Author: shyam

Market-Cap Deciles, Part III

Part I, Part II of the series.

111% vs. 11%

A portfolio of ~150, equal-weight, small-cap stocks, rebalanced monthly, gave a return of 111% from 2015 through now.

decile.9.2016-04-24

While a similar portfolio of mega-cap stocks gave a return of 11% during the same time frame.

decile.0.2016-04-24

Variance

Returns from the small-cap portfolio are accompanied by larger volatility.

decile.distribution.9.2016-04-24

decile.distribution.0.2016-04-24

Accessibility

Is the alpha accessible? Given the meager volumes in the small-cap space, narrow circuit breakers and intra-day volatility of prices, small-cap alpha is hard to access. The impact cost of trading 150 small-cap stocks every month would be pretty high for large positions.

However, a portfolio with an exposure of Rs. 10,000 – Rs. 50,000 per stock is doable. So, theoretically, you can size the portfolio between Rs. 15,00,000 – Rs. 75,00,000 to access this alpha.

Appendix

Cumulative wealth charts for each decile (both cap- and equal-weighted): (a)

Box plots of cumulative returns of stocks in each decile: (b)

March Madness 2016

world.2016-02-29.2016-03-31

Equities

Major
DAX(DEU) +3.33%
CAC(FRA) -1.04%
UKX(GBR) +0.09%
NKY(JPN) +0.86%
SPX(USA) +5.44%
MINTs
JCI(IDN) +1.51%
INMEX(MEX) +5.97%
NGSEINDX(NGA) +2.95%
XU030(TUR) +9.00%
BRICS
IBOV(BRA) +16.69%
SHCOMP(CHN) +11.96%
NIFTY(IND) +10.39%
INDEXCF(RUS) +0.37%
TOP40(ZAF) +4.08%

Commodities

Energy
Brent Crude Oil +10.30%
Ethanol +4.44%
Heating Oil +8.39%
RBOB Gasoline +38.22%
Natural Gas +13.84%
WTI Crude Oil +11.73%
Metals
Palladium +15.93%
Copper +2.35%
Gold 100oz -0.06%
Silver 5000oz +4.73%
Platinum +5.15%

Currencies

USDEUR:-4.70% USDJPY:-0.63%

MINTs
USDIDR(IDN) -1.56%
USDMXN(MEX) -4.16%
USDNGN(NGA) +0.00%
USDTRY(TUR) -4.86%
BRICS
USDBRL(BRA) -9.97%
USDCNY(CHN) -1.35%
USDINR(IND) -3.18%
USDRUB(RUS) -9.94%
USDZAR(ZAF) -7.24%
Agricultural
Cocoa -2.75%
Feeder Cattle -0.55%
White Sugar +8.29%
Cattle -4.71%
Coffee (Robusta) +9.77%
Corn -1.27%
Lumber +21.75%
Orange Juice +17.57%
Sugar #11 +4.72%
Coffee (Arabica) +11.78%
Cotton +2.76%
Soybeans +7.00%
Lean Hogs -2.05%
Soybean Meal +4.55%
Wheat +5.96%

Credit Indices

Index Change
Markit CDX EM +2.89%
Markit CDX NA HY +3.28%
Markit CDX NA IG -27.66%
Markit iTraxx Asia ex-Japan IG -6.67%
Markit iTraxx Australia -15.03%
Markit iTraxx Europe -26.80%
Markit iTraxx Europe Crossover -98.68%
Markit iTraxx Japan -9.45%
Markit MCDX (Municipal CDS) -14.58%
Markets rebounded with the Fed assuming the role of the world’s central bank…

International ETFs (USD)

global.etf.performance.2016-02-29.2016-03-31

Nifty Heatmap

NIFTY 50.2016-02-29.2016-03-31

Index Returns

index.performance.2016-02-29.2016-03-31

Market Cap Decile Performance

Decile Mkt. Cap. Adv/Decl
1 (micro) +0.54% 70/61
2 +9.38% 82/48
3 +10.53% 91/39
4 +9.03% 82/48
5 +7.85% 84/46
6 +6.78% 85/45
7 +10.83% 83/47
8 +7.10% 83/47
9 +12.46% 81/49
10 (mega) +1.97% 74/57

Top Winners and Losers

TATAMOTORS +29.00%
RELINFRA +30.19%
CAIRN +30.44%
LUPIN -15.69%
APOLLOHOSP -9.19%
COALINDIA -6.13%
Dash for trash?

ETF Performance

PSUBNKBEES +19.47%
BANKBEES +15.43%
INFRABEES +12.76%
NIFTYBEES +11.70%
JUNIORBEES +9.02%
CPSEETF +8.08%
GOLDBEES -3.22%
With bank balance-sheet clean up in full swing, banks got the better bid…

Yield Curve

yieldCurve.2016-02-29.2016-03-31

Bond Indices

Sub Index Change in YTM Total Return(%)
0 5 -0.22 +1.22%
5 10 -0.24 +1.91%
10 15 -0.30 +2.56%
15 20 -0.35 +3.94%
20 30 -0.37 +4.59%
Rate cut already factored in?

Investment Theme Performance

The worst hit asset classes saw the steepest rebound…

Equity Mutual Funds

Bond Mutual Funds

Thought to sum up the month

Why do amateurs believe they can outperform the professionals — or even identify those pros who will outperform? (Performance of individual mutual funds cannot be predicted with any greater degree of accuracy than individual stocks or bonds.)

  1. Overconfidence
  2. Optimism Bias
  3. Hindsight Bias
  4. Attribution Bias
  5. Confirmation Bias

Source: Why We Think We’re Better Investors Than We Are

Monthly Recap: Winter

world.2016-01-29.2016-02-29

Equities

Major
DAX(DEU) -3.09%
CAC(FRA) -1.44%
UKX(GBR) +0.22%
NKY(JPN) -9.14%
SPX(USA) +0.40%
MINTs
JCI(IDN) +3.52%
INMEX(MEX) +2.41%
NGSEINDX(NGA) +2.74%
XU030(TUR) +3.56%
BRICS
IBOV(BRA) +6.39%
SHCOMP(CHN) -1.50%
NIFTY(IND) -7.62%
INDEXCF(RUS) +3.10%
TOP40(ZAF) -0.60%

Commodities

Energy
Brent Crude Oil +5.42%
RBOB Gasoline +20.16%
WTI Crude Oil +0.57%
Ethanol -2.68%
Heating Oil +3.61%
Natural Gas -25.63%
Metals
Copper +1.94%
Palladium +0.74%
Platinum +7.21%
Gold 100oz +11.54%
Silver 5000oz +4.93%

Currencies

USDEUR:-0.50% USDJPY:-7.25%

MINTs
USDIDR(IDN) -2.92%
USDMXN(MEX) +0.11%
USDNGN(NGA) +0.10%
USDTRY(TUR) +0.22%
BRICS
USDBRL(BRA) +0.07%
USDCNY(CHN) -0.53%
USDINR(IND) +0.93%
USDRUB(RUS) -0.89%
USDZAR(ZAF) -0.25%
Agricultural
Cattle +3.18%
Feeder Cattle +1.22%
Lean Hogs +6.19%
White Sugar +0.02%
Coffee (Robusta) +0.51%
Corn -4.78%
Lumber +5.88%
Soybeans -2.98%
Wheat -6.37%
Cocoa +10.09%
Cotton -4.85%
Coffee (Arabica) -3.26%
Orange Juice -9.50%
Soybean Meal -4.92%
Sugar #11 +9.12%

Credit Indices

Index Change
Markit CDX EM +0.27%
Markit CDX NA HY -0.58%
Markit CDX NA IG +7.19%
Markit iTraxx Asia ex-Japan IG +5.66%
Markit iTraxx Australia +15.41%
Markit iTraxx Europe +9.54%
Markit iTraxx Europe Crossover +45.82%
Markit iTraxx Japan +12.00%
Markit MCDX (Municipal CDS) +3.25%
Jan and Feb saw a wave of volatility hit pretty much every asset class. Diversification provided scant protection in wave-after-wave of selling across world markets and asset classes. Hopefully the great purge is done and we can look forward to better days ahead…

International ETFs (USD)

global.etf.performance.2016-01-29.2016-02-29

Nifty Heatmap

NIFTY 50.2016-01-29.2016-02-29

Index Returns

index.performance.2016-01-29.2016-02-29

Market Cap Decile Performance

Decile Mkt. Cap. Adv/Decl
1 (micro) -22.65% 46/80
2 -19.11% 29/96
3 -20.26% 31/95
4 -17.46% 30/95
5 -16.40% 31/95
6 -15.09% 37/88
7 -12.49% 42/84
8 -12.19% 34/91
9 -11.15% 50/76
10 (mega) -6.23% 63/63
Mid- small- and micro-caps bore the brunt…

Top Winners and Losers

MARICO +6.81%
BHARTIARTL +8.83%
EICHERMOT +14.23%
BHEL -34.50%
PNB -22.23%
AUROPHARMA -21.41%
Eicher Motors emerged a big winner…

ETF Performance

GOLDBEES +9.31%
JUNIORBEES -6.73%
INFRABEES -6.80%
NIFTYBEES -7.07%
CPSEETF -9.72%
BANKBEES -9.83%
PSUBNKBEES -11.21%
Gold. Enuf said.

Yield Curve

yieldCurve.2016-01-29.2016-02-29

Bond Indices

Sub Index Change in YTM Total Return(%)
0 5 +0.14 +0.28%
5 10 +0.12 +0.02%
10 15 +0.15 -0.42%
15 20 +0.12 -0.41%
20 30 +0.11 -0.38%
Long bonds got shellacked…

Investment Theme Performance

Equity Mutual Funds

Bond Mutual Funds

Fund flows

FIIs sold out of both equities and bonds…

fii-investments.2014-01-01.2016-02-29

dii-investments.2014-01-01.2016-02-29

Bonds

The spread between 10-year US treasuries and Indian gilts are at levels seen in late 2013…
ust-ind-10yr-spread.2011-01-18

… and all is not hunky-dory in the US bond markets either. The spread between 10yrs and 2yrs are at their lowest since 2008…
ust-yield-curve.2s10s

… and the whole yield curve shifted down in February.
ust-yield-curve.2011-01-18

Thoughts

As we hit ‘publish’ on this article, Indian markets are enjoying a post-budget rally. Did markets find a bottom in February? Or is more pain to come? Bring on the March madness!

Introducing the Global Macro Dashboard

It is all local until it is not

World markets just witnessed a spiraling sell-off that caught most investors off-guard. The problem is that for most of the time, markets are local. Except for those times when they aren’t and correlations go to 1.

We tried singling out different factors to check if they could act as leading indicators of market sell-offs:

It is not one thing and it is never the same thing

The problem is that, statistically, no one global indicator is going to be a perfect canary in the coal mine. However, once the number of “meaningful” events crosses a threshold, correlations tend to 1.

But what exactly defines “meaningful?” Is it 1-sigma or 2-sigma? Should it be change in price or price itself? What should be the number of periods over which these statistics are calculated? The answers to these questions are going to take a while to figure out. In the meantime, we decided to create a dashboard that lets investors choose some of these filters.

You can play with our Global Macro Dashboard here: StockViz/GlobalDashboard

Welcome to glocal markets.

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.