Invest Without Emotions
A lot of thick blue squares mean that positive correlations are high. Red squares mean negative correlations are high. Whites are the doldrums.
Excess winter snow-fall in the Himalayas lead to floods in Bangladesh during spring. If we know that that there was excess snow-fall in the Himalayas this season, we can be better prepared to handle the floods four-months from now. This is the idea behind studying lagged correlations.
If we took a pair of sector indices and lagged their returns, can we find an index that “leads” an other and profit from it?
The chart above is called the cross-correlation plot. It shows that there are two lags, 5 and 9, where CNX BANK lags CONSUMPTION. A scatter plot shows how monthly-returns are correlated to each other across different lags and confirms the relationship:
We found a number of index pairs that lead/follow one another. In addition to the CNX BANK and CNX CONSUMPTION indices above, CNX INFRA and CNX CONSUMPTION, CNX IT and CNX FINANCE, CNX CONSUMPTION and AUTO display this dynamic.
We cannot draw any conclusion from this “finding.” We mined 20 indices over 5 years to dig these nuggets out. The result is spurious. From a statistical point of view, there is no index that consistently leads or lags another.
Related: Should you care about monthly returns of the Nifty?
| MINTs | |
|---|---|
| JCI(IDN) | +0.31% |
| INMEX(MEX) | -0.34% |
| NGSEINDX(NGA) | -4.51% |
| XU030(TUR) | +8.13% |
| BRICS | |
|---|---|
| IBOV(BRA) | +7.21% |
| SHCOMP(CHN) | +7.25% |
| NIFTY(IND) | -0.89% |
| INDEXCF(RUS) | +0.05% |
| TOP40(ZAF) | +1.57% |
| Energy | |
|---|---|
| RBOB Gasoline | +1.30% |
| Brent Crude Oil | +0.34% |
| Ethanol | +2.84% |
| Natural Gas | +1.79% |
| Heating Oil | +0.14% |
| WTI Crude Oil | +3.02% |
| Metals | |
|---|---|
| Copper | +3.36% |
| Gold 100oz | +2.84% |
| Silver 5000oz | +7.74% |
| Platinum | +1.95% |
| Palladium | -2.08% |
| MINTs | |
|---|---|
| USDIDR(IDN) | -0.61% |
| USDMXN(MEX) | -2.95% |
| USDNGN(NGA) | +0.10% |
| USDTRY(TUR) | -2.27% |
| BRICS | |
|---|---|
| USDBRL(BRA) | -0.74% |
| USDCNY(CHN) | -0.87% |
| USDINR(IND) | -0.79% |
| USDRUB(RUS) | -4.89% |
| USDZAR(ZAF) | -3.59% |
| Agricultural | |
|---|---|
| Cocoa | -2.31% |
| Feeder Cattle | +1.07% |
| Lumber | +3.09% |
| Wheat | +4.38% |
| Soybean Meal | -4.06% |
| White Sugar | +1.27% |
| Cattle | +2.99% |
| Corn | +2.53% |
| Orange Juice | +0.61% |
| Coffee (Arabica) | +10.90% |
| Coffee (Robusta) | +8.70% |
| Cotton | +3.23% |
| Lean Hogs | -5.21% |
| Soybeans | -0.15% |
| Sugar #11 | -0.55% |
| Index | Change |
|---|---|
| Markit CDX EM | +0.29% |
| Markit CDX NA HY | +0.29% |
| Markit CDX NA IG | -1.59% |
| Markit iTraxx Asia ex-Japan IG | -0.24% |
| Markit iTraxx Australia | +0.39% |
| Markit iTraxx Europe | +2.11% |
| Markit iTraxx Europe Crossover | +12.07% |
| Markit iTraxx Japan | -2.77% |
| Markit iTraxx SovX Western Europe | +1.53% |
| Markit LCDX (Loan CDS) | -0.04% |
| Markit MCDX (Municipal CDS) | -1.14% |
| Decile | Mkt. Cap. | Adv/Decl |
|---|---|---|
| 1 (micro) | -5.00% | 56/77 |
| 2 | -4.91% | 59/74 |
| 3 | -4.09% | 56/77 |
| 4 | -2.81% | 58/74 |
| 5 | -4.43% | 62/71 |
| 6 | -3.76% | 60/73 |
| 7 | -3.01% | 59/73 |
| 8 | -1.63% | 60/73 |
| 9 | -0.96% | 70/63 |
| 10 (mega) | -1.39% | 67/66 |
| M&MFIN | +3.04% |
| YESBANK | +3.57% |
| GSKCONS | +3.61% |
| JINDALSTEL | -11.67% |
| RCOM | -9.93% |
| BAJAJFINSV | -8.07% |
| JUNIORBEES | -0.31% |
| GOLDBEES | -0.44% |
| NIFTYBEES | -0.57% |
| CPSEETF | -0.66% |
| BANKBEES | -0.83% |
| PSUBNKBEES | -1.33% |
| INFRABEES | -3.27% |
| Sub Index | Change in YTM | Total Return(%) |
|---|---|---|
| GSEC TB | -0.14 | +0.19% |
| GSEC SUB 1-3 | -0.09 | +0.47% |
| GSEC SUB 3-8 | -0.19 | +1.12% |
| GSEC SUB 8 | -0.13 | +1.32% |
| Next Trillion | +1.51% |
| ASK Life | +0.81% |
| Low Volatility | +0.52% |
| Media, Health, IT, Telecom, Services, Pharma Quality To Price | -0.15% |
| CNX 100 Enterprise Yield | -0.42% |
| Tactical CNX 100 | -0.43% |
| PPFAS Long Term Value | -1.28% |
| Textile, Metals, Chemicals, Paper and Energy Quality to Price | -1.68% |
| Auto and Consumer Goods Quality to Price | -2.34% |
| Balance Sheet Strength | -2.43% |
| Financial Strength Value | -2.51% |
| High Beta | -2.64% |
| Magic Formula | -2.97% |
| Momentum | -3.93% |
| Quality to Price | -4.48% |
| ADAG stocks | -6.28% |
Source: How luck works
We run our proprietary momentum scoring algorithm on indices just like we do on stocks. You can use the momentum scores of sub-indices to get a sense for which sectors have the wind on their backs and those that are facing headwinds.
Traders can pick their longs in sectors with high short-term momentum and their shorts in sectors with low momentum. Investors can use the longer lookback scores to position themselves using our re-factored index Themes.
You can see how the momentum algorithm has performed on individual stocks here.
Here are the best and the worst sub-indices:
50-day performance, from January 08, 2015 through March 20, 2015:
A lot of thick blue squares mean that positive correlations are high. Red squares mean negative correlations are high. Whites are the doldrums.