arxiv: 2605.00016 · v1 · submitted 2026-04-18 · 💱 q-fin.RM

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Do Short Exposure and Systematic Risk Exposure Drive Asymmetries in the Disposition Effect?

Lorenzo Mazzucchelli , Marco Zanotti , Luca Vincenzo Ballestra , Andrea Guizzardi

Authors on Pith no claims yet

Pith reviewed 2026-05-10 07:18 UTC · model grok-4.3

classification 💱 q-fin.RM

keywords disposition effectlong short positionsframing effectssystematic riskprospect theoryinvestor behaviorETFsrealization thresholds

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The pith

Short positions exhibit a weaker disposition effect than long positions under narrow framing, but this asymmetry reverses in positively performing portfolios under integrated framing and is amplified by systematic risk.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper examines the disposition effect—the tendency to sell winners too early and hold losers too long—in both long and short positions of FTSE MIB ETFs using nearly nine million individual trades. The authors extend standard measures to narrow framing, where positions are viewed in isolation, and integrated framing, where they are considered within the overall portfolio context, while introducing a Value metric to identify the specific return thresholds at which gains or losses are realized. They demonstrate that short positions show less of the typical disposition bias than long ones when framed narrowly, yet this pattern flips in portfolios that are performing positively when framing is integrated, with systematic risk exposure widening the gaps in behavior. A reader would care because the results indicate that the disposition effect is not an inherent property of individual assets but emerges from how investors mentally organize their holdings and the risk environment surrounding them.

Core claim

We show that short positions exhibit a weaker disposition effect than long positions under narrow framing, but that this asymmetry reverses in positively performing portfolios under integrated framing. Systematic risk further amplifies these behavioral asymmetries across positions. Overall, our findings demonstrate that the disposition effect is not solely asset-specific, but is critically shaped by the interaction between portfolio context, position type, and systematic risk exposure. More broadly, the results are consistent with the joint predictions of Prospect Theory and Regret Theory, highlighting the central role of framing in investor decision-making.

What carries the argument

The novel Value metric that identifies the return thresholds at which investors realize gains versus losses, implemented through generalized Count and Total measures under narrow versus integrated framing of long and short exposures.

If this is right

The disposition effect is not uniform across position types and depends on whether investors evaluate holdings in isolation or within portfolio context.
In positively performing portfolios, integrated framing can produce the opposite behavioral pattern from what narrow framing predicts for short versus long positions.
Higher systematic risk exposure increases the magnitude of asymmetries in realization decisions between long and short holdings.
Investor selling behavior aligns with the combined implications of Prospect Theory for loss aversion and Regret Theory for regret avoidance under different framings.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

Portfolio-level performance dashboards could reduce suboptimal selling patterns if they encourage integrated framing for users holding both long and short exposures.
Platforms offering leveraged or inverse ETFs might see different bias patterns than those limited to long-only products, suggesting tailored risk warnings.
The amplifying role of systematic risk implies that behavioral effects could intensify during high-volatility periods even if individual asset returns are moderate.
Testing the same framing and risk interactions on non-ETF assets or in other geographic markets would clarify whether the observed asymmetries are market-specific.

Load-bearing premise

The chosen definitions of narrow and integrated framing accurately capture how real investors mentally group their positions when deciding to sell, and the Value metric isolates behavioral thresholds without being driven by data selection rules.

What would settle it

A replication using a comparable large transaction dataset that finds no reversal of the long-short disposition asymmetry under integrated framing specifically in positively performing portfolios would falsify the central result.

Figures

Figures reproduced from arXiv: 2605.00016 by Andrea Guizzardi, Lorenzo Mazzucchelli, Luca Vincenzo Ballestra, Marco Zanotti.

**Figure 2.** Figure 2: Histogram of the wide framing disposition effect (method Count) We note that our clients predominantly exhibit a positive disposition effect, ranging between 0 and 0.5. Referring to Odean (1998), which documents a disposition effect of 0.21, our sample corroborates this finding with an average disposition effect of 0.20. On average, our sample demonstrates behavior consistent with the disposition effect … view at source ↗

read the original abstract

This study examines the disposition effect in both long and short exposure positions in FTSE MIB tracking ETFs using a unique dataset of almost 9 million individual transactions. Building on the integrated framing approach, we extend the analysis to explicitly incorporate leverage and long short exposures, allowing us to assess how portfolio context and systematic risk exposure jointly are associated to investors realization behavior. Methodologically, we generalize Odean canonical Count and Total measures to wide and integrated framing, introduce a novel Value metric that captures the return thresholds required to realize gains versus losses, and implement these measures in dispositionEffect, an open-source R package for large-scale intraday data. We show that short positions exhibit a weaker disposition effect than long positions under narrow framing, but that this asymmetry reverses in positively performing portfolios under integrated framing. Systematic risk further amplifies these behavioral asymmetries across positions. Overall, our findings demonstrate that the disposition effect is not solely asset-specific, but is critically shaped by the interaction between portfolio context, position type, and systematic risk exposure. More broadly, the results are consistent with the joint predictions of Prospect Theory and Regret Theory, highlighting the central role of framing in investor decision-making.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

The paper extends disposition effect measures to short positions and integrated framing on a large ETF transaction dataset, with an open R package, but the new Value metric and framing definitions risk capturing data grouping rules more than pure behavioral thresholds.

read the letter

The main thing to know is that short positions show a weaker disposition effect than long ones under narrow framing, but this flips in positive-performing portfolios under integrated framing, with systematic risk making the asymmetries larger. They back this with nearly 9 million trades in FTSE MIB tracking ETFs and generalize Odean's count and total measures while adding a Value metric for realization thresholds plus an open-source R package called dispositionEffect for intraday data handling. That package and the scale of the data are the practical upsides here. The work sits squarely in prospect and regret theory territory and shows the bias is not fixed at the asset level but depends on position direction and portfolio context. This is a reasonable extension of existing framing ideas to leveraged and short exposures, which prior studies have touched less. The empirical patterns are new relative to the referenced literature. The soft spot is that integrated framing is tied to the sign of overall portfolio performance, which could correlate with how trades are selected or grouped in the data, such as through holding period rules or liquidity filters. The Value metric for return thresholds might then partly reflect those mechanical choices rather than isolating mental accounting. The abstract does not spell out robustness tests that break this link, so the mapping from observed trades to the theory predictions stays a bit loose. A reader working on behavioral trading biases or empirical extensions of prospect theory would get the most from the generalizations and the code. It is worth a serious referee because the dataset size and the released package give it enough substance to check the identification issues in review, even if revisions on alternative groupings are likely needed. I would send it to peer review rather than desk reject.

Referee Report

3 major / 2 minor

Summary. The paper examines asymmetries in the disposition effect for long versus short positions in FTSE MIB ETFs using a dataset of nearly 9 million transactions. It generalizes Odean's Count and Total measures to narrow/wide and integrated framing, introduces a novel Value metric to capture return thresholds for gain versus loss realization, and tests how portfolio context and systematic risk exposure shape realization behavior. The central claims are that short positions show a weaker disposition effect than long positions under narrow framing, that this asymmetry reverses in positively performing portfolios under integrated framing, and that systematic risk amplifies the behavioral asymmetries, with results consistent with joint predictions from Prospect Theory and Regret Theory.

Significance. If the empirical patterns survive detailed robustness analysis, the work would meaningfully extend behavioral finance by showing that the disposition effect is not asset-specific but depends on the interaction of position type, framing, and systematic risk. The release of the open-source dispositionEffect R package for large-scale intraday data and the use of a very large transaction-level dataset are clear strengths that could facilitate replication and extension.

major comments (3)

[Abstract and §3] Abstract and §3 (Value metric): the novel Value metric is presented as isolating behavioral realization thresholds, yet its construction from transaction grouping rules under integrated framing risks mechanical correlation with data-selection filters (realized trades, holding periods, liquidity), which could generate the reported asymmetry reversal without reflecting mental accounting.
[§4] §4 (integrated framing results): the claim that the asymmetry reverses in positively performing portfolios under integrated framing rests on portfolio-level performance sign determining position grouping, but no details are provided on robustness to alternative grouping rules, minimum-trade filters, or ETF-specific liquidity screens that might drive the reversal.
[§5] §5 (systematic risk amplification): the assertion that systematic risk further amplifies the asymmetries lacks reported error bars, subsample splits, or falsification tests that would distinguish amplification from confounding with volatility or leverage effects already embedded in the ETF data.

minor comments (2)

[Abstract] Abstract: the distinction between 'wide' and 'narrow' framing is introduced without a concise definition; a one-sentence clarification would aid readers.
[Data section] Data section: the proportion of long versus short positions and the exact exclusion criteria applied to the 9 million transactions should be tabulated for transparency.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their detailed and constructive comments, which have identified important areas for clarification and strengthening of our analysis. We address each major comment below and outline the revisions we will make to the manuscript.

read point-by-point responses

Referee: [Abstract and §3] Abstract and §3 (Value metric): the novel Value metric is presented as isolating behavioral realization thresholds, yet its construction from transaction grouping rules under integrated framing risks mechanical correlation with data-selection filters (realized trades, holding periods, liquidity), which could generate the reported asymmetry reversal without reflecting mental accounting.

Authors: We appreciate the referee's concern about potential mechanical correlations in the Value metric. The metric is designed to capture the return thresholds at which investors realize gains versus losses by grouping transactions under integrated framing rules, after applying uniform filters for realized trades, holding periods, and liquidity across all measures (Count, Total, and Value). We control for these factors in the subsequent regressions to isolate behavioral effects. That said, we agree that the description in §3 could be more explicit about the grouping procedure to rule out artifacts. In the revised manuscript, we will expand the methodological explanation of the Value metric construction and add robustness checks that vary the data-selection filters (e.g., alternative holding-period cutoffs and liquidity thresholds) to verify that the reported asymmetry reversal is not driven by these choices. revision: partial
Referee: [§4] §4 (integrated framing results): the claim that the asymmetry reverses in positively performing portfolios under integrated framing rests on portfolio-level performance sign determining position grouping, but no details are provided on robustness to alternative grouping rules, minimum-trade filters, or ETF-specific liquidity screens that might drive the reversal.

Authors: We agree that demonstrating robustness to alternative specifications is essential for the integrated framing results in §4. The current grouping uses the sign of overall portfolio performance to reflect mental accounting under integrated framing, consistent with the theoretical motivation. In the revised version, we will add an appendix with detailed robustness analyses, including: (i) alternative grouping rules based on individual position performance or different performance thresholds, (ii) variations in minimum-trade filters, and (iii) ETF-specific liquidity screens. These checks will confirm whether the reversal pattern in positively performing portfolios persists. revision: yes
Referee: [§5] §5 (systematic risk amplification): the assertion that systematic risk further amplifies the asymmetries lacks reported error bars, subsample splits, or falsification tests that would distinguish amplification from confounding with volatility or leverage effects already embedded in the ETF data.

Authors: The tables in §5 already report standard errors for the systematic risk interaction terms. However, we acknowledge that additional tests are needed to distinguish amplification from potential confounding with volatility or leverage. In the revised manuscript, we will expand §5 to include subsample splits by volatility quintiles and leverage levels, along with falsification tests using placebo risk measures (e.g., idiosyncratic volatility). These will be presented in the main text and an appendix to better isolate the role of systematic risk exposure. revision: yes

Circularity Check

0 steps flagged

Empirical application of generalized measures to transaction data shows no circular derivations.

full rationale

The paper is an empirical analysis that extends Odean's Count/Total measures and introduces a Value metric as explicit methodological definitions applied to a large dataset of ETF trades. No equations or first-principles derivations are presented that reduce reported asymmetries to fitted parameters, self-citations, or inputs by construction; the framing choices (narrow vs. integrated) and risk exposure interactions are stated as analytical lenses rather than derived results. The central claims are observed patterns in the data, consistent with Prospect/Regret Theory predictions but not forced by the paper's own definitions or prior self-citations.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 1 invented entities

The analysis rests on the integrated framing approach from prior behavioral literature and on Prospect Theory plus Regret Theory as explanatory frameworks; no free parameters or invented entities are explicitly introduced in the abstract.

axioms (2)

domain assumption Investors mentally frame decisions either narrowly (trade-by-trade) or in an integrated portfolio context
Invoked when extending analysis to wide and integrated framing and when interpreting asymmetries.
domain assumption Prospect Theory and Regret Theory jointly predict the observed framing-dependent asymmetries
Stated as consistency with the findings at the end of the abstract.

invented entities (1)

Value metric no independent evidence
purpose: Captures the return thresholds required to realize gains versus losses
Newly introduced measure; no independent evidence outside the paper is provided in the abstract.

pith-pipeline@v0.9.0 · 5513 in / 1597 out tokens · 56299 ms · 2026-05-10T07:18:57.657762+00:00 · methodology

discussion (0)

Reference graph

Works this paper leans on

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