Abstract. The present paper deals with further analysis of the phenomenon of securities analysts’ inability to make correct stock recommendations, with Russian stock market in 2010-2013 as a case study.

Keywords: stock market, forecasts, quotations, securities, stocks
JEL Classification: G24

KOSTANDYAN, BAKHSHI (2014) "QUALITY OF STOCK RECOMMENDATIONS IN RUSSIA". Journal of Russian Review (ISSN 2313-1578), VOL. (0), 14-21.

1. Introduction

Offering recommendations based on their analysis of financial market conditions and drawing out analytical reviews, is the primary job of securities analysts. Most investors tend to pay attention to these recommendations, as expert opinion enables them to feel a degree of certainty about the future shape of the stock market, and to make profitable investments. The question of how accurate these estimates are, however, remains open, making it the aim of this paper to use a fresh body of data to re-examine the validity of the widely shared assertion that securities analysts are unable to make correct recommendations.

2. Prior studies

To present a review of literature on the subject separate searches for relevant studies in Russian and English were performed. Russian-language sources were found using the Russian Science Citation Index (RSCI) Electronic Library web site (elibrary.ru), English-language ones were searched for using the Social Science Research Network (SSRN) web site (ssrn.com), with the time horizon of 2010 to 2013.

The search at RSCI employed the following keywords (in Russian): analysts’ forecasts, forecast power, stock recommendations. The web site’s search engine came up with 362 articles, out of which 10 we chose by their titles and abstracts for further reading, with only 5 of them available for free access. However, upon reading the articles in full all 5 were dismissed as not relevant to the subject of, or having nothing of input for the present study, therefore leaving the Russian-language part of the prior studies section empty.

The search at SSRN employed the following keywords: analysts’ forecasts, stock recommendations. The web site’s search engine came up with 1263 articles, out of which 29 were chosen by their titles and abstracts for further reading, with only 10 of them available for free access. However, upon reading the articles in full 7 were dismissed as not relevant to the subject of or having nothing of input for the present study, producing 3 articles for the English-language part of the prior studies section.

The first of these, titled Do Financial Analysts’ Forecasts About Market Quotations Prove To Be Correct? Evidence From Russia (Medvedeva K., 2011) analyzes 2783 recommendations issued during the period of 1 January 2004 to 15 April 2011 for 9 Russian blue chip companies.

The methodology of that study involved examining averaged forecast figures issued by various analytical centres. Both the recommendations (sell, reduce, hold, accumulate, buy) and the relation of real and forecast target price of a share were analyzed by comparing yesterday’s and today’s price.

The use of consensus forecasts, which help to make the most objective evaluation, seems to be reasonable. However comparing the market value of a share on the day of recommendation with its actual market value the day after is not very accurate, because there is a certain amount of time between one recommendation and the next, during which the price of a share can change both up and down.

The aforementioned paper argues that there is ‘a primitive desire ‘to sell optimism to a client’’ among the securities analysts, because a substantial period of time did not see a single ‘strong sell’ recommendation, and the total number of ‘sell’ recommendations was disproportionally small (only 2%).

The next paper, titled How well do analysts predict stock prices? Evidence from Russia (Penikas H., Proskurin S., 2013) gives an overview of the factors that are likely to affect the accuracy of such forecasts. It analyses 1572 recommendations by analysts working in Russian and international investment banks, issued during the period of 1 January 2012 to 31 December 2012. The factors analyzed comprized: the number of recommendations issued per investment bank, analyst’s gender and the industry of securites issuers.

The methodology of the study was as follows: the authors would open a position in a stock right after the recommendation was released, a long one if the recommendation was ‘buy’, a short one if it was ‘sell’. The initial amount of funds invested in each stock was 1000 units of currency in which the stock was traded, depending on the stock exchange. The authors would then fully spend 1000 units of currency on each stock irrespective of its current price. E.g., if on 17 January an analyst released the recommendation to buy Gazprom ADR, at the current price of $11.44 on LSE they would spend 1000 units of currency to buy 87.41 shares. Then, after some time they would execute reverse transaction, closing the position. The horizon within which the position was closed varied from 1 to 20 days.

The study in question analyzed a large number of recommendations made within a short time frame (1 year). The analysis covered 10 of the most important industries, that is, nearly the whole spectrum of Russia’s economy, producing a comprehensive and highly credible account of the recommendations and their accuracy.

The criterion used to assess the latter was, essentially, as follows: whether an investor lost or gained money by following a recommendation. If there had been a loss, the forecast was considered unsuccessful; if the investor had gained, the forecast was considered successful. This approach helps to identily the general trend, ignoring the minor processes that make the analysis more complicated. However, it cannot be used to analyze long-term prognoses as it discards recommendations like ‘accumulate’ or ‘reduce’, using which an investor might profit in the long-term. The conclusion was that 56.8% of expert recommendations on selling or buying stocks of Russian companies were profitable.

The third paper, titled Are Stock Recommendations Useful? (Stanislawek I., 2013) also analyzed the ability of securities’ analysts to make correct forecasts, based on 3 million recommendations on MSCI World Index stocks over the period of 10 years, from 2003 to 2012. A large portion of these, it is noted, were positive (49%), with only a small number of negative recommendations (12%). With such a strong subjective bias, the paper concludes, these recommendations are not entirely reliable, though it might be useful to pay attention to them and use them as a component of a broader investment strategy.

3. Methodology

The present paper analyzes 1417 recommendations about the stock prices of 9 Russian blue chip companies:

  1. VTB (VTB)
  2. VympelCom (VIP)
  3. Gazprom (GAZP)
  4. Lukoil (LKOH)
  5. MTS (MBT)
  6. Norilskiy Nikel (GMKN)
  7. Rosneft (ROSN)
  8. Sberbank (SBER)

The research involved two types of analysis: vertical and horizontal.

   1. Vertical analysis: are ‘buy’, ‘accumulate’, ‘hold’, ‘reduce’, and ‘sell’ recommendations correct or otherwise?

To determine whether a recommendation was correct or otherwise a share’s actual market price at the time of one recommendation was compared with the price on the day of the next one. The rationale behind choosing this approach was as follows: assuming that an investor relies entirely on analysts’ recommendations and makes no deals on his own, this model would then make good sense, since as the investor, at the moment of the next recommendation should know whether the previous forecast made by the same analyst was right.This knowledge will determine the decision whether to continue to follow his recommendations.

For ‘buy’ and ‘sell’ recommendations the conclusion was made in the following way: if the real price on the day of the second recommendation was higher that on the day of the first one, the ‘buy’ recommendation was regarded as correct; if otherwise, it was deemed to be incorrect. If the real price on the day of the second recommendation was lower that on the day of the first one, the ‘sell’ recommendation was regarded as correct; if otherwise, it was deemed incorrect.

For ‘reduce’, ‘hold’, and ‘accumulate’ recommendations, the forecast (predicted) price of a share was checked for staying within the 5% margin of deviation from its actual price on the day of the recommendation.

     2. Horizontal analysis: how much does the real market price of a share deviate from the forecast?

This type of analysis was meant to assess the accuracy of a forecast by comparing how much the actual market price of a share at the time of one recommendation deviated from the price forecast on the day of the previous one.

According to the null hypothesis, the more efficient a stock market is, the greater the extent to which recommendations errors exceed actual stock prices, and the smaller the possibility to manipulate there shares.


4. Data sources

The source of market data (real prices on the day of a recommendation and their forecast values) used in the present paper is the database of the Russian media group RosBusinessConsulting’s at quote.rbc.ru.

The paper uses only consensus forecasts showing the general market opinion of a share provided by the well-known Russian international and financial institutions, such as:

  1. Barclays Capital
  2. Citigroup Investment Research
  3. Credit Suisse First Boston
  4. Deutsche Bank
  5. Goldman Sachs
  6. JP Morgan
  7. Raiffeisen RESEARCH
  8. Sberbank Investment Research
  9. Alfabank
  10. VTB Kapital
  11. Gazprombank
  12. Uralsib Capital
  13. Finnam

The time frame of the research is from 1 January 2010 to 31 December 2013.

5. Conclusions

  1. The average proportion of errors made by securities analysts in predicting their values was 48.6%. This figure does not appear to be very high, given the possibility of price manipulations on the Russian stock market.
  2. Compared to shares issued by other companies, (both in the vertical and horizontal analysis), shares in MTS were shown to be the least predictable in terms of their price (see Figures 5 and 6). Erroneuous value predictions amounted to 57% of all forecasts, missing the market price by an average of 52%. This suggests that shares in MTS are the least manipulatable among Russian shocks.
  3. Shares in Norilskiy Nikel and VTB showed the lowest amount of errors in vertical analysis (43% and 34%, respectively), and the lowest discrepancy of forecast and actual prices in horizontal analysis (18% and 25%, respectively; see Figures 5 and 6). The relatively low amount of errors, together with the relatively high degree of forecast accuracy, suggests that shares of these companies are the most manipulatable ones.
  4. The study revealed the following curious fact: during the whole period of time analysed, from 1 January 2010 to 31 December 2013, there was not a single ‘reduce’ or ‘sell’ recommendation for any of the companies. Moreover, the largest portion of these – 45% - were ‘buy’ recommendations. This suggests that analysts deliberately ignore possible falls in prices and intentionally try to draw potential investors’ attention to positive growth prospects (see Appendix, Figure 1), a view supported by the fact that 98% of all forecasts showed upward errors (see Appendix, Figure 7).
    This agrees with Medvedeva (2011) who analyzed the same set of issuing companies from 1 January 2004 to 15 April 2011 and came to the same conclusions as the present paper’s analysis of the period from 1 January 2010 to 31 December 2013.
  5. This means that it can safely be asserted that in the last 10 years there has been not a single ‘sell’ recommendation, and the proportion of ‘reduce’ recommendations compared to the 80% bulk of ‘accumulate’ and ‘buy’ recommendation was miniscule. Covering a substantial period of time, this enables the researcher to identifity the motivating force behind securities analysts’ behaviour: blind faith in the perpetual growth of blue chips or, more likely, a primitive desire to attract as many new clients as possible by ‘selling them optimism’. Therefore securities analysis as an institution in Russia can be described as non-existent.

6. References

  1. Ireneus Stanislawek Are Stock Recommendations Useful? // 1741 Asset Management Research Note Series 4/2012. Available at: http://ssrn.com/abstract=2182731
  2. Medvedeva K. Do Financial Analysts’ Forecasts About Market Quatations Prove to Be Correct? Evidence from Russia. Available at: http://ssrn.com/abstract=1866370
  3. Penikas H., Proskurin S. How Well Do Analysts Predict Stock Prices? Evidence from Russia // Higher School of Economics Research Paper No. WP BRP 18/FE/2013. Available at: http://ssrn.com/abstract=2337416


7. Appendix



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