Investors nowadays have access to a large number of software programs and free online services that allow them to select stocks based on a customized set of conditions and variables.
Some services apply fundamental analysis to rate thousands of listed companies, perhaps on a 10-point scale, using advanced mathematical systems to determine a stock’s expected risk and return, or to simply rate it a “buy,” “hold,” or “sell.” Other methods of evaluating securities may involve technical analysis, as described in Chapter 7, Applied Systems, and Chapter 8, Formulating Your Trading Plan. There are endless ways one can approach the process, but a combination of both fundamental and technical analysis seems to be the preferred method for most investors and fund managers. Given the plethora of choices, the overriding question is still, how does one improve one’s chances of picking the stock with the best potential to go up in value? Not everyone has the stock-picking talent of Peter Lynch or Warren Buffett, or access to sophisticated quantitative stock-rating programs, so an ordinary investor or trader may often be at a disadvantage. Moreover, stock picking has almost become a lost art since the onset of the financial crisis. Sentiment has alternated between euphoria and despair, and time-proven methodologies have failed in the extraordinarily volatile environment since the financial meltdown in 2008.
This section is not meant to be a primer on how to select stocks or build portfolios using conventional value-analysis methods like the top-down or bottom-up approaches. Many other books are available on those topics. The aim is to provide some additional tools that may help in the stock-selection process through a combination of conventional and more esoteric approaches.
Before starting, it may be of interest to know how six different fundamental investment strategies have performed in Asia’s stock markets since the beginning of 1997. Research was undertaken in July 2009 by strategists Daniel McCormack and Viking Kwok at Macquarie Bank and reviewed by Tom Holland of the South China Morning Post (“Valuations Say Buy, But the Fearful Doubt Their Validity,” SCMP Monitor, December 3, 2008).
Some widely used techniques performed surprisingly poorly. Buying the shares of companies with the strongest balance sheets, for example, would have produced lousy returns.
Macquarie’s analysts ranked their universe by the Altman Z score—a common measure of financial health—and found that, over the past 10 years, the strongest 20 percent of companies significantly underperformed the rest of the market.
Buying stocks with strong earnings growth proved similarly disappointing. In this case, the Macquarie analysts ranked companies by expected earnings growth and found that the first quintile—the top 20 percent—performed just as poorly as the bottom quintile, with the second quintile doing almost as badly.
Momentum investing didn’t do well either. Although momentum investing is a popular strategy, buying stocks that have performed well recently doesn’t work. Macquarie ranked equities by their performance over the previous three months and found that the first quintile subsequently underperformed the market. The weakest quintile delivered the best returns.
In fact, by far the best strategies for buyers of Asian stocks over the last 12 years have been classic value-driven techniques. Buying stocks for their dividend yield works reasonably well, with the first quintile handsomely outperforming when markets are weak.
Simply buying the cheapest stocks in the market delivers the best returns, however.
According to Macquarie, the 20 percent of stocks with the lowest price to earnings ratios
outperformed the overall market 63 percent of the time.
It has been even better, however, to invest in the cheapest stocks ranked on a price to book value basis. In this case, buying the first quintile—Q1, or the cheapest 20 percent of stocks—has been what Macquarie calls “a massive and consistent outperformer,” whatever the state of the wider market. In view of this information, traders might do well to incorporate price to book value into their fundamental selection criteria.
The need to hone stock-picking skills is obviously critical to the performance of any investor or fund manager, and was brought home again recently when a leading fund reported the results of their trading for the past week on October 18, 2010. The report mentioned that the model portfolio returned 1.7 percent while the underlying index gained 6.7 percent. On examining the fund’s portfolio, it turned out that although many of the stocks had been in the right sectors and had appreciated nicely, all the gains were offset by some underperforming stocks or “laggards.” Using the stock-screening procedure described below, these “laggards”
might well have been excluded from the start, and the performance of the fund would have greatly improved. We shall take a closer look at two of them (151 Want Want and 828 Dynasty Fine Wines) later in the chapter.
So how to go about it? The first step is to establish a database of all those shares one has interest in and load them in a charting software program, such as TradeStation or MetaStock or any one of the many others that are available.
Yahoo! Finance, Google Finance, and quite a few others provide stock prices and fundamental data for free. One may also subscribe to a stock-screening service or use Internet sites such as Yahoo! Finance or Financial Times (at
www.ft.com
), where it is possible to compare the price performance with other stocks in the same sector. At
www.ft.com
, one may run a stock screen based on favorite parameters, including return on equity, P/E ratios, or preferred price range, and it will screen all the stocks listed in major markets around the world. It is even possible to use a screener that combines both fundamental and technical analysis such as the one provided by Financial Visualizations (at
www.finviz.com
). In addition to the financial ratios the screener identifies stocks based on technical patterns or specific candlestick formations.
It is assumed the reader has access to a charting program with a stock-screening function.
The example shown in Figure 9.4
was done by the Explorer screen function in MetaStock, but RadarScreen in TradeStation can do the screens as well.
FIGURE 9.4
Shows the result of the scan of 1,291 stocks at the close of the Hong Kong Stock Exchange on November 16, 2010.
The database in Figure 9.4
comprises about 1,300 of the most actively traded stocks on the Hong Kong Stock Exchange.
Roughly speaking, about one-third of the stocks are mainland companies listed on our local bourse. A scan of these shares therefore provides an investor or trader with an opportunity to select a stock that is tied in with the dynamic economies of China and/or Hong Kong.
Screening the stocks is a fairly simple procedure, and we find the following three methods in MetaStock’s Explorer function most useful: Price and Volume Breakout, P and F Pattern Search, and Long-Term Bullish/Bearish. (MetaStock is owned by Equis International and some functions are under the prefix Equis.)
In
Figure 9.4
, MetaStock Explorer-Equis: Price and Volume Breakout displays securities where the price is increased 5 percent and the volume is 50 percent above the 50-day moving average. A total of 24 stocks meet these criteria. The purpose is to spot stocks that are breaking out of a medium-term trading range, or down from it, and then do an astro-screen of those stocks, as explained later on.
In order to spot stocks that break out of a range, the P and F Pattern Search in the Explorer can be useful as well—“P and F” meaning Point and Finger chart analysis. Usually, only a few stocks show up in this scan, but when they do, it can be an indication the stock is moving higher or reversing. Five stocks were on the list on November 16: 5 HSBC Holdings, 19 Swire Pacific A, 2828 Hang Seng H Share Index ETF, 330 Esprit Holdings, and 589 Ports Design, and all had broken down technically. The weak P and F charts indicated the overall market might be subject to more near-term selling pressure.
Stock investors may also consider using Equis: Long-Term Bullish, which identifies stocks over their day moving average, and Long-Term Bearish, which identifies stocks below their 200-day moving average. As mentioned in an earlier chapter, 40 weeks, that is, 200 trading 200-days, is a widely followed moving average indicator, but here we are only concerned with the total
number of shares above and the total number below as a sort of sentiment indicator. As of November 22, 2010, the number above, or bullish, was 780, while the number below, or bearish, was 511. The ratio has shifted substantially since the onset of the recent correction, but the reading may still be considered bullish and adds weight to the view that the decline is corrective only, and the larger uptrend is still intact.
Incidentally, when it comes to financial statistics, Asia is still far behind the United States and Europe in terms of the huge range of stock market statistics that is available in those places.
One would expect a stock exchange to provide reliable statistics and historical data for independent research; however, for some Asian bourses, often the daily advance decline numbers do not tally and therefore cannot serve as a reliable gauge of sentiment. Moreover, the respective volume of advancing and declining stocks, VIX index, and daily data with no opening price can only be obtained through data vendors.
The next step necessitates having access to an astrological software program such as AIR Market Trader, Timing Solution, or Galactic Trader. These programs offer multi-search functions based on the “first-trade” date and scan the companies according to certain astrological inputs.
These inputs include prevailing “good” planetary aspects, such as 60 degree sextiles, or 120 degree trines, and “bad” aspects such as 90 degree squares or 180 degree oppositions, and sometimes 0 degree conjunctions as well. A number of simple models are provided with Timing Solution, so the user doesn’t need to have extensive knowledge about astrology and may just apply the good or bad screens to stocks, similar to applying the lunar-phased indicator. The result of even a simple good or bad aspect scan can sometimes turn up “nuggets” in that the scan can alert investors to a share that has the potential to start rallying before it actually breaks out.
It should be noted that the “first trade” date charts used in multi-search are separate from a company’s date of incorporation charts. Incorporation charts are drawn up when a company starts its business, and may indicate something about the ongoing operations of the company, such as changes in management, product releases, or other internal matters. First-trade charts, on the other hand, are based on the date and time of the first trade on a stock exchange; that is, when the company launches its initial public offering (IPO), and trading of its shares to the public and institutions begins. The first-trade chart is very reliable, as the time is normally always the same as the opening of trading. It used to be 10 a.m. in Hong Kong, but on March 7, 2011, it changed to 9:30 a.m. to be in line with other exchanges. The first-trade chart relates to investor interest and concerns, and is the more important of the two charts. To find the dates for a first trade database is a time-consuming job, which may deter some investors. Hopefully, the following discussion will convince some it is worth the effort.
The first-trade database we are going to use for Hong Kong shares contains 850 stocks.
Unfortunately, for about 20 or so leading shares, including HSBC Holdings, there are no known listing dates, so those stocks could not be utilized. It should also be noted that the total database of 1,300 stocks mentioned earlier was formed by adding 450 other active stocks to the 850 first-trade stocks.
Figure 9.5
shows the first scan.
Figure 9.6
shows the performance of the stock that was rated at the top of the scan, and which outperformed the Hang Seng Index (
Figure 9.7 ).
FIGURE 9.5
The first scan shows how stocks rate in a simple good/bad aspect program with the 10 highest ranked first as of November 23, 2010. The top stock in the screen, 2728 Shinhint, already appeared on the Price and Volume Breakout in early October, and again in early November.
Source: Sergey Tarassov at www.timingsolution.com .
FIGURE 9.6
2728 Shinhint daily chart (middle panel) and weekly chart (upper panel) at the close on November 23, 2010. Considering that the Hang Seng Index dropped from a high of 25,000 in early November to around 23,000 in the middle of the month, the stock has held up well and appears to be consolidating before going higher.
FIGURE 9.7
Daily chart of Hang Seng Index as of December 1, 2010.
Source:
www.advancedget.com
(Note: original GET program is now sold by eSignal data service).
The third highest ranked stock in the scan, 833 Alltronics Holdings Ltd., has been moving up sharply since early October, and may also be poised to resume its uptrend.
In
Figure 9.8
, Alltronics appeared frequently in the Price and Volume Breakout scans, but only after it started its sharp uptrend. Since September, it showed up repeatedly in the “good/bad” astro-scans, and investors could therefore be on alert that it might start rallying any time.
FIGURE 9.8
Daily chart (lower panel) and weekly chart (upper panel) of 833 Alltronics Holdings Ltd. as of November 23, 2010.
However, the standout performer was a relatively obscure company called PacMOS Technologies Holdings Limited. On October 19, 2010, and in the days that followed, it showed up at or near the top of four different astro-scans, one of which is shown in
Figures 9.9 and 9.10
.
FIGURE 9.9
“Good/bad” astro-scan from October 19, 2010.
FIGURE 9.10
On October 29, 2010, PacMOS Tech. rocketed to the upside.
Being a penny stock with an erratic price history, PacMOS might not be a stock for everybody, but it illustrates how an astro-scan can play an important role in trading, with the caveat that sometimes the stocks that are “flagged” out in the “good/bad” scans do not make a move for several weeks. For example, number four on the list (
Figure 9.9
), 102 Arnhold Holdings Ltd., only started to rally at the beginning of November, as shown in Figure 9.11
.
FIGURE 9.11
Weekly chart (top) and daily chart (bottom) of 102 Arnhold Holdings Ltd. from November 23, 2010. The ribbon bar at the bottom shows the new moon (N), full moon (F), and quarter moon (Q) phases (Section 1—Using Lunar Cycles in Trading). Note the quarter moon phase often coincides with CITs.
In other cases, the selected stocks remain stagnant. However, those that do move often outperform the market by a wide margin. A case in point is 2728 Shinhint, shown in
Figure 9.6
, which rose almost 10 percent on November 24, the day after the screen date.
The following is an example of a double screening method. Based on the list of a Price and Volume Breakout scan in
Figure 9.4
, the next step is to rank these stocks with a good/bad astro-scan as shown in Figure 9.12
.
FIGURE 9.12
Good/bad screen of the list of 24 stocks in the Price and Volume Breakout scan from Figure 9.4
. Four of the stocks did not have first-trade date and four did not meet the scan criteria, so the list comprises 16 stocks only.
Many of the stocks on the list bucked the downtrend in the market and continued to rally in spite of the 10 percent decline in the Hang Seng Index during November 2010. Daily charts of three of the stocks are shown in
Figure 9.13 for illustration.
FIGURE 9.13
Daily charts of 395 Sino Dragon (top), 319 China Metal (middle), and 592 Bossini (bottom) as of December 4, 2010.
The five stocks at the bottom of the astro-scan in Figure 9.12
did less well than the 10 top-ranked ones, indicating that the astro-scan proved helpful in selecting the stocks with the best potential. It may of course be argued that just buying all the stocks selected by the technical breakout screen would also have outperformed the market.
Perhaps so, but for investors who do not have the means to diversify to such a wide extent, the second screening by astro-scan might be an ideal solution.
This brings us back to the portfolio with some underperforming stocks, among which were 151 Want Want and 828 Dynasty Fine Wines. In
Figure 9.14
, these stocks did in fact rally with the overall market in the first half of October, and appeared initially to be well chosen.
FIGURE 9.14
Daily charts of 151 Want Want (top) and 828 Dynasty Fine Wines (bottom).
While the stocks have reasonably good fundamentals and seemingly good prospects for growth, they declined quite sharply in October and were sold in a rebalancing of the portfolio.
Had the fund manager screened them beforehand using just the simple good/bad criteria, he would have seen the stocks ranked poorly in August and again in September, as shown in
Figures 9.15 and
9.16 .
FIGURE 9.15
Astro-scan of 151 Want Want on August 9, 2010.
FIGURE 9.16
Astro-scan of 151 Want Want on September 29, 2010.
828 Dynasty Fine Wines also ranked low in several scans, the latest being at the end of September 2010, as shown in
Figure 9.17 .
FIGURE 9.17
Astro-scan of 828 Dynasty Fine Wines on September 29, 2010.
To sum up, there is little doubt that the increasingly uncertain and volatile stock market environment calls for more unorthodox methods in trading and particularly in selecting stocks.
The question is, will investors be prepared to try something different and somewhat esoteric?
Hopefully, this section has provided an in-centive.