Tag: NIFTY

Factor Holding Periods for Excess Returns

The NSE has different “strategy” indices that reflect some well known equity factors like low-volatility, quality, momentum and value. They are all shown to out-perform the NIFTY 50 TR index since inception:
cumulative returns of NSE factor 'strategy' indices

However, the excess returns of these indices, like everything else in equities, is unevenly distributed. As an investor, it could get frustrating to watch their “quality” factor investment under-perform the plain-old NIFTY 50 over many months. So broadly, for a given factor/strategy, what should the minimum holding period be for an investor to see only a positive excess return?

holding periods and excess returns for different factor/strategy indices

Factors take time to work. The longer the holding period, the less frustrating the experience. Low-volatility and Quality have the shortest holding periods of 5 years. The Alpha and Value indices require about 10 years for investors to see only positive excess returns. Also, given the lack of liquid, low-cost ETFs and index funds that track these factor indices, investors have to also contend with STT and capital-gains tax if they go the DIY route.

The edge that statistical factors have over market-cap based indices are measured over decades and require investors to be patient.

Charts and code on github.

Categories Tags ,

Chart: Number of stocks going up

We often hear market commentators croaking about the number of stocks going up vs. those going down. There is even an advance/decline line filed under technical “analysis.” However, have a look at the statistical distribution of stocks going up in any given month and see for yourself if it makes any sense paying attention to it:
NIFTY100.gainers

It is, at best, a historical artifact… something that is nice to lookup when someone says that they had a great/crappy month. When a lot of stocks have gone up, it presents a target rich environment for long-only traders. So a random selection of stocks would out-perform the index in that scenario. But good luck using it for market timing.

Code and chart are on github.

Categories Tags

Index Valuations, Part II

In Part I of Index Valuations, we showed how the relative PE (price-to-earnings ratio) and PB (price-to-book ratio) of the NIFTY 50 and NIFTY MIDCAP 50 indices have varied over time. What would a portfolio that weighted each of these based on the relative valuation ratio look like?

Backtest

Suppose, the relative ratio (R) = Ratio(MIDCAP)/Ratio(NIFTY)
Then, at the end of every month, re-weight the protfolio so that portfolio (S1) = R * NIFTY + (1-R) * MIDCAP, and
portfolio (S2) = (1-R) * NIFTY + R * MIDCAP

Ratio can either be PE or PB

PE based weights:
PE weights

PB based weights:
PB weights

It looks like:

  1. a portfolio with PB based weights is a lot less volatile than the PE based one.
  2. PB portfolio recovers much faster that the PE or plain-vanilla indices from deep drawdowns
  3. PB out-performs an equal weight portfolio

You can track and map this strategy to your portfolio using the PB weighted NIFTY/MIDCAP Theme.

Code and charts on github.

Categories Tags ,

Index Valuations, Part I

The NSE website has PE (Price to Earnings), PB (Price to Book) and Dividend Yields of indices going back a decade. Even though their methodology of calculating these has its drawbacks, they are consistently applied to all the indices. This makes an apples-to-apples comparison possible.

Here are the historical PE and PB ratios of the NIFTY 50 and NIFTY MIDCAP 50 indices:
NIFTY 50 Historical PE

NIFTY MIDCAP 50 Historical PE

And their relative ratios:
Relative NIFTY 50/MIDCAP 50 Historical PE

Relative NIFTY 50/MIDCAP 50 Historical PB

In the next part, we will explore if these can be used to time or switch between large-caps and mid-caps.

Code and charts on github.

Categories Tags

Chart: One and Two Percent Moves

  1. Prev. Close-to-Open: c2o – overnight events
  2. Close-to-Close: c2c – fundamental
  3. Open-to-Close: o2c – sentiment
  4. High-to-Low: h2l – uncertainty

NIFTY 50

One percent:
NIFTY%2050.DAILY.1pct

Two percent:
NIFTY%2050.DAILY.2pct

BANK NIFTY

One percent:
NIFTY%20BANK.DAILY.1pct

Two percent:
NIFTY%20BANK.DAILY.2pct

A lot of traders close out their positions by the end of the day. It certainly reduces the risk embedded in overnight moves (c2o) but that has been falling over the years. So has the o2c range. Perhaps it is an artifact of the bull market and reversion to the 2011-2013 range is imminent. Something to keep an eye on.

Code and charts on github.

Related: Is the Low Volatility Regime Breaking?

Categories Tags ,