Probably the reason why banks have been reluctant to pass on rate-cuts is because the yield curve has been flat as a pancake. The difference between short-term and long-term rates are near their historical lows.
Author: shyam
GARCH(1,1)
GARCH(1,1) is a common approach for modeling volatility. They were developed by Robert Engle to deal with the problem of auto-correlated residuals (which occurs when you have volatility clustering, for example) in time-series regression.
What we did:
- Picked the best fit ARIMA(p,d,q) model for historical VIX over different look back periods
- Created a GARCH(1,1) model based on ARMA(p,q)
- Predicted t+1 VIX
500-day lookback
We found that modeling based on the previous 500-day VIX closing levels gave us the least prediction errors. The appendix has the charts for other lookback periods.
Prediction vs. Actual
Note how in some periods, the predicted value (red) is just the previous value.
Prediction error
Values less than zero implies that the model prediction overshoots the actual VIX level the next day.
Prediction vs. Actual Density Plot
The model bias towards higher estimation of VIX is made explicit here.
Next steps
We will integrate this model to our morning ‘Options Daily’ posts so that we get an idea of both the current state of VIX and the expected modeled behavior.
Caveats:
- The 500-day lookback is purely empirical. Maybe some other look-back period that we have not tested would have been ideal to model. We will never know.
- Only the known history can be modeled. The outputs should be used along with market determined proxies of expected volatility.
- There is always a probability distribution around a predicted value. We will publish this in our daily posts.
Appendix
VIX Model vs. Actual across various lookback periods. (pdf)
Volatility Forecasting I: GARCH Models, Rob Reider (pdf)
Equities
| MINTs | |
|---|---|
| JCI(IDN) | +8.65% |
| INMEX(MEX) | +4.12% |
| NGSEINDX(NGA) | -3.37% |
| XU030(TUR) | +6.45% |
| BRICS | |
|---|---|
| IBOV(BRA) | +8.88% |
| SHCOMP(CHN) | +4.27% |
| NIFTY(IND) | +3.00% |
| INDEXCF(RUS) | +6.24% |
| TOP40(ZAF) | +5.65% |
Commodities
| Energy | |
|---|---|
| Brent Crude Oil | +9.37% |
| Natural Gas | +4.09% |
| Heating Oil | +3.53% |
| Ethanol | -2.34% |
| RBOB Gasoline | +3.14% |
| WTI Crude Oil | +9.25% |
| Metals | |
|---|---|
| Copper | +4.76% |
| Silver 5000oz | +8.97% |
| Palladium | +5.16% |
| Platinum | +8.59% |
| Gold 100oz | +3.85% |
Currencies
| MINTs | |
|---|---|
| USDIDR(IDN) | -8.85% |
| USDMXN(MEX) | -2.69% |
| USDNGN(NGA) | +0.43% |
| USDTRY(TUR) | -3.89% |
| BRICS | |
|---|---|
| USDBRL(BRA) | -6.14% |
| USDCNY(CHN) | -0.19% |
| USDINR(IND) | -1.19% |
| USDRUB(RUS) | -6.23% |
| USDZAR(ZAF) | -4.16% |
| Agricultural | |
|---|---|
| Cocoa | -2.16% |
| Coffee (Robusta) | +3.98% |
| Cotton | +3.77% |
| Sugar #11 | +7.09% |
| Lean Hogs | +1.75% |
| Lumber | +8.36% |
| Orange Juice | +10.30% |
| Soybean Meal | +1.05% |
| White Sugar | +3.09% |
| Coffee (Arabica) | +7.78% |
| Feeder Cattle | +6.87% |
| Wheat | -2.17% |
| Cattle | +8.30% |
| Corn | -1.86% |
| Soybeans | +0.83% |
Credit Indices
| Index | Change |
|---|---|
| Markit CDX EM | +1.73% |
| Markit CDX NA HY | +2.03% |
| Markit CDX NA IG | -9.85% |
| Markit iTraxx Asia ex-Japan IG | -18.19% |
| Markit iTraxx Australia | -11.71% |
| Markit iTraxx Europe | -7.10% |
| Markit iTraxx Europe Crossover | -37.22% |
| Markit iTraxx Japan | -8.18% |
| Markit iTraxx SovX Western Europe | -2.20% |
| Markit LCDX (Loan CDS) | +0.00% |
| Markit MCDX (Municipal CDS) | -6.68% |
Not even the Fed knows when it is going to raise rates but that did not prevent the markets to party like its 1999.
Global ETFs (USD)
Nifty Heatmap
Index Returns
For a deeper dive into indices, check out our weekly Index Update.
Market Cap Decile Performance
| Decile | Mkt. Cap. | Adv/Decl |
|---|---|---|
| 1 (micro) | +4.84% | 74/57 |
| 2 | +7.45% | 83/47 |
| 3 | +4.50% | 76/54 |
| 4 | +6.77% | 74/56 |
| 5 | +5.63% | 74/56 |
| 6 | +5.99% | 71/60 |
| 7 | +4.23% | 71/59 |
| 8 | +3.29% | 74/56 |
| 9 | +1.77% | 66/64 |
| 10 (mega) | +1.89% | 65/66 |
Green is the color of passion…
Top Winners and Losers
| HINDALCO | +18.41% |
| TATAMOTORS | +19.71% |
| VEDL | +24.22% |
| MARUTI | -6.64% |
| IBULHSGFIN | -6.62% |
| RECLTD | -3.99% |
Have metals finally found a bottom?
ETF Performance
| CPSEETF | +5.23% |
| PSUBNKBEES | +4.51% |
| INFRABEES | +2.98% |
| NIFTYBEES | +2.86% |
| BANKBEES | +2.65% |
| GOLDBEES | +1.96% |
| JUNIORBEES | +1.59% |
Gold finally found some takers…
Yield Curve
Bond Indices
| Sub Index | Change in YTM | Total Return(%) |
|---|---|---|
| 0 5 | -0.02 | +0.22% |
| 5 10 | -0.04 | +0.37% |
| 10 15 | -0.04 | +0.47% |
| 15 20 | -0.03 | +0.45% |
| 20 30 | -0.04 | +0.59% |
Bonds continued their rate-cut rally. Plus, FPIs can now buy more.
Investment Theme Performance
| Momentum | +5.64% |
| ADAG stocks | +4.50% |
| High Beta | +4.48% |
| Velocity | +4.07% |
| Next Trillion | +2.64% |
| ASK Life | +2.56% |
| The RBI Restricted List | +2.51% |
| PPFAS Long Term Value | +2.35% |
| Magic Formula | +1.95% |
| Quality to Price | +1.94% |
| CNX 100 Enterprise Yield | +1.81% |
| Financial Strength Value | +1.79% |
| Low Volatility | +1.57% |
| Balance Sheet Strength | +0.67% |
| Tactical CNX 100 | +0.00% |
Momentum came back with a bang! Pretty much every investment strategy ended this week in the green…
Equity Mutual Funds
Bond Mutual Funds
Thought for the weekend
- High stock prices, just like high house prices, are harbingers of low returns.
- Investing in price-depressed residential rental property in Atlanta is like investing in EM equities today—the future expected long-term yield is much superior to their respective high-priced alternatives.
- Many parallels exist between the political/economic environment and the relative valuation of U.S. and EM equities in the periods from 1994 to 2002 and 2008 to 2015.
- Our forecast of the 10-year real return for U.S. equities is 1% compared to that of EM equities at 8%, now valued at less than half the U.S. CAPE.
Source: Investing versus Flipping
The iShares MSCI India ETF (INDA) tracks the MSCI India Total Return Index, representing about 85% of the Indian stock market. As a follow up to our earlier post on the historical volatility of the NIFTY 
, we thought we’ll compare the volatilities of INDA and SPY, the S&P 500 ETF.
10-day volatility:
50-day volatility:
As expected, a dollar denominated emerging market ETF is more volatile than the S&P. File this away in your brain attic.
Was 2014 an anomaly?
Here’s a density plot of NIFTY volatility across 10-, 20-, 30-, and 50-day periods:
And here’s how it was in 2004 (10-years ago):
For those of who argue that the introduction of the pre-open auction call in 2010 skews these results, here’s how 2011 looked like:
The unprecedented absence of a second “hump” in the volatility density plot for 2014 should give pause to investors looking for a repeat of 2014 anytime soon.
Reversion to higher volatility?
If you look at the 50-day volatility over different time-periods, you can observe how volatile volatility is:
This year’s observed volatility is closer to last-year’s than to its long-term mean. Here’s how 2015 has panned out so far:
We should expect higher volatility as the initial bull-run wears off and volatility reverts. This will have a ripple effect on pretty much every investment/trading strategy.
Appendix
Year-wise NIFTY volatility density plots (pdf)