USELESS JUMBLED POST TO WASTE TIME.
The purest, most logically sound ‘risk modifier’ is holding some cash and some shorter term, hi-quality bonds, and having a reliable income. The bonds / income provide for ‘stable income’ in flat markets and some minor protection in big down markets. The cash provides for security and the ability to buy stocks on pullbacks and rebalance.
Then you hold some min. number of stocks to try to protect against ‘being wrong.’ Some people think it’s 10 stocks, some think it’s 10,000. That’s we have markets.
But, when system wide liquidity vanishes and buyers disappear, or forced selling happens - the quality of a company becomes irrelevant in the ‘short term’ (and the short term can last decades), and will stay irrelevant until buyers flood back into the market. This can take days, months or… depending on the cause - forever.
So… market wide order book liquidity and sector and industry and stock level order book liquidity would be great, but P123 doesn’t have it, and is not likely to get it, right?
So, in many respects there is, basically nothing that can be done with a 100% long only equity investment to limit losses in ‘all market conditions’. That’s why many of us like working at the book level and would love better ‘book’ rules and functionality.
We are now in fairly ‘rare’ / unusual historic market conditions, and have been since 2008.
So, using only ‘fundamentally derived’ rules on company fundamentals vs. ‘true value’, etc - won’t help much if the market ‘panics’ and ‘stays panicked’ or market fundamentals change significantly (nuclear bomb detonations in major cities around the US), or whatever - you are losing a LOT, if not all.
And the markets have changed. Huge, historic amounts of stock trading is now being done by High frequency and computers with much shorter hold times. Initial studies show that these conditions raise future expected volatility and also present huge questions around the future liquidity of these stocks (it can vanish rapidly and unexpectedly). These are some of the major factors suggested in 2011 ‘flash crash.’
Beyond cash and bonds, really great short systems with really tight position controls and risk budget allocations and controls may be the single ‘best’ thing in theory (by that I mean the single system most likely to retain a strong negative correlation with long only stock systems in nearly all market conditions - barring total market collapse), that can be expected to hold up in severe down markets. But there are many, many, many risks in shorting. Most people do very poorly at it, losses can be unlimited and even someone like Buffet stays away. And P123 lacks the tools to do it well at the individual stock level (for example, not true ‘estimates’ of short side liquidity or bost to borrow). So, most of us are better off steering clear on P123.
Having said that, I’ve watched several hedge funds use it ‘out of sample’ for more than 10 years and do very well in using it to smooth their risk profiles.
So, what else can be done:
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Allowing the book functionality to a) have leverage and b) force ‘long short’ systems into gross market and sector and industry and beta neutrality (based on user defined inputs), is one thing to consider. But, it requires much better data in terms of truer estimates of ‘cost to borrow’ and likely short side liquidity.
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Having the ability to create better backtests on developer / user defined Industry characteristics would be helpful. The industry ranking and factors are still very limited and hard to work with. If for example, I want to find all industries with declining margins and falling sales and increasing consolidation, it’s very hard to do so - so I can’t really learn about them in a systematic way. So, this could be improved to allow better backtesting of user defined industry characteristics to see how those contribute to future industry volatility. It’s very hard often for a company to escape industry turmoil.
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Better, more flexible market/ETF rankings on custom universes might help - at a min, I’ve had feature requests for some time, allowing us to use ETF rankings on a specified custom universe in buy, sell and hedge rules. I can create rules that work for me with these conditions and the new custom series - but need to be able to use custom series in ETF ranks.
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Better shorting data to account for estimating ‘likely cost to borrow’ and ‘likely true short availability.’
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Accounting for taxes in trading systems - to better account for the ‘risk’ of not truly understanding total system costs.
The above are in no order.
While fundamentals and logic are useful tools, there are many ‘purely mathematical’ risk control approaches that have been used by top hedge funds for more than a decade that work well enough, at least to my satisfaction. That’s why the people building them make tens of millions of dollars to billions. We can knock them all we want, but they are not (all) con men - especially pre-fees - they know what they are doing.
As far as all the other notes on what could be ‘good’ and what could be ‘bad’ on individual stocks - this feels like ‘chasing your tail’ - the ‘goodness’ or ‘badness’ of any factor depends on how it performs historically and other market participants agreeing and putting their money in those same ideas.
The simplest thing is what we all agree on - buying companies a lot of other people will want to buy in the future, enough so so that the price will be driven much higher than what we buy at.
In terms of how to operationalize that, that’s what every system is trying to do. In terms of running companies, strong margins are much preferred to weak ones. I’ve run or been on many boards, and this is near universal. Margin slippage is almost always a bad sign, but you hope that you can make it up in volume. I agree, it’s less clear in terms of investments. Really strong companies have great people, great margins, hi growth and early and continuing industry domination in rapidly emerging industries - and sometimes legal or tech based monopolies. These companies are great in theory. They are still often bad in practice as public stock investments, because people tend to overvalue them and their multiples are too high. Only backtesting and history tells us this. Really crappy ‘cigar butts’ may be good - because some backtests and investors say they might be good, but Buffett and many others don’t like them at all and insist on a quality component.