Insider-trading patterns
We have uncovered the following characteristics of insiders' transactions:
1. There is a lot of insider trading. During the past 21 years between 65% and 80% of all publicly listed firms report at least one open market transaction by an insider every year. Consequently tracking insider trading is likely to provide useful signals in most firms.
2. There are four- to five-year cycles in overall insider buying and selling activity. In the last 21 years, there were two aggregate buying cycles and two aggregate selling cycles. This finding suggests that insiders are likely to respond to macroeconomic conditions when they trade securities of their firms. The aggregate levels of insider trading should also be kept in mind when evaluating insider-trading patterns in a given firm.
3. The unconditional probability of trading against insiders is small. In small firms insiders account for 2% of the trading volume. With increasing firm size, the proportion of the trading volume initiated by the insiders falls further. In large firms insiders account for about 0.5% of the trading volume. However, insider trading is concentrated into certain months. When insiders do trade, they account for 12% of the trading volume in small firms. Similarly, when they do trade, they account for 1% of the trading volume in large firms.
4. Despite the significant increases in insider-trading sanctions during the 1980s, there was no decline in the levels of insider trading. If anything, a greater proportion of firms report insider trading in the 1990s than in the 1980s or 1970s. Overall, evidence suggests that most insiders do not worry too much about regulatory restrictions when they buy and sell shares in their own firms. In addition there appears to be a trend toward increasing amounts of insider selling over time. For the period 1980 to 1995, insiders have sold 4.3 billion more shares than they bought.
5. In large firms insiders tend to sell twice as frequently as they buy. In smaller firms insiders tend to execute four purchases for each three sale transactions. These normal levels of insider-trading activity must be kept in mind when evaluating potentially unusual insider trading in a particular firm.
6. Purchases tend to come in small denominations. Sales tend to be more likely when the trading volume increases. This finding suggests that insiders may be breaking up their purchases into smaller lots in fear of regulatory sanctions. Insiders do not seem to worry as much about the regulatory implications of their sales.
7. Insider buying is more likely to occur at the turn of the year. Insider buying is lowest during the summer months. This finding is consistent with the so-called January effect when stock prices of especially small firms rise significantly in January. This evidence suggests that at least some insiders view the expected rise in stock prices in January as a profit opportunity.
8. Insider-trading activity is positively correlated over time. Past insider buying in a given firm increases the likelihood that insiders in the same firm will continue to buy stock in the future. Past insider selling increases the likelihood that insiders will continue to sell stock in the future. The positive correlation in insider trading suggests that insiders respond to common information signals that change slowly over time.
9. Insiders do not appear to be manipulating stock prices. Manipulation implies reversals in the direction of insider trading. Evidence shows that the probability of reversals is higher at 12 months than at one month. Also, contrary to expectations, the probability of reversals is smaller for top executives.
10. Regulation of insider trading has increased along with the increased involvement of stock investors in the stock market. Insider-trading sanctions now treat illegal insider trading the same as violent crimes. Increased insider-trading regulations have reduced specific instances of insider trading that are most likely to be prosecuted. Neither the volume nor the profitability of everyday insider trading is affected by increased insider-trading sanctions.
11. Insider-trading regulations tend to benefit small, liquidity-concerned investors at the expense of large, governance-motivated investors. Increased restrictions on insider trading is likely to lower the incentives of large shareholders to participate in corporate governance.
A stock-picking strategy
1. Of the four different classes of insiders, top executives are most informed, followed by officers and directors. Large shareholders appear to be the least informed. These findings suggest that insiders' private information comes from the day-to-day contact with all operations of the firm, rather than changes in corporate strategies, potential acquisitions or dispositions, or changes in market volume.
2. On average, all insiders trade a greater number of shares when they have more valuable information. However, at extremely high levels of trades, profitability falls. In fact profitability of trades exceeding 100,000 shares is less than the profitability of trades between 10,000 shares and 100,000 shares. At extremely high trade levels, greater regulatory scrutiny becomes an important concern. The concern about highly visible 100,000 plus-share trades are especially important in large firms. It is likely that all insiders and especially top executives in large firms feel that they are subject to greater public scrutiny.
3. When examining only large trades by insiders, it is extremely important to focus only on transactions by officers, directors, and top executives. Large trades by large shareholders do not contain any information.
4. Insiders' purchases are more profitable than insiders' sales. This conclusion holds regardless of the type of insiders or firm size.
5. Insider trading is a lot more profitable in small firms than it is in large firms. Insiders earn an average of 6.2% in small firms as compared with 1.7% in large firms. For outside stock market investors who are interested in imitating insiders in large firms, selectivity is required. Outside investors are cautioned to restrict their attention only to top executives who trade more than 1,000 trades.
6. In small firms all classes of insiders appear to trade profitably. Hence distinguishing between different classes of insiders does not improve performance much. However, purchases in small firms appear to contain more information than sales. In particular, small sales volumes do not seem to have any predictive ability. Both large purchases and large sales are informative. A large purchase by a top executive in small firms outperforms the market index by 14.7% over 12 months. A large sale by a top executive is associated with 7.8% average profit.
7. Consensus among insiders also plays an important role in determining the quality of insider-trading signals. As more insiders trade in a given direction, the value of insider-trading information increases.
8. Insiders do appear to time the exercises of their stock options. Stock prices rise following insiders' exercises of put options while stock prices decline following the exercises of call options (after 1991). Hence insiders' option exercises also contain important information regarding the future direction of stock price changes. Moreover exercises of put options seem to provide stronger signals. However, other types of transactions by insiders do not appear to provide strong signals regarding the direction of future stock price changes.
9. Interaction effects between sales-purchases, identity of insiders, volume of trade, and firm size are mostly unimportant. Each of these variables exerts an independent and additive influence on the profitability of insider trading. This is good news for the stock pickers, since it simplifies the stock selection criteria.
Predicting future market returns
Our findings indicate that aggregate insider trading is a reliable predictor of the future market returns.
1. Aggregate insider trading predicts aggregate stock returns. The overall stock market increases more if the past aggregate insider trading is positive than it does if the past aggregate insider-trading signal is negative. However, stock prices do not decline following insider sell signals. They simply rise less than those following positive aggregate insider-trading signals.
2. The strength of the aggregate insider-trading signals increases with the aggregation period. Hence aggregating insider-trading signals over the past 12-month period gives more reliable signals than aggregating insider-trading signals over the past month or the past 3 months.
3. Using 12-month aggregate insider trading and a 50%-50% rule to identify buy and sell signals, stock prices increase by 28.7% following the past 12-month aggregate insider buy signals. Moreover the market rises following each of the seven years when aggregate insider trading signal is positive. In contrast, the market rises only by 12.9% following the 12 years when the past 12-month aggregate insider-trading signal is negative. Hence using aggregate insider trading predicts an additional 16-point extra return to the market portfolio.
4. Using more extreme insider-trading signals further improves the predictive content of insider trading. Using 55%-45% rule to identify buy and sell signals, the difference in market returns following positive and negative aggregate insider-trading signals grows to almost 26 points.
5. Combining firm-specific insider-trading signals with the aggregate signals leads to better forecasting of future stock returns.
6. Aggregate insider trading predicts changes in future economic growth up to two years ahead. Other studies have also shown that stock returns are also a leading indicator of future real activity up to one year ahead. Consequently it should not be surprising that aggregate insider trading forecasts furture stock returns up to one year ahead.
7. It is also possible to time industry returns using industrywide insider trading. Our results indicate that U.S. auto stocks are better predicted by using the aggregate industrywide insider trading instead of the firm-specific insider trading in each firm.
Price-earnings ratio
1. Our sample contains substantial variation in absolute P/E ratios. The median P/E ratio for the sample of firms we analyze is about 12. For the sample period 1978 to 1993, P/E ratios increase from about 8 to about 17.
2. Variations in absolute P/E ratios over time do predict future raw stock returns for our sample period of 1978 to 1993. When the absolute P/E ratios are high, expected future returns to stocks are low. When the absolute P/E ratios are low, expected future returns to stocks are high. This evidence suggests that P/E ratio is an important predictor of stock returns. In addition it is meaningful to compare P/E ratios over time. Hence a particular stock might have a P/E ratio of 10 in 1980 and 15 in 1990. This means that expected returns to the stock in 1980 are higher or lower than they would be in 1990.
3. While absolute P/E ratios predict future raw stock returns, they do not predict future net stock return. Hence, when most stocks have low absolute P/E ratios, they all tend to do well. When most stocks have high P/E ratios, they all tend to do badly. This finding suggests that the predictive power of the absolute P/E ratios arises because they predict the future market returns.
4. Insider trading is negatively related to absolute P/E levels; however, it does not attenuate the predictive power of the absolute P/E ratios. This finding suggests that movements in absolute P/E ratios mostly capture movements in risk. However, the mispricing hypotheses cannot be totally ruled out given that insiders buy low P/E stocks and they sell high P/E stocks.
5. We also use relative P/E ratios to predict relative future stock returns. For relative stock returns we compute stock returns net of the return to the equally weighted market index. Relative P/Es are computed by subtracting the market P/E from each stock's P/E ratio. The relatively high P/E ratios predict negative net stock returns, while the relatively low P/E ratios predict positive net stock returns. Specifically the relatively high P/E stocks underperform the market index by 2.2% over the next 12 months, while the relatively low P/E stocks outperform the market index by 2.3% over the next 12 months.
6. Insider trading is again related to relative P/E ratios. Insiders are more likely to buy relatively low P/E stocks. Insiders are more likely to sell relatively high P/E stocks. This finding again suggests that relative P/E ratios capture some mispricing also captured by the insider-trading variable.
7. Holding relative P/E ratios constant, insider trading still predicts the future stock returns. Hence the predictive power of insider trading is not attenuated by controlling for differences in relative P/E ratios. We can say that while insiders take relative P/E ratios into account, they base their trading decisions on additional considerations as well.
8. The relative P/E factor also retains its predictive power when we control for insider-trading activity. Whether insiders are buying or selling, relatively high P/E ratios predict lower future net stock returns. However, the net stock returns are not monotonically decreasing in P/E ratios.
9. The predictive power of the relative P/E factor weakens significantly even when we use more selective insider-trading signals such as large volume of trading or large transactions by top executives. For large insider selling by top executives, there is no longer a negative relation between relative P/E ratios and future returns. This evidence suggests that at least some of the predictive power of the relative P/E effect is due to mispricing of stocks that is also captured by insider trading.
10. There is good news for the market timers. Potential market timers can use both the absolute P/E ratios and insider trading to decide when to get in and out of the stock market. For potential stock pickers, our evidence suggests that given insider-trading information, relative P/E ratios do not add much. Hence potential stock pickers can ignore the relative P/E signals if they follow the trading activities of insiders.
Book-to-market ratio
1. Our sample displays significant variation in B/M ratios. The average B/M ratio for the sample of firms we analyze is about 0.8. For the sample period 1978 to 1993, B/M ratios range from 0.3 to 1.5. Given this variation, the differences in B/M ratios should be informative.
2. Absolute B/M ratios predict the future raw returns to stocks. As book-to-market ratio increases from the lowest to the highest groups, the raw returns approximately double for 3-month, 6-month, and 12-month horizons. Hence the value-based investment approach works.
3. Absolute B/M ratios also predict market returns, while they do not predict the relative performance of stocks. This finding suggests that differences in absolute B/M ratios are meaningful. Also some of the predictive power of the B/M ratios appears to come from predicting the time variation in market returns. These findings suggest that absolute B/M ratios would be most useful in a market-timing strategy.
4. The presence of insider trading does not attenuate the predictive power of the absolute B/M ratios. This finding suggests that the predictive power of the absolute B/M ratios cannot be attributed completely to mispricing of stocks. Hence, by using both variables, outsiders can do better in predicting future stock returns.
5. Relative B/M ratios are used to predict relative future stock performance. Relative B/M ratios do predict the relative future stock returns. There is a strong positive relation between past relative B/M ratios and future net stock returns. The lowest group of the relative B/M ratio stocks underperforms the market index by 1.7% over the next 12 months. The middle relative B/M stocks underperform the market index by 1.1%. The relative highest group of B/M stocks outperforms the market index by 1.8%. These findings suggest that relative B/M ratios must be useful in a stock-picking strategy.
6. Insiders appear to view the variations in both absolute B/M ratios and relative B/M ratios as if they represent some potential profit opportunities. Insiders are more likely to sell both absolutely and relatively low B/M stocks. Similarly insiders are more likely to buy both absolutely and relatively high B/M stocks.
7. Holding relative B/M ratios constant, insider trading still predicts future stock returns. Hence the predictive power of insider trading is not attenuated by controlling for differences in relative B/M ratios.
8. The relative B/M variable retains its predictive power when we control for everyday insider-trading activity. Whether insiders are buying or selling, high B/M ratios predict higher future net stock returns. Again, by using both variables, outsiders can do better in predicting future stock returns.
9. The predictive power of the relative B/M variable only begins to weaken when we use more selective insider-trading signals. Conditioning on large insider selling, the relative B/M ratio is in fact negatively related to future stock returns. Similarly we also examine the predictive ability of B/M ratios when we control for large trading by top executives. Once again, conditioning on large selling by top executives, we see that the relative B/M ratio is negatively related to future net stock returns.
10. Overall, our evidence suggests that the B/M approach works quite well in practice in predicting future stock returns. Unfortunately, the evidence is less clear on why it works. There is some evidence to support both the risk and mispricing explanations.
For more Information:
* Investment Intelligence & Strategy, Portfolio Management, The Stock Investor, Trading Tactics, Money Management *
We have uncovered the following characteristics of insiders' transactions:
1. There is a lot of insider trading. During the past 21 years between 65% and 80% of all publicly listed firms report at least one open market transaction by an insider every year. Consequently tracking insider trading is likely to provide useful signals in most firms.
2. There are four- to five-year cycles in overall insider buying and selling activity. In the last 21 years, there were two aggregate buying cycles and two aggregate selling cycles. This finding suggests that insiders are likely to respond to macroeconomic conditions when they trade securities of their firms. The aggregate levels of insider trading should also be kept in mind when evaluating insider-trading patterns in a given firm.
3. The unconditional probability of trading against insiders is small. In small firms insiders account for 2% of the trading volume. With increasing firm size, the proportion of the trading volume initiated by the insiders falls further. In large firms insiders account for about 0.5% of the trading volume. However, insider trading is concentrated into certain months. When insiders do trade, they account for 12% of the trading volume in small firms. Similarly, when they do trade, they account for 1% of the trading volume in large firms.
4. Despite the significant increases in insider-trading sanctions during the 1980s, there was no decline in the levels of insider trading. If anything, a greater proportion of firms report insider trading in the 1990s than in the 1980s or 1970s. Overall, evidence suggests that most insiders do not worry too much about regulatory restrictions when they buy and sell shares in their own firms. In addition there appears to be a trend toward increasing amounts of insider selling over time. For the period 1980 to 1995, insiders have sold 4.3 billion more shares than they bought.
5. In large firms insiders tend to sell twice as frequently as they buy. In smaller firms insiders tend to execute four purchases for each three sale transactions. These normal levels of insider-trading activity must be kept in mind when evaluating potentially unusual insider trading in a particular firm.
6. Purchases tend to come in small denominations. Sales tend to be more likely when the trading volume increases. This finding suggests that insiders may be breaking up their purchases into smaller lots in fear of regulatory sanctions. Insiders do not seem to worry as much about the regulatory implications of their sales.
7. Insider buying is more likely to occur at the turn of the year. Insider buying is lowest during the summer months. This finding is consistent with the so-called January effect when stock prices of especially small firms rise significantly in January. This evidence suggests that at least some insiders view the expected rise in stock prices in January as a profit opportunity.
8. Insider-trading activity is positively correlated over time. Past insider buying in a given firm increases the likelihood that insiders in the same firm will continue to buy stock in the future. Past insider selling increases the likelihood that insiders will continue to sell stock in the future. The positive correlation in insider trading suggests that insiders respond to common information signals that change slowly over time.
9. Insiders do not appear to be manipulating stock prices. Manipulation implies reversals in the direction of insider trading. Evidence shows that the probability of reversals is higher at 12 months than at one month. Also, contrary to expectations, the probability of reversals is smaller for top executives.
10. Regulation of insider trading has increased along with the increased involvement of stock investors in the stock market. Insider-trading sanctions now treat illegal insider trading the same as violent crimes. Increased insider-trading regulations have reduced specific instances of insider trading that are most likely to be prosecuted. Neither the volume nor the profitability of everyday insider trading is affected by increased insider-trading sanctions.
11. Insider-trading regulations tend to benefit small, liquidity-concerned investors at the expense of large, governance-motivated investors. Increased restrictions on insider trading is likely to lower the incentives of large shareholders to participate in corporate governance.
A stock-picking strategy
1. Of the four different classes of insiders, top executives are most informed, followed by officers and directors. Large shareholders appear to be the least informed. These findings suggest that insiders' private information comes from the day-to-day contact with all operations of the firm, rather than changes in corporate strategies, potential acquisitions or dispositions, or changes in market volume.
2. On average, all insiders trade a greater number of shares when they have more valuable information. However, at extremely high levels of trades, profitability falls. In fact profitability of trades exceeding 100,000 shares is less than the profitability of trades between 10,000 shares and 100,000 shares. At extremely high trade levels, greater regulatory scrutiny becomes an important concern. The concern about highly visible 100,000 plus-share trades are especially important in large firms. It is likely that all insiders and especially top executives in large firms feel that they are subject to greater public scrutiny.
3. When examining only large trades by insiders, it is extremely important to focus only on transactions by officers, directors, and top executives. Large trades by large shareholders do not contain any information.
4. Insiders' purchases are more profitable than insiders' sales. This conclusion holds regardless of the type of insiders or firm size.
5. Insider trading is a lot more profitable in small firms than it is in large firms. Insiders earn an average of 6.2% in small firms as compared with 1.7% in large firms. For outside stock market investors who are interested in imitating insiders in large firms, selectivity is required. Outside investors are cautioned to restrict their attention only to top executives who trade more than 1,000 trades.
6. In small firms all classes of insiders appear to trade profitably. Hence distinguishing between different classes of insiders does not improve performance much. However, purchases in small firms appear to contain more information than sales. In particular, small sales volumes do not seem to have any predictive ability. Both large purchases and large sales are informative. A large purchase by a top executive in small firms outperforms the market index by 14.7% over 12 months. A large sale by a top executive is associated with 7.8% average profit.
7. Consensus among insiders also plays an important role in determining the quality of insider-trading signals. As more insiders trade in a given direction, the value of insider-trading information increases.
8. Insiders do appear to time the exercises of their stock options. Stock prices rise following insiders' exercises of put options while stock prices decline following the exercises of call options (after 1991). Hence insiders' option exercises also contain important information regarding the future direction of stock price changes. Moreover exercises of put options seem to provide stronger signals. However, other types of transactions by insiders do not appear to provide strong signals regarding the direction of future stock price changes.
9. Interaction effects between sales-purchases, identity of insiders, volume of trade, and firm size are mostly unimportant. Each of these variables exerts an independent and additive influence on the profitability of insider trading. This is good news for the stock pickers, since it simplifies the stock selection criteria.
Predicting future market returns
Our findings indicate that aggregate insider trading is a reliable predictor of the future market returns.
1. Aggregate insider trading predicts aggregate stock returns. The overall stock market increases more if the past aggregate insider trading is positive than it does if the past aggregate insider-trading signal is negative. However, stock prices do not decline following insider sell signals. They simply rise less than those following positive aggregate insider-trading signals.
2. The strength of the aggregate insider-trading signals increases with the aggregation period. Hence aggregating insider-trading signals over the past 12-month period gives more reliable signals than aggregating insider-trading signals over the past month or the past 3 months.
3. Using 12-month aggregate insider trading and a 50%-50% rule to identify buy and sell signals, stock prices increase by 28.7% following the past 12-month aggregate insider buy signals. Moreover the market rises following each of the seven years when aggregate insider trading signal is positive. In contrast, the market rises only by 12.9% following the 12 years when the past 12-month aggregate insider-trading signal is negative. Hence using aggregate insider trading predicts an additional 16-point extra return to the market portfolio.
4. Using more extreme insider-trading signals further improves the predictive content of insider trading. Using 55%-45% rule to identify buy and sell signals, the difference in market returns following positive and negative aggregate insider-trading signals grows to almost 26 points.
5. Combining firm-specific insider-trading signals with the aggregate signals leads to better forecasting of future stock returns.
6. Aggregate insider trading predicts changes in future economic growth up to two years ahead. Other studies have also shown that stock returns are also a leading indicator of future real activity up to one year ahead. Consequently it should not be surprising that aggregate insider trading forecasts furture stock returns up to one year ahead.
7. It is also possible to time industry returns using industrywide insider trading. Our results indicate that U.S. auto stocks are better predicted by using the aggregate industrywide insider trading instead of the firm-specific insider trading in each firm.
Price-earnings ratio
1. Our sample contains substantial variation in absolute P/E ratios. The median P/E ratio for the sample of firms we analyze is about 12. For the sample period 1978 to 1993, P/E ratios increase from about 8 to about 17.
2. Variations in absolute P/E ratios over time do predict future raw stock returns for our sample period of 1978 to 1993. When the absolute P/E ratios are high, expected future returns to stocks are low. When the absolute P/E ratios are low, expected future returns to stocks are high. This evidence suggests that P/E ratio is an important predictor of stock returns. In addition it is meaningful to compare P/E ratios over time. Hence a particular stock might have a P/E ratio of 10 in 1980 and 15 in 1990. This means that expected returns to the stock in 1980 are higher or lower than they would be in 1990.
3. While absolute P/E ratios predict future raw stock returns, they do not predict future net stock return. Hence, when most stocks have low absolute P/E ratios, they all tend to do well. When most stocks have high P/E ratios, they all tend to do badly. This finding suggests that the predictive power of the absolute P/E ratios arises because they predict the future market returns.
4. Insider trading is negatively related to absolute P/E levels; however, it does not attenuate the predictive power of the absolute P/E ratios. This finding suggests that movements in absolute P/E ratios mostly capture movements in risk. However, the mispricing hypotheses cannot be totally ruled out given that insiders buy low P/E stocks and they sell high P/E stocks.
5. We also use relative P/E ratios to predict relative future stock returns. For relative stock returns we compute stock returns net of the return to the equally weighted market index. Relative P/Es are computed by subtracting the market P/E from each stock's P/E ratio. The relatively high P/E ratios predict negative net stock returns, while the relatively low P/E ratios predict positive net stock returns. Specifically the relatively high P/E stocks underperform the market index by 2.2% over the next 12 months, while the relatively low P/E stocks outperform the market index by 2.3% over the next 12 months.
6. Insider trading is again related to relative P/E ratios. Insiders are more likely to buy relatively low P/E stocks. Insiders are more likely to sell relatively high P/E stocks. This finding again suggests that relative P/E ratios capture some mispricing also captured by the insider-trading variable.
7. Holding relative P/E ratios constant, insider trading still predicts the future stock returns. Hence the predictive power of insider trading is not attenuated by controlling for differences in relative P/E ratios. We can say that while insiders take relative P/E ratios into account, they base their trading decisions on additional considerations as well.
8. The relative P/E factor also retains its predictive power when we control for insider-trading activity. Whether insiders are buying or selling, relatively high P/E ratios predict lower future net stock returns. However, the net stock returns are not monotonically decreasing in P/E ratios.
9. The predictive power of the relative P/E factor weakens significantly even when we use more selective insider-trading signals such as large volume of trading or large transactions by top executives. For large insider selling by top executives, there is no longer a negative relation between relative P/E ratios and future returns. This evidence suggests that at least some of the predictive power of the relative P/E effect is due to mispricing of stocks that is also captured by insider trading.
10. There is good news for the market timers. Potential market timers can use both the absolute P/E ratios and insider trading to decide when to get in and out of the stock market. For potential stock pickers, our evidence suggests that given insider-trading information, relative P/E ratios do not add much. Hence potential stock pickers can ignore the relative P/E signals if they follow the trading activities of insiders.
Book-to-market ratio
1. Our sample displays significant variation in B/M ratios. The average B/M ratio for the sample of firms we analyze is about 0.8. For the sample period 1978 to 1993, B/M ratios range from 0.3 to 1.5. Given this variation, the differences in B/M ratios should be informative.
2. Absolute B/M ratios predict the future raw returns to stocks. As book-to-market ratio increases from the lowest to the highest groups, the raw returns approximately double for 3-month, 6-month, and 12-month horizons. Hence the value-based investment approach works.
3. Absolute B/M ratios also predict market returns, while they do not predict the relative performance of stocks. This finding suggests that differences in absolute B/M ratios are meaningful. Also some of the predictive power of the B/M ratios appears to come from predicting the time variation in market returns. These findings suggest that absolute B/M ratios would be most useful in a market-timing strategy.
4. The presence of insider trading does not attenuate the predictive power of the absolute B/M ratios. This finding suggests that the predictive power of the absolute B/M ratios cannot be attributed completely to mispricing of stocks. Hence, by using both variables, outsiders can do better in predicting future stock returns.
5. Relative B/M ratios are used to predict relative future stock performance. Relative B/M ratios do predict the relative future stock returns. There is a strong positive relation between past relative B/M ratios and future net stock returns. The lowest group of the relative B/M ratio stocks underperforms the market index by 1.7% over the next 12 months. The middle relative B/M stocks underperform the market index by 1.1%. The relative highest group of B/M stocks outperforms the market index by 1.8%. These findings suggest that relative B/M ratios must be useful in a stock-picking strategy.
6. Insiders appear to view the variations in both absolute B/M ratios and relative B/M ratios as if they represent some potential profit opportunities. Insiders are more likely to sell both absolutely and relatively low B/M stocks. Similarly insiders are more likely to buy both absolutely and relatively high B/M stocks.
7. Holding relative B/M ratios constant, insider trading still predicts future stock returns. Hence the predictive power of insider trading is not attenuated by controlling for differences in relative B/M ratios.
8. The relative B/M variable retains its predictive power when we control for everyday insider-trading activity. Whether insiders are buying or selling, high B/M ratios predict higher future net stock returns. Again, by using both variables, outsiders can do better in predicting future stock returns.
9. The predictive power of the relative B/M variable only begins to weaken when we use more selective insider-trading signals. Conditioning on large insider selling, the relative B/M ratio is in fact negatively related to future stock returns. Similarly we also examine the predictive ability of B/M ratios when we control for large trading by top executives. Once again, conditioning on large selling by top executives, we see that the relative B/M ratio is negatively related to future net stock returns.
10. Overall, our evidence suggests that the B/M approach works quite well in practice in predicting future stock returns. Unfortunately, the evidence is less clear on why it works. There is some evidence to support both the risk and mispricing explanations.
For more Information:
* Investment Intelligence & Strategy, Portfolio Management, The Stock Investor, Trading Tactics, Money Management *
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