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.
AlphaZeroBeta uses deep reinforcement learning for market-neutral portfolios, outperforming traditional methods.
TRP uses tree-based approach for market-neutral portfolios.
Investment strategy for NYSE stocks minimizes market correlation.
This study improves mid-cap equity performance with a data-driven, market-neutral approach.
A fractal approach to the long-short portfolio optimization is proposed. The algorithmic system based on the composition of market-neutral spreads into a single entity was considered. The core of the optimization scheme is a fractal walk model of returns, optimizing a risk aversion according to the investment horizon. …
In the second part of our series we suggest new definitions of credit bond duration and convexity that remain consistent across all levels of credit quality including deeply distressed bonds and introduce additional risk measures that are consistent with the survival-based valuation framework. We then show how to use t…
The principal portfolios of the standard Capital Asset Pricing Model (CAPM) are analyzed and found to have remarkable hedging and leveraging properties. Principal portfolios implement a recasting of any correlated asset set of N risky securities into an equivalent but uncorrelated set when short sales are allowed. Whil…
Study compares short vs long strategies for equity factors, finds short strategy better.
The role of portfolio construction in the implementation of equity market neutral factors is often underestimated. Taking the classical momentum strategy as an example, we show that one can significantly improve the main strategy's features by properly taking care of this key step. More precisely, an optimized portfoli…
In this article, we analyse optimal statistical arbitrage strategies from stochastic control and optimisation problems for multiple co-integrated stocks with eigenportfolios being factors. Optimal portfolio weights are found by solving a Hamilton-Jacobi-Bellman (HJB) partial differential equation, which we solve for bo…
The present paper provides a study of high-dimensional statistical arbitrage that combines factor models with the tools from stochastic control, obtaining closed-form optimal strategies which are both interpretable and computationally implementable in a high-dimensional setting. Our setup is based on a general statisti…
We present a reactive beta model that includes the leverage effect to allow hedge fund managers to target a near-zero beta for market neutral strategies. For this purpose, we derive a metric of correlation with leverage effect to identify the relation between the market beta and volatility changes. An empirical test ba…
Quantum GBS boosts asset clustering for robust statistical arbitrage portfolios.
We consider the problem of optimal investment in a market with two cointegrated stocks and an agent with CRRA utility. We extend the findings of Liu and Timmermann [The Review of Financial Studies, 26(4):1048-1086, 2013] by paying special attention to when/if the associated stochastic control problem is well-posed and …
Machine learning improves beta forecasts, enhancing equity valuation and portfolio performance.
Anchoring is a term used in psychology to describe the common human tendency to rely too heavily (anchor) on one piece of information when making decisions. A trading algorithm inspired by biological motors, introduced by L. Gil\cite{Gil}, is suggested as a testing ground for anchoring in financial markets. An exact so…
Smart beta, also known as strategic beta or factor investing, is the idea of selecting an investment portfolio in a simple rule-based manner that systematically captures market inefficiencies, thereby enhancing risk-adjusted returns above capitalization-weighted benchmarks. We explore the idea of applying a smart strat…
WaveLSFormer learns profitable trading policies from financial time series data.
Paper uses machine learning to analyze stock market anomalies, predicting drift direction and portfolio performance.
In this article, we present a discrete time modeling framework, in which the shape and dynamics of a Limit Order Book (LOB) arise endogenously from an equilibrium between multiple market participants (agents). We use the proposed modeling framework to analyze the effects of trading frequency on market liquidity in a ve…
We point out a simple equities trading strategy that allows a sufficiently large, market-neutral, quantitative hedge fund to achieve outsized returns while simultaneously contributing significantly to increasing global wealth inequality. Overnight and intraday return distributions in major equity indices in the United …
Novel OTT method for cryptocurrency trading offers high annualized profit.
Develops a deep multi-factor model for factor investing with clear financial insights.
Paper develops new spot regression estimators using candlesticks for asset pricing.
MTRGL learns temporal correlations from multi-modal data for improved pair trading.
The quantitative aspirations of economists and financial analysts have for many years been based on the belief that it should be possible to build models of economic systems - and financial markets in particular - that are as predictive as those in physics. While this perspective has led to a number of important breakt…
Fundamental portfolio beats market portfolio under certain conditions.
This paper compares three portfolio designs for Indian stocks.
Project predicts stock prices for robust portfolio design in Indian sectors.
A new factor analysis method using ICA reduces portfolio concentration and diversifies excess kurtosis.
Paper uses neural networks to compress large portfolios of options, reducing risk and capital requirements.
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…
In this paper Portfolio Optimization techniques were used to determine the most favorable investment portfolio. In particular, stock indices of three companies, namely Microsoft Corporation, Christian Dior Fashion House and Shevron Corporation were evaluated. Using this data the amounts invested in each asset when a po…
This study compares three portfolio design approaches for stock selection.
A market portfolio is a portfolio in which each asset is held at a weight proportional to its market value. Functionally generated portfolios are portfolios for which the logarithmic return relative to the market portfolio can be decomposed into a function of the market weights and a process of locally finite variation…
New portfolios outperform traditional methods by using factor weights.
Research optimizes C++ patterns for HFT, reducing latency and improving profitability.
Study finds cryptocurrency market diversity patterns inconsistent with neutral models.
This study compares two portfolio optimization methods on Indian stocks.
Signature portfolios approximate optimal wealth in non-Markovian markets.
The effect of proportional transaction costs on systematically generated portfolios is studied empirically. The performance of several portfolios (the index tracking portfolio, the equally-weighted portfolio, the entropy-weighted portfolio, and the diversity-weighted portfolio) in the presence of dividends and transact…
The paper introduces eigen-portfolios using PCA to improve portfolio construction in finance.
The study infers risk preferences from portfolio choices and measures portfolio efficiency.
In stochastic portfolio theory, a relative arbitrage is an equity portfolio which is guaranteed to outperform a benchmark portfolio over a finite horizon. When the market is diverse and sufficiently volatile, and the benchmark is the market or a buy-and-hold portfolio, functionally generated portfolios introduced by Fe…
Survey of universal portfolio techniques for minimizing investment regret.
Investor skill levels affect optimal portfolio size, study shows.
Study on stock portfolio concentration among Finnish households and investors.
Study market-to-book ratios using Stochastic Portfolio Theory.