ETF Pairs Trading
(142447715)
Subscription terms. Subscriptions to this system cost $60.00 per month.
C2Star
C2Star is a certification program for trading strategies. In order to become "C2Star Certified," a strategy must apply tight risk controls, and must exhibit excellent performance characteristics, including low drawdowns.
You can read more about C2Star certification requirements here.
Note that: all trading strategies are risky, and C2Star Certification does not imply that a strategy is low risk.
Pairs Trading / Relative Value
Seeks to exploit differences in the price or rate of the same or similar securities. The relative value fund trades on gaps, rather than the price of a specific security aloneRate of Return Calculations
Overview
To comply with NFA regulations, we display Cumulative Rate of Return for strategies with a track record of less than one year. For strategies with longer track records, we display Annualized (Compounded) Rate of Return.
How Cumulative Rate of Return is calculated
= (Ending_equity  Starting_equity) / Starting_equity
Remember that, following NFA requirements, strategy subscription costs and estimated commissions are included in markedtomarket equity calculations.
All results are hypothetical.
Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec  YTD  

2022  +1.5%  (6%)  (4.6%)  
2023  (0.5%)  (1.4%)  (0.5%)  (2.4%) 
Model Account Details
A trading strategy on Collective2. Follow it in your broker account, or use a free simulated trading account.
Advanced users may want to use this information to adjust their AutoTrade scaling, or merely to understand the magnitudes of the nearby chart.
Started  $45,000  
Buy Power  ($496)  
Cash  $1  
Equity  $1  
Cumulative $  ($2,375)  
Includes dividends and cashsettled expirations:  ($183)  Itemized 
Total System Equity  $42,624  
Margined  $1  
Open P/L  ($110)  
Data has been delayed by 168 hours for nonsubscribers 
System developer has asked us to delay this information by 168 hours.
Trading Record
Statistics

Strategy began11/4/2022

Suggested Minimum Cap$5,000

Strategy Age (days)138.15

Age138 days ago

What it tradesStocks

# Trades62

# Profitable26

% Profitable41.90%

Avg trade duration20.9 days

Max peaktovalley drawdown9.81%

drawdown periodNov 16, 2022  Feb 20, 2023

Cumul. Return6.9%

Avg win$490.69

Avg loss$415.28
 Model Account Values (Raw)

Cash$64,810

Margin Used$64,620

Buying Power($496)
 Ratios

W:L ratio0.87:1

Sharpe Ratio2.13

Sortino Ratio2.6

Calmar Ratio1.745
 CORRELATION STATISTICS

Return of Strat Pcnt  Return of SP500 Pcnt (cumu)11.31%

Correlation to SP5000.05860

Return Percent SP500 (cumu) during strategy life4.41%
 Return Statistics

Ann Return (w trading costs)16.8%
 Slump

Current Slump as Pcnt Equity9.20%
 Instruments

Percent Trades Futuresn/a
 Slump

Current Slump, time of slump as pcnt of strategy life0.91%
 Instruments

Short Options  Percent Covered100.00%
 Return Statistics

Return Pcnt (Compound or Annual, agebased, NFA compliant)0.069%
 Instruments

Percent Trades Optionsn/a

Percent Trades Stocks1.00%

Percent Trades Forexn/a
 Return Statistics

Ann Return (Compnd, No Fees)13.3%
 Risk of Ruin (MonteCarlo)

Chance of 10% account loss17.00%

Chance of 20% account lossn/a

Chance of 30% account lossn/a

Chance of 40% account lossn/a

Chance of 60% account loss (Monte Carlo)n/a

Chance of 70% account loss (Monte Carlo)n/a

Chance of 80% account loss (Monte Carlo)n/a

Chance of 90% account loss (Monte Carlo)n/a
 Automation

Percentage Signals Automatedn/a
 Risk of Ruin (MonteCarlo)

Chance of 50% account lossn/a
 Popularity

Popularity (Today)376

Popularity (Last 6 weeks)623
 Trading Style

Any stock shorts? 0/11
 Popularity

C2 Score280

Popularity (7 days, Percentile 1000 scale)0
 TradesOwnSystem Certification

Trades Own System?

TOS percentn/a
 Win / Loss

Avg Loss$415

Avg Win$491

Sum Trade PL (losers)$14,950.000
 Age

Num Months filled monthly returns table5
 Win / Loss

Sum Trade PL (winners)$12,758.000

# Winners26

Num Months Winners1
 Dividends

Dividends Received in Model Acct184
 Win / Loss

# Losers36

% Winners41.9%
 Frequency

Avg Position Time (mins)30014.70

Avg Position Time (hrs)500.25

Avg Trade Length20.8 days

Last Trade Ago9
 Leverage

Daily leverage (average)1.92

Daily leverage (max)2.09
 Regression

Alpha0.05

Beta0.02

Treynor Index2.36
 Maximum Adverse Excursion (MAE)

MAE:Equity, average, all trades0.01

MAE:PL  worst single value for strategy

MAE:PL (avg, winning trades)

MAE:PL (avg, losing trades)

MAE:PL (avg, all trades)3.96

MAE:Equity, average, winning trades0.00

MAE:Equity, average, losing trades0.01

Avg(MAE) / Avg(PL)  All trades11.833

MAE:Equity, losing trades only, 95th Percentile Value for this strat

MAE:Equity, win trades only, 95th Percentile Value for this strat

MAE:Equity, 95th Percentile Value for this strat0.01

Avg(MAE) / Avg(PL)  Winning trades0.312

Avg(MAE) / Avg(PL)  Losing trades1.598

HoldandHope Ratio0.080
 Analysis based on MONTHLY values, full history
 RATIO STATISTICS
 Ratio statistics of excess return rates
 Statistics related to Sharpe ratio

Mean0.17508

SD0.08197

Sharpe ratio (Glass type estimate)2.13576

Sharpe ratio (Hedges UMVUE)1.54544

df3.00000

t1.23308

p0.84732

Lowerbound of 95% confidence interval for Sharpe Ratio5.76869

Upperbound of 95% confidence interval for Sharpe Ratio1.76110

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation5.15840

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.06752
 Statistics related to Sortino ratio

Sortino ratio2.03305

Upside Potential Ratio0.26856

Upside part of mean0.02313

Downside part of mean0.19820

Upside SD0.01335

Downside SD0.08612

N nonnegative terms1.00000

N negative terms3.00000
 Statistics related to linear regression on benchmark

N of observations4.00000

Mean of predictor0.15421

Mean of criterion0.17508

SD of predictor0.19514

SD of criterion0.08197

Covariance0.00694

r0.43404

b (slope, estimate of beta)0.18233

a (intercept, estimate of alpha)0.20319

Mean Square Error0.00818

DF error2.00000

t(b)0.68134

p(b)0.28298

t(a)1.25425

p(a)0.83176

Lowerbound of 95% confidence interval for beta0.96907

Upperbound of 95% confidence interval for beta1.33373

Lowerbound of 95% confidence interval for alpha0.90024

Upperbound of 95% confidence interval for alpha0.49385

Treynor index (mean / b)0.96023

Jensen alpha (a)0.20319
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.17856

SD0.08358

Sharpe ratio (Glass type estimate)2.13651

Sharpe ratio (Hedges UMVUE)1.54598

df3.00000

t1.23351

p0.84739

Lowerbound of 95% confidence interval for Sharpe Ratio5.76957

Upperbound of 95% confidence interval for Sharpe Ratio1.76063

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation5.15909

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation2.06713
 Statistics related to Sortino ratio

Sortino ratio2.03230

Upside Potential Ratio0.26161

Upside part of mean0.02299

Downside part of mean0.20155

Upside SD0.01327

Downside SD0.08786

N nonnegative terms1.00000

N negative terms3.00000
 Statistics related to linear regression on benchmark

N of observations4.00000

Mean of predictor0.13907

Mean of criterion0.17856

SD of predictor0.19159

SD of criterion0.08358

Covariance0.00709

r0.44282

b (slope, estimate of beta)0.19316

a (intercept, estimate of alpha)0.20543

Mean Square Error0.00842

DF error2.00000

t(b)0.69845

p(b)0.27859

t(a)1.25604

p(a)0.83203

Lowerbound of 95% confidence interval for beta0.99678

Upperbound of 95% confidence interval for beta1.38311

Lowerbound of 95% confidence interval for alpha0.90912

Upperbound of 95% confidence interval for alpha0.49827

Treynor index (mean / b)0.92441

Jensen alpha (a)0.20543
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.05310

Expected Shortfall on VaR0.06256
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.04630

Expected Shortfall on VaR0.06824
 ORDER STATISTICS
 Quartiles of return rates

Number of observations4.00000

Minimum0.95512

Quartile 10.97916

Median0.99290

Quartile 31.00148

Maximum1.01004

Mean of quarter 10.95512

Mean of quarter 20.98717

Mean of quarter 30.99863

Mean of quarter 41.01004

Inter Quartile Range0.02232

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high0.00000

Percentage of outliers high0.00000

Mean of outliers high0.00000
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.00000

VaR(95%) (moments method)0.00000

Expected Shortfall (moments method)0.00000

Extreme Value Index (regression method)0.00000

VaR(95%) (regression method)0.00000

Expected Shortfall (regression method)0.00000
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations1.00000

Minimum0.05843

Quartile 10.05843

Median0.05843

Quartile 30.05843

Maximum0.05843

Mean of quarter 10.00000

Mean of quarter 20.00000

Mean of quarter 30.00000

Mean of quarter 40.00000

Inter Quartile Range0.00000

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high0.00000

Percentage of outliers high0.00000

Mean of outliers high0.00000
 Risk estimates based on draw downs (based on Extreme Value T

Extreme Value Index (moments method)0.00000

VaR(95%) (moments method)0.00000

Expected Shortfall (moments method)0.00000

Extreme Value Index (regression method)0.00000

VaR(95%) (regression method)0.00000

Expected Shortfall (regression method)0.00000
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.14694

Compounded annual return (geometric extrapolation)0.13986

Calmar ratio (compounded annual return / max draw down)2.39359

Compounded annual return / average of 25% largest draw downs0.00000

Compounded annual return / Expected Shortfall lognormal2.23542

0.00000

0.00000
 Analysis based on DAILY values, full history
 RATIO STATISTICS
 Ratio statistics of excess return rates
 Statistics related to Sharpe ratio

Mean0.16010

SD0.07228

Sharpe ratio (Glass type estimate)2.21497

Sharpe ratio (Hedges UMVUE)2.19780

df97.00000

t1.35466

p0.91066

Lowerbound of 95% confidence interval for Sharpe Ratio5.42911

Upperbound of 95% confidence interval for Sharpe Ratio1.01035

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation5.41737

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation1.02178
 Statistics related to Sortino ratio

Sortino ratio2.76581

Upside Potential Ratio6.32102

Upside part of mean0.36590

Downside part of mean0.52600

Upside SD0.04380

Downside SD0.05789

N nonnegative terms44.00000

N negative terms54.00000
 Statistics related to linear regression on benchmark

N of observations98.00000

Mean of predictor0.10685

Mean of criterion0.16010

SD of predictor0.19804

SD of criterion0.07228

Covariance0.00150

r0.10470

b (slope, estimate of beta)0.03821

a (intercept, estimate of alpha)0.15600

Mean Square Error0.00522

DF error96.00000

t(b)1.03151

p(b)0.84755

t(a)1.31981

p(a)0.90498

Lowerbound of 95% confidence interval for beta0.11175

Upperbound of 95% confidence interval for beta0.03532

Lowerbound of 95% confidence interval for alpha0.39067

Upperbound of 95% confidence interval for alpha0.07863

Treynor index (mean / b)4.18973

Jensen alpha (a)0.15602
 Ratio statistics of excess log return rates
 Statistics related to Sharpe ratio

Mean0.16272

SD0.07237

Sharpe ratio (Glass type estimate)2.24860

Sharpe ratio (Hedges UMVUE)2.23117

df97.00000

t1.37523

p0.91388

Lowerbound of 95% confidence interval for Sharpe Ratio5.46320

Upperbound of 95% confidence interval for Sharpe Ratio0.97735

Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation5.45120

Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation0.98886
 Statistics related to Sortino ratio

Sortino ratio2.79919

Upside Potential Ratio6.27713

Upside part of mean0.36490

Downside part of mean0.52763

Upside SD0.04365

Downside SD0.05813

N nonnegative terms44.00000

N negative terms54.00000
 Statistics related to linear regression on benchmark

N of observations98.00000

Mean of predictor0.08756

Mean of criterion0.16272

SD of predictor0.19692

SD of criterion0.07237

Covariance0.00153

r0.10718

b (slope, estimate of beta)0.03939

a (intercept, estimate of alpha)0.15927

Mean Square Error0.00523

DF error96.00000

t(b)1.05624

p(b)0.85325

t(a)1.34637

p(a)0.90932

Lowerbound of 95% confidence interval for beta0.11341

Upperbound of 95% confidence interval for beta0.03463

Lowerbound of 95% confidence interval for alpha0.39410

Upperbound of 95% confidence interval for alpha0.07555

Treynor index (mean / b)4.13122

Jensen alpha (a)0.15927
 Risk estimates for a oneperiod unit investment (parametric)
 assuming log normal returns and losses (using central moments from Sharpe statistics)

VaR(95%)0.00794

Expected Shortfall on VaR0.00979
 assuming Pareto losses only (using partial moments from Sortino statistics)

VaR(95%)0.00495

Expected Shortfall on VaR0.00879
 ORDER STATISTICS
 Quartiles of return rates

Number of observations98.00000

Minimum0.98486

Quartile 10.99705

Median0.99953

Quartile 31.00216

Maximum1.01093

Mean of quarter 10.99391

Mean of quarter 20.99842

Mean of quarter 31.00080

Mean of quarter 41.00486

Inter Quartile Range0.00511

Number outliers low1.00000

Percentage of outliers low0.01020

Mean of outliers low0.98486

Number of outliers high1.00000

Percentage of outliers high0.01020

Mean of outliers high1.01093
 Risk estimates for a oneperiod unit investment (based on Ex

Extreme Value Index (moments method)0.08294

VaR(95%) (moments method)0.00621

Expected Shortfall (moments method)0.00856

Extreme Value Index (regression method)0.07704

VaR(95%) (regression method)0.00631

Expected Shortfall (regression method)0.00867
 DRAW DOWN STATISTICS
 Quartiles of draw downs

Number of observations4.00000

Minimum0.00340

Quartile 10.00347

Median0.00359

Quartile 30.02084

Maximum0.07226

Mean of quarter 10.00340

Mean of quarter 20.00349

Mean of quarter 30.00370

Mean of quarter 40.07226

Inter Quartile Range0.01737

Number outliers low0.00000

Percentage of outliers low0.00000

Mean of outliers low0.00000

Number of outliers high1.00000

Percentage of outliers high0.25000

Mean of outliers high0.07226
 Risk estimates based on draw downs (based on Extreme Value T

Extreme Value Index (moments method)0.00000

VaR(95%) (moments method)0.00000

Expected Shortfall (moments method)0.00000

Extreme Value Index (regression method)0.00000

VaR(95%) (regression method)0.00000

Expected Shortfall (regression method)0.00000
 COMBINED STATISTICS

Annualized return (arithmetic extrapolation)0.13147

Compounded annual return (geometric extrapolation)0.12612

Calmar ratio (compounded annual return / max draw down)1.74541

Compounded annual return / average of 25% largest draw downs1.74541

Compounded annual return / Expected Shortfall lognormal12.87840
 Analysis based on DAILY values, last 6 months only
 RATIO STATISTICS
 Ratio statistics of excess log return rates
 Statistics related to linear regression on benchmark

VAR (95 Confidence Intrvl)0.00800
 DRAW DOWN STATISTICS
 Risk estimates based on draw downs (based on Extreme Value T
 assuming Pareto losses only (using partial moments from Sortino statistics)

Last 4 Months  Pcnt Negative1.00%

Strat Max DD how much worse than SP500 max DD during strat life?326465000

Max Equity Drawdown (num days)96
Strategy Description
Markets have changed a lot since peaking in early 2022, volatility has increased, there have been large moves down in former favourite risk assets. Record inflation, higher interest rates, disrupted supply chains, heightened geopolitical tensions. The environment has changed. No longer are longonly strategies delivering great returns as they have done for the past 14 years. This new market environment now favors a long/short equity strategy, which favors a "kangaroo market", one that hops, bounces, spikes, turns, go sideways, down, up.. the increased volatility allows a market neutral strategy to generate good riskadjusted returns whilst longonly strategies will continue to struggle in this new environment.
However with tail risk still very much present in single name stocks, it's still too risky to hold mean reversion positions in them. With ETFs, we can remove that idiosyncratic risk and thus reduce portfolio volatility.
With our strategy here on C2, we trade liquid ETF pairs, for example SPY (S&P 500 Index) vs MDY (Midcap Index). Using our own unique proprietary tools & indicators we keep updated a watchlist of cointegrated ETF pairs that have a history of mean reverting price behaviour. Our tools also tell us the best spots and times to enter and exit pairs, we have backtested every ETF pair that we trade to prove profitability before entering a trade.
Each day in the last hour before market close we look for potential entry signals and exit signals on our open pairs. We aim to make all trades between 2:45  3:45PM EST (New York Time). We do this because during the opening session prices are very volatilite and spreads are wide making it hard to get stable fills for all of our followers, also during the midday session whilst prices are stable, the liquidity on the bid/ask is often shallow leading to slippage, whereas in the closing session it's the right mix of liquidity, tight spreads and stable prices to get good fills that can be replicated.
We will only ever have a maximum of 5 pair trades open at any given time, and we size our positions using 20% of current account value for each leg of a pair trade, for e.g.. on a $10,000 account we would buy $2,000 of SPY and short sell $2,000 of MDY for a pairs trade. So maximum total leverage will never exceed 200% of account value (5 pair trades x 40% in each pair trade). So this works well in a margin account, however it can also be used in a nonmargin account using 10% of account value in each leg of a pair trade so total leverage never exceeds 100%.
This strategy aims to deliver safe and robust returns that are uncorrelated to the market, as most of us already have longonly equity exposure in our personal and retirement accounts, this strategy compliments our overall portfolio very well to reduce overall volatility and drawdowns.
By subscribing to our ETF pairs trading strategy here on C2 you too can get our real time entry and exit signals to follow along or alternatively you can opt to have our entry and exit signals autotraded inside your brokerage account, with total control using your own specified position sizing that you're comfortable with.
We keep our followers updated with a monthly performance report that we send out at the end of every month, offering commentary on the market and how our pair trades are performing. When you join, you're becoming apart of a community of ETF pair traders that are committed to achieving strong riskadjusted returns that are uncorrelated to the market.
Due to liquidity requirements in getting good trade fills for all of our followers, we have a hard limit set here in the C2 platform of 150 maximum subscribers, after we reach this number it will not accept any new subscribers to our strategy.
If you have any questions or feedback feel free to send me a message, we're looking for longterm partners with our ETF pairs trading strategy as we think the market environment will favor this approach for some time yet.
Regards,
Jared.
Most values on this page (including the Strategy Equity Chart, above) have been adjusted by estimated trading commissions and subscription costs.
Some advanced users find it useful to see "raw" Model Account values. These numbers do not include any commissions, fees, subscription costs, or dividend actions.
Strategy developers can "archive" strategies at any time. This means the strategy Model Account is reset to its initial level and the trade list cleared. However, all archived track records are permanently preserved for evaluation by potential subscribers.
About the results you see on this Web site
Past results are not necessarily indicative of future results.
These results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have underor overcompensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to these being shown.
In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading. For example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program, which cannot be fully accounted for in the preparation of hypothetical performance results and all of which can adversely affect actual trading results.
Material assumptions and methods used when calculating results
The following are material assumptions used when calculating any hypothetical monthly results that appear on our web site.
 Profits are reinvested. We assume profits (when there are profits) are reinvested in the trading strategy.
 Starting investment size. For any trading strategy on our site, hypothetical results are based on the assumption that you invested the starting amount shown on the strategy's performance chart. In some cases, nominal dollar amounts on the equity chart have been rescaled downward to make current goforward trading sizes more manageable. In these cases, it may not have been possible to trade the strategy historically at the equity levels shown on the chart, and a higher minimum capital was required in the past.
 All fees are included. When calculating cumulative returns, we try to estimate and include all the fees a typical trader incurs when AutoTrading using AutoTrade technology. This includes the subscription cost of the strategy, plus any pertrade AutoTrade fees, plus estimated broker commissions if any.
 "Max Drawdown" Calculation Method. We calculate the Max Drawdown statistic as follows. Our computer software looks at the equity chart of the system in question and finds the largest percentage amount that the equity chart ever declines from a local "peak" to a subsequent point in time (thus this is formally called "Maximum Peak to Valley Drawdown.") While this is useful information when evaluating trading systems, you should keep in mind that past performance does not guarantee future results. Therefore, future drawdowns may be larger than the historical maximum drawdowns you see here.
Trading is risky
There is a substantial risk of loss in futures and forex trading. Online trading of stocks and options is extremely risky. Assume you will lose money. Don't trade with money you cannot afford to lose.
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Suggested Minimum Capital
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