Tag: quant

Macro Volatility and the NIFTY 50

This post is a continuation of our exploration of trying to use macro market indicators to time the NIFTY 50. See World Markets and the NIFTY 50 and India VIX vs. SPX VIX.

Perhaps the problem with using price moving averages was that the major moves were already done before we could short the NIFTY. What if we used volatility instead? Here is how the median of 10-day volatility of major world indices looks like:

macro.volatility

What if we went long only when volatility was below the median and went short otherwise?

macro.trade.a

Looks like the strategy works only in avoiding the 2008 crash. Using observed volatility to time trades doesn’t work. One more to the reject pile.

World Markets and the NIFTY 50

global.etf.performance.2015-12-30.2016-02-08

Global markets have sold off in tandem so far this year. The question on everyone’s mind is if markets are correlated during sell-offs, then is it possible to construct a “world markets indicator” that will allow traders to short the NIFTY?

Constructing an SMA index

There are about 40 world index ETFs listed in the NYSE that provide a dollar based proxy to world equity markets. Using historical data, one can construct an index that tracks the fraction of these markets that are trading above their simple moving averages (SMAs.) If the index dips below a certain level, it could mean that a macro sell-off is in progress and one could proceed to short the Nifty. We constructed a 5- 10- and 50-day index of global market ETFs:

macro.sma

Using the SMA index to trade

So what if we used the SMA indices to go long and short the NIFTY? What we did below was to go short the NIFTY if the fraction of world markets trading below their SMAs were below their historical medians and long otherwise.

macro.trade

Between 2007 and now, the 5- and 10-day SMAs (black, red) under-perform a buy-and-hold (blue) strategy. However, the 50-day strategy (green) helped short the 2008 crisis and the current sell-off.

But let us zoom into the period between 2011 and 2014:

macro.trade2

This is where macro under-performs buy & hold (negative returns vs. positive.)

Year-wise returns of the different strategies:

Year 5-day SMA 10-day SMA 50-day SMA Buy and Hold
2007
50.58%
7.01%
12.03%
54.77%
2008
-2.51%
65.04%
69.88%
-51.79%
2009
-20.12%
-37.06%
18.47%
75.76%
2010
-4.11%
-23.86%
-19.11%
17.95%
2011
-24.00%
-16.30%
7.68%
-24.62%
2012
14.09%
16.66%
1.22%
27.70%
2013
-19.15%
6.02%
-8.94%
6.76%
2014
1.07%
-1.97%
-1.17%
31.39%
2015
13.56%
-4.39%
25.32%
-4.06%
2016
-4.77%
-4.60%
-6.13%
-7.04%

Conclusion

  • Given the volatile nature of the SMA World Indices, expect to take a fairly large hit on trading costs.
  • The 50-SMA based strategy under-performed buy and hold in 6 out of 9 years.
  • The 50-SMA based strategy under-performed buy and hold in 3 consecutive years – 2012, 2013 and 2014 – making it a hard strategy to be faithful to.

Related: India VIX vs. SPX VIX

India VIX vs. SPX VIX

The VIX index is considered a gauge of fear in the markets. A high VIX entails high option implied volatility and occurs when traders bid up options. Given the recent market turbulence where pretty much all asset classes and equity markets across the board tanked, we wanted to check if VIX indices across markets had any relationship with each other.

VIX since 2009

The India VIX index was introduced only in 2009. Let’s start by plotting it vs. the S&P 500 (SPX) Vix to see if it passes a visual sniff test.

vix.historical

We can see at least five instances where India Vix popped without a corresponding move by SPX VIX.

Distribution

The problem with trying to nail down a relationship between the two indices is that, as one would expect, India VIX is way more dispersed than its SPX counterpart. Here’s the density plot.

india vix - spx vix density plot

India vs. spx vix density plot by year.

They might share the same suffix, but they are two completely different beasts.

Cross-correlation

The plots above look at VIX levels. Maybe we should check if the changes in VIX are related. Here’s the cross-correlation plot.

india vix and spx vix cross-correlation plot

India vix and spx vix cross correlation by year.

Conclusion

We cannot really use the two Vix indices to predict each other’s moves.

Market-Cap Deciles, Part II

We had introduced the concept of dividing the universe of stocks by market-cap deciles a while ago (StockViz.) Here are some observations.

Returns

The last year has been spectacular for small- and mid-cap stocks.

From August-2014 to Now:
decile all

For 2015:
decile 2015

So far in 2016:
decile 2016-JAN
Note: Deciles go from 1 (micro-cap) to 10 (mega-cap)

In 2015:

  1. If you had blindly invested in an equal-weight portfolio of ~145 micro-cap stocks, you would have been up ~70%
  2. Every other decile out-performed the mega-caps (decile #1)
  3. Note how the standard-deviation of returns compress as you walk up the cap

Migrations

migrations 2015
Free-float market-cap is a volatile measure in itself – when you use that to classify stocks, you end up with quite a bit of movement between deciles. Something to keep in mind while using deciles for analysis.

Market breadth indicator

The mega-cap decile (decile #1) can be used as a crude market-timing indicator. If you track the number of stocks in the decile that went up vs. the number that went down, you end up with a proxy for breadth.

long-short-nifty

Even though technically it beat the buy-and-hold NIFTY 50, the indicator produces too many trades and it doesn’t offer a large enough margin of out-performance to be useful in live trading.

Next steps

We will continue to poke around and share what we find!

Equity Returns at the Turn of the Month

The Turn of the Month Effect

A recent paper in the Financial Analysts Journal looks at the Turn of the Month effect on equities. Equity Returns at the Turn of the Month, John J. McConnell and Wei Xu:

The turn-of-the-month effect in U.S. equities is found to be so powerful in the 1926–2005 period that, on average, investors received no reward for bearing market risk except at turns of the month. The effect is not confined to small-capitalization or low-price stocks, to calendar year-ends or quarter ends, or to the United States: This study finds that it occurs in 31 of the 35 countries examined. Furthermore, it is not caused by month-end buying pressure as measured by trading volume or net flows to equity funds. This persistent peculiarity in returns remains a puzzle in search of an answer.

Does it apply to Indian markets?

The study skips over the Indian markets. So we did a quick test on the CNX 100 index to check if the effect holds. Here’s the cumulative return chart between a Buy-and-Hold CNX 100 strategy (B&H, black) and a Turn-of-the-Month CNX 100 strategy (TOM, red):

CNX100.TOM

Although the TOM strategy has lower-drawdowns, the B&H wins – both in terms of tax advantage and trading costs. The Turn-of-the-Month effect doesn’t seem to apply to Indian equities.