Investment strategy using fractional Kelly portfolios for better growth expectations.
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We investigate the use of Kelly's strategy in the construction of an optimal portfolio of assets. For lognormally distributed asset returns, we derive approximate analytical results for the optimal investment fractions in various settings. We show that when mean returns and volatilities of the assets are small and ther…
We determine Kelly criterion for a game with variable pay-off. The Kelly fraction satisfies a fundamental integral equation and is smaller than the classical Kelly fraction for the same game with the constant average pay-off.
Investigates sports betting strategies using modern portfolio theory and Kelly criterion.
We develop a general framework for applying the Kelly criterion to stock markets. By supplying an arbitrary probability distribution modeling the future price movement of a set of stocks, the Kelly fraction for investing each stock can be calculated by inverting a matrix involving only first and second moments. The fra…
In evaluating prediction markets (and other crowd-prediction mechanisms), investigators have repeatedly observed a so-called "wisdom of crowds" effect, which roughly says that the average of participants performs much better than the average participant. The market price---an average or at least aggregate of traders' b…
Optimizes financial decisions with illiquid assets using Kelly criterion.
Paper introduces a new method for risk-sensitive investment management using RL.
Risk and uncertainty will always be a matter of experience, luck, skills, and modelling. Leverage is another concept, which is critical for the investor decisions and results. Adaptive skills and quantitative probabilistic methods need to be used in successful management of risk, uncertainty and leverage. The author ex…
Investing is a compression problem, maximizing growth by minimizing divergence.
The Kelly Criterion is applied to prediction markets to analyze risk and return.
Kelly criterion, that maximizes the expectation value of the logarithm of wealth for bookmaker bets, gives an advantage over different class of strategies. We use projective symmetries for a explanation of this fact. Kelly's approach allows for an interesting financial interpretation of the Boltzmann/Shannon entropy. A…
Extends Kelly Criterion to more complex betting scenarios.
Paper introduces new risk measures for Kelly criterion.
Quantum strategy optimizes wealth growth in a double-or-nothing game.
From the Hamilton-Jacobi-Bellman equation for the value function we derive a non-linear partial differential equation for the optimal portfolio strategy (the dynamic control). The equation is general in the sense that it does not depend on the terminal utility and provides additional analytical insight for some optimal…
Optimal Kelly strategy for multi-outcome parlay bets proven using implicit cash approach.
Algorithm beats best constant rebalancing portfolio in long-term investment.
Kelly betting is a prescription for optimal resource allocation among a set of gambles which are typically repeated in an independent and identically distributed manner. In this setting, there is a large body of literature which includes arguments that the theory often leads to bets which are "too aggressive" with resp…
Forecast-to-fill strategy generates durable alpha in gold futures.
We consider the classic Kelly gambling problem with general distribution of outcomes, and an additional risk constraint that limits the probability of a drawdown of wealth to a given undesirable level. We develop a bound on the drawdown probability; using this bound instead of the original risk constraint yields a conv…
In this paper, we study the Kelly criterion in the continuous time framework building on the work of E.O. Thorp and others. The existence of an optimal strategy is proven in a general setting and the corresponding optimal wealth process is found. A simple formula is provided for calculating the optimal portfolio for a …
Solves risk-sensitive investment via duality, entropic regularization, and RL.
Prompted by a recent experiment by Victor Haghani and Richard Dewey, this note generalises the Kelly strategy (optimal for simple investment games with log utility) to a large class of practical utility functions and including the effect of extraneous wealth. A counterintuitive result is proved : for any continuous, co…
Study evaluates three position sizing methods for put-writing on S&P 500 Index options.
A new method for optimizing stakes in a single event with multiple outcomes.
We consider the problem of finding optimal strategies that maximize the average growth-rate of multiplicative stochastic processes. For a geometric Brownian motion the problem is solved through the so-called Kelly criterion, according to which the optimal growth rate is achieved by investing a constant given fraction o…
This paper optimizes sports betting strategies using neural networks and portfolio theory.
Two methods extend multivariate Kelly optimization to large problem sizes.
Study develops a multi-pair trading strategy using graph clustering and machine learning.
The influence of Commodity Trading Advisors (CTA) on the price process is explored with the help of a simple model. CTA managers are taken to be Kelly optimisers, which invest a fixed proportion of their assets in the risky asset and the remainder in a riskless asset. This requires regular adjustment of the portfolio w…
Kelly investing improved with options to reduce estimation risk.
A new portfolio model improves on Kelly's by accounting for estimation error.
Stock trading based on Kelly's celebrated Expected Logarithmic Growth (ELG) criterion, a well-known prescription for optimal resource allocation, has received considerable attention in the literature. Using ELG as the performance metric, we compare the impact of trade execution delay on the relative performance of high…
A quantum memory model for Kelly betting with amplified or attenuated outcomes.
The paper proposes an asset allocation strategy using the Sortino ratio for better performance.
Maximizes stock portfolio predictability using machine learning.
The Kelly rule fails to maximize growth in a time-changed return setting.
Financial markets, with their vast range of different investment opportunities, can be seen as a system of many different simultaneous games with diverse and often unknown levels of risk and reward. We introduce generalizations to the classic Kelly investment game [Kelly (1956)] that incorporates these features, and us…
We combine forward investment performance processes and ambiguity averse portfolio selection. We introduce the notion of robust forward criteria which addresses the issues of ambiguity in model specification and in preferences and investment horizon specification. It describes the evolution of time-consistent ambiguity…
Myopic investors make suboptimal choices that benefit others, leading to market inefficiencies.
Paper approximates Kelly betting for wealth growth.
Mathematical model for focused investing reduces diversification risks.
Study evaluates discretized arbitrage strategies in fractional financial markets.
This paper extends Kelly Criterion to include rebalancing frequency for optimal portfolio selection.
Two entropy measures quantify suboptimal portfolio performance.
A new factor analysis method using ICA reduces portfolio concentration and diversifies excess kurtosis.
This study deals with the problem of pricing European currency options in discrete time setting, whose prices follow the fractional Black Scholes model with transaction costs. Both the pricing formula and the fractional partial differential equation for European call currency options are obtained by applying the delta-…