First things first: what about emphasis on Apple vs. General Electric?
We’ll get to some of the broader strategic questions above later in separate articles. For now the focus is on portfolio wealth-building choices between Apple, Inc. (AAPL) and the General Electric Company (GE).
Our perspective, as usual, draws on the actions of the Market-Making community [MMs] as they seek to provide transaction liquidity for major institutional-investor funds typically managing Billion-dollar equity portfolios. Particularly in times like these their desires to make volume adjustments to their holdings takes on an additional sense of urgency.
In ordinary times their size precludes participating in ordinary “regular-way” auction markets. They live in a “deal” world where “other side” of their desired trade gets lined up by the MMs in private negotiations with other like-sized players so the entire “block” trade gets executed at one price, at one time, for all participants.
Usually a “cross” of instantly-balanced sellers and buyers is not available. So, the MM faced with the big-bucks trade order may stop being just a sales agent, and become a principal by “filling” the imbalance and thus putting their own MM firm capital at risk of unwanted market price moves. That will only happen (and most often does) when a separate hedging deal in separate derivatives markets transfers that risk to other willing speculators. Those often are proprietary-trade desks of other MM firms.
The cost of that equity-market liquidity is borne by the trade-initiating institution, a part of the spread between what was initially sought as a transaction price, and what can actually be done of the moment. Their acceptance acknowledges the reality of what has been negotiated (but not yet closed) between the MM buyer and the prop-trade seller of the price insurance.
Once the block trade is consummated, its price is posted on the public “regular way” markets to maintain transaction transparency. For stocks and ETFs thus involved, it is the “deal” markets run by the investors with the money muscle that lead the price parade, and the public investors simply follow along.
The hedge price-change insurance deal’s terms define the extremes of prices likely to occur during the lives of the derivatives contracts involved. In turn, prior experience with earlier, similarly proportioned forecasts provide a present perspective on what may be coming for prices in next near-term (3-6 months) markets.
Trends of Expectations
Here in Figure 1 is what those forecasts for AAPL have been showing, daily, during the past 6 months. All materials presented here have been approved by blockdesk.com.
Note: This is not a conventional price history “chart”. It is a record of MM live-date forecasts of the stock’s near-term (3-4 coming months) range of likely prices. Forecasts made each market day on the dates indicated, not after the fact. The vertical price-range forecast lines of Figure 1 are split into upside and downside prospects by the heavy-dot end-of-day market quote for the issue on the day of the forecast.
A measure of the imbalance between up and down possible price change implications is the Range Index [RI], which tells what percentage proportion of the entire forecast range lies below the current price. The thumbnail picture at the bottom of Figure 1 presents the distribution of RIs for the stock seen in the past 5 years.
AAPL’s current RI of 22 is part of its central set of experiences, suggesting that for the stock to look more attractive in comparison to its own history it might need to see RI values in the mid- to low- 10’s. They could occur either from continued expectations of rising price ranges while the price stood still, or from price pullbacks not followed by expectations of coming price ranges.
What has actually happened to AAPL’s price following 144 of its past 5 year’s MM forecasts which were like today’s is shown in the row of data between the two pictures of Figure 1.
The first 3 items in that row make price-explicit the proportions of the current, last-right vertical of the upper picture. The upside Sell Target Potential is the % difference between the High forecast and the Current Price.
Following the portfolio management discipline of TERMD (explained here) the 144 prior 22 RIs of AAPL had net position closeout payoffs of +1.7% in average holding periods of 57 market days (2 days more than 11 weeks), producing a compound annual gain rate [CAGR] of +8%.
During the holding periods seeking the upside sell targets of the prior forecasts the worst price drawdown experience in each case averaged -8.2%. Some 32% of the 144 forecasts at the end of the 3-month time limit on holding under TERMD were still below their entry costs. The other 68% (poor price performance) recovered and were profitable, slightly more than offsetting the losses of the 32%. The resulting +1.7% gives a credibility ratio of 0.12 to the current upside sell target forecast of +13.6%.
Let’s see how well all that compares to what the MMs think their clients are likely to do with GE’s price in the same coming time forecast. Figure 2 will tell of that.
GE’s past 6 months of daily MM forecasts show a distinct downward trend through the whole six months, compared to AAPL’s disappointments of only the last few months. At an upside prospect of +15.1% it offers larger gain potentials than AAPL’s +13.6%, with a smaller interim price drawdown exposure of -5.1%. The Win Odds of 68 out of each 100 is the same as AAPL’s, but at a payoff of 2.3% it is better than AAPL’s pitiful 1.7%.
The current Range Index for GE of 44 is higher (less upside potential) than the 22 of AAPL, but a check of their past 5-year histories in the thumbnail pictures at the bottom of Figures 1 & 2 shows that in terms of prior RI experiences, the present positions are some different. AAPL has a bit broader array of RI experiences, suggesting that there are wider evaluation opportunities here (in each direction) than in the case of GE. The MMs have a tighter focus on GE’s prospects than they have on AAPL.
Where there is a marked difference in the performance between GE and AAPL is in their Realized Payoffs in contrast to the MMs implied % Upside Sell targets. We measure the realized divided by the forecast, and call it our Credibility Ratio. Both GE’s 2.3%/15.1% = 0.15 and APPL’s 1.7%/13.6 = 0.13, make horrible examples compared to the Semiconductor ETF SOXL [20.9% forecast, +20.0 payoffs achieved] or even the “market proxy’ of SPDR S&P500 ETF (SPY) which at today’s mid-range RI MM forecast of 46 has a record of several hundred examples targeting upsides of +6.4% and achieving payoffs of +2.8% for a ratio of 0.44, better than double either of the article's stocks.
Perhaps the most constructive take-away for investors is that in the past few years MMs have not been pressed to make good estimates of near-term price prospects for either of these companies. That, plus the recognition that there must be lots more low-credibility (probably over-optimistic) equities forecasts to pull down the average outcomes from a 500-stock index to the point where its realizations are less than half its expectations. So its not just GE and AAPL having a hard time "getting respect".
This makes a big difference when we look to see how “speedy” each alternative may be when it comes to building the portfolio’s wealth through time. Figure 3 puts the comparisons in an easier-to-work-with table, and includes average data for all 2,000+ forecasts this day, for the best 20 of those, and for the buyable version of the market index, the SPDR S&P 500 ETF (SPY).
The data in Figure 3 for GE and AAPL in columns A through N is directly from Figures 1 and 2, positioned for easier comparability.
One dimension where GE has a trivial advantage over APPL is in terms of its “speed” of prior accomplished % payoffs at current RI levels. AAPL positions took over eleven weeks to “hatch”, while GE’s brood did it in less than 9, or 44 market days. GE’s +2.3% typical position profits are at a compound annual gain rate [CAGR] of 14%, well above AAPL’s 8%. Their CAGRs both are well below the 19% average for the overall forecast population and the 13% of the SPY market index ETF.
We take a conservative approach in appraising the potential rewards and risks of candidates for portfolio investments. We look to see what proportion of the sample of prior forecasts at RIs like today's turned out to be profitable – the Win Odds. That percentage we apply to the Realized Payoffs. We then apply the complement of the win odds (in this case for either AAPL or GE, 100%-68% = 32%) to the worst price drawdown experiences, as shown in columns O and P of Figure 3.
We then sum columns O and P in column Q to get a net Reward minus Risk tradeoff figure.
To make the comparisons between rows complete, the ability to compound the results of column Q needs to reflect the “speed” of each row’s accomplishment by including the data of column J – the average days held to accomplish the net of Q.
That is what is shown in column R, expressed in the terms frequently used in financial circles: basis points per day. A basis point is 1/100th of a percent. For reference, 19 basis points sustained for 365 days produces a double of the capital or subject of attention.
With the heroic assumption that the future will be matched by the data of the past, there now is a common basis of comparison for many complex processes. Like investing performances.
Used this way, both GE and AAPL offer an important message today. Both have Win Odds is only slightly better than 50 – 50. That leaves the loss odds of about one third of the experiences teaming up with loss exposures (-5%, and -8%) significantly larger than the reward components (both of ~2%). Then when the odds-weighted column O is combined with the weighted risk component in P, it makes the net in Q negative for both of them. Completing the evaluation, column R divides column Q results by the data in column J to get negative basis points (losses) per day.
The message for today is fugeddabout’em for now. Go find something positive, and come back to check these out in a week, or a month, or two.
But on a broader field, other comparisons are offered by Figure 3.
A plain-vanilla S&P500 index investment via SPDR S&P500 Index ETF (SPY) offers up an unimpressive less than 4 bp/day. But still positive bps per day. The best pics from the population are a world apart from these particulars and averages. Careful selection of the 20 likely most productive choices from the 2633 (the less-than 1% at the population’s top) boast an average CAGR of over 100%, the equivalent of +27.5 bp/day. The accumulated performance of the daily selections of top 20 issues since 12/31/2015 are shown in this article and on my SA blog, following TERMD portfolio management discipline, in comparison with buy&hold of SPY.
These pictured forecast histories were regularly produced by competent, involved market professionals, supported by internally employed evaluators, and following the lead of big-money institutional portfolio-manager trade orders.
Please remember this is a near-term evaluation, suggesting CAGR price gain opportunities far above multi-year trendline price growth street estimates for the group. What may appear as more attractive in a few months, providing future price-compounding capital growth opportunities may be very different from the then less attractively-priced current investment competitors. An updating follow-up visit to the group is advisable.
Additional disclosure: Peter Way and generations of the Way Family are long-term providers of perspective information, earlier helping professional investors and now individual investors, discriminate between wealth-building opportunities in individual stocks and ETFs. We do not manage money for others outside of the family but do provide pro bono consulting for a limited number of not-for-profit organizations.
We firmly believe investors need to maintain skin in their game by actively initiating commitment choices of capital and time investments in their personal portfolios. So our information presents for D-I-Y investor guidance what the arguably best-informed professional investors are thinking. Their insights, revealed through their own self-protective hedging actions, tell what they believe is most likely to happen to the prices of specific issues in coming weeks and months. Evidences of how such prior forecasts have worked out are routinely provided.
Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.