Binary Options Strategy - All Trading Strategies Reviewed

No gods, no kings, only NOPE - or divining the future with options flows. [Part 3: Hedge Winding, Unwinding, and the NOPE]

Hello friends!
We're on the last post of this series ("A Gentle Introduction to NOPE"), where we get to use all the Big Boy Concepts (TM) we've discussed in the prior posts and put them all together. Some words before we begin:
  1. This post will be massively theoretical, in the sense that my own speculation and inferences will be largely peppered throughout the post. Are those speculations right? I think so, or I wouldn't be posting it, but they could also be incorrect.
  2. I will briefly touch on using the NOPE this slide, but I will make a secondary post with much more interesting data and trends I've observed. This is primarily for explaining what NOPE is and why it potentially works, and what it potentially measures.
My advice before reading this is to glance at my prior posts, and either read those fully or at least make sure you understand the tl;drs:
https://www.reddit.com/thecorporation/collection/27dc72ad-4e78-44cd-a788-811cd666e32a
Depending on popular demand, I will also make a last-last post called FAQ, where I'll tabulate interesting questions you guys ask me in the comments!
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So a brief recap before we begin.
Market Maker ("Mr. MM"): An individual or firm who makes money off the exchange fees and bid-ask spread for an asset, while usually trying to stay neutral about the direction the asset moves.
Delta-gamma hedging: The process Mr. MM uses to stay neutral when selling you shitty OTM options, by buying/selling shares (usually) of the underlying as the price moves.
Law of Surprise [Lily-ism]: Effectively, the expected profit of an options trade is zero for both the seller and the buyer.
Random Walk: A special case of a deeper probability probability called a martingale, which basically models stocks or similar phenomena randomly moving every step they take (for stocks, roughly every millisecond). This is one of the most popular views of how stock prices move, especially on short timescales.
Future Expected Payoff Function [Lily-ism]: This is some hidden function that every market participant has about an asset, which more or less models all the possible future probabilities/values of the assets to arrive at a "fair market price". This is a more generalized case of a pricing model like Black-Scholes, or DCF.
Counter-party: The opposite side of your trade (if you sell an option, they buy it; if you buy an option, they sell it).
Price decoherence ]Lily-ism]: A more generalized notion of IV Crush, price decoherence happens when instead of the FEPF changing gradually over time (price formation), the FEPF rapidly changes, due usually to new information being added to the system (e.g. Vermin Supreme winning the 2020 election).
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One of the most popular gambling events for option traders to play is earnings announcements, and I do owe the concept of NOPE to hypothesizing specifically about the behavior of stock prices at earnings. Much like a black hole in quantum mechanics, most conventional theories about how price should work rapidly break down briefly before, during, and after ER, and generally experienced traders tend to shy away from playing earnings, given their similar unpredictability.
Before we start: what is NOPE? NOPE is a funny backronym from Net Options Pricing Effect, which in its most basic sense, measures the impact option delta has on the underlying price, as compared to share price. When I first started investigating NOPE, I called it OPE (options pricing effect), but NOPE sounds funnier.
The formula for it is dead simple, but I also have no idea how to do LaTeX on reddit, so this is the best I have:

https://preview.redd.it/ais37icfkwt51.png?width=826&format=png&auto=webp&s=3feb6960f15a336fa678e945d93b399a8e59bb49
Since I've already encountered this, put delta in this case is the absolute value (50 delta) to represent a put. If you represent put delta as a negative (the conventional way), do not subtract it; add it.
To keep this simple for the non-mathematically minded: the NOPE today is equal to the weighted sum (weighted by volume) of the delta of every call minus the delta of every put for all options chains extending from today to infinity. Finally, we then divide that number by the # of shares traded today in the market session (ignoring pre-market and post-market, since options cannot trade during those times).
Effectively, NOPE is a rough and dirty way to approximate the impact of delta-gamma hedging as a function of share volume, with us hand-waving the following factors:
  1. To keep calculations simple, we assume that all counter-parties are hedged. This is obviously not true, especially for idiots who believe theta ganging is safe, but holds largely true especially for highly liquid tickers, or tickers will designated market makers (e.g. any ticker in the NASDAQ, for instance).
  2. We assume that all hedging takes place via shares. For SPY and other products tracking the S&P, for instance, market makers can actually hedge via futures or other options. This has the benefit for large positions of not moving the underlying price, but still makes up a fairly small amount of hedges compared to shares.

Winding and Unwinding

I briefly touched on this in a past post, but two properties of NOPE seem to apply well to EER-like behavior (aka any binary catalyst event):
  1. NOPE measures sentiment - In general, the options market is seen as better informed than share traders (e.g. insiders trade via options, because of leverage + easier to mask positions). Therefore, a heavy call/put skew is usually seen as a bullish sign, while the reverse is also true.
  2. NOPE measures system stability
I'm not going to one-sentence explain #2, because why say in one sentence what I can write 1000 words on. In short, NOPE intends to measure sensitivity of the system (the ticker) to disruption. This makes sense, when you view it in the context of delta-gamma hedging. When we assume all counter-parties are hedged, this means an absolutely massive amount of shares get sold/purchased when the underlying price moves. This is because of the following:
a) Assume I, Mr. MM sell 1000 call options for NKLA 25C 10/23 and 300 put options for NKLA 15p 10/23. I'm just going to make up deltas because it's too much effort to calculate them - 30 delta call, 20 delta put.
This implies Mr. MM needs the following to delta hedge: (1000 call options * 30 shares to buy for each) [to balance out writing calls) - (300 put options * 20 shares to sell for each) = 24,000 net shares Mr. MM needs to acquire to balance out his deltas/be fully neutral.
b) This works well when NKLA is at $20. But what about when it hits $19 (because it only can go down, just like their trucks). Thanks to gamma, now we have to recompute the deltas, because they've changed for both the calls (they went down) and for the puts (they went up).
Let's say to keep it simple that now my calls are 20 delta, and my puts are 30 delta. From the 24,000 net shares, Mr. MM has to now have:
(1000 call options * 20 shares to have for each) - (300 put options * 30 shares to sell for each) = 11,000 shares.
Therefore, with a $1 shift in price, now to hedge and be indifferent to direction, Mr. MM has to go from 24,000 shares to 11,000 shares, meaning he has to sell 13,000 shares ASAP, or take on increased risk. Now, you might be saying, "13,000 shares seems small. How would this disrupt the system?"
(This process, by the way, is called hedge unwinding)
It won't, in this example. But across thousands of MMs and millions of contracts, this can - especially in highly optioned tickers - make up a substantial fraction of the net flow of shares per day. And as we know from our desk example, the buying or selling of shares directly changes the price of the stock itself.
This, by the way, is why the NOPE formula takes the shape it does. Some astute readers might notice it looks similar to GEX, which is not a coincidence. GEX however replaces daily volume with open interest, and measures gamma over delta, which I did not find good statistical evidence to support, especially for earnings.
So, with our example above, why does NOPE measure system stability? We can assume for argument's sake that if someone buys a share of NKLA, they're fine with moderate price swings (+- $20 since it's NKLA, obviously), and in it for the long/medium haul. And in most cases this is fine - we can own stock and not worry about minor swings in price. But market makers can't* (they can, but it exposes them to risk), because of how delta works. In fact, for most institutional market makers, they have clearly defined delta limits by end of day, and even small price changes require them to rebalance their hedges.
This over the whole market adds up to a lot shares moving, just to balance out your stupid Robinhood YOLOs. While there are some tricks (dark pools, block trades) to not impact the price of the underlying, the reality is that the more options contracts there are on a ticker, the more outsized influence it will have on the ticker's price. This can technically be exactly balanced, if option put delta is equal to option call delta, but never actually ends up being the case. And unlike shares traded, the shares representing the options are more unstable, meaning they will be sold/bought in response to small price shifts. And will end up magnifying those price shifts, accordingly.

NOPE and Earnings

So we have a new shiny indicator, NOPE. What does it actually mean and do?
There's much literature going back to the 1980s that options markets do have some level of predictiveness towards earnings, which makes sense intuitively. Unlike shares markets, where you can continue to hold your share even if it dips 5%, in options you get access to expanded opportunity to make riches... and losses. An options trader betting on earnings is making a risky and therefore informed bet that he or she knows the outcome, versus a share trader who might be comfortable bagholding in the worst case scenario.
As I've mentioned largely in comments on my prior posts, earnings is a special case because, unlike popular misconceptions, stocks do not go up and down solely due to analyst expectations being meet, beat, or missed. In fact, stock prices move according to the consensus market expectation, which is a function of all the participants' FEPF on that ticker. This is why the price moves so dramatically - even if a stock beats, it might not beat enough to justify the high price tag (FSLY); even if a stock misses, it might have spectacular guidance or maybe the market just was assuming it would go bankrupt instead.
To look at the impact of NOPE and why it may play a role in post-earnings-announcement immediate price moves, let's review the following cases:
  1. Stock Meets/Exceeds Market Expectations (aka price goes up) - In the general case, we would anticipate post-ER market participants value the stock at a higher price, pushing it up rapidly. If there's a high absolute value of NOPE on said ticker, this should end up magnifying the positive move since:
a) If NOPE is high negative - This means a ton of put buying, which means a lot of those puts are now worthless (due to price decoherence). This means that to stay delta neutral, market makers need to close out their sold/shorted shares, buying them, and pushing the stock price up.
b) If NOPE is high positive - This means a ton of call buying, which means a lot of puts are now worthless (see a) but also a lot of calls are now worth more. This means that to stay delta neutral, market makers need to close out their sold/shorted shares AND also buy more shares to cover their calls, pushing the stock price up.
2) Stock Meets/Misses Market Expectations (aka price goes down) - Inversely to what I mentioned above, this should push to the stock price down, fairly immediately. If there's a high absolute value of NOPE on said ticker, this should end up magnifying the negative move since:
a) If NOPE is high negative - This means a ton of put buying, which means a lot of those puts are now worth more, and a lot of calls are now worth less/worth less (due to price decoherence). This means that to stay delta neutral, market makers need to sell/short more shares, pushing the stock price down.
b) If NOPE is high positive - This means a ton of call buying, which means a lot of calls are now worthless (see a) but also a lot of puts are now worth more. This means that to stay delta neutral, market makers need to sell even more shares to keep their calls and puts neutral, pushing the stock price down.
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Based on the above two cases, it should be a bit more clear why NOPE is a measure of sensitivity to system perturbation. While we previously discussed it in the context of magnifying directional move, the truth is it also provides a directional bias to our "random" walk. This is because given a price move in the direction predicted by NOPE, we expect it to be magnified, especially in situations of price decoherence. If a stock price goes up right after an ER report drops, even based on one participant deciding to value the stock higher, this provides a runaway reaction which boosts the stock price (due to hedging factors as well as other participants' behavior) and inures it to drops.

NOPE and NOPE_MAD

I'm going to gloss over this section because this is more statistical methods than anything interesting. In general, if you have enough data, I recommend using NOPE_MAD over NOPE. While NOPE in theory represents a "real" quantity (net option delta over net share delta), NOPE_MAD (the median absolute deviation of NOPE) does not. NOPE_MAD simply answecompare the following:
  1. How exceptional is today's NOPE versus historic baseline (30 days prior)?
  2. How do I compare two tickers' NOPEs effectively (since some tickers, like TSLA, have a baseline positive NOPE, because Elon memes)? In the initial stages, we used just a straight numerical threshold (let's say NOPE >= 20), but that quickly broke down. NOPE_MAD aims to detect anomalies, because anomalies in general give you tendies.
I might add the formula later in Mathenese, but simply put, to find NOPE_MAD you do the following:
  1. Calculate today's NOPE score (this can be done end of day or intraday, with the true value being EOD of course)
  2. Calculate the end of day NOPE scores on the ticker for the previous 30 trading days
  3. Compute the median of the previous 30 trading days' NOPEs
  4. From the median, find the 30 days' median absolute deviation (https://en.wikipedia.org/wiki/Median_absolute_deviation)
  5. Find today's deviation as compared to the MAD calculated by: [(today's NOPE) - (median NOPE of last 30 days)] / (median absolute deviation of last 30 days)
This is usually reported as sigma (σ), and has a few interesting properties:
  1. The mean of NOPE_MAD for any ticker is almost exactly 0.
  2. [Lily's Speculation's Speculation] NOPE_MAD acts like a spring, and has a tendency to reverse direction as a function of its magnitude. No proof on this yet, but exploring it!

Using the NOPE to predict ER

So the last section was a lot of words and theory, and a lot of what I'm mentioning here is empirically derived (aka I've tested it out, versus just blabbered).
In general, the following holds true:
  1. 3 sigma NOPE_MAD tends to be "the threshold": For very low NOPE_MAD magnitudes (+- 1 sigma), it's effectively just noise, and directionality prediction is low, if not non-existent. It's not exactly like 3 sigma is a play and 2.9 sigma is not a play; NOPE_MAD accuracy increases as NOPE_MAD magnitude (either positive or negative) increases.
  2. NOPE_MAD is only useful on highly optioned tickers: In general, I introduce another parameter for sifting through "candidate" ERs to play: option volume * 100/share volume. When this ends up over let's say 0.4, NOPE_MAD provides a fairly good window into predicting earnings behavior.
  3. NOPE_MAD only predicts during the after-market/pre-market session: I also have no idea if this is true, but my hunch is that next day behavior is mostly random and driven by market movement versus earnings behavior. NOPE_MAD for now only predicts direction of price movements right between the release of the ER report (AH or PM) and the ending of that market session. This is why in general I recommend playing shares, not options for ER (since you can sell during the AH/PM).
  4. NOPE_MAD only predicts direction of price movement: This isn't exactly true, but it's all I feel comfortable stating given the data I have. On observation of ~2700 data points of ER-ticker events since Mar 2019 (SPY 500), I only so far feel comfortable predicting whether stock price goes up (>0 percent difference) or down (<0 price difference). This is +1 for why I usually play with shares.
Some statistics:
#0) As a baseline/null hypothesis, after ER on the SPY500 since Mar 2019, 50-51% price movements in the AH/PM are positive (>0) and ~46-47% are negative (<0).
#1) For NOPE_MAD >= +3 sigma, roughly 68% of price movements are positive after earnings.
#2) For NOPE_MAD <= -3 sigma, roughly 29% of price movements are positive after earnings.
#3) When using a logistic model of only data including NOPE_MAD >= +3 sigma or NOPE_MAD <= -3 sigma, and option/share vol >= 0.4 (around 25% of all ERs observed), I was able to achieve 78% predictive accuracy on direction.

Caveats/Read This

Like all models, NOPE is wrong, but perhaps useful. It's also fairly new (I started working on it around early August 2020), and in fact, my initial hypothesis was exactly incorrect (I thought the opposite would happen, actually). Similarly, as commenters have pointed out, the timeline of data I'm using is fairly compressed (since Mar 2019), and trends and models do change. In fact, I've noticed significantly lower accuracy since the coronavirus recession (when I measured it in early September), but I attribute this mostly to a smaller date range, more market volatility, and honestly, dumber option traders (~65% accuracy versus nearly 80%).
My advice so far if you do play ER with the NOPE method is to use it as following:
  1. Buy/short shares approximately right when the market closes before ER. Ideally even buying it right before the earnings report drops in the AH session is not a bad idea if you can.
  2. Sell/buy to close said shares at the first sign of major weakness (e.g. if the NOPE predicted outcome is incorrect).
  3. Sell/buy to close shares even if it is correct ideally before conference call, or by the end of the after-market/pre-market session.
  4. Only play tickers with high NOPE as well as high option/share vol.
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In my next post, which may be in a few days, I'll talk about potential use cases for SPY and intraday trends, but I wanted to make sure this wasn't like 7000 words by itself.
Cheers.
- Lily
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MAME 0.222

MAME 0.222

MAME 0.222, the product of our May/June development cycle, is ready today, and it’s a very exciting release. There are lots of bug fixes, including some long-standing issues with classics like Bosconian and Gaplus, and missing pan/zoom effects in games on Seta hardware. Two more Nintendo LCD games are supported: the Panorama Screen version of Popeye, and the two-player Donkey Kong 3 Micro Vs. System. New versions of supported games include a review copy of DonPachi that allows the game to be paused for photography, and a version of the adult Qix game Gals Panic for the Taiwanese market.
Other advancements on the arcade side include audio circuitry emulation for 280-ZZZAP, and protection microcontroller emulation for Kick and Run and Captain Silver.
The GRiD Compass series were possibly the first rugged computers in the clamshell form factor, possibly best known for their use on NASA space shuttle missions in the 1980s. The initial model, the Compass 1101, is now usable in MAME. There are lots of improvements to the Tandy Color Computer drivers in this release, with better cartridge support being a theme. Acorn BBC series drivers now support Solidisk file system ROMs. Writing to IMD floppy images (popular for CP/M computers) is now supported, and a critical bug affecting writes to HFE disk images has been fixed. Software list additions include a collection of CDs for the SGI MIPS workstations.
There are several updates to Apple II emulation this month, including support for several accelerators, a new IWM floppy controller core, and support for using two memory cards simultaneously on the CFFA2. As usual, we’ve added the latest original software dumps and clean cracks to the software lists, including lots of educational titles.
Finally, the memory system has been optimised, yielding performance improvements in all emulated systems, you no longer need to avoid non-ASCII characters in paths when using the chdman tool, and jedutil supports more devices.
There were too many HyperScan RFID cards added to the software list to itemise them all here. You can read about all the updates in the whatsnew.txt file, or get the source and 64-bit Windows binary packages from the download page.

MAME Testers Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

submitted by cuavas to emulation [link] [comments]

Summary of Tau-Chain Monthly Video Update - August 2020

Transcript of the Tau-Chain & Agoras Monthly Video Update – August 2020
Karim:
Major event of this past month: Release of the Whitepaper. Encourages everyone to read the Whitepaper because it’s going to guide our development efforts for the foreseeable future. Development is proceeding well on two major fronts: 1. Agoras Live website: Features are being added to it, only two major features are missing 2. TML: We identified ten major tasks to be completed before the next release. Three of them are optimization features which are very important for the speed and performance features of TML. In terms of time requirements, we feel very good to stay on schedule for the end of this year. We also are bringing in two extra resources to help us get there as soon as possible.
Umar:
Been working on changes in the string relation, especially moving from binary string representation to unistring. The idea is that now rather than having two arguments in the term, you would have a single argument for the string. Thus, the hierarchy changes from two to one and that has an effect on speed and on the storage. So the first few numbers that we calculated showed that we are around 10% faster than with the binary string. There are some other changes that need to be made with regards to the string which he is working on.
Tomas:
Had to revise how we encode characters in order to be compatible with the internet. It also was the last missing piece in order to compute persistence. The reason is that the stored data has to be portable and if TML needs characters and strings internally in the same encoding as it stores its own data, we can map strings directly into files and gain lots of speed with it. The code is now pushed in the repository and can be tested. He’s also working on a TML tutorial and likely before next update, there should be something available online.
Kilian:
Transcribed past month’s video update. You can find it on Reddit. Also, he has done more outreach towards potential partner universities and research groups and this month the response rate was better than earlier, most likely because of the whitepaper release. Positive replies include: University of Mannheim, Trier (Computational Linguistics & Digital Humanities), research group AI KR from within the W3C (https://www.w3.org/community/aik) articulated strong interest in getting a discussion going, particularly because they had some misconceptions about blockchain. They would like to have a Q&A session with a couple of their group members but first it’s important for us to have them read the whitepaper to get a basic understanding and then be able to ask respective questions. Other interested parties include the Computational Linguistics research group of the University of Groningen, Netherlands and also the Center for Language Technology of the University of Gothenburg, Sweden. We also got connected to the Chalmers University of Technology, Sweden. Also has done some press outreach in combination with the whitepaper, trying to get respective media outlets to cover our project, but so far hasn’t gotten feedback back. Been discussing the social media strategy with Ohad and Fola, trying to be more active on our channels and have a weekly posting schedule on Twitter including non-technical and technical contests that engage with all parts of our community. Furthermore, has opened up a discussion on Discord (https://discord.gg/qZtJs78) in the “Tau-Discussion” channel around the topics that Ohad mentioned he would first like to see discussed on Tau (see https://youtu.be/O4SFxq_3ask?t=2225):
  1. Definitions of what good and bad means and what better and worse means.
  2. The governance model over Tau.
  3. The specification of Tau itself and how to make it grow and evolve even more to suit wider audiences. The whole point of Tau is people collaborating in order to define Tau itself and to improve it over time, so it will improve up to infinity. This is the main thing, especially initially, that the Tau developers (or rather users) advance the platform more and more.
If you are interested in participating in the discussion, join our Discord (https://discord.gg/qZtJs78) and post your thoughts – we’d appreciate it! Also has finished designing the bounty claiming process, so people that worked on a bounty now can claim their reward by filling out the bounty claiming form (https://forms.gle/HvksdaavuJbu4PCV8). Been also working on revamping the original post in the Bitcointalk-Thread. It contains a lot of broken links and generally is outdated, so he’s using the whitepaper to give it a complete overhaul. With the whitepaper release, the community also got a lot more active which was great to see and thus, he dedicated more time towards supporting the community.
Mo’az:
Finished multiple milestones with regards to the Agoras Live website: 1. Question part where people post their requests and knowledge providers can help them with missing knowledge. 2. Have been through multiple iterations of how to approach the services in the website. How the service seeker can discover new people through the website. 3. Connected the limited, static categories on the website to add more diversity to it. By adding tags, it will be easier for service seekers to find what they are looking for. 4. Onboarding: Been working on adding an onboarding step for the user, so the user chooses categories of his interest and as a result, he will find the homepage to be more personalized towards him and his interests. 5. New section to the user profile added: The service that the knowledge provider can provide. Can be added as tags or free text. 6. Search: Can filter via free text and filter by country, language, etc. 7. Been working on how to display the knowledge providers on the platform.
Andrei:
Improved look of the Agoras Live front page: Looks more clean. Finetuned search options. Redesigned the header. It now has notification icons. If you query a knowledge provider for an appointment, he will receive a notification about the new appointment to be approved or rejected. You can also add a user to your favorites. Front page now randomly displays users. Also implemented email templates, e.g. a thank you email upon registration or an appointment reminder. What is left to do is the session list and then the basic engine will be ready. Also needs to implement the “questions” section.
Juan:
Has switched towards development of TML related features. Been working mainly on the first order logic support. Has integrated the formula parser with the TML core functionality. With this being connected, we added to TML quantified Boolean function solving capability in the same way as we get the first order logic support. It’s worth mentioning that this feature is being supported by means of the main optimized BDD primitives that we already have in the TML engine. Looking forward to make this scalable in terms of formula sizes. It’s a matter of refining the Boolean solution and doing proper tests to show this milestone to the community in a proper way.
Fola:
Have been discussing the feasibility of a token swap towards ERC20 from the Omni token with exchanges and internally with the team. Also has been discussing the social media strategy with Kilian. As we update with the new visual identity and the branding, it’s a good time to boost our social media channels and look ready for the next iteration of our look and feel. Continuing on the aspects of our visual identity and design, he’s been talking to quite a number of large agencies who have been involved in some of the larger projects in the software space. One being Phantom (https://phantom.land) who designed the DeepMind website (https://deepmind.com), the other one being Outcast (https://theoutcastagency.com) who have been working with Intel and SalesForce. We aren’t sure yet with which company we go but it’s been good to get insight into how they work and which steps they’d take into getting our project out to the wider audience. That whole process has been a lot of research into what kind of agencies we’d want to get involved with. Also, with the release of the whitepaper being such a big milestone in the history of the company, he’s been doing a lot of reading of that paper. We’re also looking to get more manpower involved with the TML website. Also going to hire a frontend developer for the website and the backend will be done according to Ohad’s requirements. Also, as a response of the community’s feedback towards the Omni deck not being user friendly, he did some outreach to the Omni team and introduced them to a partner exchange for Agoras Live. They have an “exchange-in-a-box” service which may help Omni to have a much more usable interface for the Omni Dex, so hopefully they will be working together to improve the usability of the Omni Dex.
Ohad:
Finished writing the community draft of the whitepaper. The final version will contain changes according to the community’s feedback and more elaboration on more topics that weren’t inserted in the current paper, including logics for law and about the full process of Tau. And, as usual, he’s been doing more research of second order logic, specifically, Boolean options and also analyzing the situation where the formulas in conjunctive normal form trying to extract some information from such a cnf. Also, what Juan mentioned about first order logic: People who are already familiar with TML will see that now with this change, the easiness of using TML got much more advanced. In first order formulas, expressing yourself has become much easier than before.
Q&A:
Q: What is the difference between Horn Second Order Logic and Krom Second Order Logic?
A: Horn and Krom are special cases of cnf (conjunctive normal form). Conjunctive normal form means the formula has the form of n conjunction between clauses. This clause and this clause while each clause is a disjunction of atoms: It’s this or this or this or that. And now any formula can be written in conjunctive form. Any formula can be brought to this form. Krom is the case where each clause contains exactly two atoms and Horn is the case where at most one atom in every clause is positive – thre rest are negated, that’s the definition.
Q: Now that the whitepaper has been released, how do you think it will affect the work of the developers?
A: We see the whitepaper as being a roadmap of development for us, so it will essentially be the vision that we are working to implement. Of course, we have to turn it into much more specific tasks, but as you saw from the detailed progress from last month, that’s exactly what we do.
Q: When can we expect the new website?
A: We’ve just updated the website with the whitepaper and the new website should be launching after we get the branding done. There’s a lot of work to be done and a lot of considerations taking place. We have to get the graphics ready and the front end done. The branding is the most important step we have to get done and once that is complete, we will launch the new website.
Q: What needs to be resolved next before we get onto a solid US exchange?
A: With the whitepaper released, that’s probably been the biggest hurdle we had to get over. At this point, we still have to confirm some elements of the plan with the US regulators and we do need to have some sort of product available. Be that the TML release or Agoras Live, there needs to be something out for people to use. So, in conjunction with the whitepaper and approval from the US regulators, we need to have a product available to get onto US exchanges.
Q: Does the team still need to get bigger to reach cruising speed, if so, how much by and in which areas?
A: Of course, any development team would like to have as many resources as possible but working with the resources we that have right now, we are making significant progress towards the two development goals that we have, both the Agoras Live website and the TML engine. But we are bringing in at least two more resources in the near future but there’s no lack of work to be done and also there’s no lack of progress.
Q: Will Prof. Carmi continue to work in the team and if so, in what capacity?
A: Sure, Prof. Carmi will continue coordinating with us. Right now, he’s working on the mathematics of certain features in the derivatives market that Agoras is planned to have, and also ongoing research in relevant logic.
Q: Will you translate the whitepaper into other languages?
A: Yes, we expect translations of the whitepaper to occur. The most important languages that comprise our community, e.g. Chinese. What languages exactly, we cannot tell right now, but mainly the most prominent languages that comprise our community.
Q: Is the roadmap on the website still correct and, when will we move to the next step?
A: We will be revamping the website soon including the roadmap that will be a summary of what’s been published in the whitepaper but the old version of the roadmap on the website is no longer up-to-date.
Q: What are the requirements for Agoras to have its own chain?
A: If the question means why Agoras doesn’t have its own chain right now, well there is no special reason. We need to reach there and we will reach there.
Q: When Agoras switches to its own chain, will you need to create a new payments system from scratch?
A: No, we won’t have to. We will have to integrate with the new payment channel but that’s something we are planning to do anyway. We will be integrating with several exchanges and several payment channels so it won’t be a huge task. Most of the heavy lifting is in the wallet and key management which will be done on the client side but we’re already planning on having more than one payment gateway anyway so having one more is no problem.
Q: When can we see Tau work with a real practical example?
A: For examples of applications of TML, we are currently working on a TML tutorial and a set of demos. Two of our developers are currently working on it and it’s going to be a big part of our next release.
Q: How can we make speaking in formal languages easier, with an example?
A: Coming up with a usable and convenient formal language is a big task which maybe it’s even safe to say no one achieved up until today. But we solve this problem indirectly yet completely by not coming up with any language but letting languages to be created and evolve over time through the internet of languages. We don’t have any solution of how to make formal languages very easy for everyone. It will be a collaborative effort over Tau together to reach there over time. You can see in the whitepaper in the section 4.2 about “The Critical Mass and the Tau Chain Reaction”.
Q: What are the biggest limitations of Tau and, are they solvable?
A: TML cannot do everything that requires more than polynomial space to be done and there are infinitely many things like this. For example, you can look up x time or x space complete problems. We would want to say elementary but there is no elementary complete problem but there are complete problems in each of the levels of elementary. All those, TML cannot do because this is above polynomial space. Another drawback of TML which comes from the usage of BDDs is arithmetic. In particular, multiplication. Multiplication is highly inefficient in TML because of the nature of BDDs and of course BDDs bring so many more good things that even this drawback of slow multiplication is small compared to all the possibilities that this gives us. Another limitation, which we will emphasize in the next version of the whitepaper, is the satisfiability problem. The satisfiability problem of a formula without a model to ask whether a model exists – not a model checking like right now but to ask whether a model exists – this is undecidable already on very restricted classes as follows from Trakhtenbrot’s theory. So in particular, the containment problem, the scalability problem, the validity problem, they all are undecidable in TML as is and for them to be decidable, we need to restrict even more the expressive power and look at narrower fragments of the language. But again, this will be more emphasized in the next version of the whitepaper.
Q: It looks years for projects such as Maidsafe to build something mediocre, why should Agoras be able to do similar or better in less time?
A: Early on in the life of the Tau project, we’ve identified the computational resources marketplace as one of the possible applications of Tau, so it is very much on our roadmap. However, as you mentioned, there are some other projects, e.g. Filecoin, which is specifically focusing on the problem of storage. So even though it’s on our roadmap, we’re not there yet but we are watching closely what our competitors in this field are doing. While they haven’t yet delivered on their promise of an open and distributed storage network, we feel that at some point we will have more value to bring to the project. So distributed storage is on our roadmap but it’s not a priority for us right now but eventually we’ll get there.
Q: What are the requirements in scalability, e.g. permanent storage etc.?
A: We haven’t answered that question yet.
Q: Will Tau be able to run on a mobile phone?
A: Definitely, Yes. We’re planning on being available on all computational platforms, be it a server, laptop, phone or an iPad type of device.
Q: Given a vast trove of knowledge, how can Tau determine relevance? Can it also build defenses against spam attacks and garbage data?
A: Tau doesn’t offer any predetermined solution to this. It is basically all up to the user. The user will have to define what’s criminal and what’s not. Of course, most users will not bother with defining this but they will be able to automatically agree to people who already defined it and by that import their definitions. So bottom line: It’s really up to the users.
Q: What are your top priorities for the next three months?
A: Our goal for this year (2020) is to release a first version of Agoras Live and of TML.
Q: Ohad mentioned the following at the start of the year: Time for us to work on Agoras. We need to create the Agoras team and commence work. We made a major improvement in one of Agoras’ aspects in the form of theatrical breakthrough but we’re not ready yet to share the details publicly. Is there any further news or progress with the development of Agoras?
A: If the question is whether there has been more progress in the development of Agoras, specifically with regards to new discoveries for the derivatives market, then the answer is of course yes. Professor Carmi is now working on those inventions related to the derivatives market. We still keep them secret and of course, with Agoras Live, knowledge sharing for money is coming.
submitted by m4nki to tauchain [link] [comments]

MAME 0.222

MAME 0.222

MAME 0.222, the product of our May/June development cycle, is ready today, and it’s a very exciting release. There are lots of bug fixes, including some long-standing issues with classics like Bosconian and Gaplus, and missing pan/zoom effects in games on Seta hardware. Two more Nintendo LCD games are supported: the Panorama Screen version of Popeye, and the two-player Donkey Kong 3 Micro Vs. System. New versions of supported games include a review copy of DonPachi that allows the game to be paused for photography, and a version of the adult Qix game Gals Panic for the Taiwanese market.
Other advancements on the arcade side include audio circuitry emulation for 280-ZZZAP, and protection microcontroller emulation for Kick and Run and Captain Silver.
The GRiD Compass series were possibly the first rugged computers in the clamshell form factor, possibly best known for their use on NASA space shuttle missions in the 1980s. The initial model, the Compass 1101, is now usable in MAME. There are lots of improvements to the Tandy Color Computer drivers in this release, with better cartridge support being a theme. Acorn BBC series drivers now support Solidisk file system ROMs. Writing to IMD floppy images (popular for CP/M computers) is now supported, and a critical bug affecting writes to HFE disk images has been fixed. Software list additions include a collection of CDs for the SGI MIPS workstations.
There are several updates to Apple II emulation this month, including support for several accelerators, a new IWM floppy controller core, and support for using two memory cards simultaneously on the CFFA2. As usual, we’ve added the latest original software dumps and clean cracks to the software lists, including lots of educational titles.
Finally, the memory system has been optimised, yielding performance improvements in all emulated systems, you no longer need to avoid non-ASCII characters in paths when using the chdman tool, and jedutil supports more devices.
There were too many HyperScan RFID cards added to the software list to itemise them all here. You can read about all the updates in the whatsnew.txt file, or get the source and 64-bit Windows binary packages from the download page.

MAME Testers Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

submitted by cuavas to MAME [link] [comments]

MAME 0.222

MAME 0.222

MAME 0.222, the product of our May/June development cycle, is ready today, and it’s a very exciting release. There are lots of bug fixes, including some long-standing issues with classics like Bosconian and Gaplus, and missing pan/zoom effects in games on Seta hardware. Two more Nintendo LCD games are supported: the Panorama Screen version of Popeye, and the two-player Donkey Kong 3 Micro Vs. System. New versions of supported games include a review copy of DonPachi that allows the game to be paused for photography, and a version of the adult Qix game Gals Panic for the Taiwanese market.
Other advancements on the arcade side include audio circuitry emulation for 280-ZZZAP, and protection microcontroller emulation for Kick and Run and Captain Silver.
The GRiD Compass series were possibly the first rugged computers in the clamshell form factor, possibly best known for their use on NASA space shuttle missions in the 1980s. The initial model, the Compass 1101, is now usable in MAME. There are lots of improvements to the Tandy Color Computer drivers in this release, with better cartridge support being a theme. Acorn BBC series drivers now support Solidisk file system ROMs. Writing to IMD floppy images (popular for CP/M computers) is now supported, and a critical bug affecting writes to HFE disk images has been fixed. Software list additions include a collection of CDs for the SGI MIPS workstations.
There are several updates to Apple II emulation this month, including support for several accelerators, a new IWM floppy controller core, and support for using two memory cards simultaneously on the CFFA2. As usual, we’ve added the latest original software dumps and clean cracks to the software lists, including lots of educational titles.
Finally, the memory system has been optimised, yielding performance improvements in all emulated systems, you no longer need to avoid non-ASCII characters in paths when using the chdman tool, and jedutil supports more devices.
There were too many HyperScan RFID cards added to the software list to itemise them all here. You can read about all the updates in the whatsnew.txt file, or get the source and 64-bit Windows binary packages from the download page.

MAME Testers Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

submitted by cuavas to cade [link] [comments]

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