Prediction markets and lotteries (and my one simple trick for winning the lottery)

 A short and slightly mad post today, inspired by weird thoughts I was having when I awoke from my sleep this morning (yes, you are all thinking, a completely unwanted insight into the life of Rob). Clickbait is at the end.

There has recently been an uptick in the world of prediction markets. Although not new, and certainly in the UK political betting in a market based environment has been around for yonks (Betfair exchange*, take a bow) the recent entrance of Kalshi** and Polymarket** has spiced things up somewhat. 

* I'm a sometime customer but otherwise unconnected.

** No connection, not a customer, and god knows certainly no endorsement.

Now, as Matt Levine will tell you, to an extent these markets are mostly regulatory arbitrages around the fact that gambling on sports is heavily constrained in the US; Kalshi has taken advantage of an onshore loophole during a friendly political environment, whilst Polymarket is offshore crypto and hence can do whatever it wants. But at least in theory they do help to achieve the economists wet dream of a complete market which would allow you to bet on any outcome and therefore perfectly hedge yourself.

Anyway my mad thought was this; what if I could bet on whether I will win the lottery? 

There is one thing AI is good for. One thing.

In many ways that is a straightforward bet; I could specify the numbers I was going to pick and the conditions of the bet. For example, does only the jackpot count, or subsidiary prizes? For the purposes of this discussion it's simpler to assume a lottery with just one jackpot prize which is shared if multiple numbers win. And unlike certain other bets in these markets there is no debate about whether the bet will pay off.

But this is also quite mad; as there is a much easier way to make this bet, which is to actually play the lottery! Furthermore, it would extremely difficult to find someone to take the other side of this bet. Lottery ticket type bets are massively positively skewed; the person taking the other side must be willing to accept a huge negative skew of a tiny profit if they win or a huge loss if they lose. 

Of course they could hedge this risk by buying a lottery ticket. But then for this to make sense they would have to give the buyer of the bet worse odds than the lottery itself, effectively selling the ticket at a small mark up. This can make sense, again as a regulatory arbitrage if you want to 'play' the gigantic US lotteries but don't actually live there; and some bookmakers do offer this service, but not as far as I know in a market environment where you can choose to sell the bet, only as a standard bookie:client arrangement.

Lotteries only work because there is one counterparty who is willing to take all the bets - the 'promoter'. Because they are taking all the bets, and these bets are by nature perfectly uncorrelated (in the example of the simple lottery jackpot only lottery with prize sharing we are discussing), and they set the size of the prize fund based on ticket sales, they are in a no lose situation. In fact they normally have a substantial edge; even ignoring the possibility of nobody winning. 

(In many lotteries if there are no jackpot winners the prize fund 'rolls over' to the following draw and isn't taken by the promoter. We will return to this possibility later.)

In the UK national lottery this edge is set by law and reduces the prize fund by half before it's paid out, but lottery winnings are tax free. In US state lotteries where the top line reduction is lower the prize is also subject to income tax. Broadly speaking in both cases the net prize fund is around half of the total. Buying lottery tickets, as is well known, is a subsantial -ve EV bet. It is gambling, in the pejorative sense of the word. And nonsense like this, ought to be banned.

However let's imagine a world in which there are people who are willing to take the other side of this bet. One way of doing this is to split the bets into tiny chunks. For example I could take on 0.01 pennies of risk that a given set of numbers will not win a $1 stake lottery with a $1 million dollar prize; if the market is priced perfectly then if I lose I will lose 0.01*1 million = $10,000 if the numbers come up. And I could make 1 million of these bets to cover all possible outcomes and stand to win $10,000. As the market is perfectly priced then assuming everyone buys every combination of numbers I will not make or lose anything. With a million people like me betting against lottery wins, and a million people betting on lottery wins, we'd effectively have a lottery.

Importantly though, this lottery would have no house edge. Instead of 50% of the winnings being drained away by the promoter, 0% of the winnings would be. And of course those selling lottery 'tickets' by betting against possible winning combinations would have the option of doing so at a slightly lower probability. For example, in a 1:million odds lottery offering 900,000:1 on winning. The buyers of lottery tickets are facing a 10% house edge here, but that is still much better than the 50% loss of a normal lottery. There would probably be some cost to the prediction market operating, but even if it was 5% that is still a gain for both buyers and sellers.

Note: It seems likely that buyers will overpay for long odds tickets; as per this research which was highlighted by FT Alphaville the day after I originally published this: "Contracts trading at 5 cents win only 4.18% of the time, implying mispricing of -16.36%" 

Note: The presence of multiple levels of jackpots in normal lotteries makes the house edge much less transparent than it would be for a single prize with known odds. I guess this is deliberate.

Note: Just as in a normal lottery people bet on 'lucky' numbers it might be that sellers of lottery 'tickets' do not bet against all possible numbers coming up, or vary the price they offer on certain numbers. Absurd numbers of people buy birthdays or sequences of numbers. If this happened here then the 'price' of those 'tickets' would be bid up versus totally random numbers, allowing the sellers of those 'tickets' to make higher profits. A risk premium in lotteries!

In any normal world this wouldn't be allowed to happen. Effectively the parallel lottery is free riding on the actual lottery. Governments tend to be very protective of their gambling monopolies! Of course there is nothing to stop the prediction market setting up their own 'lottery', a trusted counterparty who will draw some numbers and post them on the internet every week. But perhaps this is too complicated. After all, lottery type payoffs are already widely available on the internet in the form of dubious crypto coins masquerading as investments. Why overcomplicate things? 

Perhaps a more interesting bet with some chance of being implemented is betting on nobody winning the lottery jackpot. Remember earlier I said many lotteries have a rollover function. Take the Euromillions for example. Odds of winning the jackpot are 1 in 139 million. But typically only 20 to 30 million tickets are purchased. Hence in any given draw the chances are the jackpot will not be won. For example in October and November last year there was no winner for 13 draws and the jackpot reached 156 million Euros from a starting value of 14.8 million. 

If you calculate the exact probability assuming everyone picks their numbers randomly then you get what I would call 'reasonable' odds, so the skew on the bet isn't absurd and it isn't mad to think people would want to bet on this. 

The maths here isn't simple as the longer these stretches of no jackpot go on, the more tickets are sold as the jackpot gets more attractive (in the aforementioned period of 13 draws average sales nearly doubled from 20 million to almost 40 million by the end of the run). So you would need to be able to predict ticket sales and have a good understanding of both the rules of the lottery and betting patterns. Ironically then there will be more skill required here than just betting on random numbers.

I will finish with - as promised- my own lottery winning strategy: If you are going go bet on the lottery, normally a -EV bet as discussed, then doing so when the jackpot is very high after lots of rollovers isn't a bad idea. The retained money from earlier draws makes it a slightly +ve EV bet. Whilst this doesn't guarantee a win, it does mean that in all possible lifetimes you will come out ahead. So that's nice.

See this paper which Andre Loeffler pointed me towards after I published this post.

Are markets that are good for trend good just because they have also gone up a lot, or because carry, or...

I have a friend, ex-colleague and TTU co-host who runs a fixed income focused CTA. We have regular coffees (he pays, so his fund is doing ok) and one of our favourite topics for arguing debating making polite conversation about is why fixed income is so much better for trend than anything else. He's biased, but then arguably so am I; I started my career trading rates options, and we both managed AHL's fixed income portfolio (though not at the same time).

Certainly if you looked at the performance of fixed income it looks good! Consider this extract from my fourth book, tables 37 and 38:

Only vol is better, and that is just two markets. But then, bonds have been a great investment on a long only basis. The data in that book covers a period when bond prices could very easily be summarised as "number go up!". Here are tables 10 and 11 from the same book:

Bonds have the highest Sharpe Ratio on a long only basis (actually it's long only with position sizes adjusted daily for vol: a constant forecast of +10). 

But still, there must be something else going on here. Equities have also done awfully well long only (SR 0.46), but they have the worst trend following performance of all. FX has had crap SR long only, but did pretty well trend following. What's more, it will probably be useful to distinguish between different kinds of tailwind from secular up trends: 

• Price go up (or down, since if we're trend following long/short we are cool with that, c.f. vol)
• High Positive carry (or negative, same reasons)

Of course there are fancy ways of dealing with this, like CAPM style regressions (of which there are plenty in the book); but let's keep things simple here with some scatter plots.

What is being scattered? Well on the y-axis let's do SR of trend following, and on the x-axis the SR of the long only adjusted price return, spot price return, or cumulated carry return (the difference between spot and adjusted price). Each scattered point will represent the returns of one market over a five year period, and I colour the point to indicate the asset class. And we'll also need to do different graphs for each speed of trend following.

Messy python (requires psystemtrade)

Fast trend (momentum 8)

We would expect for faster momentum to have a relatively weak relationship. Let's see:

Yup, nothing there.

Medium trend (momentum 16)

Perhaps the start of a slope there, but not for carry.

Slow trend (momentum 64)

So adjusted prices look good, spot prices less so, and carry not much going on. Don't forget that adjusted is mechanically spot+carry, but over time that addition will make sense if they are uncorrelated. It looks like adjusted prices show clearer trends than eithier of the components do.

But is there anything special?

This doesn't tell us whether there is something special about bonds, equities or FX. Let's repeat the plots for momentum64 but without the scatter points; instead we fit a regression line to each asset class and plot that.

Now that is the money shot for this blog! We can see a clear split:

• Bonds, FX, Metals, Vol: We can convert adjusted price drift into trend SR, with a slope of around 0.9. Note: The vol line in green is the one almost perfectly aligned to the orange line going up to SR 1.0 on the x-axis.
• Ags, Energies, Equities: The relationship is much weaker 

What about the other two types of prices?

We can see there is a consistent effect in spot prices, but carry is much weaker. The exception is vol; much of the adjusted price downtrend in vol comes from the vol premium which is basically carry on the futures curve.

I won't do everything, but here are the adjusted price plots for the other two speeds.

Although the vol line has a worse intercept, the same pattern of the relationship is present.

Summary

To an extent, secular up(down) trends in asset prices make it easier to make profits from (slower) momentum. The effect is roughly 0.7 to 0.9 units of trend following SR for every unit of secular drift depending on the speed of trading. And it's remarkably consistent across asset classes that fall into this category: they are not energies, equities or ags. So there is nothing special about bonds; but there are two distinct types of asset classes. 

Here is another view: a distribution of trend SR returns in five year blocks by asset class for momentum64:

And combining with this plot, showing the distribution of adjusted price returns (SR) in five year blocks by asset class:

One last scatter plot of the medians SR from the above two plots:

We can say:

• Bonds, FX and Vol did as expected, converting trends of various strengths to momentum trend SR (they lie on an imaginary line running diagonally upwards)
• Metals, which we know is also a strong trend convertor, did even better than expected 
• Equities is definitely an underperformer as we'd expect from a poor trend convertor.
• Energies and Ags seems to have got lucky; though they are not great trend convertors they did better than expected (lying just above the imaginary line).

Is this trend conversion a property of the asset class, or just a fluke? I dunno. But it doesn't look like there is anything special about bonds. 

Wordle (TM) and the one simple hack you need to pass funded trader challenges

An unusual (but quick) mid month post, as this is a live issue I thought I'd publish this whilst it's relevant.

There has been some controversy on X/Twitter about 'pay to play' prop shops (see this thread and this one) and in particular Raen Trading. It's fair to say the industry has a bad name, and perhaps this is unfairly tarnishing what may pass for good actors in this space. It's also perhaps fair to say that many of those criticising these firms, including myself, aren't as familiar with that part of the trading industry and our ignorance could be problematic. 

But putting all that aside, a question I thought I would try and answer is this - How hard is it to actually pass one of these challenges? As a side effect, it will also tell us what the optimal vol target is to use if we're taking part in one of these challenges. Hence the clickbait article heading. I know from experience this will open me up to having to filter out 500 spam comments a day, but f*** it. 

As well as modelling Raen, I also model a much dodgier challenge later in the post, from another company which I will name only as prop firm #2. Finally I close with some generic and unquantified thoughts on the subject. 

Standalone Python code here. You can play with this to model another firms challenges.

TLDR: 

• Raen you have reasonable chance of passing their first round challenge and you should use a vol target of [scroll down to find out!] to maximise your chances.
• Prop firm #2 and most of the 'industry' use a very long bargepole, I can lend you mine
• I remain skeptical of pay to play

As to what any of this has to do with the word game Wordle (TM), read on to find out.

IMPORTANT: This is not an endorsement of Raen. I have no association with them and I remain skeptical of this entire industry. Their CEO reached out to me after this blogpost was initially published, confirmed my understanding of the challenge parameters was correct, and gave me permission to use the firms name. I made one small correction to the post as a result of that contact.

The (relatively) good guys 

The rules of the Raen challenge are this:

• You must make 20%
• You can't lose more than 2% in a single day. There is no maximum trailing drawdown. So if you lose 1.99% every day forever, you're still in the game.
• You must trade for at least 30 trading days before passing the challenge
• It costs $300 a month to do the challenge. This isn't exactly the same Raen which charges a little more, but as a rounder number it makes it easier to directly see how many months we expect to take by backing out from the cost per month. I assume this is paid at the start of the month.

Note: this is just the 1st stage of the challenge. The rules for the 2nd stage are much more nebolous, but to be fair there are no charges for those. Like I said, this prop firm appears to be amongst the relatively good guys. 

 

I've also got these parameters:

• 256 business days a year, 22 business days a month (it's actually more like 21, but again this higher figure will make the prop firm look good)
• Random gaussian returns generated with no autocorrelation. This is extremely kind as it ignores the chance of fat tails that are somewhat common in finance.
• If we get stopped out we try again, which means restarting the challenge from scratch. There are no reset fees. I assume that this reset doesn't affect the timing of monthly fees (I can't find the answer to this question on the website, but this must be the case as otherwise the cost of resetting would be free and your best strategy would be to keep making massive bets every day and you would pass eventually and only ever have to pay the first month).
• We give up if we can't pass after trying for a year (there are no time limits in the challenge, but this speeds up the computation and seems like reasonable behaviour).
• I assume there are no other limits which make it hard to hit a given risk target. This is unlikely to be a constraint except for suboptimally high vol targets.

There are two clear variables we are missing: the expected Sharpe Ratio, and the vol, both required to generate the gaussian returns. The former is assumed to be exogenous (a question to answer is how hard are these challenges to pass - if you need a SR of 4 to pass them that suggests they are probably too hard), whilst the latter we can optimise for. Note that due to the drawdown and self imposed time limit the optimal vol target won't be equal to the usual Kelly optimal. In fact this subject is intellectually interesting as well as topical since it's the first time I've looked at optimisation with a drawdown/time constraint. 

I run this as a bootstrap exercise. We try and optimise: (a) minimise the median cost, (b) maximise the probability of being funded before we give up. 

OK so two simple graphs then. Each has a different line for each SR, and the x-axis is the vol target we are running at. The y-axis on graph one is the cost, with a minus sign so we have the natural thing of a high y-axis being good. On graph two the y-axis is the probability of passing before we give up, again obviously high y-axis is good.

Median cost of getting to stage two, lines are SR, x axis is annual vol target, y axis is cost (bigger minus numbers are higher costs)

Note that for SR/vol combinations where we have a less than 50% median chance of succeeding the median cost will be equal to the monthly cost * 12. This is the case for SR<1.5

Probability of getting to stage two, lines are SR, x axis is annual vol target, y axis is probability of success

What conclusions can we draw from this?

• The optimal vol target depends on your SR and whether you are focusing on costs or probability*
• To get a greater than 50% chance of passing we need an expected SR of 1.5 or higher. 
• The expected median cost with optimal vol is going to be be $2000 for a SR of 1.5, which you can get down to $1500 if you are the next RenTech (SR of 3). 
• The expected median time to pass is going to be about 7 months for a SR of 1.5 or about 5 months if you are the next RenTech

* Experts will recognise the vol target choice as the Wordle (TM) starting word problem (yes we finally got there). The best starting word for Wordle will depend on whether you are maximising your probability of winning, or trying to minimise the number of guesses you make. Similarly, are we trying to maximise our chance of passing the challenge, or minimising our likely cost? They are not quite the same thing.

The optimal vol looking at costs is around 15 - 20%. Looking at probability of passing, it's around 12% for very high SR traders, and more like 22% for low SR traders. Basically if you're crap you have to take a bit more risk to have a chance. If you're good you can chill. Given we're assuming Gaussian returns I'd be tempted to mark these figures down a bit, although note that for high SR traders using less than optimal vol is quite harmful (very steep lines) whilst using more than optimal is less painful (this is completely at odds with Kelly of course).

Since nobody knows what their SR is, I'd suggest using 15% as a vol target. If you are incredible that is slightly more than optimal, but you still have an 80% chance of passing. If you are less incredible it may be slightly less than optimal, but then you have no business passing this challenge anyway.

The not so good guys firm #2

Here is an example of another firm's level 1 challenge, I won't name them but they are currently on the 1st page of google results for the search term "trading prop challenge" so that narrows it down. This firm has several challenge tiers in the futures space, I've chosen the lowest; but all the conditions are the same just different notional capital and $ costs. 

The rules of the challenge are this:

• You must make 6%
• The maximum drawdown is 4%; trailing based on daily balances.
• If you lose more than 2% in a day, well basically you're stopped out at 2% but the challenge doesn't end. So your max loss in a day is 2%. In practice would be slightly more because of slippage but let's be generous here.
• There is a one time activation of $130 (not exact figures again but ballpark).
• You have to do the challenge in 30 days. It costs $100 to start each challenge. If you want to extend the challenge by 30 days it costs another $100. This equates to a monthly fee of $100, so we'll model it like that.
• If you need to reset (start again because you've gone boom) it's $80. This is on top of the monthly cost since it doesn't reset the number of days to zero before you have to pay a monthly fee again.
• There are optional data fees we will ignore, because there are enough fees here already.

Now, it's worth saying that there are many other terms and conditions that make firm #2 much dodgier and less likely to fund you or give you your profit share once funded (of course we're assuming firm #1 sticks to their word as well); but we're purely here to model the challenge itself.

Here are the graphs:

Median cost of getting to stage two, lines are SR, x axis is annual vol target, y axis is cost (bigger minus numbers are higher costs)

Probability of getting to stage two, lines are SR, x axis is annual vol target, y axis is probability of success

This is not what I had expected. I had expected the challenge to be much harder, so the firm could keep collecting the fees. But this challenge is easy to pass, just use vol more than 25%. Basically you get to flip a coin a couple of times and sooner or later it will turn up heads. This strategy will work even if you are a losing trader (SR -0.5) as shown. The only benefit of being a better trader is you will pass quicker and thus pay less. 

This is an incredibly badly designed challenge. It rewards higher volatility. It doesn't discriminate at all between good and bad traders. 

So eithier (i) there are other conditions in the (very hard to find) small print that in practice make the challenge hard to pass or (ii) it's a deliberate strategy to allow almost anyone to get to the next stage. The biggest red flag is that trading with this particular firm is sim only even after you have passed the challenge. They don't want to make the initial challenge too hard; they want you as a paying customer ASAP. And people who use too much vol are ideal customers for bucket shops.

The prop firms view

Of course what we're not doing here is looking at things from the prop firm's point of view. The challenge is designed to answer the question: "is this potential trader any good or just lucky?". At least that is if you are assuming they are genuinely looking for good traders. Which prop firm #2 definitely isn't, so let's focus on Raen.

The main shortcoming of these challenges is that 30 days or even a year is a wholly insufficient time to determine if anyone has any skill, unless they are very highly skilled indeed. And again, to be fair, the initial challenge of Raen is purely a screening exercise that will essentially tell you (a) if someone has a vague idea of how to manage risk and avoid a 2% daily drawdown and (b) is eithier very good (SR somewhere over 1) or just very lucky.

Someone who shoots for a vol target that is too high will almost certainly fail. However there is still a chance of a crap trader being lucky. But hopefully the second stage will weed them out. So we aren't too worried about type 1 errors.

However even relatively highly skilled traders (say SR 1 to 1.5) will only have a coinflip chance of passing. So there is still quite a big chance of a type 2 error and missing out on the next Nav Sarao*. Perhaps that's okay. They're probably only interested in people with a SR of over 2 anyway, where the passing percentage for a year will be over 60% if they use optimal vol. Of course I'm assuming all these people have several thousand dollars to stump up to a years worth of monthly fees. There will be many who don't, and therefore also miss out on potentially being funded even if they are good traders. So I would say the possibility of a type 2 error is quite high.

* this famous gentlemen who for all his faults was an incredibly succesful futures prop trader even when he wasn't breaking the law.

 

I'd say on balance that Raen's challenge is relatively well designed given all the caveats. It's simple, it's difficulty rating feels about right, and the 2% daily drawdown acts as a simple anti muppet filter. The fact there is an optimal vol is satisfying. It would be interesting to see their internal numbers on how many people pass the first and then the second challenge; and then go on to become good traders. That will tell us what their type 1 error actually is. 

But is this all really a good idea? Some unquantified and unqualified opinions

Putting aside the statistical debate, is this all really a good thing? For the traders trying out, or for the firms themselves (assuming they again are genuine). There are many red flags in this industry, having to pay to be considered for a 'job' is always bad (although Raen's CEO clarified to me that they also accept applicants who haven't passed the challenge, presumably with some kind of filter on experience); the fact that many places are purely bucket shops where you trade against the broker is awful (again not Raen), frankly the whole thing makes my stomach churn but I'm trying to be as fair as possible here and put emotions aside.

The world of trading has changed an awful lot. In this post the founder of Raen says their shop is for people who would never the opportunity to get into Jane Street (JS). But JS is looking for people with a very particular set of skills to do a certain kind of trading which you can't do unless you have the sort of resources JS has. 

Yes we can argue that the Jane Street filter is too strict (though they hired SBF, a man who did not understand how to size trading positions, so maybe not strict enough), but it's pretty silly to pretend that Jane Street would be interested in hiring the sort of people who have the ability to be point and click futures traders. It's really not the same at all.

Raen apparently has ex JS people working there and they are 'very succesful'. I am sure they are. I'm also sure that they're almost certainly not point and click traders eithier. But is it really realistic to replicate JS by hiring a completely different set of people, without any of the filters JS uses to get specific sets of skills, using a totally different process from what JS uses, and without most of JS resources; and then sit them next to ex JS traders from whom they will presumably absorb brilliance by osmosis?

Basically if for some reason you are trying to be the next JS why are you using a hiring process which is clearly for point and click traders? There are no references to APIs that I can see on any of these challenge websites, so I assume it's point and click they are looking for.

So, is the world of point and click prop traders too inaccessible? It's probably more accessible than it was 20 years ago from an IT and cost perspective. But admittedly if you're not trading costly and dodgy retail assets,  and want to trade futures, then no you can't really do this with the $3000 or so you'd need to pass even a good trading challenge. The $100k of (notional, real?) money you get from Raen is the bare minimum I suggest in my book. You would need less in equities though, but to be eg US PDT you need $25k (for now). 

But from my perspective, the whole point and click futures industry seems very... niche. The vast majority of professional traders now are basically quants, or heavily supported by quants, and/or using data other than the charts and order books fancied by the dozen monitor setups of the cliched point and click trader. It's an area of the market that really is very efficient and where the vast majority of point and click humans can't compete even if supported by execution algos, which is why I deliberately trade much... more... slowly. 

In fact I'd say there are now significantly more people employed by the likes of JS than by genuine and profitable point and click firms. 

So we're talking about getting access to a relatively tiny industry that is frankly a bit quaint and probably still shrinking. I can understand why many people want to get into it though. Who wouldn't want to gamble for a living, make millions of dollars a year, in a job which requires no qualifications (no Phd in astrophysics needed here!), which so many films and YouTube videos have glamorised, and which eithier requires almost no work or where hard work and effort will be rewarded (depending on which video you watch). 

I can believe that there are a very small number of people who have pointed and clicked for so long, that they really do have an ability to 'feel' a particular market very well, they can glance at an L2 order book and see patterns, they know which news and statistics to focus on, they know what other markets to look at, they know how to manage risk and size positions, they have built execution algos that enable them to compete not with HFT but certainly in the sub one day area... and they are certainly better traders than me or my systems. 

As to how you would select such people, I do not know. They are not my people. Personally I am very skeptical as to whether there really are people who can sit at a computer having never traded futures before except maybe in a simulator, with no training or market experience, and have some innate trading ability that enables them to have a high probability of passing a trading challenge with the sort of SR that would make most hedge funds weep with envy, and also that those challenges are the best way of being able to tell that someone has that innate ability. 

But once again, I'm not in this industry so what do I know. 

Summary

Raen: not a bad intial screening and a more than 50% chance of a pass with a SR above 1.5. But it will cost you more than $300. Budget for several thousand bucks and use a vol target of around 15% to optimise your chances.

Unamed prop firm #2 I googled and most of this industry: stay away for gods sakes.

Pay to play: morally dubious IMHO

Random futures traders having some sort of innate talent that can be found in this way: I doubt it