James, AKREX looks interesting. Please email quarterly holdings as before. Should not be too difficult to get it done.
Georg,
Sorry for the wait but I have to download the files one by one (quarter by quarter) from Reuters Eikon.
It seems that some quarters are missing but I already download all the historical data for the fund.
Regards
James
Jim,
I have send you an email. Pls check it out.
Thanks.
Regards
James
Georg,
cc:Jim
What is the progress with the ARKEX upload?
Thanks.
Regards
James
Dear all,
This is the performance of the Fidelity® Select IT Services fund (FBSOX) as compared to the piggy back version of using Portfolio123 stock factor to choose the top 10 names using the QVGM ranking system. As you can see, it outperforms this actively managed fund by 4.5% and the benchmark (IWB) by 7% in the past 10 years.
Regards
James
James, you have to remove the market timing rules.
If we remove market timing, the performance is even better, 6% above the actual fund and 8% above the benchmark IWB in the past 10 years.
Dear all,
This is the performance of the Technology Select Sector SPDR® ETF (XLK) as compared to the piggy back version of using Portfolio123 stock factor to choose the top 10 names using the Millennial Money ranking system. As you can see, it outperforms the XLK ETF by 2.5% with a lower drawdown and a higher Sharpe ratio in past 10 years.
I am also attaching the csv file so you can upload it as a stock factor. (it takes me 8 hours to get it done)
Regards
James
XLKrev.csv (97 KB)
Here is the performance of the clone version of the hedge fund Tiger Global (managed by Chase Coleman) by using Portfolio123 stock factor to choose the top 5 names using the Core Value ranking system for the past 10 years. Also attached is the performance comparison between the clone version of Tiger Global vs the benchmark (IWB) from 1 month to 10 years.
Regards
James
Tiger Global vs IWB.xlsx (9.51 KB)
Thanks James for posting the csv file, I know it is very time consuming. (I will get to the other lists you sent me soon.)
And here is my 10 position XLK model. The simulation with variable slippage, no market timing, shows an AR= 24.9% over the last 10 years.
I think it is becoming abundantly obvious that the piggy-back method has great potential.
Georg,
Here are two lists of hedge funds (from whalewisdom.com) that you can consider cloning/piggy backing on.
https://whalewisdomalpha.com/managers-with-the-highest-sharpe-ratios-great-returns-low-volatility/
https://whalewisdomalpha.com/decades-top-20-hedge-funds-based-on-13f-filings/
Regards
James
So then the question becomes…is there a way to streamline this data into Portfolio123? Clearly there is a strong argument to made for the useful of fund holding data.
Jeff,
I think this addresses what you are interested in. This is a quote from Yuval in another thread:
-Jim
Yes, that would be a great functionality to have.
At the moment it is cumbersome to access, identify and regulalry update the holdings of ETFs.
Werner
Jim,
I believe Yuval is only referring to ETF universe only, not including mutual funds and hedge funds.
Regards
James
Thank you James
You all seem to be using different ranking factors to show your results. If you test a bunch of different ranking systems, one of them is bound to be a good performer. What’s the general result when you test a whole bunch of different ranking systems?
Jim,
I think we alll want to clone/piggy back on star hedge fund managers and ride on their stock picking skills through Portfolio123.
Can you make a suggestion to Marc/Yuval to include mutual funds/hedge funds (in addition to ETFs) in the upcoming system upgrade?
Regards
James
Marko,
The style of the ETF/mutual fund/hedge fund should be the main determinant in the choice of ranking systems. For instance, a tech/healthcare fund should use a growth-based ranking system while a mixed asset fund should used a balanced ranking system.
There will always be a case where some rankings system performs better than others. I think this is the nature of P123 (to test different rules/ranking system to acheive the best results.)
Regards
James
It appears that Quantum Computing for asset allocation is here.
Regards
James
Quantum Computing Inc. Releases Mukai, the Quantum Application Development Platform
The Mukai software stack enables developers to create and execute quantum-ready applications - today
LEESBURG, Va., Jan. 28, 2020 (GLOBE NEWSWIRE) – Quantum Computing Inc. (OTC:QUBT) (“QCI”), an advanced technology company developing quantum-ready applications and tools, announced today that the company has released its Mukai quantum application development platform. Mukai can be used to solve extremely complex optimization problems, which are at the heart of some of the most difficult computing challenges in industry and government. Its software stack enables developers to create and execute quantum-ready applications on classic computers, while being ready to run on quantum computers when those systems can achieve performance advantages. QCI has already demonstrated superior performance today for some applications built on Mukai and running on classic computers.
Mukai uses highly-optimized parallel code, and is currently centered on the quadratic unconstrained binary optimization (QUBO) formulation well known to quantum annealing users. QUBO is a pattern matching technique, also commonly used for machine learning applications.
The Mukai software stack includes two primary user/developer interfaces:
QCI NetworkX graph-analysis package that exploits that capability for graph problems
QCI qbsolv package that implements a state-of-the-art, high-performance optimization capability for QUBO problems
“Mukai enables developers to create and deploy practical applications that solve very hard problems today,” said Mike Booth, QCI’s Chief Technology Officer. “We believe this will bring immediate value to potential clients, while also providing a clear path to emerging quantum hardware. As Mukai provides an abstraction layer to the actual computing hardware, a client’s investment in application development today should pay off in two ways, without having to take the hardware platform into consideration.”
“In addition to developing the quantum application development platform, QCI is leveraging its expertise in finance, computing, and security to build applications on top of Mukai that we believe will deliver immediate value to potential clients,” said Steve Reinhardt, VP of Product Development at QCI. “The first of those, Quantum Asset Allocator (QAA), was recently announced. It provides small and medium-sized financial institutions the ability to do asset allocation in a way that was previously the province of large brokerage firms, mutual funds, and the largest quant funds. Using Mukai means it can run on either classic or quantum resources, depending on which delivers superior performance,” he added.
Mukai is available today running on QCI’s scalable, classical cloud infrastructure. For more information about Mukai or QAA, contact QCI at info@QuantumComputingInc.com.