A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Spectral portfolio theory links neural networks to wealth dynamics via SGD weight matrices.
Pipeline decomposes portfolio optimization problems into smaller, solvable subproblems.
DynMSA detects market clusters for better portfolio allocation.
New method optimizes portfolios for non-stationary markets.
The paper analyzes cryptocurrency and equity markets using advanced statistical methods.
The paper proposes a new portfolio allocation method combining RMT and machine learning.
We propose an iterative gradient-based algorithm to efficiently solve the portfolio selection problem with multiple spectral risk constraints. Since the conditional value at risk (CVaR) is a special case of the spectral risk measure, our algorithm solves portfolio selection problems with multiple CVaR constraints. In e…
This research introduces dynamic portfolio cuts using a spectral approach for graph-theoretic diversification.
Hybrid model combines risk measures for better portfolio allocation.
We study Spectral Measures of Risk from the perspective of portfolio optimization. We derive exact results which extend to general Spectral Measures M_phi the Pflug--Rockafellar--Uryasev methodology for the minimization of alpha--Expected Shortfall. The minimization problem of a spectral measure is shown to be equivale…
In this paper we propose the notion of continuous-time dynamic spectral risk-measure (DSR). Adopting a Poisson random measure setting, we define this class of dynamic coherent risk-measures in terms of certain backward stochastic differential equations. By establishing a functional limit theorem, we show that DSRs may …
We study a class of backtests for forecast distributions in which the test statistic depends on a spectral transformation that weights exceedance events by a function of the modeled probability level. The weighting scheme is specified by a kernel measure which makes explicit the user's priorities for model performance.…
New machine learning method classifies companies effectively.
Study market-to-book ratios using Stochastic Portfolio Theory.
Spectral denoising recovers meaningful network structure from noisy financial correlations.
Develops pathwise analysis for log-optimal portfolios using rough paths theory.
The study examines higher-order modern portfolio theory with complex critical points and feasible portfolio variety.
This paper investigates how two important sources of risk -- market tail risk and extreme market volatility risk -- are priced into the cross-section of asset returns across various investment horizons. To identify such risks, we propose a quantile spectral beta representation of risk based on the decomposition of cova…
The paper analyzes how stock market dimensionality changes impact portfolio performance.
We developed a strategic of optimal portfolio based on information theory and Tsallis statistics. The growth rate of a stock market is defined by using -deformed functions and we find that the wealth after n days with the optimal portfolio is given by a -exponential function. In this context, the asymptotic optim…
This paper compares modern portfolio theories and applies them to real-world portfolio selection.
This paper studies a non-stochastic version of Fernholz's stochastic portfolio theory for a simple model of stock markets with continuous price paths. It establishes non-stochastic versions of the most basic results of stochastic portfolio theory and discusses connections with Stroock-Varadhan martingales.
Develops a new model-free approach to portfolio theory using rough paths.
We construct a deep portfolio theory. By building on Markowitz's classic risk-return trade-off, we develop a self-contained four-step routine of encode, calibrate, validate and verify to formulate an automated and general portfolio selection process. At the heart of our algorithm are deep hierarchical compositions of p…
Consider a family of portfolio strategies with the aim of achieving the asymptotic growth rate of the best one. The idea behind Cover's universal portfolio is to build a wealth-weighted average which can be viewed as a buy-and-hold portfolio of portfolios. When an optimal portfolio exists, the wealth-weighted average c…
We study the problem of portfolio insurance from the point of view of a fund manager, who guarantees to the investor that the portfolio value at maturity will be above a fixed threshold. If, at maturity, the portfolio value is below the guaranteed level, a third party will refund the investor up to the guarantee. In ex…
Survey of spectral theory and dynamics for infinite volume hyperbolic manifolds.
I discuss some theoretical results with a view to motivate some practical choices in portfolio optimization. Even though the setting is not completely general (for example, the covariance matrix is assumed to be non-singular), I attempt to highlight the features that have practical relevance. The mathematical setting i…
A time-varying network reveals community structure in cryptocurrencies.
Anticipatory portfolios use richer models to optimize investments.
Signature portfolios approximate optimal wealth in non-Markovian markets.
PolyModel theory and iTransformer improve hedge fund portfolio construction.
The paper extends portfolio theory to include contingent claim functions for option pricing.
We investigate the possible drawbacks of employing the standard Pearson estimator to measure correlation coefficients between financial stocks in the presence of non-stationary behavior, and we provide empirical evidence against the well-established common knowledge that using longer price time series provides better, …
Combines option pricing and portfolio theory for optimal hedging.
Paper optimizes portfolio selection with ICX order constraints.
The theory of functionally generated portfolios (FGPs) is an aspect of the continuous-time, continuous-path Stochastic Portfolio Theory of Robert Fernholz. FGPs have been formulated to yield a master equation - a description of their return relative to a passive (buy-and-hold) benchmark portfolio serving as the numérai…
This study compares Markowitz and Single-Index models for Malaysian stocks.
Improved covariance matrix estimation for portfolio optimization with guaranteed PSD and controlled conditioning.
Utility and risk are two often competing measurements on the investment success. We show that efficient trade-off between these two measurements for investment portfolios happens, in general, on a convex curve in the two dimensional space of utility and risk. This is a rather general pattern. The modern portfolio theor…
Develops a new method for optimizing portfolios in stochastic markets.
In this study, we have investigated empirically the effects of market properties on the degree of diversification of investment weights among stocks in a portfolio. The weights of stocks within a portfolio were determined on the basis of Markowitz's portfolio theory. We identified that there was a negative relationship…
We introduce a bond portfolio management theory based on foundations similar to those of stock portfolio management. A general continuous-time zero-coupon market is considered. The problem of optimal portfolios of zero-coupon bonds is solved for general utility functions, under a condition of no-arbitrage in the zero-c…
A new portfolio optimization method using the Sherman-Morrison identity.
The investment economy is a main characteristic of prosperous society. The investment portfolio management is a main financial problem, which has to be solved by the investment, commercial and central banks with the application of modern portfolio theory in the investment economy. We use the learning analytics together…
A new notion of stochastic ordering is introduced to compare multivariate stochastic risk models with respect to extreme portfolio losses. In the framework of multivariate regular variation comparison criteria are derived in terms of ordering conditions on the spectral measures, which allows for analytical or numerical…
New method finds profitable investment opportunities by considering additional financial variables.
The question of optimal portfolio is addressed. The conventional Markowitz portfolio optimisation is discussed and the shortcomings due to non-Gaussian security returns are outlined. A method is proposed to minimise the likelihood of extreme non-Gaussian drawdowns of the portfolio value. The theory is called Leptokurti…