Without giving away too much I had some sucess with the following latley:
FRank(" ",#all,#DESC, #ExclNA) > xx (Buy Rule → hint FCF is interesting!)
Rank > x (Buy Rule)
Formula weighted portfolio rebalance (I played around with the old data vendor a lot, with not much success, with the new
data vendor (which covers more stocks), very big success!
Dynamic universe (through buy and sell rules based on volumne of the stocks)
Multi Factor Ranking (As stated before, thanks Yuval for the heads up!!!) → value, momentum (earnings, price), quality, industry momentum (price)
Very interesting is, that the above works pretty well with ports from 10-20 Stocks (the higher the more cash the port will carry bc
of the buy rule Rank > x).
But the above also works with very old ranking systems like from Olikea.
I digged in deep fundamentally on what stocks my new modells pick, and the quality is much better then before (subjective I know!).
I’ve read a lot of older posts that mention the “dynamic universe” and I assume its a custom universe that changes throughout a backtest.
But how do you set one up?
Hi Andreas, I don’t know if this will work going forward, but I’ve stopped buying biopharma. I’d noticed some bad blowups in some of those stocks, and I think it’s because my models like fcf, but biopharma that looks attractive with alot of fcf might often be milking a cash cow and might be approaching the end of patent protection.
“dynamic” universe in terms of two volumne buy rules and one volumne sell rulle
e.g. you take for exampmple the volume of the last 50 days and set buy rules (above 100k below 500k) in the sell rule for example belwo 1000k
I am agnostic to industries (besides financials, them I exclude and I exclude stocks from china). Also FCF needs to be generated from the
profit loss statement (and then feed the balance sheet), e.g. if there is no money the company makes, there is no free cash flow (exceptions are
selling assets that move from the balance sheet to profit loss, but that itself can be a signal for restructuring which can (combined with
other factors) be a positive.
Have not checked, but I think my main models do not pick biotech stocks.
Got another strategy I am working on which is mostly discreationary in the nano cap space, that captures stock promotions, the screen
of p123 scans for stocks that are prone for promotions (mostly junk) and those stocks run (about 60-120 times a year depending on the screen that results in a port)
over a 100% in one day (and you have to sell then intraday). But I am still reasearching, have to do the backtest by hand and will take a year. (there will be another tread on this) Had some converstations with traders that take the other side of the trade after the spike shorting those promotion runner
stocks (wich is an even better strat, but not possible if you can not lend those stocks, you need to be in a prop shop for this that provides
those stocks to be lended)…
The underlying portfolio itself even has an upward trift (about 10% ann.), so its you treat those stocks like option (that might run) and they
itself have generally an upwarad thrift (with high vola though).
The strat itself needs screen time (stocks run mostly after or before trading hours and you have to sell fast when the run occours, bc.
after the run they decay usually fast (thats how the short seller make money on the other side)… The strat itself has it seasons, e.g.
the big money is made in 6-12 weeks of a year. Will keep you posted…
If I got more results, will share here…
Best Regards
Andreas
P.S. Any stuff to share with the new Data and new functions you all have been successfull lately?
Andreas, as it turns out I’m working on something similar, though not specifically for “promotions”, but after reading your post there may be some of this happening for the stocks in my strategy.
Any further updates on your side?
I’m finding very cheap stocks, especially those with recent sell-offs. Most of the price moves are intraday, sometimes in the order of 100-200%. As far as I know, the intraday prices are not available with P123, so this is a difficult strategy to test, unless these stocks keep the gains inter-day.
Just this week sold NVIV, 180% in one morning, but had to watch it very closely. That said, downwards volatility as well, some of the stocks are slow bleeds.
From what I could find, this is where a given stock is promoted to potential buyers, to generate interest, sometimes regardless of underlying fundamentals, i.e. “this is the next big thing!”
Occasionally falling into the category of “pump and dump” maybe? I’m all for it if it works. But would you have to be smarter (and quicker) than the ones pumping and dumping? Wow!
Yes, like “pump and dump”, but it is more of a trading, intraday strategy than a typical P123 buy and hold. Traders use technical analysis to try and get in after the “pump” has started, and get out as the “dump” starts, or in its early stages.
I actually think this has promise for some people. After all it is something entirely different than trying to figure out the value of a company using the DDM model: many of these companies are worthless with some lame story that is being hyped. Many arguments about a an efficient-market no longer apply.
Rather, it would involve a type of game theory. My concern would be that the information is highly asymmetrical: who knows what the people organizing the pump and dump have in mind better that the people who started the pump and dump? At a minimum they know how many shares they need to unload by the end of the day.
Furthermore, they would have access to what I am doing with these nano-caps. They could see my trading-volume and subtract-out their own trading volume. They would know what I am doing in this truly ZERO SUM GAME with companies that are probably worthless. Know what I am doing and alter their behavior accordingly.
My trades (if large enough for these nano-cap companies) would alter the behavior of the other players so backtesting would have limited value.
I am absolutely sure that some people can try to play the players and win. Speaking just for myself, I would have better chance at the poker table: less information asymmetry.
The strategy I was working on really had no intention of capturing this “promotion premium” we’ll call it, frankly I was not even aware of this activity until I read Andreas’ post a few days ago. That said, the stocks I’m finding behave an awful like what he described.
Most of these stocks are (close to) worthless, one of the reasons why they are being promoted to either allow higher prices for management to sell stock personally, or a reason to sell more stock and finance operations for the next 6-12 months (some of these companies have 0 sales).
But yes, fundamentals have almost nothing to do with the price movement, which can be very counter-intuitive to an “investor”. Not to mention the extreme volatility of these stocks, which is a no-no if an investor’s of the low beta school.
Backtesting is difficult also because a) the majority of the price action can happen over only a few days (if not within 1 day), which b) requires intraday data. I’ve tested my strategy as a buy and hold, which shows promise, but again only under certain market conditions, and the backtest does not capture those sudden intraday movements (which you’d have to time).
I’m still investigating this strategy. Had some early wins, but will see if it was random chance or if there is a robust signal in the strategy.
I certainly think there might be a clear signal–call it a technical indicator–that might be used. While there is some information asymmetry it is also true that they hold a boatload of stocks and are committed to selling at a higher price. It will take some time to unload them. There are some thing that they just cannot control. You will have more flexibility and you don’t even have to invest in that stock that day. An interesting game at the very least.
I remain convinced that some people will excel at this but also that for whatever reason(s) it may not be my game.