diff --git a/docs/devguide02.md b/docs/devguide02.md index 7a0d051..d18f5f7 100755 --- a/docs/devguide02.md +++ b/docs/devguide02.md @@ -157,5 +157,5 @@ await conditionalTokens.prepareCondition( The condition ID for this condition can be calculated as `0x3bdb7de3d0860745c0cac9c1dcc8e0d9cb7d33e6a899c2c298343ccedf1d66cf` . -In this case, the condition was created with two slots: one which represents the low end of the range (0) and another which represents the hi end (1000). The slots' reported payout values should indicate how close the answer was to these endpoints. For example, if the oracle -`0xCafEBAbECAFEbAbEcaFEbabECAfebAbEcAFEBaBe` makes a report that the payout vector is `[9/10, 1/10]`, then the oracle essentially states that the score was 100, as the slot corresponding to the low end is worth nine times what the slot corresponding with the hi end is worth, meaning the score should be nine times, closer to 0 than it is close to 1000. Likewise, if the payout vector is reported to be `[0, 1]`, then the oracle is saying that the score was *at least* 1000. +In this case, the condition was created with two slots: one which represents the low end of the range (0) and another which represents the high end (1000). The slots' reported payout values should indicate how close the answer was to these endpoints. For example, if the oracle +`0xCafEBAbECAFEbAbEcaFEbabECAfebAbEcAFEBaBe` makes a report that the payout vector is `[9/10, 1/10]`, then the oracle essentially states that the score was 100, as the slot corresponding to the low end is worth nine times what the slot corresponding with the high end is worth, meaning the score should be nine times, closer to 0 than it is close to 1000. Likewise, if the payout vector is reported to be `[0, 1]`, then the oracle is saying that the score was *at least* 1000. diff --git a/docs/devguide03.md b/docs/devguide03.md index 31a7f7a..aa57d60 100755 --- a/docs/devguide03.md +++ b/docs/devguide03.md @@ -81,8 +81,8 @@ must be performed: `0x52ff54f0f5616e34a2d4f56fb68ab4cc636bf0d92111de74d1ec99040a8da118`, or `37540785828268254412066351790903087640191294994197155621611396915481249947928`. - An `odd` flag is set according to whether the hiest bit of the hash - result is set. In this case, because the hiest bit of the hashing + An `odd` flag is set according to whether the highest bit of the hash + result is set. In this case, because the highest bit of the hashing result is not set,`odd = false`. 2. The x-coordinate gets incremented by one modulo the order of the @@ -121,8 +121,8 @@ must be performed: 4. Note that the base field occupies 254 bits of space, meaning the x-coordinate we found also occupies 254 bits of space, and has - two free bits in an EVM word (256 bits). Leave the hiest bit - unset, and set the next hiest bit if `odd == true`. In our + two free bits in an EVM word (256 bits). Leave the highest bit + unset, and set the next highest bit if `odd == true`. In our example, `odd` is unset, so we're done, and the collection ID for `(A|B)` is `15652542956428979189819946045645812551494983836899331958922359020836023739349`, @@ -142,7 +142,7 @@ following manner: 1. Decompress the constituent collection IDs into elliptic curve point coordinates. Take the low 254 bits as the x-coordinate, and pick the y-coordinate which is even or odd depending on the value of the - second hiest bit. + second highest bit. - `(A|B)`, which has a collection ID of `0x229b067e142fce0aea84afb935095c6ecbea8647b8a013e795cc0ced3210a3d5`, @@ -172,7 +172,7 @@ following manner: 4596536621806896659272941037410436605631447622293229168614769592376282983323) 3. Compress the result by taking the x-coordinate, and setting the - second hiest bit, which should be just outside the x-coordinate, + second highest bit, which should be just outside the x-coordinate, depending on whether the y-coordinate was odd. The combined collection ID for `(A|B)&(LO)` is `0x6f722aa250221af2eba9868fc9d7d43994794177dd6fa7766e3e72ba3c111909`. diff --git a/docs/game2.md b/docs/game2.md index c139b46..bcb829f 100755 --- a/docs/game2.md +++ b/docs/game2.md @@ -25,7 +25,7 @@ In Tic Tac Toe, a player has 9 different options for the first move. So, the vot ![](assets/Conditional_TokenGames-06.png) -Everyone participating in the futarchy market would now decide the best move to win the overall game, by buying the correspondent outcome token in the market. Let's imagine the crowd decided to go for B2, i.e. the most hily valued outcome token was B2 at the specified market end time. The opponent player then chooses to claim square A3. +Everyone participating in the futarchy market would now decide the best move to win the overall game, by buying the correspondent outcome token in the market. Let's imagine the crowd decided to go for B2, i.e. the most highly valued outcome token was B2 at the specified market end time. The opponent player then chooses to claim square A3. ![](assets/Conditional_Token_Games-04.png) @@ -43,7 +43,7 @@ This game of a crowd-sourced Futarchy AI playing Tic Tac Toe is, of course, a ve ![](assets/Conditional_Token_Games-05.png) -So why should we make such a simple game a bit more cumbersome? Putting futarchy to the test in gamified environments may be one way of rapid-prototyping how well futarchy works for gathering diverse opinions in limited timeframes, before moving on to more complex or hi stake challenges. Just imagine, one day our little Futarchy AI may be facing the then-old [AlphaGo](https://deepmind.com/research/case-studies/alphago-the-story-so-far). +So why should we make such a simple game a bit more cumbersome? Putting futarchy to the test in gamified environments may be one way of rapid-prototyping how well futarchy works for gathering diverse opinions in limited timeframes, before moving on to more complex or high stake challenges. Just imagine, one day our little Futarchy AI may be facing the then-old [AlphaGo](https://deepmind.com/research/case-studies/alphago-the-story-so-far). *Let's see if we can beat it together!* diff --git a/docs/intro1.md b/docs/intro1.md index 4e88469..39c3850 100755 --- a/docs/intro1.md +++ b/docs/intro1.md @@ -5,14 +5,14 @@ sidebar_label: A short primer on Conditional Tokens --- **Gnosis anticipates a tokenized future in which no single currency is dominant, and tradable asset classes take on increasing informational complexity. Conditional tokens that enable prediction markets are one of these new asset classes.** -To better understand the reasoning behind the development of the conditional token framework, it’s helpful to understand the basic concept of a prediction market. Prediction markets—also referred to as information markets, idea futures, event derivatives, decision markets, or virtual stock markets—are exchange-traded markets where individuals stake on the outcome of an event. In blockchain-based prediction markets, participants stake on the market in the form of event contracts. These contracts specify the different possible outcomes of a future event, a payment structure based on those outcomes, and the event’s outcome date. Unlike financial markets such as stock or commodities futures, which traders use to hedge against risk (i.e., farmers use futures markets to hedge against low crop prices, airlines use futures markets to hedge against hi fuel prices), prediction markets primarily seek to aggregate information on particular topics of interest. The principal informational value of a prediction market lies in the price of the futures themselves, which not only represent the average assessment of market participants concerning the likelihood of an event’s outcome, but also the confidence level different participants have in their predictions. +To better understand the reasoning behind the development of the conditional token framework, it’s helpful to understand the basic concept of a prediction market. Prediction markets—also referred to as information markets, idea futures, event derivatives, decision markets, or virtual stock markets—are exchange-traded markets where individuals stake on the outcome of an event. In blockchain-based prediction markets, participants stake on the market in the form of event contracts. These contracts specify the different possible outcomes of a future event, a payment structure based on those outcomes, and the event’s outcome date. Unlike financial markets such as stock or commodities futures, which traders use to hedge against risk (i.e., farmers use futures markets to hedge against low crop prices, airlines use futures markets to hedge against high fuel prices), prediction markets primarily seek to aggregate information on particular topics of interest. The principal informational value of a prediction market lies in the price of the futures themselves, which not only represent the average assessment of market participants concerning the likelihood of an event’s outcome, but also the confidence level different participants have in their predictions. ![pm-infographic](assets/pm_infographic.png) Prediction markets have far-reaching potential as a prognostic tool. From weather forecasting to abating the destruction of the Great Barrier Reef, learn more about the vast range of use cases for PMs by delving into our blog posts on the topic. -Simple prediction markets, including our first contracts and also other known decentralized prediction market platforms such as Augur, lack sufficient infrastructure to support deeper combinatorial markets. These more complex markets provide an invaluable means by which to achieve hier resolution information discovery in respect to conditional and interdependent probabilities of future events and their perceived value. +Simple prediction markets, including our first contracts and also other known decentralized prediction market platforms such as Augur, lack sufficient infrastructure to support deeper combinatorial markets. These more complex markets provide an invaluable means by which to achieve higher resolution information discovery in respect to conditional and interdependent probabilities of future events and their perceived value. In the following section, we will analyze the setup of known prediction markets and their shortcomings, before outlining how combinatorial markets with conditional tokens can solve current deficits. ## Existing Approach to Combinatorial Markets @@ -74,5 +74,5 @@ To summarize, conditional tokens allow you to: 2. Make complex markets about how the likelihood of an event is affected by any other event. (For example: What is the probability of a global recession, if a trade war breaks out between the United States and China in the next year?) 3. Trade any asset under the condition that a specific event happens. For market observers, these markets will surface asset prices in different possible futures. (For example: you could have bought a tokenized equivalent of the British Pound contingent on the condition that no hard Brexit happens.) -Previously such instruments could only be created at a hi cost by financial institutions. The arrival of conditional tokens on Ethereum brings down the costs to a few cents and give access to everyone. All conditional tokens can be globally accessible, and payouts are securely (and cheaply) executed through smart contracts. +Previously such instruments could only be created at a high cost by financial institutions. The arrival of conditional tokens on Ethereum brings down the costs to a few cents and give access to everyone. All conditional tokens can be globally accessible, and payouts are securely (and cheaply) executed through smart contracts. diff --git a/docs/intro2.md b/docs/intro2.md index 5d156ab..ba92f0f 100755 --- a/docs/intro2.md +++ b/docs/intro2.md @@ -27,7 +27,7 @@ Each participant begins in a neutral position, with a set of all outcome token f ### Key Takeaway -This brings us to the central point of this section: trading conditional tokens is the same as predicting which outcome is more likely. Suppose a participant believes Yang will be elected. They may sell their “Trump is elected” tokens at whatever price the market will bear, and later redeem their “Yang is elected” tokens at “par” value when (and if) Yang is elected. Trading conditional tokens helps discover the price of different opinions in a neutral way, as hily probable outcomes trade close to their redeemable par value, and hily improbable outcomes naturally find their market price near zero. +This brings us to the central point of this section: trading conditional tokens is the same as predicting which outcome is more likely. Suppose a participant believes Yang will be elected. They may sell their “Trump is elected” tokens at whatever price the market will bear, and later redeem their “Yang is elected” tokens at “par” value when (and if) Yang is elected. Trading conditional tokens helps discover the price of different opinions in a neutral way, as highly probable outcomes trade close to their redeemable par value, and highly improbable outcomes naturally find their market price near zero. Readers will notice that, implicitly, there are two ways to enter a prediction market. One way is to buy a conditional token from another participant. Another way is to collateralize the issuance of new tokens (all outcomes) and divest of the unwanted outcomes. That is, sell the outcomes one thinks are overpriced. @@ -36,6 +36,6 @@ The supply and demand—buyers and sellers —of “Yang is elected” and “Tr ## Other possible use cases -Conditional tokens are built on the ERC-1155 token standard, which affords numerous advantages for their multiple use cases. For instance, ERC-1155 batch sends substantially decrease gas costs for users, making them ideal within gaming environments that encompass different tokens and hi-velocity economies. +Conditional tokens are built on the ERC-1155 token standard, which affords numerous advantages for their multiple use cases. For instance, ERC-1155 batch sends substantially decrease gas costs for users, making them ideal within gaming environments that encompass different tokens and high-velocity economies. The use case section explores how the conditional token standard can be used to improve existing decentralized applications (dapps). In the tutorials section, you’ll find the tools and know-how needed to set up, inspect, and apply the conditional tokens framework to your own projects—as well as some inspiration regarding other use cases for this new standard beyond prediction markets. diff --git a/website/pages/en/index.js b/website/pages/en/index.js index 2c2c4bc..de5365d 100755 --- a/website/pages/en/index.js +++ b/website/pages/en/index.js @@ -73,7 +73,7 @@ class HomeSplash extends React.Component {
-

Conditional Tokens are a new, application-agnostic, asset class designed to facilitate the creation of hily liquid prediction markets. They enable combinatorial outcomes for hi resolution information discovery through prediction markets.

+

Conditional Tokens are a new, application-agnostic, asset class designed to facilitate the creation of highly liquid prediction markets. They enable combinatorial outcomes for high resolution information discovery through prediction markets.

The Conditional Tokens Framework allows you to:

diff --git a/website/siteConfig.js b/website/siteConfig.js index 865a904..0e6cece 100644 --- a/website/siteConfig.js +++ b/website/siteConfig.js @@ -78,8 +78,8 @@ const siteConfig = { // This copyright info is used in /core/Footer.js and blog RSS/Atom feeds. copyright: `Copyright © ${new Date().getFullYear()} Gnosis LTD`, - hilight: { - // hilight.js theme to use for syntax hilighting in code blocks. + highlight: { + // Highlight.js theme to use for syntax highlighting in code blocks. theme: 'default', },