the superiority of deep learning over machine learning and rule-based benchmarks

SMAD6 variants in craniosynostosis : genotype and phenotype evaluation

PURPOSE: Enrichment of heterozygous missense and truncating SMAD6 variants was previously reported in nonsyndromic sagittal and metopic synostosis, and interaction of SMAD6 variants with a common polymorphism near BMP2 (rs1884302) was proposed to contribute to inconsistent penetrance. We determined the occurrence of SMAD6 variants in all types of craniosynostosis, evaluated the impact of different missense variants on SMAD6 function, and tested independently whether rs1884302 genotype significantly modifies the phenotype. METHODS: We performed resequencing of SMAD6 in 795 unsolved patients with any type of craniosynostosis and genotyped rs1884302 in SMAD6-positive individuals and relatives. We examined the inhibitory activity and stability of SMAD6 missense variants. RESULTS: We found 18 (2.3%) different rare damaging SMAD6 variants, with the highest prevalence in metopic synostosis (5.8%) and an 18.3-fold enrichment of loss-of-function variants comparedwith gnomAD data (P < 10-7). Combined with eight additional variants, ≥20/26 were transmitted from an unaffected parent but rs1884302 genotype did not predict phenotype. CONCLUSION: Pathogenic SMAD6 variants substantially increase the risk of both nonsyndromic and syndromic presentations of craniosynostosis, especially metopic synostosis. Functional analysis is important to evaluate missense variants. Genotyping of rs1884302 is not clinically useful. Mechanisms to explain the remarkable diversity of phenotypes associated with SMAD6 variants remain obscure

Personalized recurrence risk assessment following the birth of a child with a pathogenic de novo mutation

Following the diagnosis of a paediatric disorder caused by an apparently de novo mutation, a recurrence risk of 1-2% is frequently quoted due to the possibility of parental germline mosaicism; but for any specific couple, this figure is usually incorrect. We present a systematic approach to providing individualized recurrence risk. By combining locus-specific sequencing of multiple tissues to detect occult mosaicism with long-read sequencing to determine the parent-of-origin of the mutation, we show that we can stratify the majority of couples into one of seven discrete categories associated with substantially different risks to future offspring. Among 58 families with a single affected offspring (representing 59 de novo mutations in 49 genes), the recurrence risk for 35 (59%) was decreased below 0.1%, but increased owing to parental mixed mosaicism for 5 (9%)-that could be quantified in semen for paternal cases (recurrence risks of 5.6-12.1%). Implementation of this strategy offers the prospect of driving a major transformation in the practice of genetic counselling

The entrepreneurial ladder, gender, and regional development

Gender differences at five levels of entrepreneurial engagement are explained using country effects while controlling for individual-level variables. We distinguish between individuals who have never considered starting up a business, those who are thinking about it, and nascent, young, and established entrepreneurs. We use a large international dataset that includes respondents from 32 European countries, three Asian countries, and the United States. Findings show that cross-country gender differences are largest in the first and final transitions of the entrepreneurial process. In par

Everyone's a winner: the market impact of technologically advantaged agents

Using betting data, we show that a market with agents having heterogeneous utility can include a net transfer of wealth to technologically advantaged agents (TAAs) from non-TAAs with the transaction proving beneficial to both in terms of their realized utility

Subjective judgements of synergistic risks: A cognitive reasoning perspective

Mounting evidence that certain hazard combinations present synergistic risks for adverse outcomes, including violent crime, cancer, and species extinction, highlights the importance of understanding the risk attributable to combined hazards. However, previous studies indicate that individuals often misjudge synergistic risks as additive or sub-additive risks, and there is little research that explores the cognitive reasoning that may lead individuals to make such judgements. This study aims to fill this gap. Participants were asked to review several scenarios that described the risk magnitude presented by a combined hazard. They were required to judge whether each scenario was possible and to explain the reasoning that led to their judgement. The results show that many participants demonstrated an awareness of synergistic risk and that their reasoning was typically characterized by rudimentary knowledge of an underlying causal mechanism for the increased risk (e.g., a chemical reaction between drugs). Conversely, several participants adopted a line of reasoning that precluded the concept of synergistic risk. Many of these participants appeared to employ an additive model of risk, corresponding to the notion of ‘adding’ one hazard to another. Contrary to much previous research, we found little evidence to indicate that people tend to employ a sub-additive model of risk for combined hazards. Implications for future research and the improvement of risk communications concerning synergistic risks are discussed