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We perform return interval analysis of 1-min {\em{realized volatility}} defined by the sum of absolute high-frequency intraday returns for the Shanghai Stock Exchange Composite Index (SSEC) and 22 constituent stocks of SSEC. The scaling…

Statistical Finance · Quantitative Finance 2009-09-11 Fei Ren , Gao-Feng Gu , Wei-Xing Zhou

This paper solves the consumption-investment problem under Epstein-Zin preferences on a random horizon. In an incomplete market, we take the random horizon to be a stopping time adapted to the market filtration, generated by all observable,…

Mathematical Finance · Quantitative Finance 2024-01-09 Joshua Aurand , Yu-Jui Huang

In the past 20 years, momentum or trend following strategies have become an established part of the investor toolbox. We introduce a new way of analyzing momentum strategies by looking at the information ratio (IR, average return divided by…

Statistical Finance · Quantitative Finance 2014-07-09 Fernando F. Ferreira , A. Christian Silva , Ju-Yi Yen

Traditional risk factors like beta, size/value, and momentum often lag behind market dynamics in measuring and predicting stock return volatility. Statistical models like PCA and factor analysis fail to capture hidden nonlinear…

Computational Engineering, Finance, and Science · Computer Science 2025-09-23 Wenyan Xu , Jiayu Chen , Dawei Xiang , Chen Li , Yonghong Hu , Zhonghua Lu

We propose a novel model to achieve superior out-of-sample Sharpe ratios. While most research in asset allocation focuses on estimating the return vector and covariance matrix, the first component of our novel model instead forecasts the…

Portfolio Management · Quantitative Finance 2026-04-07 Nolan Alexander , William Scherer

This study introduces a novel approach to walk-forward optimization by parameterizing the lengths of training and testing windows. We demonstrate that the performance of a trading strategy using the Exponential Moving Average (EMA)…

Trading and Market Microstructure · Quantitative Finance 2026-02-12 Tomasz Mroziewicz , Robert Ślepaczuk

Parametric Portfolio Policies (PPP) estimate optimal portfolio weights directly as functions of observable signals by maximizing expected utility, bypassing the need to model asset returns and covariances. However, PPP ignores policy risk.…

Portfolio Management · Quantitative Finance 2026-02-25 Miguel C. Herculano

Universal features in stock markets and their derivative markets are studied by means of probability distributions in internal rates of return on buy and sell transaction pairs. Unlike the stylized facts in log normalized returns, the…

Information Theory · Computer Science 2009-11-11 Lukas Pichl , Taisei Kaizoji , Takuya Yamano

Financial markets can be seen as complex systems that are constantly evolving and sensitive to external disturbance, such as systemic risks and economic instabilities. Analysis of resilient market performance, therefore, becomes useful for…

General Finance · Quantitative Finance 2019-09-04 Junqing Tang , Hans R. Heinimann

Mean-reverting behavior of individuals assets is widely known in financial markets. In fact, we can construct a portfolio that has mean-reverting behavior and use it in trading strategies to extract profits. In this paper, we show that we…

Portfolio Management · Quantitative Finance 2024-06-26 Sung Min Yoon

We study the continuous time portfolio optimization model on the market where the mean returns of individual securities or asset categories are linearly dependent on underlying economic factors. We introduce the functional $Q_\gamma$…

Portfolio Management · Quantitative Finance 2015-01-29 O. S. Rozanova , G. S. Kambarbaeva

It has been widely observed that capitalization-weighted indexes can be beaten by surprisingly simple, systematic investment strategies. Indeed, in the U.S. stock market, equal-weighted portfolios, random-weighted portfolios, and other…

Portfolio Management · Quantitative Finance 2018-09-12 Adrian Banner , Robert Fernholz , Vassilios Papathanakos , Johannes Ruf , David Schofield

We use supervised learning to identify factors that predict the cross-section of returns and maximum drawdown for stocks in the US equity market. Our data run from January 1970 to December 2019 and our analysis includes ordinary least…

Statistical Finance · Quantitative Finance 2023-12-05 Lisa R. Goldberg , Saad Mouti

The construction of an efficient portfolio with a good level of return and minimal risk depends on selecting the optimal combination of stocks. This paper introduces a novel decision-making framework for stock selection based on fractional…

Statistics Theory · Mathematics 2025-07-04 Poulami Paul , Chanchal Kundu

Income and risk coexist, yet investors are often so focused on chasing high returns that they overlook the potential risks that can lead to high losses. Therefore, risk forecasting and risk control is the cornerstone of investment. To…

Applications · Statistics 2023-11-14 Xinyuan Song

Strategic asset allocation requires an investor to select stocks from a given basket of assets. The perspective of our investor is to maximize risk-adjusted alpha returns relative to a benchmark index. Historical returns are used to provide…

Applications · Statistics 2019-12-03 Vadim Sokolov , Michael Polson

The efficient frontier (EF) is a fundamental resource allocation problem where one has to find an optimal portfolio maximizing a reward at a given level of risk. This optimal solution is traditionally found by solving a convex optimization…

Machine Learning · Computer Science 2023-10-17 Philippe Chatigny , Ivan Sergienko , Ryan Ferguson , Jordan Weir , Maxime Bergeron

Continued interest in sustainable investing calls for an axiomatic approach to measures of risk and reward that focus not only on financial returns, but also on measures of environmental and social sustainability, i.e. environmental,…

Mathematical Finance · Quantitative Finance 2026-02-19 Gabriele Torri , Rosella Giacometti , Darinka Dentcheva , Svetlozar T. Rachev , W. Brent Lindquist

This paper introduces a novel methodology for index return forecasting, blending highly correlated stock prices, advanced deep learning techniques, and intricate factor integration. Departing from conventional cap-weighted approaches, our…

General Finance · Quantitative Finance 2024-05-06 Tian Tian , Ricky Cooper , Jiahao Deng , Qingquan Zhang

We consider the multi-period portfolio optimization problem with a single asset that can be held long or short. Due to the presence of transaction costs, maximizing the immediate reward at each period may prove detrimental, as frequent…

Optimization and Control · Mathematics 2025-02-07 Chutian Ma , Paul Smith