Value Investing Strategy Performance in Singapore

Hi, I am Lau Shi Ern and I tested a few value investing strategies after I read this tread: https://www.valuebuddies.com/thread-6746.html

The results were not encouraging, so I was wondering whether anyone can share some of your real investing experience to see if the results I have here are correct?

The Setup:
I tested the market cap, price-to-book ratio, price-to-earnings ratio, and the EV-to-EBITDA ratio using historical data from 1st Jan 2015 to 1 Aug 2017(2 years 8 months). I assume that the investor forms his portfolio at the start of the year and rebalance his portfolio yearly. Rebalancing means sell stocks that don't fulfill the criteria to buy new stocks that fulfill the criteria. Except for the market cap test, all other tests exclude companies that have a market capitalisation of SGD0 to SGD50 million. This is to avoid companies that are illiquid and thus unrealistic for the investor to buy. All stocks in a portfolio are equal weighted and rebalancing occurs on 1 Jan 2015, 1 Jan 2016 and 1 Jan 2017.

Correction: The returns are price returns and do not include dividends reinvested due to lack of good data provider.

In the market cap chart, below 1.46 means the investor gain 46%. 0 to 50 means that stocks that have a market cap from SGD0 to SGD50 million on the rebalancing date will be in that portfolio 0 to 50.



In the price to book chart here: 0 to 0.5 means stocks that fall between 0 to 0.5 price to book ratio will be in this porftolio.




Basically all of these strategies only breakeven by the end of 2 years 8 months. Unless an investor is willing take risks buying smaller companies, or it would be difficult to get higher returns.

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Nice work...
But I'd point out that your work doesn't answer the question you have posted.

All this would tell me the relative performance of each of the sub category within the parameter that you have back tested over the 2 yrs + period.

It tells me nothing about "value investing"
For example, it tells me that over the 2 yrs period (which is not that long), those with the smallest market cap outperformed all the other cateogries of market caps, AS A GROUP.
Unless you equate looking at market cap as = value investing, then the data is not relevant to answering the question you have posted.
(I am guessing the data cited here is just a reflection of huge increases in a few of the micro cap companies, so that skewed the line)

Also, grouping under certain parameters means that all members are artifically grouped together under that parameter, regardless of their actual value.
For example, under price:book, say the 0.5-1 times category, there could be company A that was trading at PB of 0.7 times, but its earnings were supeior , outlook was great blah blah.
Company was trading at PB of say 0.9, also in this category, but was showing losses blah blah.
So over the next 2 years they performed very differently but were grouped into this category, so their performance sort of "nullified" each other.
In short, what I m saying is that your data, isn't very relevant to value investing, cos there's nothing about value here.
Lastly, how about the price? Performance is all about price relative to value. One cannot say something is undervalued without looking at the price, and the price relative to value in any of the company in any of your categories, would've been very different.
For some the price could be far below, some could be far above, some could be exactly at the intrinsic value.
So again, the data is not relevant.

I enjoyed your charts immensely though.
Lotsa work.
If the data is correct, we can interpret some stuff from it, just not value investing.

Shi Ern,
Tell you a secret.
Remove all the S-Chip from SGX.
Do your back test again.

I learn this the easy way from a senior valuebuddies here.

Hi,

I assume your data has already screened out non-value stocks but listing out the criterions for that may help other valuebuddies members to understand your point of view!

Ray

Quote: I assume that the investor forms his portfolio at the start of the year and rebalance his portfolio yearly.

Quote:all other tests exclude companies that have a market capitalisation of SGD0 to SGD50 million.

Quote:All stocks in a portfolio are equal weighted

Quote:Unless an investor is willing take risks buying smaller companies,

The above assumptions are generally not valid for value investing.
Your approach is more akin to technical analysis since there is no in depth analysis of the worth of the companies through financial statements and annual reports.

Nice testing out there. Could you share how do you do back testing? Which data source and software do you use? Do you account for survivorship bias? Why do you breakdown the data into the specified "bins"? for example, it's not the same interval length for PE ratio for your different chart lines. i.e -18 to -6, -6 to 0.

Thanks.

(12-09-2017, 07:29 AM)chialc88 Wrote: Shi Ern,
Tell you a secret.
Remove all the S-Chip from SGX.
Do your back test again.

I learn this the easy way from a senior valuebuddies here.

Ok. Let me try. I suspect the S-Chip are mainly in the SGD0 to SGD50mil category that has been removed from most other charts. I will double check.

(12-09-2017, 09:54 AM)noob_investor Wrote: Nice testing out there. Could you share how do you do back testing? Which data source and software do you use? Do you account for survivorship bias? Why do you breakdown the data into the specified "bins"? for example, it's not the same interval length for PE ratio for your different chart lines. i.e -18 to -6, -6 to 0.

Thanks.

I use Python, my data is not very good as it has some manual work involve. For example the returns are price returns because the data provider don't have total returns which includes dividends.

Survivorship bias can't be accounted because the data source is not good. They promise to upgrade for me but have not done so.

I suspect the bias is not huge because only use last 3 years. For more than 3 years, the bias will accumulate alot.

No particular reason for the bins, just random assignment of bins.

(12-09-2017, 09:46 AM)yeokiwi Wrote:

Quote: I assume that the investor forms his portfolio at the start of the year and rebalance his portfolio yearly.

Quote:all other tests exclude companies that have a market capitalisation of SGD0 to SGD50 million.

Quote:All stocks in a portfolio are equal weighted

Quote:Unless an investor is willing take risks buying smaller companies,

The above assumptions are generally not valid for value investing.
Your approach is more akin to technical analysis since there is no in depth analysis of the worth of the companies through financial statements and annual reports.

Ok. no problem.

Equal weight is an estimate of the average random guy value investing portfolio, since the returns will be just the average. Another assumption is that it is hard to buy illiquid small cap counters between SGD0 to SGD50mil.

(12-09-2017, 12:21 AM)TTTI Wrote: Nice work...
But I'd point out that your work doesn't answer the question you have posted.

All this would tell me the relative performance of each of the sub category within the parameter that you have back tested over the 2 yrs + period.

It tells me nothing about "value investing"
For example, it tells me that over the 2 yrs period (which is not that long), those with the smallest market cap outperformed all the other cateogries of market caps, AS A GROUP.
Unless you equate looking at market cap as = value investing, then the data is not relevant to answering the question you have posted.
(I am guessing the data cited here is just a reflection of huge increases in a few of the micro cap companies, so that skewed the line)

Also, grouping under certain parameters means that all members are artifically grouped together under that parameter, regardless of their actual value.
For example, under price:book, say the 0.5-1 times category, there could be company A that was trading at PB of 0.7 times, but its earnings were supeior , outlook was great blah blah.
Company was trading at PB of say 0.9, also in this category, but was showing losses blah blah.
So over the next 2 years they performed very differently but were grouped into this category, so their performance sort of "nullified" each other.
In short, what I m saying is that your data, isn't very relevant to value investing, cos there's nothing about value here.
Lastly, how about the price? Performance is all about price relative to value. One cannot say something is undervalued without looking at the price, and the price relative to value in any of the company in any of your categories, would've been very different.
For some the price could be far below, some could be far above, some could be exactly at the intrinsic value.
So again, the data is not relevant.

I enjoyed your charts immensely though.
Lotsa work.
If the data is correct, we can interpret some stuff from it, just not value investing.

Ok. so sorry, I didn't know it is not value investing.

The idea is too simulate the results of the average value investing porftolio using different common value investing ratios?
Maybe it can be used like a ETF investing benchmark for different ratios.