Our DAOQE – 2100NEWS crypto DA (Tokens, Coins) orderbook quality evaluation is determined by taking into account “market quality” via quantitative order book data. We measure the market quality of each DA using a combination of 6 metrics (derived from trade and order book data) that aim to measure the cost to trade, liquidity, market stability. We analyze the market on the exchange with the highest volume. Our ultimate mission here is to promote transparency in the industry such that investors are more informed about where they invest. Due to the fact that trading volume may be fake, it is misleading to use it as a sole gauge of liquidity.
Two systems were implemented:
- An absolute scoring system to assign a fixed score to any given Digital asset (DA) orderbook and
- A relative grading system to assign each Digital Assets (DA) a grade (excellent, good, ordinary, Poor, Extremely weak) based on its total score in relative comparison to its peers on the markets.
Since the spread being calculated using the best bid and offer, it is misleading to use it as a sole gauge of liquidity and therefore as the market cost to trade; it must be used in conjunction with a depth measurement to find the likely transaction price for any given size of a transaction.
Investors or traders take a position in the market. They make money based on the price movements of the asset. We assume that exchange markets that contain traders looking to actively participate and invest in market movements (investor markets) are healthier than markets predominantly made up of market makers with no ‘real’ investors. Investors who take a position in the market are likely to trade more actively in times of volatility. Price movements may cause limit orders to be filled and new investors will likely join the market to react to price movements. In times of high volatility, market makers reduce volumes at each position or increase the spread they are willing to provide for the market. This makes the asset less liquid and means that smaller trades will cause larger price movements. To avoid large slippage, traders, therefore, need to trade smaller amounts.
1. Market Cost to Trade (spread)
Derived from order book data, a spread represents the difference between the best bid (Buy – the highest price at which someone is willing to buy) and the best ask (Sell – the lowest price at which someone is willing to sell). Spreads are tight when markets are liquid. The wider the spread, the more costly it is to trade on a given market. The tighter the spread, the more likely your order will be filled as the best bid and the best ask are closer together. Hence, the tighter the spread the higher grade. Higher spreads increase market friction.
Cumulative order volume in the book above is represented by the area below the green and red lines.
2. Liquidity (depth)
Digital Asset (DA) Order book depth represents the value of the active limit orders on a given Digital Asset (Token or Coin), it is the total volume of orders in the order book. It provides an idea of how much it is possible to trade on an exchange, and how much the price is likely to move if large amounts are traded. The deeper the books on a given market, the more liquidity that a market can provide. Liquidity is important in terms of maintaining an actively traded market, but also in terms of being able to reduce slippage and resist market shocks when large orders are matched. A DA with greater average depth is likely to be more stable (i.e flash crashes are much less likely) and allows trading of greater amounts at better prices. Thin order books can only handle a limited number of market participants, and most likely cannot match large orders without avoiding significant slippage and flash crashes. Therefore, the higher the market depth, the higher the grade.
3. Score calculation
An absolute scoring system to assign a fixed score to any given Digital asset (DA) orderbook. A market order is an order to buy/sell a certain quantity of the asset at the best available price in the book. The first asset will be traded at the ask (resp. bid) price and the remaining one(s) will be traded some ticks upper (resp. lower) in order to fill the order size. For Score calculation, we need the price of last executed trade and six prices and two total volumes from orderbook. Orderbook data helps determine where the price of particular Digital Asset could be heading as orders are filled. We make three tests in order to find out 6 best available prices (marked at the chart below) at which we can buy or sell the following amount of assets:
- two prices if we put market order for particular Digital Asset with such quantity that order value will be 0,1 BTC or equivalent value in (ETH, USDT …)
- two prices if we put market order for particular Digital Asset with such quantity that order value will be 1 BTC or equivalent value in (ETH, USDT …)
- two prices at the fifth price level of (ask/bid) side in the orderbook
Where depth Up is the total volume that would be required to move the price upwards to the fifth level of the ask side, and depth Down is the total volume that would be required to move the price downwards to the fifth level of the bid side.
4. Grade calculation
A relative grading system assigns each Digital Assets (DA) a grade based on its total score in relative comparison to its peers on the markets. We calculate peer’s Average Score and Standard deviation.
Grades are determined as:
Excellent <= score >= avg + 1.3*Stdev
Good <= avg+0.5*Stdev =< score < avg + 1.3*Stdev
Ordinary <= avg-0.125*Stdev =< score < avg + 0.5*Stdev
Poor <= avg-1.3*Stdev =< score < avg – 0.125*Stdev
Extremely weak <= score < avg – 1.3*Stdev
We hope you enjoyed reading our methodology. We are open to comments and suggestions and hope to build on this system in the future to make it as robust, transparent and helpful as possible.