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A Dynamic Portfolio of Investment Strategies: Applying Capital Growth with Drawdown Penalties

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... Interesting modifications with similar aims are Bayesian extensions of the Kelly strategy proposed in (Browne and Whitt, 1996;Balka et al., 2017;Chu et al., 2018). Similarly, approaches based on probabilistic risk constraints for limiting the probability of a "drawdown" were discussed in (Busseti et al., 2016) and (Mulvey et al., 2011). Finally, limiting the worst-case probabilistic scenario using the framework of distributionally robust optimization was explored in (Sun and Boyd, 2018) and in (Blanchet et al., 2018) for the Markowitz's strategy, respectively. ...
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We investigate the most popular approaches to the problem of sports betting investment based on modern portfolio theory and the Kelly criterion. We define the problem setting, the formal investment strategies, and review their common modifications used in practice. The underlying purpose of the reviewed modifications is to mitigate the additional risk stemming from the unrealistic mathematical assumptions of the formal strategies. We test the resulting methods using a unified evaluation protocol for three sports: horse racing, basketball and soccer. The results show the practical necessity of the additional risk-control methods and demonstrate their individual benefits. Particularly, we show that an adaptive variant of the popular ``fractional Kelly'' method is a very suitable choice across a wide range of settings.
Article
Full-text available
We investigate the most popular approaches to the problem of sports betting investment based on modern portfolio theory and the Kelly criterion. We define the problem setting, the formal investment strategies and review their common modifications used in practice. The underlying purpose of the reviewed modifications is to mitigate the additional risk stemming from the unrealistic mathematical assumptions of the formal strategies. We test the resulting methods using a unified evaluation protocol for three sports: horse racing, basketball and soccer. The results show the practical necessity of the additional risk-control methods and demonstrate their individual benefits. Particularly, an adaptive variant of the popular ‘fractional Kelly’ method is a very suitable choice across a wide range of settings.
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The Kelly criterion can be used to maximize returns in a game with win rate p and odds b; however, optimization theoretically requires wagering over an infinite number of time steps. Despite the fact that Kelly's theory has been extended to most of the trading strategies used in financial markets, there is still a large gap between the theoretical determination of optimal bidding fractions and practical application of these methods. In this paper, we illustrate the difference between the theoretical and simulation results obtained from a gambling situation involving a finite number of bidding steps T( = W + L), where W and L respectively denote the numbers of wins and losses. The optimal bidding fraction based on the Kelly criterion should employ the win\loss proportion W/T rather than the win rate p; however, it is not possible to obtain the value of a priori. W. Thus, profits under the Kelly formula are calculated by applying win rate p and the win\lose proportion W/T. In this paper, we denote pt as the current win\lose proportion before time step t as an alternative to win rate p. The proposed approach does away with the need to apply win rate p and produces profits that are nearly optimal under Kelly betting.
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