Power, Not Fear: A Collusion-Based Account of Betting Market Inefficiency

Abstract

We examine racetrack betting market inefficiency. We argue that the overround -an established measure of inefficiency -may be seen as a reflection of bookmakers' collusive returns maximising behaviour, rather than simply as their response to an adverse selection problem. We test, and find empirical support for, several proposed market effects of bookmaker (market maker) collusion. Besides number of race participants, overround varies significantly according to (1) whether or not the race is the last at the race meeting, (2) racetrack location, (3) day of the week (weekday vs. weekend), (4) type of race (handicap vs. non-handicap), and (5) type of race event (Flat/National Hunt). The study provides fresh insight into the origins of betting market inefficiency, where the link between market structure and context and bookmaker behaviour is a key feature. Regarding the broader implications, the study alerts us to the potential for financial market inefficiencies such as the bid-ask spread to be explained, in part, as a consequence of market makers' opportunistic behaviour wherever and whenever it is possible for intermediaries to exploit their understanding of investor behaviour.

Dinâmicas do Desempenho Financeiro, da Mudança Estratégica e da Concentração Industrial em Empresas Brasileiras

“…Essa concentração, independentemente das mudanças estratégicas, afeta estruturalmente, de forma corrente e defasada, todos os indicadores, sendo incentivadora do crescimento e do valor de mercado e inibidora da lucratividade. Portanto ela oferece o contexto para geração ou aniquilamento das eficiências da competição empresarial (Bruce & Marginson, 2013).…”

“…A teoria econômica destaca a existência de diferentes estruturas de mercadoconcorrência perfeita, monopólio, oligopólio e concorrência monopolística (Simonsen, 1979) -que podem estimular o bom ou o mau desempenho. Altas taxas de concentração estão relacionadas ao maior valor de mercado das empresas quando a concentração permite restringir entrada de novos competidores no setor ou no grupo estratégico, dessa forma, gerando ineficiências no mercado como o conluio (Bruce & Marginson, 2013). Porém a desconcentração gera eficiências na competitividade empresarial por meio dos produtos levados ao mercado e clientes atendidos, que refletem em maiores vendas e lucros (Bharadwaj & Varadarajan, 2005).…”

“…Ademais, em setores desconcentrados, independente das mudanças estratégicas, pois há aumento na lucratividade a longo prazo, devido ao ambiente benéfico para que haja eficiências derivadas da maior competitividade empresarial (Bruce & Marginson, 2013). Entretanto, nesses setores, podem ocorrer decréscimos no crescimento empresarial no longo prazo porque a concorrência cria limites para que as empresas cresçam, já que precisam ratear o volume que vendem entre os concorrentes (Hill, Kelly, & Highfield, 2010).…”

Does The Betting Industry Price Gender? Evidence from Professional Tennis

“… 7. Despite their relevance in other studies, our model excludes certain time variables such as when the season starts or whether the competition takes place on a weekend (Bruce & Marginson, 2014) which could show collinearity with the “tournament progress” variables, given that the final rounds of tennis tournaments always take place at weekends.…”

“…In particular, SURPRISE_1 has a mean of 20.95% in women's matches vs. 19.97% in men's; that is, a difference of 0.98% with p-val<0.01, while the respective values for SURPRISE_2 are 21.85% vs. 21.48%; that is, a difference of 0.37% p-val<0.05.5 In this case, the difference in means tests show that the volume of attention is lower in WTA matches than in ATP matches. ATTENTION has a mean of 12.19% for women's matches vs. 29.09% for men's; which is a difference of 16.90 % p-val<0.01.6 This category includes the nine "Master Series" tournaments for the ATP, and the "Premier Mandatory" and "Premier 5" for the WTA (Women's Tennis Association has categorised these tournaments as WTA1000 from 2021).7 Despite their relevance in other studies, our model excludes certain time variables such as when the season starts or whether the competition takes place on a weekend,(Bruce & Marginson, 2014) which could show collinearity with the "tournament progress" variables, given that the final rounds of tennis tournaments always take place at weekends.8 The coefficients on the other variables in the models remain the same overall as those shown in Tables 4, 5 and 6. Results available upon request.…”