Share New Research 
Intro
Superior algo returns can be thought of as being the result of two components: a great strategy regarding ‘what stocks to buy’ (the stock selection component, SEL) and a ‘clever timing’ (the in & out component, I/O) regarding when we are ‘in’ the market and hold the stocks versus when we are ‘out’ of the market and hold alternative assets such as bonds. We often focus on optimizing SEL and tend to neglect I/O; thus, for an important discussion of recent I/O tactics, see here.
Focus of this thread: Optimal SEL + I/O combinations
It is worthwhile to separately optimize SEL and I/O. However, the ultimate total return will also be determined by a certain synergy or dissonance between the two components. So, it seems that we won’t get around the arduous task of individually testing (all possible) combinations to identify optimal SEL + I/O pairs, which is the eventual focus of this thread. I reckon a preparatory step can be to dig up all the hidden SEL and I/O treasures from this forum and beyond to see what inputs are available for the combinations.
Ultimate objective
Let's get rich together, why not?
Peter Guenther
(Simplified) Demonstration of concept: SEL[“QQQ”] + I/O[“In & Out”]
In the following backtest, I combine a simple tech stock selection strategy, via buying the QQQ ETF, with the 3 Nov 2020 version of the “In & Out” strategy, which is one possible in & out-type tactic (see the In & Out thread for more tactics; link above). The backtest is from 1 Jan 2008 to 30 Oct 2020. The total return is 1,723%.
The components seem to integrate nicely: the QQQ alone (no in & out) would have yielded about 515% during the backtest period, while the In & Out strategy without a tech selection (only holding the market, SPY) would have resulted in about 1,100%.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Peter Guenther
And an additional (simplified) application, combining a yet more specific tech stock selection, the semiconductor industry, with the In & Out algo. Below are the specs for the same backtest period as above.
SEL[“SOXX”] + I/O[“In & Out”]
Total return: 1,686%
SOXX alone (i.e., always in): 559%
Implications
The In & Out combines slightly better with the QQQ selection (see above) than the SOXX selection, improving the returns from 515% to 1,723% versus from 559% to 1,686%.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Nathan Swenson
Just messing around with Flex4 QQQ version. Changing TLT and IEF to TMF and TYD pumps results up to 3539% return.
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Peter Guenther
Nathan Swenson: Absolutely, and great point! If we really trust our strategy, leveraged products, such as the 3 x leveraged bond ETFs, can substantially boost returns. In the attached backtest, I have taken it one step further and used 3 x leverage for all holdings, the 'in' side and the 'out' side. Of course, one would not put all the money on a highly leveraged strategy like this. The max drawdown is 50%+, so this can be psychologically quite distressing. It may be something for a (small) portion of one's total investment, if one feels comfortable with leveraged products.
3 x leveraged SEL[“QQQ”] + I/O[“In & Out”]
'In' holdings: TQQQ
'Out' holdings: TMF, TYD (as per Nathan's test above)
Total returns: 21,882%
Note: The In & Out is the latest 'lazy trader edition', reducing the total number of trades from above 3,000 (see in the QQQ version above) to 207 ... 207 glorious trades to get us to the 20,000%+ :)
As always, for details regarding the latest versions of I/O strategies, see our discussion here.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Nathan Swenson
Wow! Well, I wouldn't likely use TQQQ due to the decay, For bonds, my thinking is that holding period is shorter and they should be less volatile resulting in less decay. Anyway, that was my thinking. Those results are amazing!
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Matthew Wormington
Per comments made in the other "In and Out" thread, perhaps the risk-off asset selection is at least as critical as the risk-on asset selcetion to provide good performance in the future.
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Mateusz Pulka
Peter Guenther
If may I ask about your last algo.
You set symbol for long order:
self.HLD_IN = {self.STKS: 1}
but in the code when you want to send an order to market you have:
wt[self.MRKT] = 1
Is it a mistake or is it right? Cause HLD_IN parameter suggests that here you should have:
wt[self.STKS] = 1
By the way:
Great work with algorith.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Joshua Tsai
You can use TIPS instead of bonds (to slightly reduce returns, but it's widely applicable). Then again, the US gov's only option during bad economic times is to lower rates, and it's very unlikely the Fed would decrease rates as a section of the economy was faltering. I've also looked into going long volatility during market downturns, but it hasn't worked well.
I've attached the global ETF rotation strategy that was modified from the tutorial one on Quantconnect.
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Peter Guenther
gpw radar Thanks for joining this thread and well spotted! This looks like a bug from combining the In & Out with the QQQ stock selection; will post an update soon.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Joshua Tsai
Using TIPs we achieve similar returns, but the Sharpe is much worse.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Peter Guenther
Corrected: 3 x leveraged SEL[“QQQ”] + I/O[“In & Out”]
'In' holdings: TQQQ
'Out' holdings: TMF, TYD (as per Nathan's test above)
Total returns: 15,438%
Not quite the 20,000%+, still some way to go :)
Thanks to gpw radar for spotting a bug in the earlier code which I think resulted in holding the SPY and TQQQ in parallel, i.e. on margin / leveraged. In future editions, I will try and record the leverage so that similar issues pop up quickly,
At least the max drawdown also decreased from 50%+ to 40%+, still quite steep of course.
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Peter Guenther
@Joshua Tsai: Thanks for sharing these results regarding TIPs, a long volatility strategy, and the ETF rotation outline. Much appreciated and great thinking!
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Tien Duy Vo
Thanks for sharing the code. I used your last version ( Corrected: 3 x leveraged SEL[“QQQ”] + I/O[“In & Out”] ) in a small backtest from 2019-now. However, based on the orders I can not see any "In" or "Out" orders. The strategy buys TQQQ, TMF, and TYD and sells it in the same time frame. Despite all this, the performance looked good. I still wonder whether this was intentional.
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Nathan Swenson
Based on corrected version and only using TQQQ and TMF, no TYD.
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Nathan Swenson
Almost qualifies for competition with nearly 80% alpha score. Pretty tough for anyone to beat 23000% return over this period!
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Nathan Swenson
Large drawdown of course, but otherwise good numbers.
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Tien Duy Vo
Nathan Swenson Which version did you used? Did you checked the orders?
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Peter Guenther
Great series of tests there Nathan Swenson, thanks for sharing! You cracked the 20,000% again, nice :)
Tien Duy Vo: Thanks for joining the discussion! I am not 100% whether you looked at the order data below, this is from the Corrected algo version above running from 1 Jan 2008 to today. I have copied in a part of 2019. What should be happening is that the algo alternates between holding the leveraged bond ETFs (TMF and TYD) versus holding the leveraged tech stock selection (TQQQ). For example, see the first lines with the negative quantities (-70701 and -29249): it's selling the bonds on 18 Jan 2019 which it was holding before. In parallel, it's buying the TQQQ (see positive quantity 55093). Then on 24 Jun 2019, it's selling the TQQQ quantity (-55093) and it's investing the money in the bonds (see positive quantities). So, the algo sometimes holds the TQQQ and sometimes the bonds, based on the in & out indicator (see the variable self.be_in in the code). Not sure whether this answers the question?
(Sidenote: there are some "invalid" entries in there, were it doesn't seem to be able to get a price for TQQQ. However, this doesn't seem to affect the holdings.)
Time Symbol Price Quantity Type Status Value Tag 2019-01-18T16:30:00Z TMF 18.09502674 -70701 Market Filled -1279336.485 2019-01-18T16:30:00Z TYD 41.89420637 -29249 Market Filled -1225363.642 2019-01-18T16:30:00Z TQQQ 45.31716207 55093 Market Filled 2496658.41 2019-06-24T15:30:00Z TQQQ 63.66676589 -55093 Market Filled -3507593.133 2019-06-24T15:30:00Z TMF 24.64069751 71190 Market Filled 1754171.256 2019-06-24T15:30:00Z TYD 50.32595584 34820 Market Filled 1752349.782 2019-09-06T15:30:00Z TQQQ 64.62641568 65562 Market Filled 4237037.065 2019-09-06T15:30:00Z TMF 32.36969776 -71190 Market Filled -2304398.783 2019-09-06T15:30:00Z TYD 55.32687056 -34820 Market Filled -1926481.633 2019-09-11T15:30:00Z TQQQ 64.55644122 -65562 Market Filled -4232449.399 2019-09-11T15:30:00Z TMF 29.42790146 71810 Market Filled 2113217.604 2019-09-11T15:30:00Z TYD 53.32674448 39628 Market Filled 2113232.23 2019-11-01T15:30:00Z TQQQ 0 59469 Market Invalid 0 2019-11-01T15:30:00Z TMF 28.76884979 -71810 Market Filled -2065891.103 2019-11-01T15:30:00Z TYD 53.35052892 -39628 Market Filled -2114174.76 2019-11-01T15:30:00Z TQQQ 70.48427795 59269 Market Filled 4177532.67 2019-11-05T16:30:00Z TQQQ 72.61350093 -59269 Market Filled -4303729.587 2019-11-05T16:30:00Z TMF 26.83698518 80200 Market Filled 2152326.211 2019-11-05T16:30:00Z TYD 51.835342 41577 Market Filled 2155158.014 2019-12-06T16:30:00Z TQQQ 0 56469 Market Invalid 0 2019-12-06T16:30:00Z TMF 27.60375618 -80200 Market Filled -2213821.246 2019-12-06T16:30:00Z TYD 51.82537367 -41577 Market Filled -2154743.561 2019-12-06T16:30:00Z TQQQ 77.21182285 56515 Market Filled 4363626.168The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Tien Duy Vo
Peter Guenther : Thanks for the clarification. You are right. If I start the algo on 01/01/2008, I get the same result as you have posted. However, if I start the algo on 01/01/2018 then I get these results.
+2018-01-02 11:30:00TQQQBuy MarketFill: $48.15361309433875 USD
2071Filled +2018-01-02 11:30:00TMFBuy MarketFill: $20.750885826 USD
2404Filled +2018-01-02 11:30:00TYDBuy MarketFill: $42.892753618 USD
1158Filled +2018-01-05 11:30:00TMFSell MarketFill: $20.760609765 USD
-2404Filled +2018-01-05 11:30:00TYDSell MarketFill: $42.60804548 USD
-1158Filled-2018-02-02 11:30:00TQQQSell MarketFill: $55.87096473697939 USD
-2071FilledThe material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Nathan Swenson
Ok, I see that this strategy works much better with SPY derivatives rather that NQ. Just switching over to SPXL in tandem with TMF (no TYD) I get nearly 40,000% return:
https://www.quantconnect.com/terminal/processCache?request=embedded_backtest_3f192d90a6cb21b1968829b75efdb63f.htmlThe material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
HughStryker
Thanks for the update!
I'm happy that Jovad included an options straddle, as I was planning to replace VXX in the Dragon portfolio with a rolling straddle on SPY to serve as the long vol component. As I haven't used options in QC before, Jovad's algo is very useful as a starting point.
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Sairaj Patil
This is amazing Derek Melchin
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Jovad Uribe
Hi everyone,
This week Derek built a strategy he heard on episode #10 of the Better System Trader podcast. The guest, Perry Kaufman, explained the strategy idea came from George Douglas Taylor in the '50s, but Derek reversed the strategy rules. The strategy trades IWM and QQQ, and the backtest can be viewed here. It generates a 0.845 Sharpe ratio and a drawdown of 2.7% when backtested over the last several years.
Adding this strategy to the InternFund algorithm increases the diversification as we do not currently trade IWM or QQQ. Although the historical Sharpe ratio decreases slightly from 1.931 to 1.902, the compounding annual return increases from 6.845% to 7.019%, and the max drawdown decreases from 3.8% to 3.3%. With this new deployment, our backtest has a max drawdown of just $1,379. This deployment (with an increased max drawdown limit) is attached below.
Shile also built a Risk Parity strategy inspired by this article. During his research, he noticed that the drawdown was a whopping 43.4%, outlined in this backtest. To reduce this drawdown, the effects of risk parity were increased by shorting TBT, a -2x 20+ Years ETF, which gives us a positively leveraged position. Then, the dip of SPXL was bought, then sold using the Risk Management inspired by this Strategy Library Addition. See the results of the strategy here.
Previously, Ernest mentioned that our 60:40 strategy would exceed a 100% allocation ratio. We added an update to this strategy ensuring that it does not exceed this ratio. The line we updated is:
quantity = self.CalculateOrderQuantity(ticker, weight * self.SF_AR / sum(self.weight_by_ticker.values()))
Tamim Fund pointed out that our Fibonacci Option Straddle was primarily purchasing Apple. We converted the strategy to the algorithm framework and added a dynamic universe selection model to remove look-ahead bias. To further clarify the strategy's logic, if the market sentiment of a stock is down, the bid price for the call option will decrease and fall below the retracement level, causing a sell. If market sentiment is up, then the bid price may cross above the retracement, causing a buy. Many TA traders use this strategy, but their execution may take some time. The strategy attempts to enter the same position but quicker. I have attached the backtest here. As we cannot implement this in the InternFund, we will not continue with it.
As for the InternFund's performance, here is a screenshot of our latest track record.
This week our strategy lost 0.099276% of its value while SPY gained ~1.8%. Although this is a small setback, we aim to improve our algorithms alpha of 0.067.
Our backtest produces a whopping Treynor ratio of 2.298. It is no surprise that this ratio is high because the current risk-free rate (10YR Treasury Rate) is at a low 0.69%, and our beta of 0.031 is also low. However, this is one indication that our algorithm is a worthwhile investment.
Thanks for tuning in for this week's update. Constructive criticism and feedback help us build better strategies for the fund. Stay tuned for more updates!
Cheers,
Jovad Uribe
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Shile Wen
Hi Everyone!
We are planning on continuing the InternFund past summer!
This week, we are allocating 5% of our portfolio to Taylor Robertson’s post on using Leveraged ETFs. This led to a .4% decrease in drawdown as well as a 1.7% increase in the CAGR. Furthermore, our strategy is now very close to a Sharpe of 2.0, sitting at 1.98. After that, we increased the ratios of our existing strategies to take advantage of the cheap leverage offered by IB, and the new deployment algorithm is attached below.In addition, I also implemented a very simple seasonal strategy described in this article, and the results can be seen here. The high drawdown of 11.4% did not justify the returns of only 4.356%, so this strategy will not be making it into our InternFund algorithm.
Derek implemented an ETF rotation strategy that was sourced from RotationInvest. During each monthly rebalance, it calculates the trailing 3-month Sharpe ratio of SPY, EFA, and GLD. For the top-ranking ETF, it'll invest in it only if it's trading above its 150-day simple moving average. Otherwise, it allocates 100% of the portfolio to a bond ETF (TLT).
When backtested since 2015, this strategy generates a 1.218 Sharpe ratio and an annual standard deviation of 0.118. By comparison, the S&P 500 produces a 0.712 Sharpe ratio and 0.185 annual standard deviation over the same period. See the backtest results here. We will add this strategy to the deployment algorithm next week.
Furthermore, Jovad implemented the Golden Butterfly Portfolio from this article in this backtest. After a few alterations, he achieved a relatively low drawdown at 4.4% and a CAGR of 3.9%, and the updated backtest can be found here. Unfortunately, when added to our algorithm, the drawdown increases while the CAGR decreases (backtest), so it will not be making it into our live deployment.Our updated track record can be seen here:
And we are only $1 away from a new equity high!
Best Regards,
Shile Wen
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
HughStryker
Thanks for the update, Shile. What the InternFund is doing is very cool and I'm learning a lot.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Derek Melchin
Week 7: A Little Turbulence
Hi everyone,
The InternFund had a sharp increase in volatility this week. However, we are still within our allowed max drawdown of $1000. Here's an image of our live track record over the last 7 weeks.
This week, we built a few more strategies with the hope of adding more to the InternFund algorithm.
Shile worked on a trend following strategy that measured the strength of the trend using an Ordinary Least Squares (OLS) model. When the past 50 days of close data have an r2 > .7, and the (current price - the average of the absolute values of the residuals) is at least the predicted value from the OLS model, we hold SPY, else, we liquidate our position. This model only had a Sharpe of .475 with a large drawdown of 34.2%, so this strategy will not be making it into the InternFund. The backtest can be found here.
I built a strategy that was inspired by Scott Andrews (aka "The Gap Guy"). Each market open, it fits a linear regression model using overnight gaps as the independent variable and the open-to-close returns as the dependent variable. It trains the model using the previous 10 weeks of data, using only weekdays that match the current trading day. After the model is trained, it predicts the direction of the current day's intraday return given the overnight gap and places its trade. The strategy achieves a 0.488 Sharpe ratio when backtested since 2015. See the backtest for reference. Since this strategy underperforms our benchmark, we didn't integrate it into the InternFund algorithm.
I also built a strategy I sourced from InvestiQuant that takes advantage of the long-bias in traders after a bull market breakout. Whenever the SPY has a multi-month breakout during a bull market rally but then gaps down into the next open, the strategy longs from the open until 15 minutes before the close. Backtesting the strategy since 2015 generates a 0.991 Sharpe ratio, outperforming the buy-and-hold Sharpe ratio of 0.742. See the backtest results here. After integrating this strategy into the InternFund algorithm, the Sharpe ratio of the algorithm backtest increases from 2.103 to 2.161. See the attached backtest for a copy of our latest deployment (with an extended drawdown limit).
In regards to the ETF rotation strategy we published last week, there was actually a bug in it. Line 71 should have read
if data[top_symbol].Price >= sma:instead of
if data[symbol].Price >= sma:After fixing this, the strategy underperforms the SPY, so we did not add it to our live deployment.
Thanks for tuning in for our weekly update!
Best,
Derek Melchin
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Mark Reeve
Hi guys,
I am wondering is it possible to combine several strategies like this using the algorithm framework?
Is there a reason you chose to avoid using the Algorithm Framework, other than simplicity?
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Shile Wen
Hi Mark,
It would be possible to combine these strategies using the Algorithmic Framework, however, we chose to stick with the classic algorithm because it is easier to account for multiple strategies.
From my experience, an algorithm developed using the Algorithmic Framework is best suited to a single signal type, however, our algorithm is a Frankenstein’s monster of various strategies that aren’t related. If we were to divide up our algorithm strategies into separate projects, then it would totally be viable for us to use the Algorithmic Framework on the strategies individually.
Best,
Shile Wen
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Samuel Schoening
You guys have helped me a lot so I just wanted to reach out and make sure you know that the orders for VXX may not be executing as you go back in history. This is because the price was over 30,000 in 2010 due to countless splits. Same goes for UVXY. The data is not adjusted so the order will not fill. That is why I just trade with 1 or 100 billion dollars in my backtests lol. With that said, this is very compelling research and do please keep up the good work!
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Josh M
It has been a few months -- any live trading update from the intern team?
Cool project and great work!
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Zicai Feng
hey interns, your self.max_dd is a fixed amount, should change it to a ratio as a % of the portfolio value. Because as your portfolio gets bigger due to profitable trades, a fixed amount that was set during a smaller AUM will just terminate your strategy randomly. I am sure Jared would understand and let you risk a fixed % of AUM rather than a fixed dollar amount with a fluctuating n growing AUM
Keep up the good work and build those RenTech libraries!
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Derek Melchin
Hi Zicai,
Thank you. We will adjust the drawdown limit if the InternFund is launched again this summer.
Best,
Derek Melchin
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Zicai Feng
Hope it gets launched again :). Btw, similarly, your stop loss limit in your tesla example is a fixed amount. Similar reason to above, it should be a % number not a fixed $ amount as tesla price is all over the place depending on the price of dogecoins
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
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