چولگی سیستماتیک و غیرسیستماتیک موردانتظار؛ شواهدی نوین از قیمت‌گذاری گشتاور مرتبه سوم

هدف: ترجیحات بخت‌آزمایی سرمایه‌گذاران موجب گرایش افراد به سهام با چولگی (گشتاور سوم توزیع بازده) مثبت می‌شود. این نوع ترجیحات در شرایط اقتصادی مختلف بازار متفاوت است. در پژوهش حاضر، با استفاده از رتبۀ موردانتظار چولگی سیستماتیک و غیرسیستماتیک، آزمون قیمت‌گذاری گشتاور سوم توزیع بازده سهام در شرایط کلی/ صعودی و نزولی بازار بررسی شده است.روش: در راستای تحقق هدف، پس از پیش‌بینی رتبۀ چولگی سیستماتیک و غیرسیستماتیک موردانتظار براساس متغیرهای قیمتی و شرکتی و بخش‌بندی شرایط بازار به صعودی و نزولی، بازده سبدهای سرمایه‌گذاری آزمون در چارچوب روش‌های تحلیل سبد سرمایه‌گذاری و مدل فاما و مک‌بث (1973) بررسی می‌شود.نتایج: نتایج حاصل نشان‌دهندۀ قیمت‌گذاری عامل چولگی سیستماتیک موردانتظار و نبود قیمت‌گذاری چولگی غیرسیستماتیک موردانتظار در شرایط کلی است؛ اما با تفکیک بازار به شرایط صعودی/نزولی، ضمن تایید قیمت‌گذاری عامل چولگی سیستماتیک، صرف ریسک آن در شرایط صعودی، مثبت و در شرایط نزولی، منفی است. قیمت‌گذاری چولگی غیرسیستماتیک موردانتظار در هر دو حالتِ صعودی و نزولی تایید می‌شود.نوآوری: در این پژوهش، برای نخستین بار آزمون چولگی سیستماتیک و غیرسیستماتیک موردانتظار با استفاده از رتبۀ مقطعی (به‌جای مقدار) و به تفکیک شرایط صعودی/نزولی بازار انجام شده ‌است. همچنین تایید قیمت‌گذاری بخش غیرسیستماتیک چولگی موردانتظار در هر دو شرایط صعودی و نزولی، از دیگر نوآوری‌های این پژوهش به‌شمار می‌رود.

Predicted Systematic and Idiosyncratic Skewness: New Evidence from Pricing the Third Moment of Stock Return ‎Distribution

Lottery preferences cause investors’ tendency toward high skewed (third moment of return distribution) stocks. Such preferences differ based on various market conditions. In this study, using predicted systematic and idiosyncratic skewness ranks, pricing of the third moment of stock return distribution was empirically tested in Bear/Bullish market conditions. The predicted systematic skewness was shown to be priced, while the idiosyncratic part was not. After considering market states, the predicted systematic skewness had positive and negative risk premiums in the bearish and bullish markets, respectively. In addition, there was significant evidence of pricing idiosyncratic skewness in both bullish and bearish markets. In this study, for the first time, an empirical test of both systematic and idiosyncratic skewness was done based on different market conditions. The evidence of priced idiosyncratic skewness in both bull and bear markets was another contribution of this work.IntroductionThe empirical and theoretical evidence of nonnormal return distribution has encouraged researchers toward working on higher moments of return. Skewness as the third moment of this distribution is considered as an indicator of investors’ lottery preferences. In other words, investors tend to have stocks with higher skewness in their portfolios. Similar to other types of risk, skewness has the two systematic and idiosyncratic parts. Since the idiosyncratic part is believed to be removed during diversification, the expected return should be attributed to the systematic part. In this paper, it was investigated whether systematic or idiosyncratic skewness could be priced.Expost (historical) skewness is noisy enough to prevent us from testing the relationship between stock return and skewness. The noisy characteristics of skewness can be avoided by having predicted skewness based on firm characteristics. In this work, firm and price characteristics, which are important to investors with lottery preferences, were used to predict both systematic and idiosyncratic skewness separately. The relationship between skewness and stock return is sensitive to market conditions. For example, the higher the unemployment rates are during bearish markets, the lower and higher the investments and investors’ tendency toward lottery stocks will be, respectively. Thus, it is believed that skewness may have a different relationship with stock returns during bullish or bearish markets. In this paper, pricing of systematic and idiosyncratic skewness was done by both considering and not considering market conditions, the results of which were then compared with each other. Method and DataIn this work, skewness was categorized as systematic and idiosyncratic skewness. After predicting each of them based on price variables and firm characteristics and dividing market conditions, we formed the test portfolios based on the predicted skewness ranks. Then, we used portfolio analysis and Fama MacBeth’s approach (1973) to empirically investigate the returns of the test portfolios in bullish and bearish market conditions together with cumulative return portfolio and separately. The sample used in this study included 268 firms, which were active in Tehran Stock Exchange between the years of 2001 and 2020. We extracted the price variables and firm characteristics for the firms by using TSECLIENT and Rahavard Novin 3 software. FindingsThe results of not considering market conditions showed that the predicted systematic skewness was priced, while the predicted idiosyncratic skewness was not. However, after dividing market states into bullish and bearish markets and separately testing them in each state, not only the predicted systematic skewness, but also the predicted idiosyncratic skewness was priced. In this case, the predicted systematic skewness had positive and negative risk premiums in the bearish and bullish states, respectively. In addition, there was significant evidence of pricing idiosyncratic skewness in both bullish and bearish markets. Conclusion and discussion The findings of this paper first revealed that using predicted skewness led to the results that were more matched with the theories behind skewness and had a relationship with stock return. Thus, it seemed that using predicted skewness significantly decreased the empirical errors made by the noise of this variable. Second, the predicted systematic skewness had an opposite relationship with stock return due to the different market states. It showed that investors acted differently toward highskewed stocks in a bullish compared to the bearish market. And third, the predicted idiosyncratic skewness was priced, while it was believed to have been removed during diversification.