Timber related stocks initial coverage part III

This is the final part of the “Timber related stocks initial coverage” series.  In part I (Read more here), an overview of Malaysia timber export performance was presented.  While in part II (Read more here), wooden furniture companies that have high exposure to US market were selected for analysis.  

In this final part, the analysis will focus on companies that involve in both upstream and downstream timber business as these companies provide a good proxy for overall timber market.

There are many timber products and concession companies in Malaysia but only four integrated timber companies listed on Bursa Malaysia.  They are JTIASA, SUBUR, TAANN and WTK.  As usual, a quick ranking using AlphaFactor for these companies are presented in Table 1.

Based on Table 1 data, TAANN and WTK’s scores are pretty decent.  Thus, the subsequent analysis will focus on these two companies.

Table 1 (as at 28-Dec-2016)

Stocks	Momentum	Valuation	Growth	Efficiency	Quality	Average
JTIASA	1	5	2	4	2	2.8
SUBUR	3	2	4	4	4	3.4
TAANN	5	3	2	2	1	2.6
WTK	3	1	3	3	2	2.4

As part of the standard procedure, both companies are scanned for any potential financial statement anomaly using Beneish M-Score (Read more here).  Table 2 is the Beneish M Score results.  Both companies’ scores are good.

Table 2

Beneish M-Score	2015	2014	Benchmark (lower better)
TAANN	-2.368119291	-2.983416968	< -1.78
WTK	-2.03312734	-3.014439885	< -1.78

The valuation method for these integrated timber companies will be different from the valuation approach applied in the part II analysis of this timber stocks coverage series.  Both TAANN and WTK have more than 30 years track records and both also paid dividend for the past 10 years (See Chart 1 and Chart 2).  DDM method may be more appropriate to value these companies.

Chart 1

Chart 2

The most important factor for the DDM valuation is the g (growth rate) assumption.  One of the popular textbook approach is using the RR*ROE (Retention Rate * Return On Equity) formula while another approach is using the historical dividend growth rate.  In this analysis, a proxy based on world timber export market growth will be used.

Chart 3 is the world timber export historical market value ranging from 1990 to 2014.  These data were taken from International Tropical Timber Organization (ITTO) statistics database.  In 1990, the export market was about US$ 60 billion then gradually increased to US$ 140 billion in 2014.  As depicted in the chart, the growth was quite volatile.  The average growth rate over the past 25 years was around 3.5%.  Based on the assumption that timber market will continue to grow at this pace, the long term growth projection for timber stocks like TAANN and WTK will be 3.5% per annum.

Chart 3

  

Table 3 and Table 4 are the fair value for TAANN and WTK based on DDM method with various k (required rate of return).

Table 3.  TAANN DDM value

k	g	DDM value (RM)
5.0%	3.5%	6.00
6.0%	3.5%	3.60
7.0%	3.5%	2.57
8.0%	3.5%	2.00
9.0%	3.5%	1.64
10.0%	3.5%	1.38

Table 4.  WTK DDM value

k	g	DDM value (RM)
5.0%	3.5%	1.33
6.0%	3.5%	0.80
7.0%	3.5%	0.57
8.0%	3.5%	0.44
9.0%	3.5%	0.36
10.0%	3.5%	0.31

The closing prices for TAANN and WTK on 28-Dec-2016 were RM3.94 and RM0.99 respectively.  For an investor who is looking for a 5% return per annum, both TAANN and WTK prices are attractive.  But for an investor who is looking for 7% return per annum, both TAANN and WTK prices are not cheap at this moment based on DDM method.

Another common method to estimate the required rate of return is using CAPM (Capital Asset Pricing Model).

k = R(f) + β[R(m) – R(f)]

where,

k = required rate of return

R(f) = risk free rate

β = beta, sensitivity of price movement between stock and market

R(m) = market risk

Table 5.  Required rate of return for TAANN and WTK (data source www.reuters.com and www.ftse.com )

	R(f)	β	R(m)*	k
TAANN	3.2%	0.37	10%	5.7%
WTK	3.2%	1.61	10%	14.2%

* Blended 3Y volatility of KLCI and EMAS Index

Based on the required rate of return in Table 5, the fair value for TAANN and WTK are RM 4.1 and RM 0.2 respectively.

The valuation for TAANN seems decent when compare to the 28-Dec-2016 closing price at RM3.94 but WTK seems over-valued when compare to the closing price of RM0.99.

A closer look on the Balance Sheet of WTK one can find that its book value per share is RM2.74 while the cash per share is RM0.84.  As such, the market price is underpinned by its cash and asset position.

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.

MACD Divergence accuracy checkpoint

The accuracy of analysis methods using either mathematical modelling or technical indicator should be reviewed from time to time.  Today I am going to reviewed the accuracy of MACD divergence indicator, one of my favourite technical indicator.  The detail of using MACD divergence was discussed thoroughly in previous article (Read more here), this article will review its accuracy using a real world example.

I started to monitor FLBHD (Focus Lumber Berhad) on 23-Aug-2016 as the stock price plunged to new low but its MACD indicator did not make new low.  This scenario is classified as “MACD divergence trending”, an encouraging sign that a reversal may happen soon.

On 1-Sep-2016, the stock price hit the lowest point at RM1.42, and then it started to recover.  At that point, the MACD indicator did not register new low so the “MACD divergence trending” was still intact.  The critical valley 1, 2 and 3 were forming thus the chances of achieving “MACD divergence confirmation” was high. 

On 9-Sep-2016, the MACD line finally cut above the signal line, indicating that the MACD divergence was formed thus I bought 1,000 shares of FLBHD near the closing bell at RM1.50 based on the following rules.

Rule	Description	Price/Level	Comment
1	Entry point	RM1.50	MACD Divergence confirmation
2	Stop-loss point	RM1.42	Lowest price point that coincide with MACD line level near valley 3
3a	Exit point 1	RM1.68	Lowest price point that aligned with lowest MACD line level near valley 1 (Yellow arrow in Graph 1)
3b	Exit point 2	See comment	Any price point as long as MACD line crosses zero level
3c	Extended exit point	See comment	If the price breakout from downtrend line (blue line in Graph 1) before hitting criteria 3a and 3b, ignore the criteria 3a and 3b and readjust the exit point per trend line and wave count analysis.
4a	Potential Positive return	12.00%	[(exit point 1)/(entry point) -1]
4b	Potential Negative return	-5.30%	[(stop-loss point)/(entry point) - 1]
4c	Positive return probability	70%	Based on historical observation
4d	Negative return probability	30%	Based on historical observation
4e	Expected return	6.81%	E(R) = (positive return probability)*(potential positive return) + (negative return probability)*(potential negative return)

After I bought FLBHD, the stock price moved lower to RM1.47 on the next few days.  As it did not go below the stop-loss point, I continued to hold the stock.  Then, the stock started to edge upward on the 4^th day then moved backward after hitting the downtrend line.

On 10-Oct-2016, the stock price broke out from the downtrend line before the MACD line crossed zero level.  As such, both rules 3a and 3b were void.   The new exit point will be based on trendline and wave count analysis, which will be covered in another article.

MACD divergence is a good technical indicator for trading as it provide very clear entry, stop-loss and exit points.  This helps to create a robust trading system that can be followed easily.  My long-term plan is to code it into an auto-trading application and let the system run by itself.  Feel free to contact me if you are interested to co-develop the software.

Happy trading!

Graph 1

Picture 1

Picture 2

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.

Timber related stocks initial coverage part II

Based on the analysis in part I (Read more here), US housing market is performing better than other region.  Thus, companies that have high wooden furniture export to US market may continue to do well.  However, this assumption requires further analysis to identify the company earnings growth quality, whether it was due to foreign exchange rate or business growth.   Secondly, as the timber business is cyclical, companies that have higher cash reserved could weather the downturn better and the ability to pay dividend is higher too.  Finally, either single stage or multistage DDM model may not be appropriate to evaluate the stocks as the perpetual value is hard to estimate.  Thus, the Monte Carlo valuation model based on P/E ratio, using three years projection is recommended.

A quick search on Bursa Market Place yielded the following stocks (Table 1).  The five columns of ratings are AlphaFactor developed by S&P Capital IQ (Read more here).  It is a free and easy tool to help investor to screen the stocks in Bursa Malaysia.  Most stocks that have exposure to US market have good rating except Sern Kou.  Thus, Sern Kou is removed from the subsequent screening.

Table 1

Stocks	Momentum	Valuation	Growth	Efficiency	Quality	Average
SHH	1	1	1	1	1	1
LiiHen	2	1	1	1	1	1.2
Latitude Tree	3	1	1	1	1	1.4
Jaycorp	3	1	1	1	1	1.4
HomeRiz	2	2	1	1	1	1.4
PoHuat	3	2	2	2	1	2
Sern Kou	2	5	4	4	5	4

Table 2 is the percentage of revenue from US market.  Only 4 companies derived more than 50% revenue from US market.  Thus, HomeRiz and Jaycorp are excluded in subsequent screening as these companies may require different valuation method.

Table 2

Stocks	% of revenue from US (2015)
SHH	Only stated all products mainly exported to US.  No numbers were given in AR
Latitude	92%
PoHuat	79%
LiiHen	79%
HomeRiz	40%
Jaycorp	28%

The next step is to use Beneish M-Score (Read more here) to scan for any potential financial manipulation (Table 3).  Most of the companies passed the Beneish M-Score test except SHH on year 2015.  It is due to the high receivable level on 2015, which was doubled to RM12,714,843 compared to 2014 level RM6,353,626.  The company acknowledged the credit risk in 2015 annual report.  The receivable level has subsequently improved to RM8,323,000 in the Q4’2016 balance sheet, tallied with cash flow from operating adjustment figures.

Table 3

Beneish M-Score	2015	2014	Benchmark (lower better)	Comment
SHH*	-2.85377	-1.57566	< -1.78	* 2016 and 2015.
LiiHen	-2.82747	-1.96595	< -1.78
Latitud*	-2.53439	-2.03448	< -1.78	* 2016 and 2015.
PoHuat	-2.06839	-2.26697	< -1.78

 

Table 4 is the growth comparison for US housing start, Malaysia wooden furniture export, companies’ revenue and profit after tax attributable to owners.  From 2013 to 2015, the US housing start is growing at CAGR 12.24%.  Malaysia wooden furniture export CAGR is 3.36% due to the negative growth in 2013.  All four companies exhibited similar trend in 2013 at a different degree.  Most of the companies are doing well in recent years except SHH.  Even though its US market exposure is the highest among the companies, its earnings trend is very volatile.  As such, combining with the Beneish M-Score results, SHH will be excluded in the subsequent analysis.

   

From 2014 to 2015, assuming that USD appreciated against RM at the rate of 20%, thus, either the revenue or profit has to gain more than 20% in order to be classified as business growth.  Among the remaining three companies, only LiiHen and PoHuat meet these criteria.  Latitud Q4’16 PAT attributable to owner was at -6.8%.  In fact, Latitud stated in the Q4’16 unaudited report that US sales was declining due to strong competition.  As such, Latitud will be excluded in the subsequent analysis.

Table 4

	2013	2014	2015	CAGR	Comment
US Housing Start	18.44%	7.85%	10.70%	12.24%
Wooden Furniture Export	-12.41%	10.30%	15.13%	3.61%
SHH revenue	-3.84%	15.09%	-0.57%	3.24%	Q4'16 growth 6.7%
LiiHen revenue	-8.83%	25.98%	37.43%	16.43%	Q2'16 + growth intact
Latitud revenue	-4.67%	31.87%	9.06%	11.09%	Q4'16 growth 8.5%
PoHuat revenue	-8.69%	5.36%	20.35%	5.01%	Q3'16 + growth intact
SHH PAT attributable to owner	n/a	432.19%	-20.03%	106.30%	Q4'16 growth 79%.
LiiHen PAT attributable to owner	-17.25%	59.45%	103.79%	39.06%	Q2'16 + growth intact
Latitud PAT attributable to owner	117.22%	100.75%	21.64%	74.40%	Q4'16 growth -6.8%
PoHuat PAT attributable to owner	10.59%	41.90%	64.62%	37.21%	Q3'16 + growth intact

Table 5 is the financial strength of the remaining two companies based on their most recent financial results.  Both companies have decent cash level and able to serve the debt without additional funding.

Table 5

	LiiHen	PoHuat
D/E Ratio	0.12	0.17
Cash/Share	0.69	0.27
Debt/Share	0.17	0.17
NTA/Share	1.33	0.97
Price 30/9/2016	3.10	1.53
P/Cash	4.51	5.62
P/Book	2.33	1.58

Finally, the valuation model is based on Monte Carlo simulation with the following assumption

1.       PE ranges from 7 – 10.  Based on average historical range.

2.   The lowest EPS for any particular forecasted year are fixed at 10% lower than 2015 value.  The intention is to capture any unforeseen impact such currency fluctuation or market slowdown.

3.      The highest EPS for any forecasted year are maxed at 15% or lesser than the previous forecast year.  The intention is to capture any possible market share expansion.

4.       The average EPS for any forecasted year are maxed at 8.5% or lesser than the previous forecast year.  The intention is to capture the average growth below the CAGR of US housing start.

5.       3000 samples are used in the simulation.

Table 6a and Table 6b are the forecasted prices using Monte Carlo simulation for LiiHen and the potential return scenario based on the closing price as at 30-Sep-16 (LiiHen: RM3.1).  Table 7a and 7b are the forecasted prices using Monte Carlo simulation for PoHuat and the potential return scenario based on the PoHuat closing price as at 30-Sep-16 (PoHuat: RM1.53). 

Table 6a

LiiHen	2016F	2017F	2018F
Average	2.88	3.11	3.36
Min	1.96	1.96	1.96
Max	4.00	4.50	5.10
Median	2.80	3.04	3.30

Table 6b

LiiHen	2016F	2017F	2018F
Average	-7.10%	0.32%	8.39%
Min	-36.77%	-36.77%	-36.77%
Max	29.03%	45.16%	64.52%
Median	-9.68%	-1.94%	6.45%

Table 7a

PoHuat	2016F	2017F	2018F
Average	1.49	1.61	1.74
Min	1.12	1.12	1.12
Max	1.90	2.20	2.50
Median	1.52	1.60	1.71

Table 7b

PoHuat	2016F	2017F	2018F
Average	-2.61%	5.23%	13.73%
Min	-26.80%	-26.80%	-26.80%
Max	24.18%	43.79%	63.40%
Median	-0.65%	4.58%	11.76%

Based on the simulation results, both LiiHen and PoHuat are trading around the average value as at 30-Sep-2016, with LiiHen slightly on the high side.  PoHuat valuation seems fairer might due to potential EPS dilution of outstanding warrant that expired on 2020.  The valuation model in this article only factored in certain percentage of dilution up to 2018. 

This part II analysis is based on publicly available data, using mainly quantitative approach.  Qualitative method such as supply chain analysis, product mix, and new product development quality and capability are not covered.

Part III will focus on conventional timber companies that have logging, plywood manufacturing and other timber harvesting business.

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.