Aviation Related Stock, Revisit (Part I)

In a previous article dated 8 June 2018 (Read more here), SAM Engineering stock prices for 2019 to 2021 were forecasted using Monte Carlo simulation.  The forecasted median price was around RM6 while the forecasted min and max price were around RM4 and RM8 respectively.   In fact, SAM Engineering hit RM8.64 in 2019 and plunged to RM4.20 during the Covid-19 pandemic sell-off in March 2020.  Figure 1 shows the forecasted and the actual price range for SAM Engineering.

The Monte Carlo model is known for predicting extreme outcome.  In the long run, the stock price is believed to revert to mean (or median).  As such, after the huge price drop, SAM Engineering is trading around RM5.82 as at 30 April 2020. 

Figure 1: Monte Carlo Forecast vs Actual

  

The next question to ask is – the forecasted price range still hold?  While it appears that the price is reverting to mean (or median), this could be just the market have yet to come up with new forecast model as many argued that in such a volatile market, there are just too many uncertainties.

However, as the valuation guru Prof Aswath Damodaran said (Read more here),

“I know that that you are trying to make a judgment call in a period of incredible volatility, where no one (managers, analysts, governments) know what is coming, but your reasoned guess is as good as anyone's estimate. So, be bold, make your best estimate and move on!”

Thus, a post-Covid19 Monte Carlo model will be designed to incorporate the impact of the pandemic such as volatility, earnings; the shape and the duration of economy recovery.  It will be covered in Part II of this series.

Stay@Home!

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.

Malaysia Covid-19 Forecast using Generalized Logistic Function (Updated 28-Apr-2020)

In a previous article dated 14-Apr-2020 (beginning of the Phase 3 MCO), the Generalized Logistic Function (GLF) model predicted the total case of Covid-19 in Malaysia would be plateauing around 6200 cases by mid-June (Read more here).  Also, the daily new positive cases would go below 50 by end of Phase 3 MCO (Read more here).

Today is the end of Phase 3 MCO, and the daily new cases reported was 31, whereas the past two days daily cases were at 40 and 38 respectively.  This shows that the Covid-19 trend in Malaysia is well predicted by the GLF model and fellow Malaysians are doing a good job to flatten the curve!

Besides GLF, other method such as Susceptible-Infected Recovered (SIR) is also a popular choice among scholars. The Data-Driven Innovation (DDI) Lab of Singapore University of Technology and Design predicted that the pandemic will be 97 per cent contained in Malaysia by May 7.  It further predicted the figure will then increase to 99 percent by May 20, with full containment on July 8 (Read more here).

The prediction by DDI Lab using SIR model is pretty much in line with GLF model prediction, which is still targeting the cumulative case to be plateauing around 6200 by mid-June.

Based on the GLF model updated best-case scenario, by the end of Phase 4 MCO (12-May-2020), the daily new cases would go below 10, entering the single digit phase.  This number is derived purely using quantitative approach.  It does not factor in traffic movement (flight routes reopen), new vaccine development and other qualitative measures such as reopening additional business sectors.

Hang in there, it is almost over.  Please continue to Stay@Home for now!

Stock Screening Using TradingView

While Bursa Market Place is still my number one choice of free stock screening tool for Malaysia Stock Market (link), lately I found that TradingView’s free screening tool provides more knobs for screening (link). 

TradingView serves as the quick tool to screen stocks that fit your selection criteria.  Once you get the list, move to Bursa Market Place to study the detail financial info.

Here’s a simple video to walk you thru the navigation process.  Once you are familiar with it, you can add more criteria according to your preference.

Enjoy the video, Stay@Home.

This article is only meant for education purposes and not act as a recommendation for any particular stock investment. As such the author accepts no liability real (or otherwise) for any investment made by an investor.

Has S&P500 Found Its Bottom?

In a previous article (Read more here), we examined whether KLCI has found its bottom using Gann Fan.  75% of the responses said not yet while 25% said no idea.  It seems like readers are expecting KLCI to go down further.

Today, let’s look at S&P500, please cast your vote at the end of the article.

From crisis to crisis, how much did the S&P500 drop, according to Gann Fan?

1987 Black Monday  – 2001 DotCom Bubble

Drop to 3/1 support line

2001 DotCom Bubble - 2008 Lehman Brothers

Crash below 8/1

  

2008 Lehman Brothers – 2020 Corona Crisis

Drop to ?

What do you think?

I think S&P500 will drop to

2/1

3/1

4/1

8/1

below 8/1

Dunno

 

pollcode.com free polls

Malaysia Covid-19 Forecast using Generalized Logistic Function (Updated 19-Apr-2020)

Added daily new cases graph, and range of plateau (worst and best case prediction) for cumulative cases.  No big changes to the model for now.  Still target 6200 by mid-June, worst case 6700 while best case 5800.  By end of Phase 3 MCO, daily new cases shall be lower than 50.

These numbers are derived purely using quantitative approach.  The model does not factor in traffic movement (reopen flights), new vaccine development, new target test cluster (such as mass testing of migrants), and other qualitative measures.

Will update the model from time to time if any big changes occur.

Please Stay @ Home.

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Malaysia Covid-19 Forecast using Generalized Logistic Function (Updated 14-Apr-2020)

In a previous article (Read more here), a Simple Logistic Function (SLF) was chosen to model the Covid-19 growth trend in Malaysia at the end of 1^st phase Movement Control Order (MCO).  During that time, the SLF model appeared to be adequate as the goodness-of-fit of the curve was reasonable.  However, at the end of the 2^nd phase of MCO (14-Apr-2020), the SLF model is no longer adequate to explain the development of Covid-19 in Malaysia.

A more robust model, Generalised Logistic Function (GLF) is now needed (Read more here), as suggested by some international research papers (Read more here).  There are few reasons why the SLF model is inadequate to predict the growth of the Covid-19.  Firstly, the Covid-19 development is not happened in a closed-system.  SLF is commonly used in studying the growth of bacteria in laboratory.  In the Covid-19 case, although MCO is implemented, it is not a true closed-system, there are leakages that will impact the growth pattern such as test capacity, asymptomatic patients, previous undisclosed linked clusters, and MCO violations.  Secondly, the previous model might appear good due to insufficient data points.  As time passed, more data are now available to show the actual trend of the development.

The GLF, in mathematical form, is

The constants A, K, C, Q, B and v are determined by minimizing the sum of square of the 21-Days rate of change between the actual cumulative cases and the GLF.  Graph 1 is the cumulative positive cases while Graph 2 is the 21-Days rate of change.  From the graphs, GLF (orange curve) fitted very well to actual data (blue curve).  Meanwhile, SLF (grey curve) is poorly fitted as at 14-Apr-2020.

Based on the fitted GLF, the predicted total cases are around 6200 at the middle of June 2020.  This number is derived purely using quantitative approach.  It does not factor in traffic movement, new vaccine development and other qualitative measures.  Nevertheless, the number could be further reduced if we abided to the MCO, and practice good social distancing.  Stay@Home! 

Has KLCI Found Its Bottom?

Let’s look at some interesting charts, from crisis to crisis, how much did the KLCI drop, according to Gann fan?

1986 Commodities Shock – 1997 Asian Financial Crisis

Drop to 8/1 support line

1997 Asian Financial Crisis – 2001 DotCom Bubble

Drop to 4/1 support line

2001 DotCom Bubble - 2008 Lehman Brothers

Drop to 4/1 support line

2008 Lehman Brothers – 2020 Corona Crisis

Drop to ?

What do you think?

I think will bottom at

3/1

4/1

8/1

Dunno

 

pollcode.com free polls

Malaysia Covid-19 Forecast using Generalised Logistic Function (Updated 14-Apr-2020)

In a previous article (Read more here), a Simple Logistic Function (SLF) was chosen to model the Covid-19 growth trend in Malaysia at the end of 1^st phase Movement Control Order (MCO).  During that time, the SLF model appeared to be adequate as the goodness-of-fit of the curve was reasonable.  However, at the end of the 2^nd phase of MCO (14-Apr-2020), the SLF model is no longer adequate to explain the development of Covid-19 in Malaysia.

A more robust model, Generalised Logistic Function (GLF) is now needed (Read more here), as suggested by some international research papers (Read more here).  There are few reasons why the SLF model is inadequate to predict the growth of the Covid-19.  Firstly, the Covid-19 development is not happened in a closed-system.  SLF is commonly used in studying the growth of bacteria in laboratory.  In the Covid-19 case, although MCO is implemented, it is not a true closed-system, there are leakages that will impact the growth pattern such as test capacity, asymptomatic patients, previous undisclosed linked clusters, and MCO violations.  Secondly, the previous model might appear good due to insufficient data points.  As time passed, more data are now available to show the actual trend of the development.

The GLF, in mathematical form, is

The constants A, K, C, Q, B and v are determined by minimizing the sum of square of the 21-Days rate of change between the actual cumulative cases and the GLF.  Graph 1 is the cumulative positive cases while Graph 2 is the 21-Days rate of change.  From the graphs, GLF (orange curve) fitted very well to actual data (blue curve).  Meanwhile, SLF (grey curve) is poorly fitted as at 14-Apr-2020.

Based on the fitted GLF, the predicted total cases are around 6200 at the middle of June 2020.  This number is derived purely using quantitative approach.  It does not factor in traffic movement, new vaccine development and other qualitative measures.  Nevertheless, the number could be further reduced if we abided to the MCO, and practice good social distancing.  Stay@Home!