{"id":567,"date":"2025-12-08T14:00:00","date_gmt":"2025-12-08T14:00:00","guid":{"rendered":"https:\/\/www.tejwin.com\/en\/insights\/factor-research-short-interest-ration-part-1\/"},"modified":"2026-09-23T18:19:35","modified_gmt":"2026-09-23T18:19:35","slug":"factor-research-short-interest-ration-part-1","status":"publish","type":"insight","link":"https:\/\/www.tejwin.com\/en\/insights\/factor-research-short-interest-ration-part-1\/","title":{"rendered":"Factor Research \u2013 The SIR Short-Selling Factor: Extracting Negative Signals from Institutional Borrowing Activity \u2013 SIR Part 1"},"content":{"rendered":"
\"Factor<\/figure>\n

The Short-Side Sentiment Factor: Isolating Smart Money Signals in Taiwan\u2019s Market<\/a><\/span><\/h2>\n

Short selling is often regarded as a channel through which \u201csmart money\u201d conveys negative private information. Yet in Taiwan\u2019s stock market, the information contained in short-selling activity is far from straightforward. This is largely due to the market\u2019s unique dual-track mechanism: retail investors primarily short stocks through margin shorting, while institutional investors\u2014especially foreign institutions\u2014utilize securities borrowing and lending (SBL).<\/strong> <\/mark>The coexistence of these two structurally different channels introduces considerable noise into the signal.<\/p>\n

This study aims to isolate and highlight the component of short-selling behavior<\/strong> that truly reflects informed trading. Specifically, we focus on SBL short sales, a segment dominated by institutional investors<\/strong>,<\/mark> and construct a factor that more cleanly captures the sentiment embedded in informed short-selling\u2014namely, the Short Interest Ratio (SIR)<\/strong><\/mark>. Using Taiwan as the empirical setting, we examine the factor\u2019s cross-sectional return predictability, explore its interaction with firm size, and ultimately evaluate its practical value in strengthening portfolio robustness through factor-based strategy backtesting.<\/p>\n

<\/strong><\/em> Dive into the Factor Library for deeper research insights!<\/strong><\/em><\/a><\/p><\/blockquote>\n

Tracing Informed Traders Through SBL Short Selling in Taiwan<\/span><\/h2>\n

Taiwan\u2019s short-selling framework is shaped by two distinct mechanisms: margin short selling, predominantly used by retail investors, and SBL short selling, a channel for institutional investors, including foreign institutions. These two systems represent fundamentally different trader profiles, leading to very different informational interpretations behind their short-selling activities.<\/p>\n

Local academic research provides strong evidence supporting this distinction. Studies by Lee et al. (2017) and Ting et al. (2018) reach highly consistent conclusions: retail-driven margin short selling behaves more like noise trading, and high margin short balances often precede positive future returns due to subsequent price reversals. In contrast, short selling conducted through the institutional SBL channel reliably predicts negative future returns, indicating that it is institutional short sellers\u2014not retail traders\u2014who act as informed participants in the market.<\/p>\n

Building on this foundation, our core hypothesis is straightforward: in Taiwan\u2019s market, only institutional short-selling activity captures the true negative information implied by smart money<\/strong>.<\/mark> Accordingly, to construct a factor that accurately reflects the expectations of informed traders, we focus exclusively on SBL short-sale balances<\/strong> as the basis for measuring short-selling sentiment.<\/p>\n

Factor Analysis<\/span><\/h2>\n

This section outlines the construction of the Short Interest Ratio (SIR) factor and the portfolio-sorting framework used to evaluate its predictive ability. We adopt portfolio sorting as the primary empirical approach and assess whether SIR delivers stable and economically meaningful cross-sectional return predictability\u2014abstracting from transaction costs at this stage. Our analysis proceeds through three perspectives:<\/p>\n

    \n
  1. Descriptive Statistics<\/strong><\/li>\n
  2. Return Analysis<\/strong><\/li>\n
  3. Information Coefficient (IC) Analysis<\/strong><\/li>\n<\/ol>\n

    Together, these components allow us to examine the SIR factor from both distributional and performance-based angles, setting the foundation for later strategy construction and backtesting.<\/p>\n

    This study uses data obtained entirely from Taiwan Economic Journal (TEJ)<\/strong> database, include:<\/p>\n