Default Risk and Momentum Effect; Some Evidence from Tehran Stock Exchange Maysam Ahmadvand1 (Corresponding Author) Seyedeh Mahboobeh Jafari2 Hamidreza Kordlouie3 Abstract The purpose of this paper is to analyze the relationship between default risk and momentum effect using data from companies listed on Tehran Stock Exchange.To calculate default risk,we used Black-Scholes-Merton (BSM) option pricing model. To describe momentum effect, by determining the formation period to be 6 months, and the holding period to be 3,6, or 12 months, we firstlyexamined the profitability of short term (3/6), midterm (6/6), and long term (12/6) momentum strategies and found that during 2010-2015 time period, only midterm momentum strategy is profitable.Then,we showedthere is no relationship between default risk andmomentum effect. KeyWords: Momentum effect, Default risk, Asset valuation, Tehran Stock Exchange. 1. Ph.D. Student in Finance, Allameh Tabatabaei University, [email protected] 2. Ph.D. in Accounting, Assistant Professor, Islamic Azad University, South Tehran Branch, [email protected] 3. Ph.D. in Finance, Associate Professor, Islamic Azad University, Islamshahr Branch, hamidreza [email protected] 30 Iranian Journal of Finance 1. Introduction Momentum effect, ascontinuation of mid-term returns, has been seen during last two decades and different periods of time. There are some evidence of this effect in the USA (Jegadeesh and Titman, 1993, 2001), Europe (Rouwenhorst, 1998), Asia (Hameed andKusnadi, 2002) and Latin America (Muga and Santamaria, 2007a). Despite of the widespread evidence, the origin of its formation has always been controversial; a number of experts have based their explanations on risk, and the others have tried to explain the effect in terms of the theory ofbehavioral finance. On the other side, a number of new studies claim that a key variable to present a satisfying explanation for momentum effect is default risk. Using data of the USA’s stock market, Avramov et al. (2007) suggest that momentum strategies lead to significant earnings only on the stocks with low credit ratings. However, conducting several studies in the UK’s stock market, Agrawal and Taffler (2008) conclude that momentum effect is a direct consequence of under-reaction of the market to insolvency risk.Although these two mentioned studies consider momentum effect from different aspects, both of them believe that its origin is high default risk stocks. Avramov et al., (2007) used credit ratings and showed that momentum effect is considerable only in stocks with low credit rating. However, a company’s default risk can change significantly before any rising or falling in its credit rating.Considering merely credit rated stocks, makes the sample biased, at least regarding company’s size; therefore, it affects the results significantly. It is essential to consider a significant relationship between momentum effect and size reported by previous researches (for example Hong et al., 2000). Agrawal and Taffler (2008) used Altman’s Z score, which is exclusively based on accounting data as a dummy variable for indentifying companies with financial insolvency and companies with good financial health. In addition to this simplification, using accounting data to estimate a company’s default risk might have many important shortcomings. This kind of information is based onprevious data, which cannot specify the vision correctly. Also, since these models do not consider asset volatility, companies with equal accounting ratios provide similar levels of default risk. Moreover, these two researchers used a measure without any significant relationship with size or book to market ratio, in spite of several empirical evidence indicating an association between momentum effect and these two characteristics of stock. As a matter of fact, Default Risk and Momentum Effect; Some … 31 many studies have used various concepts such as information uncertainty (Jiang et al., 2005; Zhang, 2006),stocksthat are hard to value or to arbitrage (Baker and Wurgler, 2006), or stocks attracting limited attention(Aboody et al., 2010), so that they can demonstrate some of stock’s characteristics (such as size, book to market ratio, volatility, stock market cycle, etc.) do not help returns continuation, which is a factor of momentum effect (Abinzano et al., 2014). In order to analyze the relationship between default risk and momentum effect, the present study has applied a measure based on the Black-Scholes- Merton (BSM) option pricing model, where a firm’s default risk is derived from the market prices of its stock (Black and Scholes, 1973; Merton, 1974). This method solves a number of problems related to default risk criterion, used in the mentioned studies. According to the results, high default risk is a feature ofalosers’ portfolio, while default risk ofawinners’ portfolio is moderate-to- low. The findings indicate default risk cannot be a key factor in describing momentum factor. This study makes several contributions to the literature. First of all, we test whether momentum effect is exclusive to financially distressedor insolventfirms. Secondly, the BSM model is used as a measure of default risk which includes much less constraints about the sample and covers future expectations of stock effectively. Thirdly, liquidity enters in the analysis as an additional variable and a robustness test will be performed, and finally, the source of profits earned by momentum strategy is explained. 2. Literature Review and Background of the Study The reversal-momentum strategies are a set of irregularities explored in academic research. The momentum strategies focus on the association between stock relative returns and market relative returns in thepast period. The simple rule of momentum strategy is as follows: a stock with better or weaker performance in the past, will continue this process in the future. Therefore, a momentum strategy creates a portfolio which purchases past winner stocks and sells past loser stocks. For the first time, Jegadeesh and Titman (1993) reported about the momentum strategy achieving abnormal returns in a long period of time. Jegadeesh and Titman (1993) created portfolios which purchased stocks with better performance (winner stocks) in the last 3, 6, 9 and 12 months and sold stocks with weaker performance (loser stocks) in the last 3, 6, 9 and 12 months, but the periods of holding them were different. Jegadeesh and Titman 32 Iranian Journal of Finance (1993) set the holdingperiod as 3, 6, 9 or 12 months and repudiated the existing portfolios at the end of each period in accordance with their performance in that period. They also used the overlapping strategies approach. According to their observationsin the period of 1965-1989, selecting stocks on the basis of their performance in the last 6 months and holding them for the next 6 months created in average %12.01 excess returns in a year. A substantial finding was that the average of winners’ or losers’ portfolios market value in the period of 1965-1989 was less than the market average. This proved momentum for smaller stocks or firms was stronger. In the next period of time (i.e. 1990-1998), Jegadeesh and Titman (2001) remove stocks with the price of less than $ 5 at the beginning of the holding period and stocks belonging to the least deciles of market value (i.e. the smallest stocks) from their analysis, so that they could neutralize the effect of small stocks. Their findings suggested that the average return of momentum strategy was %1.39 for each month. They also studied the momentum of the period from 1965 to 1998 and observed that the average excess return was %1.23 for each month (annually %14.76). Therefore, the momentum, observed in the period of 1965-1989 has not been due to the sample size or the time period. Momentum strategies profitability in long-term periods,as well as in different markets has also been examined. Rouwenhorst (1998) continued the approach of Jegadeesh and Titman (1993) and analyzedmomentum for an international portfolio including 12 European markets. Using deciles to identify winner and loser stocks on the basis of their past performance, he reported momentum strategies profitability of the European mentioned markets as approximately %1 for every month from 1980 to 1995. This results in the cases of either small or big stocks works quite similar, and indicates the fact that Jegadeesh and Titman’s (1993) findings have not been got accidently. In fact, the correlation between the USA’s market and European markets shows the momentum factor is common among different markets. Moskowitz and Grinbelatt (1999) investigated total profitability of momentum strategies in different industries. Their findings argued that the profitability of momentum strategies in a particular industry is the source of fulfillment of a major part of total profitability of momentum strategies in a market. According to their research, even after applying factors of firm size and book to market ratio in terms of Fama-French three-factor model, momentum still exists and shows off. Grinbelatt and Moskowitz (1999) then adjusted momentum strategies in accordance with the type of industry and showed that the profitability of these Default Risk and Momentum Effect; Some … 33 strategies (after the adjustment) reduced significantly. Unlike Jegadeesh and Titman's findings (1993), their studies arguedthat industry-based strategies were profitable both for small and big stocks and there was no significant relationship between