The iceberg is commissioned (buy) by Jason.

1. The premise:The first time I learned how to write a strategy, I was commissioned by Ice Mountain: This article mainly refers to the strategy of the dam:https://www.fmz.com/strategy/188435In general, the strategy is not much different from the strategy of the big house, the writing is a bit rough.

2.前因When buying and selling digital currencies in bulk, the market price of the currency you want to buy/sell may be affected by the larger transaction amount.PullingI'm not going to sell it.The dishesI'm not sure. 1 pull: pull up the price, raise the currency 2 - Selling the coin directly, regardless of the price, causing the price to fall 3 Trading Currency Stocks: Currencies used for trading, such as the BTC/USDT trading pair,BTC is a trading currency.4 Value Currency Balance: The currency that the user charges, as in the example of BTC/USDT trading pairs, is the currency of the user.USDT is a currency

Ice Mountain commissioned:Operations: This is the process of automatically breaking down large orders intoMultiple assignmentsIn addition to the above, you can also set up an automated ordering system based on the latest buy/sell price and the price policy set by the customer.Automatic re-commissioning when the previous order is fully traded or the latest price deviates significantly from the current orderEffect: Reduce the impact of bulk buy/sell orders on the market price, making bulk purchases more affordableAvoid increasing your purchasing costs by paying large amounts to increase pricesIf you sell in bulk, you can.Avoid reducing your selling profit due to low prices caused by large sales orders

The data parameters are compared:

1. The price of the order is equal to the last purchase price X (~1-depth of the order)
2. Actual market commission depth = (last transaction price - last commission price) / last commission price
3. Random number of single purchases = average number of single purchases X ((100 - number of single average floating points) % + (number of single average floating points X2) % X average number of single purchases X random number 0 to 1
4. Available amount = Accounting currency, random number of purchases, minimum number of total remaining purchases
5. Quantity of purchases = Available amount / commission price
6. Total remaining purchases = Total purchases - (currency of initial accounting - currency of accounting)

The rules:

1. Automatic withdrawal if the latest transaction price is more than the depth of the order X2 (indicates too large deviation)
2. Stop commissioning when the total transaction of the strategy is equal to the total number of assignments
3. The latest transaction price is above the maximum limit of the purchase price stop order
4. Restore orders at the latest transaction price below the maximum purchase price limit

The main parameters:

1. Amount of purchase
2. Number of single purchases
3. The Depth of Engagement
4. The highest price
5. Price rounding intervals
6. Average floating point number of single purchases
7. Minimum number of transactions

I thought:

1. Get all outstanding orders and cancel orders
2. Acquire the initialization account balance to determine if it is greater than the total purchase amount
3. Calculating the commission price
4. Calculate the number of single purchases
5. Calculate the amount available
6. Calculate the number of purchases
7. Execute the purchase
8. Resting time
9. Judging whether the last order was successful
10. Successful logging
11. Failure to judge whether the deviation is too large and too large needs to be undone

Suggestions

1. Recommended to retest with ETH_USDT

The tactics are not perfect, and the buzzards who want to pass point to one or two.