Hot Deals for Monday WW01'2019

Welcome to Hot Deals for Monday, where you have opportunities to Buy or Sell!

Opportunity 1

Marketing and retail footwear looking for new investors to acquire 20% stake in company.  Consistent dividends of 5% or more for over 5 years.

Opportunity 2

Company dealing in outdoor and gym equipment, has been in business for 15 years.  NTA around RM7.5 mil.  Profit ranging from RM0.5 mil – RM1.0 mil.  Profit guarantee is feasible.  Offering price RM5.0 mil.

Opportunity 3

An established education institution (college) with 3 licenses for sale at RM3 million.  Students of over 500 and EBITDA of RM0.5 million per annum.

Opportunity 4

A European company is looking to acquire or JV with beverages company (including water or milk players) in Malaysia, Myanmar or China.

Opportunity 5

Sale of Software & IT business with revenues of over RM100 million and net income in the range of RM1.5 - 2.0 million.  Controlling stake (approx. 70%) is available.

Opportunity 6

Buyer looking for power plant (100MW and above) in Malaysia, Myanmar, Laos, Vietnam, Indonesia, Philippines and Bangladesh.

If you are interested in the above opportunities or would like to offer your hot deals, please contact info@mpcap.com.my or 603 - 2283 1170 for further details!

Logit Regression on Overnight S&P500 Performance and Its Impact on KLCI

In a previous article, we demonstrated the capabilities of logistic regression (“logit”) on predicting potential loan defaulters (Read more here).  This week, we intend to illustrate another example of logit model application.

We often hear that overnight Wall Street’s performance might have an impact on the next day’s KLCI results, but how shall we quantify this?  To answer the question, we could use logit model to study the probability of the KLCI to close positively or negatively, given the performance of overnight S&P500.

In a logit model, if KLCI gains on the next day, it will be labelled as “1”, while it will be labelled as “0” if KLCI has loss on the next day.  X is the overnight S&P500 performance while b₀ and b₁ are the coefficients.  The coefficients are then estimated using Maximum Likelihood Estimation (MLE)

Chart 1 is the probability of KLCI Gain/Loss on next day given overnight S&P500 performance based on the logit model.  The probability distribution shows that if overnight S&P500 gained 5%, it is probably 99% sure that KLCI will gain on the following day.  If overnight S&P500 gained 1%, the chances for KLCI to gain on the next day is around 70%.  What if overnight S&P500 loss is 2%?  Then the probability of KLCI to close positively on the following day would be around 15%.

Chart 1

Table 1 shows the first 5 rows of the data and their respective equations while Table 2 is the summary of the logit with the estimated coefficients. 

Table 1

Table 2

Reference:

CFA Program Level II Reading Assignment by Sanjiv R. Das, PhD, Richard A. DeFusco, PhD, CFA, Dennis W. Mcleavey, CFA, Jerald E. Pinto, PhD, CFA, and David E. Runkle, PhD, CFA

Earn Money in a Future Without Jobs

Futurist Martin Ford says intelligent machines will replace humans in the workforce, causing massive unemployment and rattling the economy. His basic solution is a base income for all. And that is gaining traction.

The fear that automation might displace workers leading to unemployment goes back to over 200 years – the Luddite revolts in England. And this concern comes up every few years.

Progress is going to lead to new things and with new industries and they will need people for the new jobs. There will be new kinds of work. And that has been the positive story so far.

There is a lot of evidence to show that technologies are rapidly climbing the skills ladder. There will be impact on tasks done by accountants, financial analysts, journalists, lawyers, radiologists and so forth.

We could, of course, face underemployment rather than unemployment. You and I could face a very utopian framework – work less, more leisure, more family time and more time to do meaningful things in life. The best way forward then is to have some kind of guaranteed base income. The fear of this is that there may be too many people riding in the economic cart and not enough pulling the cart. So that will be a real challenge of future societies!

This Photo by Unknown Author is licensed under CC BY-SA-NC

The Future of Renewal Energy

In a recent study (by Jacobson and Delucchi) it was concluded that renewable energy based on wind, water and sunlight (“WWS”) could provide all new energy globally by 2030 and replace current non-renewable energy sources by 2050.

Projected global energy demand by 2030 is 17 trillion watts. Table 1 shows estimates of the potential energy available from various renewal energy sources:

Table 1: Availability of Global Renewable Energy

Table 2 presents results based on assumption that 90% of global energy is supplied by wind and solar, and 10% by other renewable.

Table 2: Infrastructure Requirements for Supplying All Global Energy in 2030 from Renewable Sources

What are the current issues?

(i)         Net Energy

Renewal energy sources generally have low net energy ratio, compared to fossil fuels (oil and coal). Net energy is the ratio of energy available for final consumption divided by energy required to produce it (or energy return on energy invested, the “EROI”). Table 3 demonstrates the net energy ratio for various energy sources.

Table 3: Net Energy Ratios for Various Energy Sources

(ii)        Intermittency

            Most energy supplies cannot be matched to demand as easily as fossil fuels. Energy diversity is one approach to intermittency and the other is to have battery storage. The latter needs further development.

A complete transition to renewable energy will likely take several years. In the meantime, fossil fuels especially natural gas-fired plants are best suited for balancing energy supply-demand.

Reference:

The Economics of Renewal Energy, David Timmons, Jonathan M. Harris, and Brian Roach, Tufts University

Merry Christmas

Great Opportunity to Invest!

We have been touting an established college for sale for several weeks.  We think it is an interesting opportunity!

·        College has been in operation for over 30 years;

·        It has 3 licenses – KL, Penang and JB;

·        All 3 places show positive EBITDA;

·        Over 500 students are currently enrolled;

·        Quality output, so there is no problem on placement of students;

·        Key course is Hospitality and Tourism (diploma);

·        Good faculty and well run by family-owners;

      Asking price of RM3 million is enterprise value and is negotiable!  This is a 2019 Prospect for someone in education or interested to be in education!

Hypothetical Model to Predict PTPTN Defaulter – An Illustration

In regression analysis, logistic regression (“logit”) uses a logistic function to model a binary dependent variable.  It is used in various fields, including machine learning, most medical fields, and social sciences (Read more here).  In a business application, it can be used to predict the likelihood of a homeowner defaulting on a mortgage, by inputting homeowner’s data such as age, income, credit scores and other relevant information (Read more here).

Data such as school exams results, courses offered by University, type of schools, urban or rural, number of siblings, attendance records and other relevant personal data could be used as input for the logit model.

We do not have the information so this article will use “artificial” data to illustrate the capability of the logit model.  For simplicity, only five (5) independent variables are considered in the logit model.

·        Number of A’s in Sijil Pelajaran Malaysia (SPM) = X₁

·        Course offered by University – Science (When X₂ = X₃ = X₄ = 0)

·        Course offered by University – Technology = X₂

·        Course offered by University – Art = X₃

·        Courser offered by University – Business = X₄

The following picture is the artificial data for the logit model.  A total of 500 rows of data were created.  The first column shows whether the student will default the loan, 1 means default while 0 means no default.  Second column is the number of A’s that the student scored in SPM.  Column 3 to 5 are the courses offered by University to that student (triple zero means the course offered is Science).  While the last 4 columns are the equations for logit model.

Once the regression coefficients are determined by using Maximum Likelihood Estimation (MLE), the probability equation is

For example, let’s say a student scored 9 A’s in SPM and was offered a Science course in University, the chances for this student to default PTPTN loan is 0.24.  On the other hand, a student who scored 4 A’s in SPM and was offered an Arts course in University, the default probability is higher at 0.88.

So how could we use this model?  For those students who have higher default rate, a guarantor might be required.  If a complete credit rating system is established, government could potentially offload their financial burden to the private sector.  The above framework is possibly useful for PTPTN in evaluating applicants for its loans. 

Making Money While You Sleep

“If you don’t find a way to make money while you sleep, you will work until you die” – Warren Buffett

Passive income can become a tool to cover your costs. That will allow you to focus on things you want to do rather than earn to meet sustenance. Here are just five of those for your review:

(i)         Own dividend payment shares

            As a shareholder of a dividend paying company, you collect cash rewards for the financial risks of your investment. That’s passive income from hard work of employees and management.

(ii)        Own rental real estate

            Being a landlord is a time-honoured approach to generating cash. Rental income has to exceed cost of owning the property. Otherwise invest in Real Estate Investment Trust, which are generally bound to payout high dividends.

(iii)       Silent partner in a viable business

            This limited partnership approach will mean financial support without being involved in the day to day operations. Hopefully, the business adopts a high distribution to encourage investors.

(iv)       Loan money to Company/Government

            Investing in corporate bonds or P2P structures could be reasonably lucrative. And bondholders always rank ahead of shareholders. Select the P2P funder carefully by reviewing track record and default rates.

(v)        Pay off Debts

           

            Paying of debts is the biggest effective raise of all. Money no longer is going towards debt service. That means you have more breathing room to meet any new costs.

            The aim is to work to cover costs of living and hopefully have something extra. And if you get to control your time and have better financial flexibility, then you are making money while you sleep.

Renewable Energy: Measuring the Benefits

The International Renewable Energy Agency (“IRENA”) conducted a study on the linkages between the energy system and the world’s economies within a single quantitative framework.

Accelerating deployment of renewable energy will fuel economic growth, create new employment opportunities, enhance human welfare and contribute to a climate safe future.

Doubling the share of renewables in the global energy mix increases global GDP in 2030 by up to 1.1% equivalent to USD1.3 trillion. Global welfare increases by 2.7% compared to a 0.6% GDP improvement. And direct and indirect employment in the sector increases to 24.4 million by 2030. Trade will also increase in power and end-use sectors.

What is it currently?

About 7.7 million people are now employed by the renewable energy sector worldwide. Solar PV is the largest renewable energy employer with 2.5 million jobs worldwide. Residential solar PV systems are 65% cheaper now than in 2008. In an auction, Dubai contracted the lowest ever price of U.S. 6 cents per kilowatt-hour and this is without any financial support.

Doubling share of renewable by 2030, could prevent nearly 9 gigatonnes of carbon emission and help stabilize the climate. If the right policy mix is enacted then governments create much needed jobs and clean energy. In India, the goal is to install 100GW of solar PV and 60GW of wind turbines which will generate more than 1 million jobs by 2022. The economics are now undeniable!

References:

1. The Economics of Renewable Energy: Falling Costs and Rising Employment, Adnan Z. Amin

2. Renewable Energy Benefits: Measuring the Economics, International Renewable Energy Agency

The Economics of Christmas

Christmas is typically a peak selling season for retailers. For some, it represents as much as 30% of annual sales.

The average American will spend USD700 on holiday gifts and goodies. That totals more than USD465 billion according to National Retail Federation estimates. And if that money was spent on U.S. made products, it could generate 4.6 million jobs. Christmas Day itself is the least active day of the year in the Western world.

Despite overall spending and economic stimulus arguments advanced, one economist’s analysis suggests overall Christmas spending is a deadweight loss under orthodox microeconomic theory. Why? Because of the effect of gift-giving. This loss is calculated as the difference between what the gift giver spent on the item and what the gift receiver would have paid for the item. For example in 2001, the estimate was USD4 billion in deadweight loss in the U.S. alone. In other words, 25% of all purchases could be unwanted items (others suggest it lies between 10% to 33%).

Pope Francis likened the obligation to buy gifts at Christmas as “material slavery”. The sooner we are free and get back to the real meaning of Christmas – the gift of a Saviour born to save everyone “who calls on His (Jesus) Name”. Amen!

“Merry Christmas Everyone”

Reference:

Surprise! Christmas Spending Isn’t Good for the Economy, David Kyle Johnson

Hot Deals for Monday WW51'2018

Welcome to Hot Deals for Monday, where you have opportunities to Buy or Sell!

Opportunity 1

Marketing and retail footwear looking for new investors to acquire 20% stake in company.  Consistent dividends of 5% or more for over 5 years.

Opportunity 2

Company dealing in outdoor and gym equipment, has been in business for 15 years.  NTA around RM7.5 mil.  Profit ranging from RM0.5 mil – RM1.0 mil.  Profit guarantee is feasible.  Offering price RM5.0 mil.

Opportunity 3

An established education institution (college) with 3 licenses for sale at RM3 million.  Students of over 500 and EBITDA of RM0.5 million per annum.

Opportunity 4

A European company is looking to acquire or JV with beverages company (including water or milk players) in Malaysia, Myanmar or China.

Opportunity 5

Sale of Software & IT business with revenues of over RM100 million and net income in the range of RM1.5 - 2.0 million.  Controlling stake (approx. 70%) is available.

Opportunity 6

Buyer looking for power plant (100MW and above) in Malaysia, Myanmar, Laos, Vietnam, Indonesia, Philippines and Bangladesh.

If you are interested in the above opportunities or would like to offer your hot deals, please contact info@mpcap.com.my or 603 - 2283 1170 for further details!

“Qualitative” Regression On KLCI

Common linear regression is quantitative in nature.  However, it could be used as a qualitative measure under certain condition.  For example, suppose we want to examine the seasonality of stocks returns, we could estimate the regression model using “dummy” variables as independent variables.  A “dummy” variable takes on a value of 1 if a particular condition is true and 0 if that condition is false.

Using the KLCI monthly closing return data from November 2011 to November 2018, we can estimate a regression including an intercept and 11 dummy variables, one for each of the first 11 months of the year.  The equation that we estimate is

Return_t = b₀ + b₁Jan_t + b₂Feb_t + … + b₁₁Nov_t + e_t

where each monthly dummy variable has a value of 1 when the month occurs and a value of 0 for other months.  The intercept b₀, measures the average return for KLCI in December because there is no dummy variable for December.

The following table shows the results of the regression.

The low R² suggests that a month-of-the-year effect in KLCI returns may not be very important for explaining KLCI returns.  However, the significance of F-Test is that it is below the conventional level of 5%, which indicates that we cannot reject the null hypothesis that all of the coefficients jointly are equal to 0.  This means that we could look at the seasonality effect on certain months that are statistically significant such as December (Intercept), May, June, August, September and November.  Amongst those months, only December has positive average return while other months have negative average returns.  Will the history repeat itself in December 2018, perhaps window dressing for this holiday season?

Reference:

CFA Program Level II Reading Assignment by Sanjiv R. Das, PhD, Richard A. DeFusco, PhD, CFA, Dennis W. Mcleavey, CFA, Jerald E. Pinto, PhD, CFA, and David E. Runkle, PhD, CFA

2019: Year of Deceleration?

Goldman Sachs (“GS”) is of the view that global economy is poised to slow moderately from 3.8% in 2018 to 3.5% in 2019. With probably five more 25bp hikes to the Fed Funds rate (reaching 3.5%) in 2019, a slowdown looks more apparent. For the U.S., it is deceleration from 2.9% in 2018 to 2.5% in 2019 and 1.6% in 2020. It is only emerging markets that are bucking the trend (see table below). India and Russia provide the bright spots (for 2020).

Table 1: Our Global Growth Outlook

As GS puts it, slower growth in a number of developed economies is because of capacity constraints and less so for emerging markets.

Some economists are taking a more sinister view, that recession in the U.S. will begin in 2020. The timing of a downturn may be in dispute but headwinds are growing stronger and numerous for the U.S. economy – interest rates; borrowing costs; trade policies; inflation; earnings growth; and general sentiment/business outlook. “Gravity can’t be defied forever” says Ian Shepherdson, chief economist at Pantheon Macroeconomics.

A potential bright spot could be the G20 Summit in Buenos Aires, Argentina. (The G20 represents 19 states and the EU and accounts for 85% of global GDP and 2/3 of the world’s population). But if trade tensions escalate between U.S. and China, China’s growth is negatively impacted by up to 0.4% while the U.S. will have a negative impact of up to 0.1%. So it is in everyone’s interest to find a viable solution and provide a reasonable growth trajectory for others to sustain their growth.

Reference:

Landing the Plane, Global Economic Analysis, Goldman Sachs Economic Research

Economic Cost of Drug Abuse

Drug abuse inflicts harm on public health and safety globally each year. It threatens development and smooth functioning of societies.

Heroin, cannabis and cocaine are the drugs most frequently reported by people entering treatment worldwide. It is estimated only 1 in 6 problem drug users worldwide, some 4.5 million people, receives the required treatment. There is a wide variation from region to region. In Africa, only 1 in 18 drug users receives treatment. In Latin America, Caribbean, Eastern and South-eastern Europe about 1 in 11 get treatment. In North America, it is 1 in 3. Cost of treatment is estimated at USD200-USD250 billion or 0.3-0.4% of global GDP. Research in the U.S. suggests over USD1 investment in treatment yields a return of USD4 and USD12 in reduced crime and healthcare costs.

Globally, it is estimated drug-related deaths account for between 0.5-1.3% of all causes of death for people aged 15-64. Beyond death, there are at least 14 million drug injecting users worldwide. Productivity lost by labour non-participation is USD120 billion (or more) in the U.S. while it is 0.3-0.4% of GDP in Australia and Canada.

Drug abuse and poverty are often linked in multiple ways. Drug abuse may arise from stress with poverty, social strain and other difficult events. In addition, there is often less access to support systems. In an inverse direction is where drug abuse depletes users’ income leading to more crime and other social disorders. Legalising drugs would not ensure underground markets would cease. The “medical” cannabis program in Colorado, U.S. has led to more car accidents with usage further increased.

What are proven measures to reduce overall cost of drug abuse?

(i)         Drug prevention is cost-effective;

(ii)        Early intervention for new users;

(iii)       Drug treatment for addicts;

(iv)       Family and community support for addicts;

(v)        A more efficient justice system to deter drug abuse and alternatives to imprisonment;

(vi)       Social programs; and

(vii)      policies/initiatives against drug trafficking in all development programmes.

What about in Malaysia? It was estimated that registered drug users was about 0.5 million in 2015 with a relapse rate of over 50%. Peer influence and curiosity are top contributing factors, according to Dr Tam Cai Lian of Monash University, Malaysia. This is somewhat dissimilar to other parts of the world. But stress-related substance abuse is increasing. Treatment programmes cost about RM300 million annually and increasing! Of the drug addicts, over 80% are Malays with the highest numbers in PAS-led states like Kelantan and Terengganu.

References:

1. Economic Consequences of Drug Abuse, https://www.incb.org

2. Contributory Factors: Drug Abuse in Malaysia, https://www.incb.org

This Photo by Unknown Author is licensed under CC BY-NC-ND

Cost of Corruption – Accept It or Fight It?

High levels of corruption act like an additional tax. It is accepted in some places as cost of doing business or for getting things done. For Malaysia, it is 1-2% of GDP or about RM10 billion annually (see, 22 June 2018). In just 10 years, we could have lost RM100 billion, excluding the shenanigans of 1MDB. Global Financial Integrity Report (“GFI”) suggests Malaysia lost up to USD431 billion (RM1.8 trillion) in illicit outflows (see, 13 November 2018).

According to Transparency International, corruption is pervasive with over 68% of countries identified as having serious corruption problem. In Palestine it is USD800 million lost each year due to tax evasion. In Indonesia, one-fifth of rice distributed for an anti-poverty programme disappeared. In Pakistan, 43% polled faced a demand for bribes with local government, 69% with the judiciary and 84% dealing with the police. And that’s the Islamic Republic of Pakistan. Let alone those without a religious/shariah compliant requirement.

In communist China, the campaign against corruption began in 2012 with Xi Jinping. He vowed to crack down on “tigers and flies” -  high-level officials and local civil servants alike. As of 2016, 120 high-ranking official and five national leaders were “netted”. More than 100,000 people have been indicted for corruption. Reaction to the campaign has been mixed. Initial cynicism among the public has now turned to popular support. There are some concerns with China’s legal community. The deep-seated cultural issues used to be addressed including, gift giving during holidays, securing patrons for promotion, hosting banquets for minor deals, exchanging favours and the whole gamut of guanzi has to be dealt with.

What about Malaysia? We need to rope in the whole band of suspects into a “Kamunting” like “resort” and secure the loot before it destroys the very fabric of this nation. It is not acceptable in any religion this practice of “greasing” to speed things up or to “bend” the rules. A quick closure and recovery of loot will certainly restore the economy and integrity of this nation. The recent amnesty on tax is one way but not sufficiently aggressive. These parties with their access to funds (overseas) can cause serious trouble. Never underestimate a wounded animal!

References:

1)           Corruption: Cost for Developing Countries (Transparency international UK)

2)           Anti-corruption campaign under Xi Jinping (https://en.m.wikipedia.org)

This Photo by Unknown Author is licensed under CC BY-NC

Hot Deals for Monday WW50'2018

Welcome to Hot Deals for Monday, where you have opportunities to Buy or Sell!

Opportunity 1

Marketing and retail footwear looking for new investors to acquire 20% stake in company.  Consistent dividends of 5% or more for over 5 years.

Opportunity 2

Company dealing in outdoor and gym equipment, has been in business for 15 years.  NTA around RM7.5 mil.  Profit ranging from RM0.5 mil – RM1.0 mil.  Profit guarantee is feasible.  Offering price RM5.0 mil.

Opportunity 3

An established education institution (college) with 3 licenses for sale at RM3 million.  Students of over 500 and EBITDA of RM0.5 million per annum.

Opportunity 4

A European company is looking to acquire or JV with beverages company (including water or milk players) in Malaysia, Myanmar or China.

Opportunity 5

Sale of Software & IT business with revenues of over RM100 million and net income in the range of RM1.5 - 2.0 million.  Controlling stake (approx. 70%) is available.

Opportunity 6

Buyer looking for power plant (100MW and above) in Malaysia, Myanmar, Laos, Vietnam, Indonesia, Philippines and Bangladesh.

If you are interested in the above opportunities or would like to offer your hot deals, please contact info@mpcap.com.my or 603 - 2283 1170 for further details!