In financial applications, the Kelly criterion is a well-known strategy for maximizing long-term growth, but is often criticized for its high-risk approach. To mitigate this effect, previous research proposed two risk-adjusted Kelly criteria in a finite investment horizon: the inflection point, which identifies optimal marginal return, and the optimal reward-to-risk ratio. These approaches maintain the core benefits of the Kelly criterion while reducing risk. As the investment size is used as a proxy for risk, the theory is developed under a linear and smooth setting. However, in practical cases such as transaction costs, reward and risk become non-homogeneous and non-smooth, thus requiring the development of a novel non-smooth analysis framework for risk-adjusted Kelly strategies, which we conduct in this paper. After developing the theory, we apply it to several practical settings, and extend the framework to multiple assets. The research concludes with an empirical analysis of the risk and reward of the risk-adjusted Kelly strategies applied to transaction costs, confirming the superiority of the proposed strategies to the classical Kelly criterion.
Modern portfolio theory identifies diversification as the primary tool for risk reduction. However, under model uncertainty, this cornerstone may no longer remain optimal. This paper investigates the tension between portfolio diversification and concentration under dependence uncertainty. In the absence of model uncert...
This paper investigates optimal portfolio choice for a risk-averse investor who is operating in a
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C. Achudume· International Journal of Com...· 0 citations
We study a long-run risk-sensitive portfolio problem with proportional transaction costs in a continuous-time market whose log-prices are given as a L\'{e}vy process, and rebalancing is possible only at random moments of investment opportunities. Using a Schauder fixed-point argument, we solve the ergodic Bellman equat...
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Kelly criterion is known as a useful tool in the stock market. Yet its efficiency is limited due to its simplicity because it was designed to solve binary gambling problems. Luckily, by switching its coefficients and conclude multiple outcomes in other models, the limitations can be receded or solved. This paper aims a...
Hao-Cheng Liu· Journal of Innovation and De...· 0 citations
This study asks whether environmental, social, and governance (ESG) screening changes the risk-return profile of an Indian large-cap equity portfolio. The Nifty 100 ESG index is compared with its unscreened parent, the Nifty 100, so the only systematic difference is the ESG screen and reweighting applied to a common co...
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