Can Investors Profit from Measuring Stock Liquidity with Ordered Fuzzy Numbers?

Abstract In this paper, we investigate whether measuring stock liquidity based on an ordered fuzzy numbers representation of a limit order book allows investors to develop a profitable investment strategy. To this end, we examine the data from 259 companies listed on the Warsaw Stock Exchange between January 2014 and December 2021. We apply several methods commonly used in asset pricing studies to obtain baseline results. These were then supplemented with a series of robustness checks. Our strategy which employs a liquidity measure based on ordered fuzzy numbers generates a weekly return of 0.184% (0.199%) for equal- (value-) weighted portfolios, which translates into an annual return of 9.568% (10.348%). This return remains positive after adjusting for risk and considering trading costs and short-sales restrictions. The strategy outperforms the market buy-and-hold strategy, generating a Sharpe ratio several times higher. These results are useful for investors and portfolio managers, as they may assist them in refining their investment strategies.

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Publication Details

Journal
Computational Economics
Published
2025-09-19
DOI
https://doi.org/10.1007/s10614-025-11076-y
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Can Investors Profit from Measuring Stock Liquidity with Ordered Fuzzy Numbers?

Adam Marszałek, Szymon Stereńczak
Computational Economics
Stock Market Forecasting Methods
article

Can Investors Profit from Measuring Stock Liquidity with Ordered Fuzzy Numbers?

Adam Marszałek, Szymon Stereńczak
article en

Abstract

Abstract In this paper, we investigate whether measuring stock liquidity based on an ordered fuzzy numbers representation of a limit order book allows investors to develop a profitable investment strategy. To this end, we examine the data from 259 companies listed on the Warsaw Stock Exchange between January 2014 and December 2021. We apply several methods commonly used in asset pricing studies to obtain baseline results. These were then supplemented with a series of robustness checks. Our strategy which employs a liquidity measure based on ordered fuzzy numbers generates a weekly return of 0.184% (0.199%) for equal- (value-) weighted portfolios, which translates into an annual return of 9.568% (10.348%). This return remains positive after adjusting for risk and considering trading costs and short-sales restrictions. The strategy outperforms the market buy-and-hold strategy, generating a Sharpe ratio several times higher. These results are useful for investors and portfolio managers, as they may assist them in refining their investment strategies.

Computational Economics
Poznań University of Economics and Business (PL), Cracow University of Technology (PL)
Openalex Percentile: Top 70%
Stock Market Forecasting Methods
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