Malaysia: How To Build A Safe Penny Stock Portfolio – Part 3

Perfect Match – The Blend Of Strategic (Fundamentals) And Tactical (Algorithm) Plan Of Action


PEG Corporate Finance and Research view:

In Part 1 and Part 2 of this article series – we recap how most traders lose big money as they chase blindly on “aggressive” stocks without having an edge over others or an effective trading system to do it. In other words, instead of buying low and selling high, they frequently buy high and sell low and repeat the cycle again and again.

This is especially true in the case of penny stocks where fundamentals are usually over-exaggerated and valuations over-priced.

However, we also show that there could be a simple way (out of many others) of building a fundamental penny stock portfolio by using consensus calls and recommendations by analysts.

This simple approach could save many elite investors and traders’ anguish in buying over-priced speculative or manipulated penny stocks with little fundamentals.

Yet , we also mentioned that having a “value” penny stocks portfolio even if constructed correctly would not be the “cup of tea” for some traders and investors who desire faster and yet risk-manageable returns of such a portfolio.

For aggressive investors who tend to be more interested in more volatile stocks, selection and timing are critical as well. It is a well-known adage that stocks tend to trend only around 30% of the time and remain motionless for the balance of 70% of the time in a year.

Having fundamentally sound stocks but not delivering any returns could be disastrous to one’s portfolio in a rising bull market, especially where growth and momentum plays take precedence over value plays.

It is also damaging to the emotional health of elite traders who holds sound flat stocks in a rising market as not being able to reap the returns of a bull market in this case could be akin to having a spread of good foods in front of you but not being able to eat it (or eat it until much later).

Hence, selection and timing becomes critical to elite traders and investors who want to maximise the returns of their portfolio in the most optimum time possible.

This could easily be done using tactical approaches such as quantitative analysis and algorithms to pick the right stock selection and timing to enter and exit such stocks.

In quantitative analysis and algorithms, we use a lot of the application of probability and statistics to finance and the stock market. We can use mathematics and algorithms in pricing stock valuations and derivatives and also to use them to manage the risk of trading and investing in these financial instruments.

As an elite trader, they will also help you to develop the skill and knowledge to protect yourself against the turbulence of financial markets and your portfolio and also to provide a more effective way to manage the risks and returns of your portfolio.

To layman, the biggest benefit is probably the right selection and timing of your stock entries and exit but as you can see from the above, their benefits are much more than that.

Quantitative study and finance is important for all the above reasons and much more.

In Modern Quantitative Finance, Harry Markowitz is generally credited with beginning the quantitative investment movement when he published a “Portfolio Selection” in the Journal of Finance in March of 1952.

Markowitz used math to quantify diversification and is cited as an early adopter of the concept that mathematical models could be applied to investing.

Robert Merton, a pioneer in modern financial theory, won a Nobel Prize for his work research into mathematical methods for pricing derivatives. The work of Markowitz and Merton laid the foundation for the quantitative (quant) approach to investing.

Obviously, quantitative analysis emerged from the rise of the computer era, which made it easier than ever before to analyse huge amounts of data in short amounts of time. Big data analytics may ring a bell and is often a term that you see in many media articles nowadays.

In quantitative trading and analysis, we typically use voluminous amount of data to identify trading patterns, build models to assess those patterns, and use the information to make predictions about the price and direction of securities.

Once the models are built and the information is gathered, the next step for some big quants is to use the data to set up automated trades of securities.

Quantitative analysis is different from qualitative analysis, which looks at factors such as how companies are structured, the makeup of their management teams, what their strengths and weaknesses are, etc.

Quantitative investing can be widely practised both as a stand-alone discipline and they also can be used in conjunction with traditional qualitative analysis for both return enhancement and risk mitigation.

However, from our experience, the best use of both qualitative and quantitative analysis is to match and blend them together.

In an easier way to visualise, humans do most of the work in qualitative analysis while machines do most of the work in quantitative analysis.

A blend will see the best of both humans and machines in an unbeatable combination – sort of like a perfect match and this is what we do in our Trading and Quantitative Research Lab.

Today, hedge fund managers have embraced the methodology and advances in computing technology that further advanced the field, as complex algorithms could be calculated in the blink of an eye.

Algorithms or mathematical models are now used very successfully to make trading decisions and the best hedge fund managers in the investment and trading business today uses quantitative analysis and mathematical models of algorithms to excel in the investment world.

Quantitative analysis can be used to identify patterns that may lend themselves to profitable security trades, but that isn’t its only value. While making money is a goal every investor can understand, quantitative analysis can also be used to reduce risk.

The pursuit of so-called “risk-adjusted returns” involves comparing risk measures such as alpha, beta, r-squared, standard deviation, and the Sharpe ratio to identify the investment that will deliver the highest level of return for the given level of risk. The idea is that investors should take no more risk than is necessary to achieve their targeted level of return.

We now return to addressing the best selection of a penny stocks portfolio which are both reasonably sound in fundamentals (using analyst selections) and yet will give us enough traction (returns and time) to hold such a portfolio.

From both our big data intensive and mathematical-intensive algorithm models, we can now determine that from our fundamental stocks selection table in Part 2, there are at least 20 stocks which have strong fundamental upside and also have very strong quantitative strengths such as trend, momentum, volatility, etc.

This is just one simple yet easy to understand method to create a reasonably safe portfolio of penny stocks.

However, there are much more powerful methods available from our algorithms as mathematics is often “said to be the language of the Gods” and it can be used to create both simple and also complex models depending on the needs of the individual or the portfolio.

Please note that all algorithms calculated are dynamic and will change as prices, volume and other proprietary factors etc. move in real time.  All information pertaining to any technical or algorithm content are the proprietary assets of our affiliate partner, Bulls and Bears Research.

A final selection of such “consensus” penny stocks portfolio with very high returns potential are show in the table below. Using machine-calculated models, we can easily track and monitor such a portfolio daily without any human intervention. That is the massive power of algorithms in stock trading and investment decisions.

In Part 4, we look at how quantitative analysis and algorithms can be used to create a “speculative” penny stock portfolio and yet be able to keep the risk to more manageable levels. Have you ever blindly chase speculative fast-moving stocks and are filled with fear as soon as you buy them?

Now you don’t have to. With the returns and risks quantified in advance and in an easy to understand and track approach, you can still trade penny “speculative” stocks (or even all type of tradeable stocks) and yet not worry of getting your farm burned down.


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You should consult with your licensed investment adviser before attempting any real-life trading or investments in the marketplace. All information provided can change without notice and is not guaranteed for accuracy and completeness and is not for use by the general public. Please view the full disclaimer and terms and conditions notice here.

Please note that all algorithms calculated are dynamic and will change as prices, volume and other proprietary factors etc. move in real time.  All information pertaining to any technical or algorithm content are the proprietary assets of our affiliate partner, Bulls and Bears Research.

For more information on the algorithm, please contact our Corporate Finance and Research unit at:

Steven Liew
Head of Strategy

Albert Ting
Head of Corporate Finance