Author: shyam

Basis Trades using Futures

Introduction

When we discussed cash-futures basis, it was pointed out that the fair value of a futures contract is a function of the underlying price, interest rates, dividends and time to expiration. The same logic applies to the fair value of contracts across expiration dates. For example, as of close on April 30, 2015, NIFTY futures contracts had the following values: 8177.35 (April), 8244.05 (May), 8275.30 (June).

Some of our clients wanted us to check if this basis can be traded. Is it possible to profit from going long the near contract and short the far contract on a consistent basis? Before we look at profitability, lets chart the basis.

The basis

Here is how the basis between different contracts look (2000 through now):

NIFTY.futures.basis

Here is the summary statistic of the basis:

summary statistics

Here is the same data with futures expiry dates removed:

summary statistics

With the extreme values removed, we can now check if we can trade the nearest expiry contract with the farthest.

50-day Average Basis Trade Back-Test

Lets take a look at the Near vs. Farthest basis and draw a 50-dma through it:

NIFTY.futures.basis.50dma

The basis is not stable and what’s worse, it appears to be trending. Lets try our simple trading rule: go long the basis if it is above 50-dma and short if otherwise.

Here’s how the back-test works out (2005 through now):

NIFTY.futures.basis.50dma.trade.2005

Lets check the back-test on a smaller subset (2010 through now):

NIFTY.futures.basis.50dma.trade.2010

A ~20% profit in a 10 year time-frame is barely enough to cover transaction costs. Besides, it looks like the strategy hit a wall in 2010.

Conclusion

It appears that the basis trade described above is not profitable enough after considering transaction costs and taxes. Also, whatever meager profits were there seem to have been arbitraged away lately.

Is there a correlation between USDINR and Tech stocks?

tl;dr

No.

The Myth

Regular viewers of CNBC might have heard the refrain that “IT stocks went up because the rupee went down.” But it turns out that it is the classic case of the journalist/reporter/anchor going in search of a reason to explain a random market event. If there is such a correlation, then a scatter plot of USDINR returns vs. CNX IT index returns should unearth it.

Scatter Plots of Returns

Weekly:
CNX IT.USDINR.scatter.weekly

Daily:
CNX IT.USDINR.scatter.daily

As you can see, there is no obvious link between USDINR and technology stocks. But what if the effect manifests after a lag?

Cross-Correlation Plots of Returns with Lag

Weekly:
CNX IT.USDINR.ccf.weekly

Daily:
CNX IT.USDINR.ccf.daily

Conclusion

Currency moves alone cannot be your go-to explanation for fluctuations in tech stocks.

Monthly Recap: Good investing hurts

world.2015-03-31.2015-04-30

Equities

Major
DAX(DEU) -4.28%
CAC(FRA) +0.26%
UKX(GBR) +3.14%
NKY(JPN) +1.69%
SPX(USA) +1.41%
MINTs
JCI(IDN) -7.83%
INMEX(MEX) +1.82%
NGSEINDX(NGA) +9.31%
XU030(TUR) +3.34%
BRICS
IBOV(BRA) +9.54%
SHCOMP(CHN) +18.51%
NIFTY(IND) -3.65%
INDEXCF(RUS) +3.82%
TOP40(ZAF) +4.73%

Commodities

Energy
WTI Crude Oil +23.33%
Ethanol +7.84%
Heating Oil +15.86%
RBOB Gasoline +14.75%
Brent Crude Oil +19.90%
Natural Gas +4.57%
Metals
Copper +6.91%
Palladium +5.40%
Gold 100oz -0.37%
Silver 5000oz -3.01%
Platinum -0.82%

Currencies

USDEUR:-4.08% USDJPY:+0.18%

MINTs
USDIDR(IDN) -0.96%
USDMXN(MEX) +1.88%
USDNGN(NGA) -0.62%
USDTRY(TUR) +4.23%
BRICS
USDBRL(BRA) -6.36%
USDCNY(CHN) +0.06%
USDINR(IND) +1.48%
USDRUB(RUS) -10.79%
USDZAR(ZAF) -0.61%
Agricultural
Cocoa +4.00%
Coffee (Arabica) -0.94%
Coffee (Robusta) +1.94%
Cotton +4.63%
Soybean Meal -3.44%
Corn -4.25%
Lean Hogs +22.47%
Lumber -8.52%
Orange Juice -8.61%
Soybeans -0.44%
Sugar #11 +7.58%
Feeder Cattle -2.02%
Wheat -8.19%
Cattle -7.48%
White Sugar +4.89%

Credit Indices

Index Change
Markit CDX EM +3.58%
Markit CDX NA HY -0.55%
Markit CDX NA IG -2.44%
Markit iTraxx Asia ex-Japan IG +7.09%
Markit iTraxx Australia +6.74%
Markit iTraxx Europe +9.57%
Markit iTraxx Europe Crossover +1.39%
Markit iTraxx Japan -3.23%
Markit iTraxx SovX Western Europe +2.17%
Markit LCDX (Loan CDS) -0.11%
Markit MCDX (Municipal CDS) +1.70%
Both the NIFTY and the rupee put in performances that they sooner forget. Stretched evaluations met a tepid earnings season and retroactive tax demands on FIIs. May will see more firms coming out earnings and we expect the markets to remain choppy.

Nifty Heatmap

CNX NIFTY.2015-03-31.2015-04-30

Index Returns

For a deeper dive into indices, check out our weekly Index Update.
index performance.2015-03-31.2015-04-30

Market Cap Decile Performance

Decile Mkt. Cap. Adv/Decl
1 (micro) +3.97% 82/50
2 +10.85% 82/49
3 +7.66% 78/53
4 +6.24% 68/64
5 +4.32% 72/59
6 +2.89% 68/63
7 +2.84% 71/61
8 -2.06% 66/65
9 -3.55% 64/67
10 (mega) -2.64% 58/74
This doesn’t make any sense…

Top Winners and Losers

UPL +10.97%
GLENMARK +13.25%
TATASTEEL +13.76%
APOLLOHOSP -16.95%
WIPRO -14.35%
SRTRANSFIN -12.97%
A smorgasbord of performance…

ETF Performance

GOLDBEES +3.56%
PSUBNKBEES +2.07%
BANKBEES +1.54%
JUNIORBEES -0.62%
CPSEETF -2.15%
NIFTYBEES -3.29%
INFRABEES -5.49%
Infrastructure got whipped…

Yield Curve

yield Curve.2015-03-31.2015-04-30

Bond Indices

Sub Index Change in YTM Total Return(%)
GSEC TB -0.09 +0.66%
GSEC SUB 1-3 -0.60 +0.25%
GSEC SUB 3-8 +0.04 +0.20%
GSEC SUB 8 +0.16 -0.07%
Listless…

Investment Theme Performance

Equity Mutual Funds

Bond Mutual Funds

Thought to sum up the month

Good investing hurts. Investors pay a high price for comfort and get paid a high price for doing what few others will. That will always be the case.

Source: This Was Never Easy

Weekly Recap: May Day

world.2015-04-24.2015-05-01

Equities

Major
DAX(DEU) -3.02%
CAC(FRA) -2.98%
UKX(GBR) -1.20%
NKY(JPN) -2.44%
SPX(USA) -0.49%
MINTs
JCI(IDN) -6.42%
INMEX(MEX) -1.97%
NGSEINDX(NGA) +0.64%
XU030(TUR) -1.90%
BRICS
IBOV(BRA) -0.74%
SHCOMP(CHN) +1.09%
NIFTY(IND) -1.49%
INDEXCF(RUS) +0.34%
TOP40(ZAF) -1.57%

Commodities

Energy
Heating Oil +3.51%
Ethanol -0.06%
Brent Crude Oil +2.61%
Natural Gas +9.66%
RBOB Gasoline +2.36%
WTI Crude Oil +3.93%
Metals
Gold 100oz +0.07%
Palladium +0.62%
Copper +6.91%
Platinum +0.85%
Silver 5000oz +1.90%

Currencies

USDEUR:-2.96% USDJPY:+1.06%

MINTs
USDIDR(IDN) +0.20%
USDMXN(MEX) +1.01%
USDNGN(NGA) -0.26%
USDTRY(TUR) -0.40%
BRICS
USDBRL(BRA) +1.68%
USDCNY(CHN) +0.14%
USDINR(IND) -0.22%
USDRUB(RUS) +1.76%
USDZAR(ZAF) -0.36%
Agricultural
Cocoa +0.61%
Coffee (Arabica) -7.30%
Coffee (Robusta) -3.84%
Cotton +1.74%
Cattle -7.32%
Lean Hogs +6.12%
Lumber -1.59%
Orange Juice -0.83%
Soybeans -0.05%
Sugar #11 -1.75%
Feeder Cattle -0.68%
Wheat -3.04%
White Sugar -0.35%
Corn -1.17%
Soybean Meal +0.13%

Credit Indices

Index Change
Markit CDX EM -0.13%
Markit CDX NA HY -0.15%
Markit CDX NA IG +1.38%
Markit iTraxx Asia ex-Japan IG -0.23%
Markit iTraxx Australia +0.03%
Markit iTraxx Europe +0.76%
Markit iTraxx Europe Crossover +7.53%
Markit iTraxx Japan +0.72%
Markit iTraxx SovX Western Europe -0.02%
Markit LCDX (Loan CDS) +0.00%
Markit MCDX (Municipal CDS) -0.41%
Are world markets prepping for “sell in May and go away?”

Nifty Heatmap

CNX NIFTY.2015-04-24.2015-04-30

Index Returns

For a deeper dive into indices, check out our weekly Index Update.
index performance.2015-04-24.2015-04-30

Sector Performance

sector performance.2015-04-24.2015-04-30

Advance Decline

advance.decline.line2.2015-04-24.2015-04-30

Market Cap Decile Performance

Decile Mkt. Cap. Adv/Decl
1 -8.22% 64/68
2 -5.11% 56/75
3 -5.87% 50/81
4 -3.93% 57/74
5 -4.40% 62/69
6 -3.90% 61/70
7 -3.51% 56/75
8 -4.70% 64/67
9 -4.26% 59/72
10 -1.21% 70/62
An ocean of red, nary a green in sight…

Top Winners and Losers

MOTHERSUMI +7.93%
SIEMENS +10.80%
UPL +12.87%
UBL -12.70%
APOLLOHOSP -12.21%
ITC -7.36%
What’s next for ITC?

ETF Performance

BANKBEES +2.20%
GOLDBEES +1.00%
JUNIORBEES -0.71%
NIFTYBEES -1.19%
PSUBNKBEES -1.47%
CPSEETF -2.27%
INFRABEES -3.91%
Have banks found a bottom?

Yield Curve

yield Curve.2015-04-24.2015-04-30

Bond Indices

Sub Index Change in YTM Total Return(%)
GSEC TB -0.18 +0.18%
GSEC SUB 1-3 -0.04 +0.34%
GSEC SUB 3-8 -0.00 +0.26%
GSEC SUB 8 +0.02 +0.12%
Rates went down a smidgen…

Investment Theme Performance

Magic Formula turned into Tragic Formula thanks to the cliff dive in KPIT stock. But the specks of green may be indicating that the current correction is on its last legs…

Equity Mutual Funds

Bond Mutual Funds

Thought for the weekend

The issue of inequality has never been about the fairness of the results, but should focus on the equality of opportunity.

The neo-classical solutions that the markets will take care of everything risks the kind of social instability seen in places like Ferguson, Baltimore, or worse.

You can use comparative advantages, such as low labor costs and convenient geographic proximity to markets, to spur development. But the Porter-Jacobs framework doesn’t explain why India and China succeeded and Kenya and Egypt didn’t.

You are left with culture: both the Jews and the Romani (Gypsies) have historically been outcasts in Europe. How did one group succeed and acquire power (e.g., the Rothchilds) and the other remains shunned throughout the region?

Source: May Day thoughts on inequality (and development)

Gaps and the Pre-Open Call Auction

tl;dr

You should not treat opening prices before and after October 18, 2010 the same.

Call Auction in the pre-open session

If you don’t know how the pre-open session works, here’s a good explainer from BSE:

When you run back-tests that use the opening price, this change will most likely trip you up.

Before and after

Nifty opening gaps since 2000:

CNX NIFTY.gap

Notice the shift in the median before and after the auction was introduced (all figures in %):
gap summary

Before:
CNX NIFTY.hist.2

CNX NIFTY.hist.3

After:

CNX NIFTY.hist.4

Conclusion

One way to make the opening prices comparable is to take tick-level data and compute a synthetic opening price yourself, just like how the closing price in computed. And you can use this synthetic open across your entire data set.

Otherwise, you will have to take you back-test results with a healthy dose of skepticism and make sure that there is enough room in your analysis to account for this.