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EVALUATING THE ACCURACY OF STOCK ANALYSTS’ RECOMMENDATIONS PUBLISHED IN BISNIS INDONESIA NEWSPAPER†
Arnold Kaudin & Yustin Hendro Pranoto
Academic Staff of the Faculty of Economics Satya Wacana Christian University & Alumnus of the Faculty of Economics Satya Wacana Christian University
ABSTRACT
Many investors have not enough knowledge, skill, and time to learn which stocks are the candidate to buy or sell. A stock analyst provides recommendation and help investors to make buy or sell decision. The purpose of this study is to investigate the stock analysts’ recommendation accuracy published in Bisnis Indonesia daily newspaper. The data used in this research is analysts’ recommendation published in Bisnis Indonesia along the year 2005. There are 1,196 buy recommendations, 500 sell recommendations, and 649 price recommendations; released by six security companies. The technique used to measure the accuracy of price prediction is the Chi Square and to measure the accuracy of recommendation to sell or buy is Wilcoxon Match Pair Test. The result shows that the stock price and recommendation to sell tend to be inaccurate while recommendation to buy tends to be accurate. Keywords: recommendation accuracy, stock analyst, price recommendation,
recommendation to sell, recommendation to buy
1. INTRODUCTION
The rapid development of the Indonesian financial market in recent years enables investors to choose various investment instruments. One among the alternatives which have been growing rapidly and becoming more popular for the last decade is investment in stock. The Capital Market Supervisory Agency reported that during the period 1995- 2005, stock exchanges in Indonesia recorded an average annual increase of 12.76 percent in term of indices (Indonesian Capital Market Master Plan 2005-2009). In the Jakarta Stock Exchange, alone in 2005, the indices increased as high as 16.20 percent from 1,000.87 to 1,162.35. The market capitalization achieved the value of 710,433,652 million rupiah, grew for around 259 percent in five year period. The average trading volume was 73 million shares per day, around twice as high the average volume from five year period before. There were around 207 companies’ shares listed and around
† This paper was presented in The 4th UBAYA International Annual Symposium on Management 2007. We’d like to thank the participants for valuable suggestions.
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130,000 investors serviced by more than 100 securities companies. The industry has been growing as the number of players in capital market increases from year to year.
As the industry grows and becomes more complex, not all of the investors, both institutional and individual, have enough expertise in analyzing the market. Most of them are only interested in accelerating the growth of their funds. They do not have enough knowledge, skill, and time to learn which stocks are the candidate to buy or sell. Therefore, as the stock market develops, the profession of financial (stock) analysts exists. Many investors find that choosing and managing investments is not their forte and turn to financial analysts‡ (Penman, 2003:12). A stock analyst gives recommendation and help investors to make buy or sell decision as those people are the ones fully equipped with knowledge and skill. Related to their professions, these people have connection to the corporate side and thus have access to the most actual and more complete information.
Analyst report contains a description of company’s business, how the analysts expect the company to perform, earnings estimates, price estimates or price targets for year ahead, and recommendations as to buy, to hold, or sell (Jones, 2002:298). Further, analysts should do more than simply recommend companies expected to grow rapidly. One of the most important responsibilities of an analyst is to forecast earnings per share for particular companies because of the widely perceived linkage between expected earnings and stock returns. Most research concerning quality of analysts entails measuring the ability of analysts to determine the expected earnings (See, for instance, Andersson and Hellman [2004], Eames and Glover [2003], and Armstrong [1983]).
In fact, the recommendation and or advice made by analysts are not always accurate. For cases in U.S., according to Bodie et al. (2005:10), only the smallest fraction of firms were assigned sell recommendations and many firms given buy recommendations were privately called or worse by the analysts. As the analysts must establish good relation to the management of the companies he or she in charge of, there is a possibility that publishing sell recommendations would be hurt for the companies’ side (the management) and after the sell recommendation those analysts would get trouble in accessing information. There is a perception that sell recommendation is the beginning of distrust. It has been common in U.S. that “neutral” rating is the euphemism for sell. Some well known cases entails recommendations to sell in U.S. are the case of Boston Chicken and Bank of America. Jegadeesh and Kim (2004) documents that the frequencies of sell recommendations in G7 countries between 1993 and 2002 are far less than that of buy recommendations. Wong (2002) provides evidence that analyst in Australia issue more recommendations to buy compared to recommendations to sell. Recommendations
‡ In this paper the terms financial analyst and stock analyst are used interchangeably due to different terminologies used by different authors.
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to sell have stronger impact to prices but weaker impact to trading activity. This implies that analysts are conscious of the benefit of issuing positive recommendations and the cost of issuing negative recommendations.
The inaccurate recommendation may also come from inaccurate prediction of the price movement. Off course this is a technical matter. Jones (2002:300) adapted Hovanesian article in Business Week that illustrated how sell recommendation from large investment bankers such as Credit Suisse First Boston (CFSB), UBS Warburg, Merrill Lynch, Morgan Stanley Dean Witter, etc may lead to wrong investment decision. For example, among 1,328 stocks covered by CFSB, only eleven stocks were recommended to be sold. Ironically, among those eleven, after 52 weeks, only five were really declined and one other was stagnant. Three from four stocks recommended to be sold by UBS Warburg had grown for 64.2 percent, 9.3 percent, and 17.9 percent.
Bodie et al. (2005:10) argue that agency problems may lead to scandals. Conflict of interest and distorted incentives played a role in these scandals as the analysts were commonly compensated not for the accuracy or insightfulness of their analysis, but for their role in garnering investment banking business for their firms. Analysts working in brokerage house receive commission based on trading volume which is affected by their recommendations (Palepu et al., 2004:9). In U.S, the conflict of interest between the analysts who play in stock research business and its investment bank materialized in new regulations adopted by NASD and NYSE that sever the ties between investment bank and research department. Madureira (2004) finds that after the new regulations analysts provide less optimistic ratings for the stocks. Further, after the regulations, the big 10 brokerage houses have been twice more likely to put a stock in a pessimistic rating than the non-big 10. This indicates that before the regulation, the bigger the brokerage houses, the bigger the possibility of recommendations manipulated.
Another study concerning the conflict of interest was conducted by Agrawal and Chen (2007). They find that the level of analysts’ stock recommendations is positively related to the magnitude of the conflict of interest between the investment bank and research department. The optimistic bias stemming from the conflict was pronounced during the late 1990s stock market bubble. However, they also find that investor are sophisticated enough to adjust for the bias. Another finding is when the analysts’ investment bank was the lead underwriter of an IPO of the recommended stock in the past five years or a secondary IPO in the past two years (mentioned as affiliated analyst), the recommendations are more optimistic than if the analysts’ investment bank had no underwriting relation to a company’s recommended stock. However, the affiliated analysts’ earnings forecasted found to be more pessimistic than the unaffiliated analysts’ forecast (Malmendier and Shantikhumar, 2005)
Accuracy of recommendations becomes the eminent point in this study. Investors based their decisions, or at least some part of their decisions, on the analysts’ advice or
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recommendations. Thus, it becomes important to evaluate the performance of the stock analysts. So far, it is very difficult to find research concerning stock analysts’ recommendation accuracy for the Indonesian case. There is still a lack of empirical evidence whether the Indonesian analysts’ recommendations are informative. The obstacle to make such an evaluation is the data, which is very limited and only distributed to investment bankers’ customers exclusively. Media such as Bisnis Indonesia daily newspaper, Tabloid Kontan, Investor magazine, e-bursa.com, and some others provide publicly available stock recommendations.
The purpose of this study is to investigate the stock analysts’ recommendation accuracy published in Bisnis Indonesia, which is considered as the most consistent media publishing recommendations from stock analysts; and to arrange the analysts’ ranking based on the level of prediction accuracy. Before going through a deeper exploration of security analysts’ behavior and the market’s perception, this preliminary study is conducted to determine the accuracy of stock analysts’ recommendations for the Indonesian case.
2. THEORETICAL BACKGROUND AND PRIOR STUDIES
Rather than do their own security analysis, individual investors may choose to rely on the recommendations of the professionals (Jones, 2002:298). When a stock analyst decides that a stock will experience a change in price and inform his or her findings to investors, the investors will give response to the information. Thus the price will be affected. If the information widespread, there will be more responses from more investors and the price will be affected more. The analysts predict business prospect to find mispriced securities. They provide recommendation to buy for the under-priced securities and recommendation to sell for the overpriced securities. When an analyst decides that a stock value is under-priced, the response should be actions to buy which result in an increasing stock price. On the contrary, when an analyst decides that a stock value is overpriced; the response should be actions to sell which result in a decreasing stock price. Observations show that stock prices in the New York and Tokyo Stock Exchange are highly affected by recommendations from analysts (Bawazer, 1991).
Though theoretically all brokerage house customers and portfolio managers who receive analysts’ expert advice should achieve investment success, in reality there are several factors that make it difficult to consistently outperform the market (Reilly and Norton, 2006:510): 1. Efficient markets enable the market to review and absorb information and therefore
stock prices generally approximate fair market value. With many market players, it is difficult for investors to find situation where stock may not be fairly valued.
2. Most analysts spend most of their times in a relentless search of one or more contact or one more piece of information. This preoccupation with more information can keep the analysts’ mind off the final output – that is, their stock recommendations.
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3. There are forces pulling on the sell-side analyst. If the investment bankers are assisting a firm in a stock or bond offering, it will be difficult for an analyst to issue a negative evaluation of the company. Besides, the analyst is in frequent contact with the top officers of the company he or she analyzes. Although there are guidelines about receiving gifts and favors, it is sometimes difficult to separate personal friendship and impersonal corporate relationships.
Analysts based their recommendations on some analytical tools. They analyze current performance of the target and its prospect. They estimate the future earnings per share of the target, determine whether the current market price is over or under valued, and finally provide recommendations to buy, to hold, to sell (also mentioned as stock ranks by Morgan and Stocken, 2001) or the variety of these basic forms of recommendations. Nevertheless, missed recommendations have been common and create skeptical among investors or other users of analysts’ recommendations. Some argue that it is not always clear how the recommendation follows from the analysis, or indeed whether it is justified (Penman, 2003:12) and the motives of the analysts providing advice may not be transparent (Morgan and Stocken, 2001).
On the other hand Bradshaw (2004) proves that analysts’ recommendations do work for the investors. He links valuation techniques used by analysts to recommendations by examining consistency between analysts’ earnings forecast and their stock recommendations. He used four valuation models to link earnings forecast and stock recommendations. He found that analysts’ recommendations are more correlated with heuristic valuations model than with present value models, and buy-and-hold investors would earn higher returns relying on present values models that incorporate analysts’ earnings forecasts than on analysts’ recommendations. Bradshaw also explained that personal opinions or biases dominate recommendations based on present value model. Wong (2002) explains that analysts’ recommendations in Australia were observed to be associated with abnormal returns on the day they were officially released to clients. Stocks issued with sell recommendations continued to experience negative abnormal returns in the post-recommendation period while returns to buy recommendations were partly due to price pressure. Hold recommendations were informative as buy rather than sell signals. She also finds that abnormal returns were observed in the pre- recommendations period, means that analysts had poor timing ability, reactive in making recommendations, recommend privileged clients first, and left behind the traders. Similar to Wong, but in term of volume (U.S case), Puckett (2002) finds that analyst’ initiations of recommendations to buy are preceded by abnormal institutional volume and abnormal net buying positions taken by those institutions for up to four days before the initiations of coverage are made public.
Welch’s findings (2000) probably can provide an explanation about the abnormal return during pre-recommendations period. According to Welch, analysts’ recommendations
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may also be affected by prior recommendations. He finds that an analyst’s recommendation revision has a positive influence on the next two analysts’ revisions. The influence can be traced to short-lived information and is stronger when short run ex-post returns are accurately predicted by the revisions. The influence becomes stronger during the bullish market.
Baber et al. (2002) study the returns of stock recommended by analysts over the 1996- 2000 periods in U.S. They find that during the period 1996-1999 the more highly recommended stocks earned greater market-adjusted returns than did those that were less highly recommended. The opposite happened in year 2000 where the least favorably recommended stocks earned an annualized market-adjusted returns of 48.66 percent while the stocks most highly recommended fell 31.20 percent. The pattern prevailed during most months of 2000, regardless of whether the market was falling or rising, and was observed for both tech and non-tech stocks. Further they propose that the result should add to the debate over the usefulness to investors of analysts’ stock recommendations. Ho (2005) examines whether investment decisions based on analyst ratings without studying the full reports is sound. He finds that analysts are unable to forecast stock performance in the short term (1-2 weeks) as during the short period the excess return are indistinguishable from zero. Analysts’ ratings reflect excess return best about seven months later.
Another study by Jegadeesh et al. (2004) provides evidence that stocks which receive higher recommendations tends to have positive momentum and higher trading volume. On average, stocks favorably recommended by the analysts outperform stocks unfavorably recommended by the analysts but the predictive ability of the level of analyst recommendation is not significant. This poor performance is caused by the analysts’ failure to quickly downgrade stock rejected by some investment signals (valuation multiples, accounting accruals, capital expenditure). They conclude that analyst recommendations may be partly driven by incentives that are not entirely related to the investment performance of the analysts’ recommendations.
A study by Ribeiro et al. (2004) provides evidence from Portuguese investment banks that trading strategies based on analysts’ recommendations have a negative performance regardless of the investment horizon. However, they find a positive significant return on the day the recommendations are published. They conclude that the positive impact is partially consistent with market efficiency and supports that analysts have forecasting skills.
Stock analysts are highly trained individuals who possess expertise in financial analysis and background of the industry. Theoretically, all brokerage house customers and portfolio managers who receive analysts’ expert advice should achieve investment success (Reilly and Norton, 2006:510). As analysts have knowledge, skill, and information, we believe that the price and buy or sell recommendation given is based
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on a deep calculation and analysis. Thus, our hypotheses are that analysts’ price recommendation and their recommendation to buy or sell are accurate.
3. SAMPLES AND RESEARCH METHOD
The population of this research is all analysts’ recommendations published in the Bisnis Indonesia newspaper along the year 2005. The samples include price recommendations and clear recommendation to sell or buy the stocks. More specific recommendations such as exit, take profit, hold, etc are excluded to avoid bias in interpretation. There are 649 price recommendations, 500 sell recommendations, and 1,196 buy recommendations; released by six security companies: Bhakti Sekuritas, BNI Sekuritas, Mandiri Sekuritas, Ciptadana Sekuritas, Trimegah Sekuritas, and Sarijaya Sekuritas.
The price recommendation is considered to be accurate when the price at the second day after the recommendation matches with the two-days before recommendation price. We use the two days before and after recommendation date price by consideration that the two-day period is a neutral time horizon because: 1. The recommendation must be for a short-term horizon since it is published in a
daily newspaper. 2. In many occasions, analysts provided more than one recommendation for one stock
in a month.
Nevertheless, the recommendations may also affect the price at the recommendation date, one day after the recommendation date, five days after the recommendation date, etc. The technique used to measure the accuracy of price prediction is the Chi Square Test. We assume that price recommendations are considered to be accurate when the proportion of correct price recommendations (in aggregate) achieves the 50 percent level.
To determine the effect of the sell or buy recommendations, we compare the two days before recommendation date price to the two days after the recommendation date price. The recommendation to sell is considered to be accurate when the price at the second day after the recommendation date is lower than two-days before recommendation price. The buy recommendation is considered to be accurate when the price at the second day after the recommendation is higher than the two-days before recommendation price. To measure the accuracy of recommendation to sell or buy is Wilcoxon Match Pair Test.
The ranking of security companies which provide the highest level of accuracy for their price recommendation, recommendation to sell and recommendation to buy is
After the Kolmogorov-Smirnov Test, we find that the distribution of the data is not normal. Thus we use the non parametric technique of Wilcoxon Match Pair Test to measure the differ- ence between the two days before the recommendation price and the second day after the rec- ommendation price.
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determined by comparing the number of accurate recommendations. The security companies included in the ranking process must produce not less than 52 recommendations during the year 2005. The number 52 is established by consideration that there must be at least one recommendation (in average) released for every week. Security companies which released too few recommendations cannot be compared to those which actively published their recommendations.
4. RESULTS
Table 1 show that Bhakti Sekuritas was the most productive security company publishing stock recommendations in Bisnis Indonesia in 2005. It released 671 recommendations, which comprised of 221 price recommendations, 313 recommendations to buy, and 137 recommendations to sell. BNI Sekuritas following in the second place with 574 stock recommendations, which comprised of 345 recommendations to buy and 229 recommendations to sell. Almost all of recommendations published by Mandiri Sekuritas were price recommendations while Trimegah seems to prefer releasing recommendations to buy or to sell. Ciptadana Sekuritas was the least active among the six as it only released 70 recommendations for the whole year.
Table 1 The Number of Recommendations Released By the Analysts
Source: Bisnis Indonesia in year 2005, processed
The following are the test results and discussions from price recommendation accuracy, recommendation to sell accuracy, recommendation to buy accuracy, evaluation of accuracy from each recommendation provider, and ranking of accuracy.
4.1 Test Result of the Price Recommendation Accuracy
Among 649 price recommendations given along 2005, only 37 (or 5.7 percent) recommendations matched the target and the other 612 (or 94.3 percent) were missed. As mentioned before, we assume that price recommendations are considered to be accurate when the proportion of correct price recommendations achieves the 50 percent
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level. The Chi Square Test results in a Chi Square score of 509.438 with significance level of 0.00 (Lower than 0.05). This means that the proportion of correct recommendation is not 50 percent. Thus, in general, the price recommendations are not accurate.
4.2. Test Result of the Recommendation to Sell Accuracy
The recommendation to sell is considered to be accurate when the price at the second day after the recommendation date is lower than the price at two-days before recommendation date. The following table shows the result of Wilcoxon Match Pair Test for the accuracy of recommendation to sell:
Table 2 Wilcoxon Match Pair Test for the Accuracy of Recommendations to Sell
Among 500 recommendations to sell published in Bisnis Indonesia along 2005, there are 239 data of price differentiation which have negative ranks. This means that the price at the second day after the recommendation date is lower than the price at two- days before recommendation. The other 219 data of price differentiation have positive ranks, which show that the price at the second day after the recommendation date is higher than the price at two-days before recommendation. The other 42 data shows that the price at the second day after the recommendation date matches to the price at two- days before recommendation.
The p-value of the Wilcoxon Match Pair Test is 0.290. As the test was one sided, the value, divided by two equals to 0.145, which is higher than 0.05. Therefore, we accept that the price at the second day after the recommendation date is higher than or matches to the price at the two-days before recommendation date, which means that the sell recommendation is not accurate.
During year 2005 the Indonesian stock market experienced a bullish period. Many recommendations to sell became not relevant. Many stocks predicted to loose experienced increasing in price because of the domination of sentiment to buy during the bullish period. Therefore, in general, the recommendation to sell is not accurate.
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Source: data processed
4.3 Test Result of the Recommendation to Buy Accuracy
The recommendation to buy is considered to be accurate when the price at the second day after the recommendation date is higher than the price at two-days before recommendation date. The result of Wilcoxon Match Pair Test for the accuracy of recommendation to buy is shown in the following table:
Table 3 Wilcoxon Match Pair Test for the Accuracy of Recommendations to Buy
Among 1,196 recommendations to buy published in Bisnis Indonesia along 2005, there are 711 data of price differentiation which have positive ranks, means the price at the second day after the recommendation date is higher than the price at two-days before recommendation. The other 376 data of price differentiation have negative ranks, which means that the price at the second day after the recommendation date is lower than the price at two-days before the recommendation date and the other 109 data price shows that the price at the second day after the recommendation date matches to the price at two-days before the recommendation date.
The p-value of the Wilcoxon Match Pair Test is 0.000 which is lower than 0.05. Therefore, we reject that the price at the second day after the recommendation date is lower than or matches to the price at the two-days before recommendation date. As it is higher, the recommendation to buy is generally accurate.
The bullish period in the stock market had strengthened sentiment to buy and pulled the price up in general. Thus many recommendations to buy match the targeted price or the targeted trend. In case the investors read and consider recommendations published in Bisnis Indonesia, the result indicates that those investors give immediate response (two days) to the recommendation.
4.4 The Analysts’ Level of Accuracy
Table 4 shows the level of accuracy of price recommendations per analyst:
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Source: data processed
Table 4 The Level of Accuracy of Price Recommendation
Source: data processed
As mentioned before, the security companies included in the ranking process must produce not less than 52 recommendations along the year with consideration publishing one price recommendation in average every week. The table shows that Mandiri Sekuritas provided 356 price recommendations with 8 percent level of accuracy, Bhakti Sekuritas provided 221 price recommendations with 3 percent level of accuracy, and Ciptadana Sekuritas provided 56 price recommendations with 2 percent level of accuracy. The more price recommendations provided, the higher the level of accuracy, but the level of accuracy remains low.
In fact, price recommendations can be separated into price recommendation to sell and price recommendation to buy as shown in Table 5. Panel 1 shows the price recommendation to buy. In general, the level of accuracy from price recommendation to buy obtains 46 percent. Mandiri Sekuritas was the most active producer of price recommendations to buy with its 354 recommendations, which achieved 53 percent level of accuracy. The second most active producer was Bhakti Sekuritas (121 recommendations) whose level of accuracy was only 25 percent, lower than Ciptadana Sekuritas which produced only 56 recommendations but achieved 41 percent level of accuracy.
Panel 2 shows the price recommendation to sell from each analyst. In general, the level of accuracy was only 21 percent. Bhakti Sekuritas was the most active (if not the only) producer of price recommendation to sell with 100 recommendations which achieved 19 percent level of accuracy. It seemed that the bullish market did not attract many analysts to produce price recommendations to sell.
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Table 5 Price Recommendation to Buy and Price Recommendation to Sell
Source: data processed
The following table shows the accuracy of recommendation to sell:
Table 6 The Level of Accuracy for the Recommendation to Sell
Source: data processed
Majalah Ekonomi Tahun XVII, No.3 Desember 2007
The aggregate level of accuracy for recommendation to sell is 48 percent. The table shows that the best three recommendations to sell provider were Sarijaya Sekuritas with 63 percent level of accuracy, followed by Bhakti Sekuritas (58 percent), and Trimegah Sekuritas (43 percent). Again, the low level of accuracy from recommendation to sell might be caused by the bullish market period.
Table 7 The Level of Accuracy for the Recommendation to Buy
Source: data processed
Table 7 shows that Sarijaya Sekuritas had the highest level of accuracy for the recommendations to buy. Among 172 recommendations it released, 130 were accurate. The level of accuracy was 76 percent, and this level is considered as the best1. In the second place is Trimegah Sekuritas which produced 348 recommendations to buy and achieved 62 percent level of accuracy, followed by Bhakti Sekuritas (313 recommendations with 58 percent level of accuracy), and BNI Sekuritas (345 recommendations with 51 percent level of accuracy). In aggregate, the level of accuracy for recommendations to buy is 59 percent.
We consider that the level of accuracy from recommendation to buy has not been a reflection of the analysts’ quality since during bullish period the price moves in an uptrend. Thus, any recommendations to buy have a bigger opportunity to match the target price.
5. CONCLUSIONS
This study examines the accuracy of stock analysts’ recommendations published in Bisnis Indonesia newspaper along year 2005. Our findings are:
1 Mandiri Sekuritas achieved 75 percent level of accuracy. However; it only produced four recommendations along the year and therefore not comparable to the ones which actively pro- duced the recommendations.
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1. The proportion of accuracy from price recommended by the analysts does not achieve 50 percent level. Thus, we conclude that in general the price recommendation published in the Bisnis Indonesia newspaper is not accurate.
2. The two-days after recommendation price of stocks recommended to be sold are higher than the two-days before recommendation price. If the recommendation is accurate, it should be lower. This means that in general the sell recommendation is not accurate.
3. For the recommendation to buy, the two-days after recommendation price of stocks recommended to be sold are significantly higher than the two-days before recommendation price. Therefore, we conclude that the recommendation to buy is generally accurate.
4. The best rates of accuracy for price recommendation published in Bisnis Indonesia newspaper along 2005 are as follows: Mandiri Sekuritas (8 percent), Bhakti Sekuritas (3 percent), and Ciptadana Sekuritas (2 percent).
5. The best three rates of accuracy for sell recommendations published in Bisnis Indonesia are as follows: Sarijaya Sekuritas (63 percent), Bhakti Sekuritas (58 percent), and Trimegah Sekuritas (43 percent). The best three rates of accuracy for buy recommendations are Sarijaya Sekuritas (76 percent), Trimegah Sekuritas (62 percent), and Bhakti Sekuritas (58 percent).
6. LIMITATIONS
Some limitations from this study are: 1. The recommendations resulted from fundamental and technical analysis cannot be
detected since the information to make distinction cannot be achieved. Besides, recommendations that are published in Bisnis Indonesia daily newspaper are the representation of financial institutions (securities companies), not the individual analyst.
2. Some more specific recommendation types such as buy on weakness, sell on strength, trading buy, trading sell, accumulate buy, speculative buy, hold, take profit, exit are excluded from samples to avoid ambiguity. The samples includes only clear “buy” or “sell”recommendations.
3. The two days before and after recommendation price that is used as time indicator to evaluate the accuracy of buy and sell recommendations; and the 50 percent level of accuracy to evaluate the accuracy of price recommendation can be considered as subjective.
4. The results do not reflect the real quality of the analysts as the observation is conducted during bullish market period.
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Majalah Ekonomi Tahun XVII, No.3 Desember 2007 EVALUATING THE ACCURACY OF STOCK ANALYSTS’ RECOMMENDATIONS PUBLISHED IN BISNIS INDONESIA NEWSPAPER Arnold Kaudin & Yustin Hendro Pranoto Academic Staff of the Faculty of Economics Satya Wacana Christian University & Alumnus of the Faculty of Economics Satya Wacana Christian University ABSTRACT Many investors have not enough knowledge, skill, and time to learn which stocks are the candidate to buy or sell. A stock analyst provides recommendation and help investors to make buy or sell decision. The purpose of this study is to investigate the stock analysts’ recommendation accuracy published in Bisnis Indonesia daily newspaper. The data used in this research is analysts’ recommendation published in Bisnis Indonesia along the year 2005. There are 1,196 buy recommendations, 500 sell recommendations, and 649 price recommendations; released by six security companies. The technique used to measure the accuracy of price prediction is the Chi Square and to measure the accuracy of recommendation to sell or buy is Wilcoxon Match Pair Test. The result shows that the stock price and recommendation to sell tend to be inaccurate while recommendation to buy tends to be accurate. Keywords: recommendation accuracy, stock analyst, price recommendation, recommendation to sell, recommendation to buy 1. INTRODUCTION The rapid development of the Indonesian financial market in recent years enables investors to choose various investment instruments. One among the alternatives which have been growing rapidly and becoming more popular for the last decade is investment in stock. The Capital Market Supervisory Agency reported that during the period 1995- 2005, stock exchanges in Indonesia recorded an average annual increase of 12.76 percent in term of indices (Indonesian Capital Market Master Plan 2005-2009). In the Jakarta Stock Exchange, alone in 2005, the indices increased as high as 16.20 percent from 1,000.87 to 1,162.35. The market capitalization achieved the value of 710,433,652 million rupiah, grew for around 259 percent in five year period. The average trading volume was 73 million shares per day, around twice as high the average volume from five year period before. There were around 207 companies’ shares listed and around This paper was presented in The 4 th UBAYA International Annual Symposium on Management 2007. We’d like to thank the participants for valuable suggestions. -283-
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