The low (high) abnormal returns of stocks with a high (low) left tail risk is a financial anomaly studied in empirical capital asset pricing research. This anomaly is caused by undesirable and unexpected events that incur severe losses for investors, and this loss has the characteristic of continuity. Since the prediction of left-tail risk can help formulate an appropriate trading strategy, this study aims to predict the left-tail risk through past left tail risk information via portfolio analysis and Fama and Macbeth's (1973) regression. To this end, the data of 307 companies of Tehran Stock Exchange and Iran Fara Bourse from 2005 to 2020 were used. The results revealed the ability to predict the left tail risk by past risk information in the research sample. Further exploration by additional portfolio analysis suggested that the future left-tail risk prediction power by past information left-tail risk is greater among stocks with small size characteristics and high unsystematic volatility, but only a small portion of the market is devoted to stocks with these characteristics.

Objective: Left tail risk shows the probability of the occurrence of undesirable events. Investors who undergo the left tail risk are likely to experience considerable negative returns since the left tail risk oftentimes continues to the next period. Thus, if individual investors show scant attention to the left tail risk, holding the risky stocks, high levels of negative return are almost inevitable. The purpose of this study is to investigate whether or not the attention of individual investors to the risk is limited. Method: Data from one hundred and twenty (120) companies listed in Tehran Stock Exchange during the period from 2010 to 2018 was analysed using Fama regression and Macbeth. Results: The results of the present research suggest that individual investors, due to their little capacity and confidence in accepting risks, pursue a conservative investment program and their selling of their stocks depends on the probability of the left tail risk persistence in the next period.

Objective: Left-tailed risk illustrates the probability of unfavorable events that could occur in a range wider than three variances of the distribution function. Although such events have a very low occurrence probability, they would cause significant losses in case of occurrence. This research aims at examining the cross-sectional effects of left-tailed risk on expected excess returns. The present research also examines the probability of the persistence of left-tiled risk in the future. Methods: In this research two proxies of value at risk and expected shortfall are used to measure left-tailed risk. For this purpose, a sample of 120 companies listed in the Tehran stock market in the period of the years 2010-2017 have been selected. Research hypotheses were examined with the use of Fama and Macbeth regression. Transition matrix was used to determine the probability of left-tailed risk persistence in the future. Results: According to the findings of the research, left-tailed risk has a significant and negative effect on the expected excess returns. The findings also suggested that the negative returns of the left tail will have a persistence probability of over 50% in the future. Conclusion: The findings of the present research illustrate a new anomaly in the financial area, which is the negative effect of left-tail risk on the expected excess returns, and persists in the future.

Idiosyncratic volatility puzzle and left tail risk anomaly are the most persistent studied anomalies in empirical research in the field of asset pricing. The aim of this study is to introduce the left tail risk as a driver for creating idiosyncratic volatility. In addition, the present study is trying to determine how the idiosyncratic volatility puzzle occurs. In this study, univariate and bivariate portfolio analysis as well as Fama and Macbeth (1973) regression have been used. For this purpose, the information of companies listed in the Tehran stock exchange and Iran Fara bourse during the years 1384 to 1398 has been used. The results of this study indicate the existence of the idiosyncratic volatility puzzle and left tail risk anomaly in the research sample. The idiosyncratic volatility puzzle is no longer detected when idiosyncratic volatility-sorted portfolios are neutralized to left tail risk, regression control for left tail risk and factor models include a left tail risk factor. The left tail risk plays an important role to explain idiosyncratic volatility puzzle. The reason for this explanation is the falling stock price pressure with high left-tail risk on stocks with high unsystematic volatility.

Capital asset pricing models have not considered factors that cause capital market anomalies. The theories of extreme value are one of the arguments for explaining anomalies. Based on the extreme value theory, a tail risk is an adverse event that negatively impacts excess stock returns. Therefore, this study aimed to investigate combining the anomalies of size, value and idiosyncratic risk with tail on stock excess returns. In this study, we have used two criteria of Aggregate Tail Risk and Hybrid Tail Covariance Risk to measure the tail risk. For this purpose, using the systematic removal method, a sample of 136 firms listed on the Tehran Stock Exchange in the period from 2008 to 2019 was selected. The research hypotheses were tested using the Five-Factor Fama and French model (2015). The results suggested that the combination of size and tail risk portfolio and the combination of value and tail risk portfolio have a negative effect on excess return on risk. The results also showed that the combination of idiosyncratic and tail risk portfolios positively and significantly affect stock excess returns. Therefore, by combining these portfolios, investors can gain excess returns in the Iranian capital market. The results generally indicated that tail risk could be added to asset pricing models in addition to the variables of the five-factor Fama and French model.

Accurate assessment of systematic risks in financial markets can lead to favorable capital allocation. Systematic tail risk is adverse events that, if they occur, can affect stock returns. Therefore, the purpose of this study is to investigate the effect of tail risk on excess stock returns. In the present study, two criteria of cumulative tail risk and combined tail covariance risk were used to measure tail risk. For this purpose, using the systematic removal method, a sample of 136 companies listed on the Tehran Stock Exchange (TSE) in the period 2009 to 2019 was selected. Research hypotheses were tested using the five-factor model of Fama and French regression. The results showed that the combination of size portfolio and tail risk and the combination of value portfolio and tail risk have a negative effect on excess stock returns. In addition, the results indicate that the combination of profitability portfolio and tail risk and the combination of investment portfolio and tail risk does not lead to excess stock returns. In general, the results showed that tail risk can be added to asset pricing models in addition to the variables of the five-factor model of Fama and French.

Knowledge of the renal vascular anatomy greatly contributes to the success of surgical, invasive and radiological procedures of the retroperitoneal region. In today’s era of transplant, this knowledge is of utmost importance in performing donor nephrectomy so that number of fatal intra-operative complications can be prevented. Herein, we report on a rare anomaly of left renal vein in which dual retro-aortic left renal veins were noted and one of them drained into the left common iliac vein.

We herein report a case of 20-year-old man who underwent a contrast-enhanced computerized tomography of the pelvis for a workup of complicated urinary tract infection, which showed presence of classical horseshoe kidney and incidental left-sided infrarenal inferior vena cava (IVC). The left IVC joined the left renal vein and crossed anterior to the aorta, uniting with the right renal vein to form a normal right-sided prerenal IVC. Horseshoe kidney is a renal fusion anomaly found in about 0.2% of the general population and is more common in men ....

Abstract Capital market anomalies are caused by factors that have not been considered in capital asset pricing models. One of the arguments for explaining anomalies is the theory of extreme value. According to the theory of extreme value, tail risk is an adverse event that can have a negative impact on excess stock returns. Therefore, the aim of the present study was to investigate the effect of combining momentum anomalies and idiosyncratic risk with tail risk on excess stock returns. In the present study, two criteria of cumulative tail risk and combined covariance tail risk have been used to calculate tail risk. The sampling method in this study is systematic elimination and the time period of the research years from 2007 to 2019 has been selected. The number of sample companies includes 136 companies listed on the Tehran Stock Exchange (TSE) and the 5-factor regression of Fama and French was used to test the research hypotheses. The results indicate that the combination of idiosyncratic risk portfolio and tail risk has a positive and significant effect on excess stock returns. Therefore, by combining this portfolio, investors can gain returns in the Iranian capital market. Also, the results showed that the combination of momentum portfolio and tail risk does not lead to excess stock returns. In general, the results showed that tail risk can be used to explain the existence of idiosyncratic risk anomalies.