Bitcoin has very little correlation with other financial instruments. It is literally outside the traditional financial world. It was the best performing asset of the last decade, and its fundamentals keep getting better, so I expect it to do well in the next.
Personally, I prefer hedging with bitcoin, over gold or bonds. Compared to gold, bitcoin is more scarce, and easier to store and transact, and impossible to counterfeit. Boomers like gold, and millennials/zoomers like bitcoin, so as the population shifts, it favors bitcoin over gold (no offense to boomers).
Having said that, I wish I had more bonds and gold, so that I could sell them for stocks and bitcoin, during this crisis.
First, I have a short model which shorts 50 stocks. Depending on the recent performance of that model itself, I allocate 0%, 10%, 20%, or 30% of my NAV to it. (I use three different moving averages. If the short port is above all of them I short 0%, and I short 10% extra for each MA itâs below. On average Iâm shorting about 15%, and the portfolio does not really make much profit but helps a lot with drawdowns.). The moving averages are very short, and I was shorting the full 30% already before the crisis hit the markets.
Second, I always hedge 50% of my long position by shorting IWM. There is no timing at all here. The idea is that no timer is perfect, so Iâm always protected. (Hedging with 50% already prevents a very large amount of drawdown, and hedging 100% is not worth the cost.)
So in summary, I was 30% short, and 70% long of which half was hedged. So my net exposure was only 35% of my NAV.
But to top it off, my long model starting picking so-called âmerger and acquisitionâ companies. These are a kind of shell companies whose purpose is to acquire some other company some time in the future. Their share price hardly changes. At first there were just 1 or 2, but after the first few -10% days my whole long port was filled with them. I did not actually buy them, so I went to cash instead. Note: I do not use a P123 model at the moment, I developed my own stuff. I did not know these kind of companies existed in my universe and they âaccidentallyâ popped up. Lucky accident.
The longs I did have at the beginning did worse than the market I think. At some moment I decided to cover all my shorts, because they did not outperform a simple short of the whole market (like IWM). Taking everything together, I did not have a loss, nor a profit.
I decided to get back in when the Russell2000 was roughly at 40% drawdown. Iâm now long for about 50% of my NAV.
FWIW. I am guessing that this will not change your holdings even a basis point but perhaps it will bring a smile to know that even a very conservative portfolio of equity ETFs and bitcoin (minimum variance portfolio) should hold bitcoin: 2.2% bitcoin.
The âTangency Portfolioâ (that maximizes the Sharpe Ratio) should hold 50% bitcoin (and 50% XLK) if historical trends in returns persist. The Shape ratio for this portfolio is 1.15 with an annual return of 36%. The first data available for price data for bitcoin through Yahoo! was 9/17/14.
Good Call. As I said above people have the option of using discretion by adjusting the expected future returns.
Iâm probably overweight bitcoin based on your 2.2% number.
I havenât played around with XLK, but do have a portfolio of 50% TQQQ (triple leverage nasdaq100) and 50% GBTC (bitcoin greyscale trust).
Looks to me this bitcoin price data goes back to before 2010. I downloaded it and looked at it, it looks like the dates are in unix time format. https://www.blockchain.com/charts/market-price
Am I the only one who believes that Bitcoin will eventually go to 0? The technology is antiquated compared to newer cryptocurrencies. Two major problems: (a) Cost of mining. Who is paying for it? That cost is coming from somewhere. That somewhere is going to eat into the value of bitcoins. (b)Speed of transactions. Itâs very slow for a currency that wants to take over the world.
My public models have all outperformed. While I designed my models with a great deal of care so that I would have confidence in future outperformance (all three of my currently live models have outperformed since inception despite being focused on value while growth was in style, and I have taken down my bond ETF model after the flash crash because of liquidity concerns) I have to admit that I didnât plan for this particular scenario.
Part of the reason for this outperformance is because they filter out energy stocks when oil prices are falling. Falling oil prices have been a reliable leading indicator of recessions these past two times.
I have shut down my port models for now and hold cash, TLT, and IEF. I will likely stay that way for a while and began wondering if my cash in a brokerâs sweep vehicle/bank will be safe there. This article, Can banks withstand the impact of covid-19? provided one perspective and some information that others might find helpful.
From the article, near the end of their analysis, is this:[quote]
It is tempting to hope that after the lockdown closures, economies that have been protected by state aid channelled through the banks will then bounce right back. If Euromoney had a dollar or a euro for every analyst report suggesting this happy outcome since mid February, we could keep ourselves in toilet roll and hand sanitizer for life. More likely though, the consensus now holds a U-shaped recovery as the very best we can hope for, with a long convalescence after the lockdowns in which some companies, especially highly leveraged ones in vulnerable cyclical sectors, will fail.
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My concern about possible bank failures may be overly pessimistic due to the over-the-top Fed support intentions. The alternative safe haven in my mind continues to be federal bond funds. I am almost entirely into a safety-first mode for now. Thoughts?
Brilliant, Yuval. I read your post on Optimisation on your site. How do you avoid optimisation with 100 or so ranking factors? With each one you added, didnât you refer to the factor returns to see if it improved them? If so, is that not optimisation?
Secondly, how did you choose weightings for all the factors?
Thank you very mich.
Rod
This model is generating a tiny bit of alpha. It picks large caps, stable dividends, and quality factors (similar to ROA, ROE, etc.)
Quality Select Investor - Large Caps - 20 Stocks https://www.portfolio123.com/app/r2g/summary?id=1584335
Regarding bitcoin: bitcoin is risky and could go to zero, but for none of the commonly stated reasons. Those reasons have been around for several boom-bust cycles, and bitcoin continues to trend up in 4-year cycles (every 4 years the supply of new bitcoin is cut in half).
Regarding cost and speed, it is the countless altcoins that focus on low cost and high speed that go to zero, not bitcoin. Turns out, if you prioritize medium of exchange over store of value, people spend your coins as soon as they get them, and the price canât appreciate.
Regarding volatility, it is the stablecoins that focus on being pegged to the dollar, that are not worth investing in, precisely because it has no volatility (you can just hold the dollar and get the same thing).
Rod, very good questions indeed.
I donât avoid optimization. For a while I tried not optimizing, but I gave up. I optimize by necessity. I just do it as robustly as I can. I have a ranking system that functions as a libraryâit has well over a hundred nodes. I try different combinations (weighting nodes by multiples of 2%) and test them over different time periods on different universes. Right now I have six different universes and six different time periods I test on. I take the ranking systems that perform best on each combination of universe and time period (36 combinations) and average the weights of them all.
It is also my opinion that there is no need to avoid optimization. Optimization is not the same as overfitting. Your methods are similar (if not the same) as many widely used methods to avoid overfitting even while optimizing, I believe.
Not only do I agree but I do some things that I think are similar (in my own way).
I wonder if it would attract any members to P123 to be able to automate the optimization of 36 ranking systems and universes with 100 nodes in some way.
How long does it take to develop and test 100 nodes? 100 nodes before you start to optimize the ranking system for 36 universes.
I understand that Marco is already working on attracting members (or at least one paying member) by working on this. So this is not a request. Not even a suggestions as, again, Marco is working on this (if I understand correctly).
Automated methods are already being developed at P123 and will be made available to some members. And eventual roll-out to everyone over time.
This may be true also. The designers that do not do this are having trouble beating their benchmarks.
Understandably, some are using the other excellent tools (and methods) available at P123. I, for example, am using books a lot now. I believe some methods of diversification can beat the SP500 with considerably less risk. Others use timing or fundamental analysis.
With my plan I can only test rankings for about the last three years. I can test screens (thankfully) back to 1999. It seems I would need to upgrade to try to replicate such work Yuval. I am grandfathered into an old price plan so that would be a big extra chunk financially:)
Hi Yuval
Can you please give me a hint as to how you optimise weighting nodes by multiples of 2%? If you have 5 nodes, and there are say 45 potential 2% levels (0 - 90%) then that ends up at 1.2 million combinations using my high school math. How do you do it?
