Financial Ratio Ranking: The Composite Method (Electronics Sector)

In previous article, the composite ranking method using financial ratios were discussed based on Plantation sector (Read more here).  This week, Electronics sector is selected for discussion.

It is very common for electronics companies listed on Bursa Malaysia to maintain high cash position and low debt level.  Thus, certain financial ratio such as D/E and interest coverage ratio may not be meaningful.  As such, few ratios are replaced to focus more on the operating efficiency and free cash flow generation.

Also, financial ratios are computed using financial statements.  Different companies may have different approaches to recognize their costs.  For instance, MPI cost of sales is very high but their Selling, General & Administration (SG&A) costs are low.  As such, MPI’s gross margin is relatively low compared to its peers but its operating profit margin is on-par with its peers.  Thus, Gross Margin is replaced with EBITDA Margin for this analysis.

Source: Dynaquest Sdn. Bhd. STOCKBASE platform.  See “Notes” at the end of this article for Copyrights details.

Disclaimer:  The above analysis does not imply any buy or sell recommendation.  The author disclaims all liabilities arising from any use of the information contained in this article.

Disclosure: The author may have interest in the stocks of the companies in this article.

Notes:  The data are the property of Dynaquest Sdn. Bhd.  It is subject to Intellectual Property Rights and T&C.  Do not reproduce without the consent from Dynaquest Sdn. Bhd.  (The author has signed a “Data Sharing Agreement” with Dynaquest Sdn. Bhd., based on a “Data Sharing Fee”, to use the data from Dynaquest Sdn. Bhd.’s STOCKBASE platform in this blog.  The content of this blog in no way represents the views or opinions of Dynaquest Sdn. Bhd.)

Using Financial Ratio to Screen Stocks: The Composite Approach

Stocks selection is always a challenging task.  They are many stock screening tools available on the web but most of them have rather simple screening function based on dividend yield, PE or market capitalisation.  Financial ratio screening is also available but the screening process is on stand-alone basis and may not provide ranking information.

In stock analysis, financial ratios are very useful tools to gauge a company’s financial health, operating efficiency and earnings quality.  There are many categories of financial ratios such as Activity Ratios, Liquidity Ratios, Solvency Ratios, Profitability Ratios, Valuation Ratios and others.  Often, ratios from different categories may give contradicting messages.  This article will discuss a simple method to rank companies using various financial ratios, the “composite” way.

First, we shall identify the ratios that we would like to include in the ranking process.  The following ratios are chosen for illustration purposes only.

Category	Ratio	Interpretation
Activity Ratios	Current Assets turnover	Higher Better
	Total assets turnover	Higher Better
Liquidity Ratios	Current Ratio	Higher Better
	Operating Cash Flow to Debt	Higher Better
Solvency Ratios	Debt to Equity Ratio	Lower Better
	Interest Coverage	Higher Better
Profitability Ratios	Gross Profit Margin	Higher Better
	Net Profit Margin	Higher Better
	Return On Equity	Higher Better
Valuation Ratios	Price to Earnings	Lower Better

Next, we choose ten companies from the same sector.  For this article, we have chosen the Plantation Sector in Malaysia.  The following table shows the respective financial ratios for ten plantation companies listed on Bursa Malaysia.

Source: Dynaquest Sdn. Bhd. STOCKBASE platform except 1,000,000.00.  See “Notes” at the end of this article for Copyrights details.

* 1,000,000.00 was inserted for company which has zero debt to avoid "divide by zero issue"

Once the financial ratios are ready, we could rate it according to a scale from 10 (Favourable) to 1 (Least Favourable).

From the above table we could see that some companies may have scored well in certain ratios but performed poorly on other ratios.  For quick comparison purposes, we could then calculate the average rating for each company as depicted in the following table.

This method is useful for investors who would like a first cut screening before carrying out more detailed financial analysis.  Investors shall not make investment decision solely based on a ratio analysis as there are other factors that may impact prospects for any investment in plantation stocks.

Disclaimer:  The above analysis does not imply any buy or sell recommendation.  The author disclaims all liabilities arising from any use of the information contained in this article.

Disclosure: The author may have interest in the stocks of the companies in this article.

Notes:  The data are the property of Dynaquest Sdn. Bhd.  It is subject to Intellectual Property Rights and T&C.  Do not reproduce without the consent from Dynaquest Sdn. Bhd.  (The author has signed a “Data Sharing Agreement” with Dynaquest Sdn. Bhd., based on a “Data Sharing Fee”, to use the data from Dynaquest Sdn. Bhd.’s STOCKBASE platform in this blog.  The content of this blog in no way represents the views or opinions of Dynaquest Sdn. Bhd.)

Why Property Prices Are High?

Digress a bit this week...

Google Trends Search Term Data & Bitcoin Price

In previous article, KLCI movement was forecasted using Google Trends’ Data (Read more here).  This week, the relationship between Bitcoin Price and its search frequency on Google will be discussed.

Google Trends (Read more here) is a website by Google that analyzes the popularity of top search queries in Google Search across various regions and languages. The website uses graphs to compare the search volume of different queries over time (source: Wikipedia).

The following chart shows the relative query frequency of the term “Bitcoin” in Google Search and the Bitcoin price from Jan 2016 to Sep 2018.  The blue line is the normalized “Bitcoin” search term frequency while the orange line is the normalized Bitcoin price.  There is a very strong correlation between these two parameters.  This could be due to Bitcoin traders or investors who are internet savvy at the same time.  Speculators may monitor the “Bitcoin” search term frequency to predict the next movement of the Bitcoin price.

Ringgit Malaysia (RM) Exchange Rate After GE14

In previous article, RM exchange rate movement based on Brent Crude Oil and other political factors was demonstrated (Read more here).  Today, let's look at the impact of GE14 to RM.

The chart below shows the relationship between RM and Brent Crude Oil.  The scattered blue dots are the actual data of USD/RM corresponding to respective Brent Crude Oil price from July 2005 to July 2015 while the scattered red dots are the actual data of USD/RM corresponding to respective Brent Crude Oil price from August 2015 to December 2017.  The green dots are pre-GE14 data while the yellow dots are post-GE14 data in 2018.

Before the 1MDB scandal was exposed, RM was strongly correlated with oil price.  This is shown by the blue dashed curve (July 2005 – July 2017, R² = 0.74).  After the 1MDB scandal was exposed, RM was weakened to about one standard deviation from the historical trend.  It was trading on the red dashed curve four month before the GE14.  However, RM was further weakened to 1.5 standard deviation curve (dashed yellow curve) immediate after GE14.  This could be due to the additional negative news exposed by the newly elected Government.

Moving forward, RM is expected to trade along the yellow curve before Malaysia finds a sound solution to solve its financial and economic issues.  According to EIA and OECD data, oil price is projected to trade around USD69 – 73 per barrel in 2018 (Read more here).  This suggests the RM will be trading in the range of RM4.05 to RM4.15.  Meanwhile, on 4^th September, Standard Chartered Bank suggested the ringgit will trade at RM4.0 against the USD by end of 2018 and RM4.1 by end of 2019 (Read more here).

Source: Knoema

KLCI Trend from Elliot Wave’s Perspective

In previous article, the Histogram analysis showed that the KLCI would build its support base around 1670 region (Read more here).   The latest KLCI chart below shows that the prediction is indeed reliable.  The KLCI consolidated for about a week and then started to move upward.

This article will look at the KLCI trend by using Elliot Wave (EW) approach (Read more here).  Based on the above chart, the KLCI appeared to have completed the 1, 2, 3, 4, 5 wave.  By combining both histogram and EW analysis, the immediate resistance for KLCI is around 1760 – 1780.  This could be the wave “a” ending point.  If the KLCI is to be trending at a, b, c wave, then highly likely it might pull back to retest 1720 level, and subsequently might trend upward again to complete wave “c”.

The histogram chart above was first published in previous article, reproduce here for convenience.

Where is the support for KLCI? From A Histogram Perspective

The KLCI has been “battered” by exit of foreign investor.  The KLCI was at 1846 on 8 May 2018.  It has dropped to 1665 by 28 June 2018.  This is about 10% or 181 points drop.  The question is where the next support line?

In technical analysis charting, support and resistance levels are two important parameters to determine entry and exit points, coupled with volume information.  This method however, requires some users’ discretion to “draw” the lines on the chart.  This could lead to ambiguity.  One method to overcome this uncertainty is by using histogram (Read more here).

Chart below shows the volume weighted histogram of weekly closing price of KLCI from June 2009 till Jun 2018.  Clearly from the chart, 1630 is a strong support line.  At the time this article was written, the KLCI was trading around 1680.  The immediate strong support based on the histogram is 1670.  There are several strong support lines between 1630 to 1670, thus, the KLCI might be able to build its base around this region.