😶‍🌫️Best buying timing for the marketBest buying timing for the market

● Best buying timing for the market

Changes in stock prices caused by earnings announcements in the United States are relatively honest. Information on performance is leaked in advance and is not reflected in the stock price in advance. In the case of the domestic market, even though information on performance flows in advance, and the performance meets or exceeds the analyst’s consensus, the stock price tends to decline due to cell-on if it does not meet the so-called street consensus. The US market tends to reflect stock prices as good or bad when performance is good. In this case, investors may think that the trading timing will be relatively boring. However, there is a way to set the optimal buying timing by analyzing the performance announcement while investing in US stocks.

In order to use earnings announcements in the U.S. market to set the best timing for buying, it is necessary to go a step further from the habit of looking at numbers and interpret “time difference response” and “industry context” together.

U.S. stocks respond first to headline numbers when earnings announcements come out, followed by conference calls and Q&As, and then analyst comments permeate the market in turn the next day. Between them, there is a gap of as few hours as possible or as many days as possible. Reading this gap is the key to buying timing.

In particular, in the case of the tech sector, the benefit of future structural changes is more important to the stock price than short-term performance figures such as this quarter and the next quarter. Short-term trading investors give out their supplies by reflecting them in short-term figures, and investors who see structural future changes can secure them. For this reason, the ability to interpret in industry and technology trends in conference calls and Q&A content is very important and determines the rate of return.

The order of performance trading I write is as follows.
First, immediately after disclosure, only the direction of sales, profits, margins, and cash flows is quickly judged. For equipment and parts companies, order, backlog, and book-to-bill are particularly important.
Second, check the changes in guidance and narrative in conference calls. The numbers are the present and the narrative is the future.
Third, it connects with the S-curve of the sector and technology to which the company belongs. If the industry is structurally transformed, there may be a reversal even if there is a headline miss. That’s why it’s important to study industry and technology. You can increase the probability of an investment.
Finally, look at the price. There are stages from panic immediately after the start of the market, re-evaluation after the call, and the next day’s wave, so the timing of the sale is determined by dividing.

Yesterday’s AEHR was an example of my straightforward application of this principle. Disappointed by the headlines after yesterday’s quarterly earnings report, the stock plunged to -27%, and I bought at -25% below $24.

Sales fell year-on-year to $11 million in the quarter ending in August, and profits also turned to the red. Reservations barely surpassed sales at $11.4 million, but visibility weakened as the backlog decreased from the previous quarter. A sharp decline is natural if you look at the numbers.

However, upon confirming the conference call, I caught the structural growth point. AEHR is originally a silicon carbide (SiC)-centric wafer-level burn-in (WLBI) equipment company. It has been directly hit by the EV cycle slowdown in the last two years, and the fallout remains in the numbers for the current quarter. However, in this call, the company clearly showed that its business composition is rapidly diversifying.

First, burn-in for AI processors began in earnest. Through the Sonoma platform secured by Incal acquisition, additional orders from large customers came in from PPBI, and production systems began to be installed in Hyperscaler and OSAT. Particularly noteworthy is the emergence of a new application called WLBI for HDD parts, accounting for more than 15% of quarterly reservations. Switching large-capacity HDDs and HAMRs increases the pressure to filter out initial life defects of ASIC and sensors for optical and head driving in the wafer stage, and the demand comes into AEHR’s FOX-XP and WaferPak. In summary, it has been specifically confirmed that there are several axes of growth from SiC single axis to AI, HDD, silicon photonics, and GaN.

This analysis is very important. If the headline shows the “quantity” of performance, the confidence call shows the “quality” of the business. In the tech industry, there is a section through which a rise in quality compensates for a drop in quantity. Understanding the industrial cycle can capture opportunities in this transition period. Data center investment is not just about GPUs these days. Spread of AI reasoning grows storage and network, optical cable, and reliability test together. So, the expansion of the AI package burn-in (SONOMA) and the adoption of HDD parts WLBI, as AEHR refers to, are signs of structural change enough to cover short-term numbers.

The 200-day moving average is crucial when comparing AEHR’s optimal purchase timing through technical analysis in connection with the previous article. The candle broke through the 200-day mark and fully settled at the end of June, and the stock price tripled in a little more than three months. Judging from the 150-day and 200-day golden crosses, the time of entry into the upward trend was mid-September, and yesterday’s price was lower than that point.

In the case of AEHR, it is reasonable to view this decline as short-term volatility unless it enters a structural downward trend. It will be more advantageous to get the best timing to buy if you learn the sense of market reaction from performance announcements on top of thorough industry and technology analysis.