Tag: quantitative value

The Relative Value Trap

Throwing away the wheat and keeping the chaff.

Our previous discussions on timing revolved around changing exposures to all factors. This includes both price based factors (volatility, momentum) and fundamental factors (quality, value.) While my personal preference, given its ease of implementation and low turnover, is factor rotationmulti-factor investing is a legitimate contender as well.

However, in the absence of liquid ETFs and index funds that track these individual factors, implementing such strategies is non-trivial and comes with cost-challenges and tracking errors. At the same time, being exposed to a single factor is a test of endurance – very few investors have the patience and time-horizon to stick through the ebb and flow single-factor portfolios. We touched upon this on our post of Magic Formula, a deep-value investment strategy.

So, is there a simple way to time a single factor?

Today, we pick the Value factor and run through some intuitive approaches to time it.

The Market Price-to-Book

Value factor strategies use relative value rankings to create portfolios. The problem with relative value is that if the market as a whole is expensive, which it usually is at the peak of bull markets, then the portfolio ends up with junk that can’t find a bid even during a bullish regime. Consequently, when the market inevitably turns, these portfolios suffer steep drawdowns.

What if, we were long the value factor only when the market is between a one-standard-deviation of historical valuations?

Timing the Value Factor

We go long the NIFTY500 VALUE 50 TR index if NIFTY 50 (alternately, MIDCAP 50) price-to-book is between bands. Stay in cash otherwise.

Using the NIFTY 50 PB ratio holds promise with annualized returns of the strategy clocking in at 8.75% vs. buy-and-hold’s 6.41% and shallower drawdowns to boot. However, we expect costs and taxes to pare away most of those excess returns.

Also, the problem with strategies that “go to cash” is that it brings with it cash management problems. Investors find other uses for the cash in their account and it is quite possible that when the time comes to buy, the cash would be blocked for use some where else.

Using Market PB to Manage Exposures

An alternative to timing the Value factor is to change the relative exposures of large and mid-cap allocations based on the market’s price-to-book. Here, you are always invested in the market but over-weight the cheaper index.

Suppose, the relative ratio, R = MIDCAP PB/NIFTY PB

Then, at the end of every month, re-weight the portfolio so that,

S1 = R * NIFTY + (1-R) * MIDCAP

On a monthly rebalance frequency, S1 clocks in a slightly higher annualized return compared to NIFTY 50 TR. However, it remains a disappointment after you consider transaction costs and taxes.

Combining Value and Momentum

What if, we first applied a relative-momentum cut-off before ranking stocks based on value? And managed risk by having a 10% trailing stop-loss? Would that overcome the adverse selection problem? After all, you are applying a value filter on stocks that are already moving higher.

We setup such a portfolio, Value in Flight, to track such a strategy.

What leaps out of this performance chart is that momentum over-powers value both on the upside and on the downside. During a bull market, investors likely fool themselves into believing that they have invested in a “value” portfolio while it is momentum driving returns.

Besides, using momentum with a stop-loss increases churn.

The bottom half of the chart shows how churn increases with market volatility.

It appears that combining value and momentum incurs all the costs of a momentum strategy and all the downsides of a relative-value strategy.

Conclusion

We tested three intuitive approaches to avoid adverse selection in relative value strategies. The first one used market valuations to time the value factor while the second used it to change relative weights within a portfolio. The third tried to combine momentum and value. None of these approaches make sense after considering transaction costs and taxes.

While the number of blind alleys in investment strategy research is potentially unlimited, we believe that the last word on this subject is yet to be written.

Which side of the trade are you on?

We are big fans of Research Affiliates, the latest piece from Jason Hsu hits the nail on the head:

 

Because sentiment is contagious, because timing price corrections is hard, because we all want to brag about our four-bagger stock picks, because irrational markets can outlast our conviction and courage—we look the value gift horse in the mouth and protest, “But there is a risk that the fundamentals continue to deteriorate and this cheap firm gets cheaper.” Or we say, “This company could be the next Google and Apple; at the current 600 PE, it is attractively priced. Let’s hold it longer.”

 

Its very hard, going in, to tell the difference between “value” and “value trap.” But telling the difference may not be as important as being able to overcome our own behavioral tendencies.

 

The dread of catching a falling knife and the desire to collect the greatest possible gain are not wrong qualitatively. It is absolutely true that many value stocks eventually go bust and that some growth stocks go on to become the next Google. The fear and greed are just off quantitatively.

 

Source: Who Is On the Other Side of the Trade?

Related:
Inside the Mind of a Lemming
Strategy Performance Roundup

Fundamental Quantitative Scores for Stocks

We are big fans of quantitative investment strategies, here at StockViz. The primary reason driving our obsession is that they work! They work because they impose discipline and gives us a framework to measure risk-adjusted returns. As a sign of our unwavering focus for providing our clients with an investment edge, we are now making our Fundamental Quantitative Scores for Stocks accessible to our trading/demat clients.

Fundamental Quantitative Scores rank each stock based on a single metric: for example, Return on Capital (ROC), Leverage, Total Accruals To Total Assets, etc. These ranks provide a snapshot of how the company is doing vs. all the other investment options out there.

Here’s a screenshot for Glenmark:

quantitative fundamental scores for glenmark

A couple of these metrics (Earnings Yield and Book to Market) are price based (and hence the blue highlight). The scores also indicate the total number of stocks that were analyzed on that metric. For example, Glenmark is ranked 748 out of 957 on Sales Growth Index. We’ll be discussing each of these metrics over the next couple of weeks.

 

Related:

Machine Learning Stocks
Quantitative Value Series
StockViz Trading/demat Account

The Use of Historical Financial Statement Information to Separate Winners from Losers

In a paper published in January 2002, Joseph Piotroski explored whether a simple accounting-based fundamental analysis strategy can give better returns to an investor. He came up with a way to score balance-sheets based on financial strength – the higher the score, the better were the prospective returns. Scientifically curious readers can take a look at Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers (pdf)

We created a Theme based on this score. Basically, balance-sheets are scored based on current profitability, stability and operational improvements for two years (using 3 years of data.) The rationale is that stocks that score high on these criteria should out-perform over a period of time.

You can take a look at the this theme here: Financial Strength Value

Similar themes: Magic Formula Investing, Quality to Price, Balance-sheet Strength.
[stockquote]PRECOT[/stockquote]

Balance-sheet Strength

We saw how you can use quantitative methods to score balance-sheets with the STA, SNOA and PROBM models. When you put them all together, you get a portfolio of stocks with incredibly strong (and believable) balance-sheets. We put together a Theme that tracks such a portfolio of stocks.

Check out the “Balance-sheet Strength” theme – a portfolio of 20, equally weighted stocks for the value investor in you.

Stocks to avoid based on this model:

PIIND [stockquote]PIIND[/stockquote]
TTKPRESTIG [stockquote]TTKPRESTIG[/stockquote]
SHASUNPHAR [stockquote]SHASUNPHAR[/stockquote]
APARINDS [stockquote]APARINDS[/stockquote]
CCL [stockquote]CCL[/stockquote]
EIDPARRY [stockquote]EIDPARRY[/stockquote]
VINATIORGA [stockquote]VINATIORGA[/stockquote]
NAVNETPUBL [stockquote]NAVNETPUBL[/stockquote]
APLAPOLLO [stockquote]APLAPOLLO[/stockquote]
AVTNPL [stockquote]AVTNPL[/stockquote]

Note: we ignored stocks that don’t had 3 years worth of statements.