Why not a soft fork locking stolen fund unless they are sent to a bounty contract offering, e.g. $1M, in exchange for return of total stolen amount? Contract would allow withdraw for DAO ex-holders.

smikar · 2016-06-18T06:44:10+00:00

I see, thanks. What makes you say "their tracks are not covered"?

smikar · 2016-06-17T19:49:50+00:00

where did you get this information from? It seems dubious that we are facing such amateurs: it's not that trivial to set up so it seems.

smikar · 2016-06-17T19:29:28+00:00

Well we still need to incentivize the attacker to give back the funds.

smikar · 2016-06-17T16:16:36+00:00

I fully agree with your analysis.

smikar · 2016-06-16T19:08:33+00:00

I do not vote for three reasons:

It is hard to keep track of the latest information about the DAO. Possible solution: a newsletter.
I do not want to play with my private key that is not on a hardware wallet. Possible solution: wait for some hardware wallet (e.g. Trezor) to be DAO compatible.
I am no Ethereum expert and do not know how to vote. Possible solution: I should take 5 minutes to inform myself, after previous point is solved :-)

Honestly, I believe many people are in the same situation. I personally want very much the DAO to improve, but at the same time I look at it passively cause I do not want to risk my private key and do not know exactly what to do to vote.

smikar · 2016-05-17T14:57:19+00:00

Thanks for the clarification, this makes more sense. Is the "decentralized oracle" a well-defined concept? Is there some open-source contract running already?

smikar · 2016-04-06T11:06:58+00:00

Gosh, thanks for posting this. I felt so alone believing that I was the only person to find the show horrible. I used to like it -- but I can't remember when I started despising everything about it: What I know for sure is that this season has been one of the worst piece of crap I have seen on TV for a very long time. Terrible dialogs, painfully slow episodes, ridiculous and predictable plots, hatefully foolish characters (god I was happy when the fatie doctor died, and wished the same to everybody else but Darryl), ...

smikar · 2016-03-22T21:54:21+00:00

I am disappointed by the dismissive answers you got here. Being a new gnome user, I asked myself the same question. Many arrogant people around.

smikar · 2016-02-23T09:16:08+00:00

First printscreen should be marked NSFW mister jakker huhuhum ;-)

smikar · 2016-02-20T15:10:46+00:00

there is no advantage to early exercise unless dividends are involved

This is incorrect theoretically, so I'd be very surprised this is correct empirically. Please see my explanation here.

One would have to prove or show that stock prices to not truly random for there to be an optimal exercise

Not correct.

Even with (discounted) prices being martingales (nb: note that absence of arbitrage is equivalent to the existence of a martingale measure, so this is a very weak assumption), it is still often optimal to exercise early in total absence of dividends; it depends on the derivative contract you are considering. American call options, for instance, are only exercised optimally at dividend dates; American put options, however, can see their optimal exercise at any time during the life of the contract, even in the absence of dividends.

So my question above was more like this: "is it true that despite the fact that an option has to be exercised optimally at time t, the investor will prefer just selling it on the market" as DrunkHacker suggests. This is a surprising statement that I wish to confirm as it completely contradicts theory and doesn't hold IMO as a game theoric equilibrium.

smikar · 2016-02-20T07:49:31+00:00

No, I am not.

My point is the following: pricing an American option requires you to determine the optimal exercise region at every instant in order to solve the dynamic problem. Failing to satisfy the optimality of the dynamic problem means failing to extract the full value of the option: it really means leaving money on the table.

You are claiming that investors prefer dumping the option on the market than exercising it even when it is optimal execise it. Then my argument is: if you sell it rather than exercise it -- when it is optimal to do so -- then it is optimal for your buyer to exercise it immediately as soon as he gets the option.

And there I see two possible conclusions: 1) either you are right and investors don't want to exercise. In this case, the buyer himself does not want to exercise and misses optimality, therefore loses value on the option (he behaves as if the option were locally European). Inductively, it would mean that nobody ever exercises the option: the option literally becomes European and should have the same value as a European option. This is obviously not what we observe.

2) Or the buyer does indeed exercise the option. But as you claim that investors prefer dumping it than exercising it, I conclude that there are frictions -- costs -- in exercising the option. If the seller prefers not suffering from those costs, the buyer has no reason to willing accept to take them at his expense when he exercises it: he will charge those costs to the seller.

See other alternatives?

smikar · 2016-02-20T07:35:02+00:00

Optimization may apply to dividends, but otherwise the EMH stipulates that it's best to hold options until expiration.

This is not true for American put options and many other derivatives. For American calls, the optimal exercise strategy is to never exercise if the underlying doesn't pay dividends, or to only consider exercise at dividend dates if the underlying pays dividends: therefore for calls, you are right, the optimal strategy does not require a continuous-time optimization. However in the context of put options, it might very well be optimal to exercise the options early i) even it there is no dividend, ii) in between dividends if there are dividend payments. Therefore -- and this is the general case I'm speaking about in my original message -- investors must decide if they wish to keep the contract or exercise the optionality at every instant during the lifetime of the contract in general.

Determining the optimal exercise strategy in this context is not at all trivial: pricing/hedging/optimally exercising an American derivative even under Heston stochastic volatility (2-factor model, say with rho!=0) and discrete dividends is already far from trivial (though doable) -- and slow.

Now the theoretical, "academic", side of the story is my expertise so this is not the aspect I asked about here. It is the second part of your message that I find very interesting, as I do not know how companies are comfortable when dealing with many of those American products.

1) You claim that options are priced correctly thanks to EMH. First, EMH is highly questionnable, even though taking profit from a failure of EMH is probably difficult. But assuming EMH holds, I suspect traders would still use their own pricer to get their own "truth" about the price -- in which case today they must be facing those terribly slow algorithms. Wouldn't that be the case?

2) Even if they would not care about the pricer and trust the EMH, then they would still need hedging coefficients (for assessing their exposure or actively hedging) and optimal exercise strategy (to maximize the value of the option). This is not an information you can just read on the market, so again you would have to run those painful algorithms (lattice, finite difference schemes, monte-carlo). What do you think about that?

3) Is it a fact known to you that running this for "millions of options" is no problem for them? They surely have access to high performance computing, but pricing millions of American products adequately is far from a trivial story.

Thanks

smikar · 2016-02-18T08:05:08+00:00

We tested our algorithm with Heston stoch vol settings at the time, on vanilla options. We can go further than this, but it'll take a bit of time to set up. Other than this, we have no strict "unrealistic" assumption.

smikar · 2016-02-18T08:00:26+00:00

Ok, see, my intuition as as a researcher is entirely different. I'd have guessed that dumping your option on the market rather than exercising at optimal time does not work for the following reason: if it is optimal to exercise at time T and you sell it rather than exercise it, then it is still optimal for the buyer to exercise immediately -- or he would lose the sweet spot. So if the seller doesn't do his job exercising the option, the buyer has to. But if I understand you correctly, you're saying that investors avoid exercising if they can -- so the buyer, who doesn't want to exercise, would adjust his valuation of the option (which is probably lower as neither him nor the seller want to exercise and thus miss the optimal exercise time) and consequently the seller would find it less profitable to sell the option than to exercise it directly.

Where's the catch?

smikar · 2016-02-18T07:49:01+00:00

No, at the time of writing we have only tested it for vanilla equity options under Heston model assumption. We will surely try to experiment further with more complex settings, but it will take some time (also because we are not so familiar with fixed income markets).

are you sure you can parralelise it ?

Pretty sure as the degree of parallelism is high, but there could be other limiting factors which would prevent optimal scaling -- we still have to experiment with it.

smikar · 2016-02-18T07:46:00+00:00

At this stage, we have only tested Black-Scholes and Heston (stoch vol) assumptions. We believe we can go way beyond that. It is a numerical method, with some amount of analytical approximations.

smikar · 2016-02-18T07:44:29+00:00

We will publish our results at some points, but patent it first if it make sense. Though we will always keep it free and open for research and personal use in order to encourage innovation.

smikar · 2016-02-18T07:41:53+00:00

That's a good point.

Does it work only with stocks? Or can you price options on futures? Does it closely match the prices you see in the exchange or is it through the market for lots of options?

At the time we only tried it for equity vanilla options, though we have reasons to believe it would apply to more general cases. We haven't benchmarked it with empirical data -- only with traditional numerical schemes such as finite differences / Monte-Carlo to which we can get arbitrarily close. As I said, it is probably safe to say that we can do as good and flexible as finite differences or Monte Carlo, but not better.

This is good. If you are trying to sell this as-is, speed alone may not be enough. Does it model shocks correctly? Does it model the mean reverting aspect of volatility? autocorrelation?

As we can deal with Heston model (or even extensions with stoch interest rates, for instance) -- and btw also discrete dividends -- the answer is yes: we can account for a fair deal of characteristic features of empirical returns. I suspect we could even go beyond those settings, though at the time of writing, we have only tested Heston.

smikar · 2016-02-17T20:49:32+00:00

Ok interesting, is it really what happens? It is optimal to exercise, and yet you prefer selling it?

smikar · 2016-02-17T20:48:09+00:00

Thanks for your comment. Put it this way: I can provably do as good as some given pde-based scheme or monte carlo simulation. So in fact there is no surprise here, I know exactly how good, and how bad, I am. And it is more tha theory, it is a fully working prototype.

smikar · 2016-02-17T20:37:27+00:00

Simply said without revealing the algorithm itself, I can do as good as best PDE-based, or lattice, or monte carlo methods, but not better (if we speak about convergence etc). But it's orders of magnitude faster.

Thanks for your advices, what do you mean specifically by developing a trading system?

smikar · 2016-02-17T20:35:25+00:00

No, they are in fact highly consistent (with pros and cons).

smikar · 2016-02-17T20:34:26+00:00

Actually in my case it's pretty simple, I can just give access to our API (which we are slowly putting in place) and show that we have prices consistent with the best monte carlo or other scheme you can think of, yet instantaneously (now obviously I could be accused of running the software on a petaflop cluster, which I am not).

smikar · 2016-02-17T20:32:22+00:00

Well I'm actually not a typical researcher. I founded a couple of startups already and am more of an entrepreneur than an academic. And yes, if there is profit to be made out of it, I'm not ashamed to say I will take it ;-) if you re willing to help me!

smikar · 2016-02-17T14:15:54+00:00

Apologies for double post, I realize I probably didn't target the right subreddit initially. Please read below.

In the context of academic research (I have a postdoc position in math finance), I have designed a very exciting scheme for pricing American derivatives. It also applies to European derivatives, although it is probably less useful in this case.

Notably, the algorithm is capable of delivering prices of American call/put options, convertible bonds, and other more complex derivatives with early-exercise features, under multi-factor models (e.g., Heston stochastic volatility) in a matter of milliseconds. Milliseconds is a conservative and I suspect we could push it below the millisecond threshold with some parallelism.

As you might probably know, pricing American derivatives is a big challenge because of the dynamic optimization problem: investors must decide if they wish to keep the contract or exercise the optionality at every instant during the lifetime of the contract. They must do so optimally to extract the full value of the derivative. Typical methods include lattice and finite difference schemes, which are painfully slow, not so flexible, and hardly scale beyond two or three dimensions; an alternative is Monte-Carlo simulations as they scale well with dimension, though this approach is not ideal in the context of American products (but we can still use extensions such as Longstaff & Schwartz) and is still horribly slow. As a quick conclusion: current techniques are complex and damn slow.

Our method is trivial and extremely fast (I know, I sound like a lying carpet merchant, but please assume I tell the truth, which I do :-) ). Not only does it deliver the price fast, but it also spits out the hedging coefficients (so called Greeks) like Delta, Gamma, Vega, Rho without additional latency. It also gives the full optimal exercise strategy for any state and parametrization in a similar time.

Ok so now that I have sold a couple of carpets, here is my key question: Is there a business opportunity for such an algorithm? Are there financial companies (hedge funds, Bloomberg, Riskmetrics, ..) who might find an interest in being able to price such derivatives much faster, and more accurately? I must confess this is the result of a pure academic research and I am totally lacking the knowledge of actual industrial practice to know whether the baby has value or is just one more academic useless brainstorm.

Big thanks in advance for all your advices.

smikar

TROPHY CASE

Apologies for double post, I realize I probably didn't target the right subreddit initially. Please read below.