arXiv subjects

Vladimir Markov

Publications and source records attributed to Vladimir Markov.

9 recordsLinked to original sources

arXiv2025

Optimal Diversification and Leverage in a Utility-Based Portfolio Allocation Approach

We examine the problem of optimal portfolio allocation within the framework of utility theory. We apply exponential utility to derive the optimal diversification strategy and logarithmic utility to determine the optimal leverage. We enhance existing methodologies by incorporating compound probability distributions to model the effects of both statistical and non-stationary uncertainties. Additionally, we extend the maximum expected utility objective by including the variance of utility in the objective function, which we term generalized mean-variance. In the case of logarithmic utility, it provides a natural explanation for the half-Kelly criterion, a concept widely used by practitioners.

q-fin.PM↗

arXiv2023

Portfolio Optimization Rules beyond the Mean-Variance Approach

In this paper, we revisit the relationship between investors' utility functions and portfolio allocation rules. We derive portfolio allocation rules for asymmetric Laplace distributed $ALD(μ,σ,κ)$ returns and compare them with the mean-variance approach, which is based on Gaussian returns. We reveal that in the limit of small $\fracμσ$, the Markowitz contribution is accompanied by a skewness term. We also obtain the allocation rules when the expected return is a random normal variable in an average and worst-case scenarios, which allows us to take into account uncertainty of the predicted returns. An optimal worst-case scenario solution smoothly approximates between equal weights and minimum variance portfolio, presenting an attractive convex alternative to the risk parity portfolio. We address the issue of handling singular covariance matrices by imposing conditional independence structure on the precision matrix directly. Finally, utilizing a microscopic portfolio model with random drift and analytical expression for the expected utility function with log-normal distributed cross-sectional returns, we demonstrate the influence of model parameters on portfolio construction. This comprehensive approach enhances allocation weight stability, mitigates instabilities associated with the mean-variance approach, and can prove valuable for both short-term traders and long-term investors.

q-fin.PM↗

arXiv2023

Optimal portfolio allocation with uncertain covariance matrix

In this paper, we explore the portfolio allocation problem involving an uncertain covariance matrix. We calculate the expected value of the Constant Absolute Risk Aversion (CARA) utility function, marginalized over a distribution of covariance matrices. We show that marginalization introduces a logarithmic dependence on risk, as opposed to the linear dependence assumed in the mean-variance approach. Additionally, it leads to a decrease in the allocation level for higher uncertainties. Our proposed method extends the mean-variance approach by considering the uncertainty associated with future covariance matrices and expected returns, which is important for practical applications.

q-fin.PM↗

arXiv2023

The impact of big winners on passive and active equity investment strategies

We investigate the impact of big winner stocks on the performance of active and passive investment strategies using a combination of numerical and analytical techniques. Our analysis is based on historical stock price data from 2006 to 2021 for a large variety of global indexes. We show that the log-normal distribution provides a reasonable fit for total returns for the majority of world stock indexes but highlight the limitations of this model. Using an analytical expression for a finite sum of log-normal random variables, we show that the typical return of a concentrated portfolio is less than that of an equally weighted index. This finding indicates that active managers face a significant risk of underperforming due to the potential for missing out on the substantial returns generated by big winner stocks. Our results suggest that passive investing strategies, that do not involve the selection of individual stocks, are likely to be more effective in achieving long-term financial goals.

q-fin.PM↗

arXiv2019

Bayesian Trading Cost Analysis and Ranking of Broker Algorithms

We present a formulation of the transaction cost analysis (TCA) in the Bayesian framework for the primary purpose of comparing broker algorithms using standardized benchmarks. Our formulation allows effective calculation of the expected value of trading benchmarks with only a finite sample of data relevant to practical applications. We discuss the nature of distribution of implementation shortfall, volume-weighted average price, participation-weighted price and short-term reversion benchmarks. Our model takes into account fat tails, skewness of the distributions and heteroscedasticity of benchmarks. The proposed framework allows the use of hierarchical models to transfer approximate knowledge from a large aggregated sample of observations to a smaller sample of a particular algorithm.

q-fin.TR↗

arXiv2019

Quintet Volume Projection

We present a set of models relevant for predicting various aspects of intra-day trading volume for equities and showcase them as an ensemble that projects volume in unison. We introduce econometric methods for predicting total and remaining daily volume, intra-day volume profile (u-curve), close auction volume and special day seasonalities and emphasize a need for a unified approach where all sub-models work consistently with one another. Historical and current inputs are combined using Bayesian methods, which have the advantage of providing adaptive and parameterless estimations of volume for a broad range of equities while automatically taking into account uncertainty of the model input components. The shortcomings of traditional statistical error metrics for calibrating volume prediction are also discussed and we introduce Asymmetrical Logarithmic Error (ALE) to overweight an overestimation risk.

q-fin.TR↗

arXiv2014

Design and Implementation of Schedule-Based Trading Strategies Based on Uncertainty Bands

We propose a design for schedule-based execution trading strategies based on uncertainty bands. This formulation: 1) simplifies strategy specification and implementation; 2) provides for flexible allocation among passive, opportunistic, aggressive, and dark pool crossing execution tactics; 3) allows for rapid enhancements as new optimization methods, scheduling techniques, alpha models, and execution tactics are developed; and 4) yields information at macroscopic (strategic) and microscopic (tactical) levels that is easily published to trading databases and front-end applications.

q-fin.TR↗

arXiv2014

On the design of sell-side limit and market order tactics

This article provides a novel framework to evaluate limit order tactics that highlights expected fill price, adverse price selection cost, and opportunity cost. We formulate the problem of optimal execution of market orders with nonlinear market impact, power law decay kernel, and stochastic and deterministic liquidity constraints. We demonstrate how these tactics can be incorporated in the uncertainty bands framework.

q-fin.TR↗

arXiv2009

Comment on "Casimir energies with finite-width mirrors"

We comment on a recent publication [1] by Fosco, Lombardo and Mazzitelli on Casimir energies for material slabs (`finite width mirrors') and report a discrepancy between results obtained there for a single mirror and some previous calculations. We provide a simple consistency check which proves that the method used in [1] is not reliable when applied to approximations of piecewise constant profile of the mirror. We also present an alternative method for calculation of the Casimir energy in such systems based on our recent work. Our results coincide both with perturbation theory and with some older \cite{Bordag'95} and more recent \cite{Vassilevitch'08} calculations, but differ from those of [1].

hep-th↗