This is from a talk I gave at r/finance 2016.

To start, I define the Overnight Effect as buying at the close and selling at the open, and the intraday as buying at the open and selling at the close.

I applied the above strategy using the 9 sector SPDRs and assuming 2bps roundtrip transaction cost.
The plot with XLF is shown above (Financial Sector SPDR).

First and foremost let’s look at the average returns (in % so 0.04 is 4 bps).

BuyandHold Overnight Intraday
XLV 0.04 0.02 -0.01
XLI 0.04 0.02 -0.02
XLY 0.05 0.03 -0.02
XLP 0.04 0.01 0
XLB 0.04 0.02 -0.03
XLK 0.04 0.03 -0.02
XLU 0.03 0.01 -0.02
XLE 0.03 0 -0.01
XLF 0.02 0.02 -0.04

 

As we can see the overnight effect beats the intraday for almost every instrument giving some indication of a  potential risk premium.

Let’s look at the Sharpe Ratios of the effect on the various instruments.

BuyandHold Overnight Intraday
XLF -0.07684 0.1331 -0.4741
XLE 0.1131 -0.1151 -0.199
XLU 0.3519 0.2838 -0.3567
XLK 0.3784 0.4227 -0.4082
XLB 0.2021 0.2716 -0.3932
XLP 0.7242 0.1746 -0.1451
XLY 0.3988 0.4399 -0.3377
XLI 0.3086 0.2863 -0.3678
XLV 0.565 0.325 -0.2494

 

Again even after adjusting for volatility risk the overnight beats the intraday and in some cases the buy and hold.

Looking at the maximum drawdowns

BuyandHold Overnight Intraday
XLF 0.8269 0.3495 0.8323
XLE 0.5736 0.352 0.6283
XLU 0.4648 0.2219 0.6411
XLK 0.5304 0.2948 0.6634
XLB 0.5982 0.3621 0.6923
XLP 0.3239 0.1727 0.571
XLY 0.5905 0.189 0.6662
XLI 0.6226 0.3445 0.6268
XLV 0.3917 0.2195 0.4564

 

Again, the overnight draws down less than the intraday and the buy and hold.

Let’s look at volatility

BuyandHold Overnight Intraday
XLF 0.02328 0.01339 0.01938
XLE 0.01951 0.01031 0.01562
XLU 0.01198 0.006205 0.01068
XLK 0.01371 0.008576 0.01154
XLB 0.01684 0.00961 0.01371
XLP 0.009034 0.006716 0.008399
XLY 0.01474 0.0091 0.01319
XLI 0.01455 0.009019 0.01187
XLV 0.01122 0.006811 0.009929

 

Logically the Overnight has the smallest volatility as the holding time is less than the buy and hold.

 

After all of that performance analysis let’s run a Kolmogorov-Smirnov test to see if the two strategies have different return distributions.

Statistic P.Value
XLF 0.1395 0
XLE 0.1001 0.0000000001089
XLU 0.07207 0.000009468
XLK 0.08355 0.0000001395
XLB 0.1162 0.0000000000000292
XLP 0.07804 0.000001143
XLY 0.1056 0.000000000007585
XLI 0.106 0.000000000006056
XLV 0.06616 0.00006519

As we can see it’s fairly clear that the two return streams come from different distributions which puts another tradeable instrument on the table.
 

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