Uncovering predictability of individual and team success: Significant Hot Hand Effect in International Cricket

We investigate the predictability and persistence (hot-hand effect) of individual and team performance by analyzing the complete recorded history of international cricket. We introduce an original temporal representation of performance streaks, which is suitable to be modelled as a self-exciting point process. We confirm the presence of predictability and hot-hands across the individual performance and the absence of the same in team performance and game outcome. Thus, Cricket is a game of skill for individuals and a game of chance for the teams. Our study contributes to recent historiographical debates concerning the presence of persistence in individual and collective productivity and success. The introduction of several metrics and methods can be useful to test and exploit clustering of performance in the study of human behavior and design of algorithms for predicting success.

Cognitive Biases on the Iran Stock Exchange: Unsupervised Learning Approach to Examining Feature Bundles in Investors’ Portfolios

This paper innovatively analyses the joint occurrence of cognitive biases in groups of stock exchange investors. It considers jointly a number of common fallacies: confirmation bias, loss aversion, gambler’s fallacy, availability cascade, hot-hand fallacy, bandwagon effect, and Dunning–Kruger effect, which have hitherto been studied separately. The paper aims to highlight the diverse range of investor’s profiles which are characterised by such fallacies, and the considerable differences observed based on their age, stock market experience and perception of market trends. The analysis is based on k-means and hierarchical clustering, feature importance and Principal Component Analysis, which were applied to data from the Tehran Stock Exchange. There are a few essential findings which contribute to the existing literature. Firstly, the results show that gender does not have a role to play in diversifying the investors’ profiles. Secondly, cognitive biases are bundled, and we distinguish four investors’ profiles; thus, they should be analysed jointly, not separately. Thirdly, the exposure to cognitive biases differs significantly due to the individual features of investors. The group most vulnerable to almost all analysed biases are inexperienced investors, who are pessimistic about market developments and have invested a large amount. Fourthly, the ages of investors are essential only in connection with other factors such as experience, market perception and investment exposure. Young (20–40 years), experienced investors with huge investments (+1000 mln rials/+24,000 USD) are mostly less exposed to all biases and much less risk-averse. Additionally, older (50+) and experienced investors (5–10 years) who are more optimistic about trends (hot hand bias) were affected much less by cognitive biases, only showing vulnerability to the Dunning–Kruger effect. Fifthly, more than 40% of investors apply consultation and technical analysis approaches to succeed in trading. Finally, from a methodological perspective, this study shows that unsupervised learning methods are effective in profiling investors and bundling similar behaviours.

Uncovering predictability of individual and team success: Significant Hot Hand Effect in International Cricket

We investigate the predictability and persistence (hot-hand effect) of individual and team performance by analyzing the complete recorded history of international cricket. We introduce an original temporal representation of performance streaks, which is suitable to be modelled as a self-exciting point process. We confirm the presence of predictability and hot-hands across the individual performance and the absence of the same in team performance and game outcome. Thus, Cricket is a game of skill for individuals and a game of chance for the teams. Our study contributes to recent historiographical debates concerning the presence of persistence in individual and collective productivity and success. The introduction of several metrics and methods can be useful to test and exploit clustering of performance in the study of human behavior and design of algorithms for predicting success.

Hedge Fund Flows and Performance Streaks: How Investors Weigh Information

Cash flows to hedge funds are highly sensitive to performance streaks, a streak being defined as subsequent quarters during which a fund performs above or below a benchmark, even after controlling for a wide range of common performance measures. At the same time, streaks have limited predictive power regarding future fund performance. This suggests investors weigh information suboptimally, and their decisions are driven too strongly by a belief in continuation of good performance, consistent with the “hot hand fallacy.” The hedge funds that investors choose to invest in do not perform significantly better than those they divest from. These findings are consistent with overreaction to certain types of information and do not support the notion that sophisticated investors have superior information or superior information processing abilities. This paper was accepted by David Simchi-Levi, finance.

Hot Boot

Everyone knows that athletes can get the ‘hot hand’ and have a streak in which they perform better than normal, or an awful slump. But, a trio of psychologists – Gilovich, Vallone, and Tversky – published an analysis in 1985 showing that two NBA teams showed no such effects in either field goals or free throws. Later in 1989, Tversky and Gilovich debunked the hot hand in a further article in this journal. Basketball players were not the only ones to be dumbfounded. Yet, belief in the hot hand has been blamed for all sorts of anomalous bets on outcomes in sports, games in casinos, and trades in the stock market.

The Entropy Method

Everyone knows that athletes can get the ‘hot hand’ and have a streak in which theyperform better than normal, or an awful slump. But, a trio of psychologists – Gilovich,Vallone, and Tversky – published an analysis in 1985 showing that two NBA teamsshowed no such effects in either field goals or free throws. Later in 1989, Tversky andGilovich debunked the hot hand in a further article in this journal. Basketball playerswere not the only ones to be dumbfounded. Yet, belief in the hot hand has beenblamed for all sorts of anomalous bets on outcomes in sports, games in casinos, andtrades in the stock market.

Continuous-time state-space modelling of the hot hand in basketball

We investigate the hot hand phenomenon using data on 110,513 free throws taken in the National Basketball Association. As free throws occur at unevenly spaced time points within a game, we consider a state-space model formulated in continuous time to investigate serial dependence in players’ success probabilities. In particular, the underlying state process can be interpreted as a player’s (latent) varying form and is modelled using the Ornstein-Uhlenbeck process. Our results support the existence of the hot hand, but the magnitude of the estimated effect is rather small as the underlying success probabilities are elevated by only a few percentage points.

A regularized hidden Markov model for analyzing the ‘hot shoe’ in football

We propose a penalized likelihood approach in hidden Markov models (HMMs) to perform automated variable selection. To account for a potential large number of covariates, which also may be substantially correlated, we consider the elastic net penalty containing LASSO and ridge as special cases. By quadratically approximating the non-differentiable penalty, we ensure that the likelihood can be maximized numerically. The feasibility of our approach is assessed in simulation experiments. As a case study, we examine the ‘hot hand’ effect, whose existence is highly debated in different fields, such as psychology and economics. In the present work, we investigate a potential ‘hot shoe’ effect for the performance of penalty takers in (association) football, where the (latent) states of the HMM serve for the underlying form of a player.