diff --git a/_On_Ice/algo_config_backup.json b/_On_Ice/algo_config_backup.json index 6f9bf52..45d33c5 100644 --- a/_On_Ice/algo_config_backup.json +++ b/_On_Ice/algo_config_backup.json @@ -1,13 +1,25 @@ { - "Config_Updated_Timestamp": 1777098091913, - "Allow_Ordering_Aster": false, - "Allow_Ordering_Extend": false, - "Loop_Sleep_Sec": 5.00, - "Max_Target_Notional": 0.00, - "Min_Time_To_Funding_Minutes": 10, - "Price_Worsener_Aster": 0.0, - "Price_Worsener_Extend": 0.0, - "Target_Open_Cash_Position": 10, - "Print_Summary_Each_Loop" : true, - "Flip_Side_For_Testing": false + "Updated_Timestamp": 1777433705326, + "Config": { + "Loop_Sleep_Sec": 0.0, + "Max_Order_Over_Notional_Ratio": 1.05, + "Max_Target_Notional": 0.0, + "Min_Time_To_Funding_Minutes": 60, + "Min_Fund_Rate_Pct_To_Trade": 0.0, + "Price_Worsener_Aster": 0.0, + "Price_Worsener_Extend": -0.1, + "Switch_To_Taker_Seconds": 1, + "Target_Open_Cash_Position": 10 + }, + "Logging": { + "Log_Summary_Each_Loop": false, + "Print_Summary_Each_Loop": false + }, + "Overrides": { + "Allow_Ordering_Aster": true, + "Allow_Ordering_Extend": true, + "Flatten_Open_Positions": false, + "Flip_Side_For_Testing": false + } + } \ No newline at end of file diff --git a/algo.ipynb b/algo.ipynb index 5d468f0..9c2d0cd 100644 --- a/algo.ipynb +++ b/algo.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 4, + "execution_count": 22, "id": "d1eed397", "metadata": {}, "outputs": [], @@ -13,12 +13,13 @@ "import valkey\n", "\n", "with open('algo_config.json', 'r', encoding='utf-8') as file:\n", - " ALGO_CONFIG = json.load(file, object_hook=lambda d: structs.Algo_Config(**d))" + " ALGO_CONFIG = json.load(file)\n", + " ALGO_CONFIG = structs.Algo_Config(**ALGO_CONFIG)" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 23, "id": "c6151613", "metadata": {}, "outputs": [], @@ -38,23 +39,31 @@ "1" ] }, - "execution_count": 12, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "config_update = {\n", - " # 'Min_Time_To_Funding_Minutes': 60,\n", - " # 'Allow_Ordering_Aster': True,\n", - " # 'Allow_Ordering_Extend': True,\n", - " # 'Loop_Sleep_Sec': 0.00,\n", - " # 'Min_Fund_Rate_Pct_To_Trade': 0.001,\n", - " # 'Flip_Side_For_Testing': False,\n", - " # 'Price_Worsener_Extend': 0.0,\n", - " # 'Log_Summary_Each_Loop': False,\n", - " 'Print_Summary_Each_Loop': True,\n", - " 'Flatten_Open_Positions': False,\n", + " # 'Config': {\n", + " # 'Loop_Sleep_Sec': 0.00,\n", + " # 'Min_Time_To_Funding_Minutes': 60,\n", + " # 'Min_Fund_Rate_Pct_To_Trade': 0.001,\n", + " # 'Price_Worsener_Extend': 0.0,\n", + " # 'Price_Worsener_Aster': 0.0,\n", + " # 'Switch_To_Taker_Seconds': 1,\n", + " # },\n", + " 'Logging': {\n", + " 'Log_Summary_Each_Loop': False,\n", + " 'Print_Summary_Each_Loop': True,\n", + " },\n", + " # 'Overrides': {\n", + " # 'Allow_Ordering_Aster': True,\n", + " # 'Allow_Ordering_Extend': True,\n", + " # 'Flip_Side_For_Testing': False,\n", + " # 'Flatten_Open_Positions': False,\n", + " # },\n", "}\n", "VAL_KEY.publish('fr_orchestrator_input', json.dumps(config_update))" ] diff --git a/algo_config.json b/algo_config.json index 39b370f..874d047 100644 --- a/algo_config.json +++ b/algo_config.json @@ -1,16 +1,24 @@ { - "Config_Updated_Timestamp": 1777411434591, - "Allow_Ordering_Aster": true, - "Allow_Ordering_Extend": true, - "Loop_Sleep_Sec": 0.0, - "Max_Target_Notional": 0.0, - "Min_Time_To_Funding_Minutes": 60, - "Min_Fund_Rate_Pct_To_Trade": 0.0, - "Price_Worsener_Aster": 0.0, - "Price_Worsener_Extend": -0.1, - "Target_Open_Cash_Position": 10, - "Log_Summary_Each_Loop": false, - "Print_Summary_Each_Loop": true, - "Flatten_Open_Positions": false, - "Flip_Side_For_Testing": false + "Updated_Timestamp": 1777478176165, + "Config": { + "Loop_Sleep_Sec": 0.0, + "Max_Order_Over_Notional_Ratio": 1.05, + "Max_Target_Notional": 0.0, + "Min_Time_To_Funding_Minutes": 60, + "Min_Fund_Rate_Pct_To_Trade": 0.0, + "Price_Worsener_Aster": 0.0, + "Price_Worsener_Extend": -0.1, + "Switch_To_Taker_Seconds": 1, + "Target_Open_Cash_Position": 10 + }, + "Logging": { + "Log_Summary_Each_Loop": false, + "Print_Summary_Each_Loop": true + }, + "Overrides": { + "Allow_Ordering_Aster": true, + "Allow_Ordering_Extend": true, + "Flatten_Open_Positions": false, + "Flip_Side_For_Testing": false + } } \ No newline at end of file diff --git a/algo_orchestrator.py b/algo_orchestrator.py index 12969ec..6de9cd6 100644 --- a/algo_orchestrator.py +++ b/algo_orchestrator.py @@ -26,7 +26,6 @@ load_dotenv() LOG_FILEPATH: str = os.getenv("LOGS_PATH") + '/Fund_Rate_Algo_Orchestrator.log' ALGO_CONFIG: None | dict -# ALGO_CONFIG: None | Algo_Config = None async def orchestrator() -> None: global ALGO_CONFIG @@ -35,7 +34,7 @@ async def orchestrator() -> None: VK_PUBSUB = VAL_KEY.pubsub() VK_PUBSUB.subscribe(VK_IN) - print(f"Subscribed to '{VK_IN}'. Waiting for messages...") + logging.info(f"Subscribed to '{VK_IN}'. Waiting for messages...") for message in VK_PUBSUB.listen(): if message['type'] == 'message': @@ -46,7 +45,7 @@ async def orchestrator() -> None: with open('/algo_local_drive/algo_config.json', 'r', encoding='utf-8') as f: # ALGO_CONFIG = json.load(f, object_hook=lambda d: Algo_Config(**d)) ALGO_CONFIG = json.load(f) - ALGO_CONFIG['Config_Updated_Timestamp'] = timestamp + ALGO_CONFIG['Updated_Timestamp'] = timestamp for k, v in data.items(): if ALGO_CONFIG.get(k, None) is not None: @@ -54,12 +53,11 @@ async def orchestrator() -> None: VAL_KEY.set(VK_OUT, json.dumps(ALGO_CONFIG)) with open('/algo_local_drive/algo_config.json', 'w', encoding='utf-8') as f: - # print('SAVING FILE') json.dump(ALGO_CONFIG, f, indent=4) - print(f"Algo Config Updated @ {timestamp}; {data}") + logging.info(f"Algo Config Updated @ {timestamp}; {data}") except valkey.exceptions.ConnectionError as e: - print(f"Could not connect to Valkey. Please check the publish server is up; {e}") + logging.info(f"Could not connect to Valkey. Please check the publish server is up; {e}") except KeyboardInterrupt: logging.info('ORCHESTRATOR SHUTTING DOWN...') except Exception as e: @@ -78,7 +76,7 @@ async def main() -> None: with open('/algo_local_drive/algo_config.json', 'r', encoding='utf-8') as f: # ALGO_CONFIG = json.load(f, object_hook=lambda d: Algo_Config(**d)) ALGO_CONFIG = json.load(f) - ALGO_CONFIG['Config_Updated_Timestamp'] = round(datetime.now().timestamp()*1000) + ALGO_CONFIG['Updated_Timestamp'] = round(datetime.now().timestamp()*1000) # async with engine.connect() as CON: await orchestrator() diff --git a/docker-compose.yml b/docker-compose.yml index cfa8096..2473da0 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -1,4 +1,4 @@ -# tail -f Fund_Rate_Algo.log Fund_Rate_Aster_User.log Fund_Rate_Aster.log Fund_Rate_Extended_FR.log Fund_Rate_Extended_OB.log Fund_Rate_Extended_Trades.log Fund_Rate_Extended_User.log +# tail -f Fund_Rate_Algo_Orchestrator.log Fund_Rate_Algo.log Fund_Rate_Aster_User.log Fund_Rate_Aster.log Fund_Rate_Extended_FR.log Fund_Rate_Extended_OB.log Fund_Rate_Extended_Trades.log Fund_Rate_Extended_User.log services: # algo: diff --git a/engine_best_funding_rate.ipynb b/engine_best_funding_rate.ipynb index c7d80a9..d5c1eba 100644 --- a/engine_best_funding_rate.ipynb +++ b/engine_best_funding_rate.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 38, + "execution_count": 28, "id": "0b5ca901", "metadata": {}, "outputs": [], @@ -12,34 +12,26 @@ "import numpy as np\n", "from datetime import datetime\n", "import time\n", - "import json\n" + "import json\n", + "import valkey\n", + "from dataclasses import dataclass, field\n", + "\n", + "VAL_KEY = valkey.Valkey(host='localhost', port=6379, db=0, decode_responses=True)" ] }, { "cell_type": "code", - "execution_count": 93, - "id": "e33ec721", + "execution_count": 29, + "id": "20665e82", "metadata": {}, "outputs": [], "source": [ - "### Extended Current FR ###\n", - "r = json.loads(requests.get('https://api.starknet.extended.exchange/api/v1/info/markets').text)\n", - "df_extend_current_mkt_stats = pd.DataFrame(r['data'])\n", - "\n", - "df_extend_current_mkt_stats['funding_rate'] = df_extend_current_mkt_stats['marketStats'].apply(lambda x: x.get('fundingRate',{}))\n", - "df_extend_current_mkt_stats['funding_rate_ts'] = df_extend_current_mkt_stats['marketStats'].apply(lambda x: x.get('nextFundingRate',{}))\n", - "df_extend_current_mkt_stats['min_order_size'] = df_extend_current_mkt_stats['tradingConfig'].apply(lambda x: x.get('minOrderSize',{}))\n", - "df_extend_current_mkt_stats['min_price_change'] = df_extend_current_mkt_stats['tradingConfig'].apply(lambda x: x.get('minPriceChange',{}))\n", - "df_extend_current_mkt_stats['max_leverage'] = df_extend_current_mkt_stats['tradingConfig'].apply(lambda x: x.get('maxLeverage',{}))\n", - "\n", - "df_extend_current_fr = df_extend_current_mkt_stats[['status','name','assetName','collateralAssetName','category','min_order_size','min_price_change','max_leverage','funding_rate','funding_rate_ts']]\n", - "df_extend_current_fr['funding_rate_ts_dt'] = pd.to_datetime(df_extend_current_fr['funding_rate_ts'], unit='ms')\n", - "df_extend_current_fr = df_extend_current_fr.loc[df_extend_current_fr['status']=='ACTIVE',:]" + "### ********** TODO: ADD IN VOLUME DATA TO FILTER MKTS ###" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "id": "53647b40", "metadata": {}, "outputs": [], @@ -56,7 +48,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "id": "1f3b65ee", "metadata": {}, "outputs": [], @@ -70,27 +62,173 @@ }, { "cell_type": "code", - "execution_count": 94, + "execution_count": 32, + "id": "e33ec721", + "metadata": {}, + "outputs": [], + "source": [ + "### Extended Current FR ###\n", + "r = json.loads(requests.get('https://api.starknet.extended.exchange/api/v1/info/markets').text)\n", + "df_extend_current_mkt_stats = pd.DataFrame(r['data'])\n", + "\n", + "df_extend_current_mkt_stats['funding_rate'] = df_extend_current_mkt_stats['marketStats'].apply(lambda x: x.get('fundingRate',{}))\n", + "df_extend_current_mkt_stats['funding_rate_ts'] = df_extend_current_mkt_stats['marketStats'].apply(lambda x: x.get('nextFundingRate',{}))\n", + "df_extend_current_mkt_stats['min_order_size'] = df_extend_current_mkt_stats['tradingConfig'].apply(lambda x: x.get('minOrderSize',{}))\n", + "df_extend_current_mkt_stats['min_price_change'] = df_extend_current_mkt_stats['tradingConfig'].apply(lambda x: x.get('minPriceChange',{}))\n", + "df_extend_current_mkt_stats['max_leverage'] = df_extend_current_mkt_stats['tradingConfig'].apply(lambda x: x.get('maxLeverage',{}))\n", + "\n", + "\n", + "# df_extend_current_fr = df_extend_current_mkt_stats[['status','name','assetName','collateralAssetName','category','min_order_size','min_price_change','max_leverage','funding_rate','funding_rate_ts']]\n", + "# df_extend_current_fr['funding_rate_ts_dt'] = pd.to_datetime(df_extend_current_fr['funding_rate_ts'], unit='ms')\n", + "# df_extend_current_fr = df_extend_current_fr.loc[df_extend_current_fr['status']=='ACTIVE',:]" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "782a5d56", + "metadata": {}, + "outputs": [], + "source": [ + "@dataclass(kw_only=False)\n", + "class Asset_Leverage:\n", + " exchange: str\n", + " lh_asset: str\n", + " rh_asset: str\n", + " max_leverage: int\n", + " max_notional: float\n", + " # max_leverage_notional: list = field(default_factory=list)\n", + "\n", + "### MANUAL LEVERAGE DATA ###\n", + "LEVERAGE_BY_EXCH: list[Asset_Leverage] = [\n", + " Asset_Leverage('ASTER', 'ASTER', 'USDT', 75 , 20_000 ), Asset_Leverage('EXTEND', 'ASTER', 'USDT', 25, 400_000 ),\n", + " Asset_Leverage('ASTER', 'AAVE' , 'USDT', 10 , 115_290), Asset_Leverage('EXTEND', 'AAVE' , 'USDT', 50, 500_000 ),\n", + " Asset_Leverage('ASTER', '4' , 'USDT', 50 , 5_000 ), Asset_Leverage('EXTEND', '4' , 'USDT', 5 , 100_000 ),\n", + " Asset_Leverage('ASTER', 'BNB' , 'USDT', 100, 10_000 ), Asset_Leverage('EXTEND', 'BNB' , 'USDT', 50, 500_000 ),\n", + " Asset_Leverage('ASTER', 'BTC' , 'USDT', 150, 300_000), Asset_Leverage('EXTEND', 'BTC' , 'USDT', 50, 4_000_000),\n", + " Asset_Leverage('ASTER', 'CHIP' , 'USDT', 50 , 5_000 ), Asset_Leverage('EXTEND', 'CHIP' , 'USDT', 5 , 100_000 ),\n", + " Asset_Leverage('ASTER', 'CLU' , 'USDT', 50 , 10_000 ), Asset_Leverage('EXTEND', 'WTI' , 'USDT', 5 , 1_000_000),\n", + " Asset_Leverage('ASTER', 'DOGE' , 'USDT', 75 , 80_000 ), Asset_Leverage('EXTEND', 'DOGE' , 'USDT', 50, 500_000 ),\n", + " Asset_Leverage('ASTER', 'ENA' , 'USDT', 25 , 30_473 ), Asset_Leverage('EXTEND', 'ENA' , 'USDT', 50, 500_000 ),\n", + " Asset_Leverage('ASTER', 'ETH' , 'USDT', 150, 300_000), Asset_Leverage('EXTEND', 'ETH' , 'USDT', 50, 4_000_000),\n", + " Asset_Leverage('ASTER', 'HYPE' , 'USDT', 300, 1_000 ), Asset_Leverage('EXTEND', 'HYPE' , 'USDT', 50, 1_000_000),\n", + " Asset_Leverage('ASTER', 'INIT' , 'USDT', 50 , 5_000 ), Asset_Leverage('EXTEND', 'INIT' , 'USDT', 5 , 100_000 ),\n", + " Asset_Leverage('ASTER', 'LIT' , 'USDT', 50 , 2_500 ), Asset_Leverage('EXTEND', 'LIT' , 'USDT', 25, 400_000 ),\n", + " Asset_Leverage('ASTER', 'SOL' , 'USDT', 100, 50_000 ), Asset_Leverage('EXTEND', 'SOL' , 'USDT', 50, 1_000_000),\n", + " Asset_Leverage('ASTER', 'SUI' , 'USDT', 75 , 5_416 ), Asset_Leverage('EXTEND', 'SUI' , 'USDT', 50, 500_000 ),\n", + " Asset_Leverage('ASTER', 'TRUMP', 'USDT', 50 , 5_567 ), Asset_Leverage('EXTEND', 'TRUMP', 'USDT', 25, 400_000 ),\n", + " Asset_Leverage('ASTER', 'WLFI' , 'USDT', 25 , 104_869), Asset_Leverage('EXTEND', 'WLFI' , 'USDT', 10, 250_000 ),\n", + " Asset_Leverage('ASTER', 'XAG' , 'USDT', 100, 50_000 ), Asset_Leverage('EXTEND', 'XAG' , 'USDT', 10, 1_000_000),\n", + " Asset_Leverage('ASTER', 'XAU' , 'USDT', 75 , 2_500 ), Asset_Leverage('EXTEND', 'XAU' , 'USDT', 25, 2_000_000),\n", + " Asset_Leverage('ASTER', 'XMR' , 'USDT', 50 , 10_000 ), Asset_Leverage('EXTEND', 'XMR' , 'USDT', 25, 400_000 ),\n", + " Asset_Leverage('ASTER', 'XPT' , 'USDT', 3 , 30_000 ), Asset_Leverage('EXTEND', 'XPT' , 'USDT', 5 , 1_000_000),\n", + " Asset_Leverage('ASTER', 'XRP' , 'USDT', 100, 40_000 ), Asset_Leverage('EXTEND', 'XRP' , 'USDT', 50, 500_000 ),\n", + " Asset_Leverage('ASTER', 'ZEC' , 'USDT', 75 , 6_250 ), Asset_Leverage('EXTEND', 'ZEC' , 'USDT', 10, 250_000 ),\n", + " Asset_Leverage('ASTER', 'ZORA' , 'USDT', 5 , 100_000), Asset_Leverage('EXTEND', 'ZORA' , 'USDT', 5 , 100_000 ),\n", + "]\n", + "df_leverage_by_exch = pd.DataFrame(LEVERAGE_BY_EXCH)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, "id": "62815940", "metadata": {}, "outputs": [], "source": [ "### ASTER Current FR from Mark Price Req ###\n", - "r = json.loads(requests.get('https://fapi.asterdex.com/fapi/v3/premiumIndex').text)\n", - "df_aster_current_mkt_stats = pd.DataFrame(r)" + "# r = json.loads(requests.get('https://fapi.asterdex.com/fapi/v3/exchangeInfo').text)\n", + "# df_aster_current_mkt_stats = pd.DataFrame(r)\n", + "# ### ASTER Current FR from Mark Price Req ###\n", + "# r = json.loads(requests.get('https://fapi.asterdex.com/fapi/v3/premiumIndex').text)\n", + "# df_aster_current_mkt_stats = pd.DataFrame(r)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, + "id": "271a67c1", + "metadata": {}, + "outputs": [], + "source": [ + "### ASTER CURRENT FR - WS ###\n", + "df_aster_current_fr = pd.DataFrame(json.loads(VAL_KEY.get('fund_rate_aster_all')))\n", + "df_aster_current_fr = df_aster_current_fr[['s','E','r','T']].rename({'s':'symbol','E':'funding_rate_updated_ts_ms','r':'funding_rate','T':'next_funding_ts'}, axis=1)\n", + "df_aster_current_fr['funding_rate_updated_dt'] = pd.to_datetime(df_aster_current_fr['funding_rate_updated_ts_ms'], unit='ms')\n", + "df_aster_current_fr['funding_rate'] = df_aster_current_fr['funding_rate'].astype(float)\n", + "df_aster_current_fr['time_delta_to_next_funding'] = pd.to_datetime(df_aster_current_fr['next_funding_ts'], unit='ms') - pd.Timestamp.now()" + ] + }, + { + "cell_type": "code", + "execution_count": 36, "id": "1ce2fde4", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "### EXTEND CURRENT FR - WS ###\n", + "df_extended_current_fr = pd.DataFrame(json.loads(VAL_KEY.get('fund_rate_extended_all')))\n", + "df_extended_current_fr = df_extended_current_fr[['symbol','funding_rate_updated_ts_ms','funding_rate']]\n", + "df_extended_current_fr['funding_rate_updated_dt'] = pd.to_datetime(df_extended_current_fr['funding_rate_updated_ts_ms'], unit='ms')\n", + "df_extended_current_fr['funding_rate'] = df_extended_current_fr['funding_rate'].astype(float)\n", + "\n", + "# df_extended_current_fr = df_extended_current_fr.merge(df_extend_current_mkt_stats[['name','assetName','status', 'funding_rate_ts','max_leverage']].rename({'name':'symbol','funding_rate_ts':'next_funding_ts'}, axis=1), on='symbol', how='left')\n", + "df_extended_current_fr = df_extended_current_fr.merge(df_extend_current_mkt_stats[['name','assetName','status', 'funding_rate_ts']].rename({'name':'symbol','funding_rate_ts':'next_funding_ts'}, axis=1), on='symbol', how='left')\n", + "df_extended_current_fr = df_extended_current_fr.loc[df_extended_current_fr['status']=='ACTIVE',:]\n", + "df_extended_current_fr['USDT_Symbol'] = df_extended_current_fr['assetName'] + 'USDT'\n", + "df_extended_current_fr['time_delta_to_next_funding'] = pd.to_datetime(df_extended_current_fr['next_funding_ts'], unit='ms') - pd.Timestamp.now()" + ] }, { "cell_type": "code", - "execution_count": 95, + "execution_count": 37, + "id": "ff88b413", + "metadata": {}, + "outputs": [], + "source": [ + "### COMBINED CURRENT FR - WS ###\n", + "df_comb_current_fr = df_extended_current_fr.merge(df_aster_current_fr, left_on='USDT_Symbol', right_on='symbol', how='inner', suffixes=('_ext', '_ast'))\n", + "df_comb_current_fr['next_funding_at_same_time'] = (abs(df_comb_current_fr['time_delta_to_next_funding_ext'].dt.total_seconds() - df_comb_current_fr['time_delta_to_next_funding_ast'].dt.total_seconds()) / 60) < 1\n", + "df_comb_current_fr['net_funding_rate'] = (df_comb_current_fr[['funding_rate_ext', 'funding_rate_ast']].max(axis=1) - df_comb_current_fr[['funding_rate_ext', 'funding_rate_ast']].min(axis=1)).where(df_comb_current_fr['next_funding_at_same_time'], df_comb_current_fr['funding_rate_ext'])\n", + "df_comb_current_fr['net_funding_rate_abs'] = df_comb_current_fr['net_funding_rate'].abs()\n", + "\n", + "### NET MULT ###\n", + "df_comb_current_fr = df_comb_current_fr.merge(df_leverage_by_exch.loc[df_leverage_by_exch['exchange']=='EXTEND'], left_on='assetName', right_on='lh_asset').merge(df_leverage_by_exch.loc[df_leverage_by_exch['exchange']=='ASTER'], left_on='assetName', right_on='lh_asset', suffixes=('_ext', '_ast'))\n", + "df_comb_current_fr['net_mult'] = 1 / ( ( 0.5 / df_comb_current_fr['max_leverage_ext'] ) + ( 0.5 / df_comb_current_fr['max_leverage_ast'] ) )\n", + "df_comb_current_fr['net_mult'] = df_comb_current_fr['net_mult'].round(2)\n", + "df_comb_current_fr['net_mult_x_net_fr_abs'] = df_comb_current_fr['net_funding_rate_abs'] * df_comb_current_fr['net_mult']" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "f5ade993", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'symbol_ast': 'CHIPUSDT', 'symbol_extended': 'CHIP-USD'}" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_best_fr_rate = df_comb_current_fr[['symbol_ext','symbol_ast','net_mult_x_net_fr_abs','net_funding_rate_abs','net_funding_rate','next_funding_at_same_time']].sort_values(by='net_mult_x_net_fr_abs', ascending=False).reset_index(drop=True)\n", + "df_best_fr_rate['hourly_dollars_per_1k'] = df_best_fr_rate['net_mult_x_net_fr_abs'] * 1000\n", + "df_best_fr_rate['hourly_dollars_per_1k'] = df_best_fr_rate['hourly_dollars_per_1k'].round(2)\n", + "\n", + "best_next_funding_pair = {'symbol_ast':df_best_fr_rate['symbol_ast'][0],'symbol_extended':df_best_fr_rate['symbol_ext'][0]}\n", + "best_next_funding_pair" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "0972d5f4", "metadata": {}, "outputs": [ { @@ -103,2413 +241,277 @@ "type": "integer" }, { - "name": "symbol", + "name": "symbol_ext", "rawType": "str", "type": "string" }, { - "name": "markPrice", + "name": "symbol_ast", "rawType": "str", "type": "string" }, { - "name": "indexPrice", - "rawType": "str", - "type": "string" + "name": "net_mult_x_net_fr_abs", + "rawType": "float64", + "type": "float" }, { - "name": "estimatedSettlePrice", - "rawType": "str", - "type": "string" + "name": "net_funding_rate_abs", + "rawType": "float64", + "type": "float" }, { - "name": "lastFundingRate", - "rawType": "str", - "type": "string" + "name": "net_funding_rate", + "rawType": "float64", + "type": "float" }, { - "name": "interestRate", - "rawType": "str", - "type": "string" + "name": "next_funding_at_same_time", + "rawType": "bool", + "type": "boolean" }, { - "name": "nextFundingTime", - "rawType": "int64", - "type": "integer" - }, - { - "name": "time", - "rawType": "int64", - "type": "integer" + "name": "hourly_dollars_per_1k", + "rawType": "float64", + "type": "float" } ], - "ref": "913c6dcd-9dae-469b-b650-2f6d0f0daf1b", + "ref": "33130419-3234-458e-82da-43648a261793", "rows": [ [ "0", - "GNSUSD", - "0.65303424", - "0.65303424", - "0.65605033", - "0", - "0", - "1777420800000", - "1777395861000" - ], - [ - "1", - "TRUTHUSDT", 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1TRUTHUSDT0.009510970.009483490.009431090.000033390.0001000017773992000001777395861000
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3SBETUSDT7.055230387.0792346700.000050000.0000500017774208000001777395861000
4BANKUSDT0.033941850.033912300.034073090.000012500.0001000017773992000001777395861000
...........................
517BLESSUSDT0.005996190.005995970.005898930.000050000.0001000017774064000001777395861000
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519DYDXUSDT0.157561380.157547740.158820180.000100000.0001000017774208000001777395861000
520AMZNUSD258.86770000258.86770000259.864696410017774208000001777395861000
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0ACTIVEENA-USDENAUSDCrypto1000.0000150.000.00001317773956000002026-04-28 17:00:00ENAUSDT
1ACTIVEAVNT-USDAVNTUSDCrypto100.000110.000.00001317773956000002026-04-28 17:00:00AVNTUSDT
2ACTIVEEUR-USDEURUSDTradFi100.00001100.000.00001517773956000002026-04-28 17:00:00EURUSDT
3ACTIVESUI-USDSUIUSDCrypto100.000150.000.00001317773956000002026-04-28 17:00:00SUIUSDT
4ACTIVEWIF-USDWIFUSDCrypto100.000125.00-0.00003517773956000002026-04-28 17:00:00WIFUSDT
.......................................
112ACTIVEFARTCOIN-USDFARTCOINUSDCrypto100.0000125.000.00001317773956000002026-04-28 17:00:00FARTCOINUSDT
113ACTIVEZORA-USDZORAUSDCrypto10000.0000015.000.00001317773956000002026-04-28 17:00:00ZORAUSDT
114ACTIVEAPEX-USDAPEXUSDCrypto100.0000110.000.00001317773956000002026-04-28 17:00:00APEXUSDT
117ACTIVEZRO-USDZROUSDCrypto100.000110.000.00001317773956000002026-04-28 17:00:00ZROUSDT
118ACTIVEAMD_24_5-USDAMD_24_5USDTradFi0.10.0110.000.00000017773956000002026-04-28 17:00:00AMD_24_5USDT
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112 rows × 6 columns

\n", "" ], "text/plain": [ - " USDT_Symbol funding_rate_ts_dt_ex funding_rate_ex symbol \\\n", - "0 ENAUSDT 2026-04-28 17:00:00 0.000013 ENAUSDT \n", - "1 AVNTUSDT 2026-04-28 17:00:00 0.000013 AVNTUSDT \n", - "2 EURUSDT 2026-04-28 17:00:00 0.000015 NaN \n", - "3 SUIUSDT 2026-04-28 17:00:00 0.000013 SUIUSDT \n", - "4 WIFUSDT 2026-04-28 17:00:00 -0.000035 WIFUSDT \n", - ".. ... ... ... ... \n", - "107 FARTCOINUSDT 2026-04-28 17:00:00 0.000013 FARTCOINUSDT \n", - "108 ZORAUSDT 2026-04-28 17:00:00 0.000013 ZORAUSDT \n", - "109 APEXUSDT 2026-04-28 17:00:00 0.000013 NaN \n", - "110 ZROUSDT 2026-04-28 17:00:00 0.000013 ZROUSDT \n", - "111 AMD_24_5USDT 2026-04-28 17:00:00 0.000000 NaN \n", + " symbol_ext symbol_ast net_mult_x_net_fr_abs net_funding_rate_abs \\\n", + "0 CHIP-USD CHIPUSDT 0.003527 0.000388 \n", + "1 HYPE-USD HYPEUSDT 0.001114 0.000013 \n", + "2 BTC-USD BTCUSDT 0.000975 0.000013 \n", + "3 ETH-USD ETHUSDT 0.000975 0.000013 \n", + "4 BNB-USD BNBUSDT 0.000867 0.000013 \n", + "5 XAU-USD XAUUSDT 0.000862 0.000023 \n", + "6 DOGE-USD DOGEUSDT 0.000780 0.000013 \n", + "7 XMR-USD XMRUSDT 0.000733 0.000022 \n", + "8 XPT-USD XPTUSDT 0.000630 0.000168 \n", + "9 SUI-USD SUIUSDT 0.000540 0.000009 \n", + "10 ASTER-USD ASTERUSDT 0.000487 0.000013 \n", + "11 ENA-USD ENAUSDT 0.000433 0.000013 \n", + "12 LIT-USD LITUSDT 0.000433 0.000013 \n", + "13 ZEC-USD ZECUSDT 0.000388 0.000022 \n", + "14 SOL-USD SOLUSDT 0.000333 0.000005 \n", + "15 WLFI-USD WLFIUSDT 0.000186 0.000013 \n", + "16 XRP-USD XRPUSDT 0.000133 0.000002 \n", + "17 INIT-USD INITUSDT 0.000118 0.000013 \n", + "18 4-USD 4USDT 0.000118 0.000013 \n", + "19 AAVE-USD AAVEUSDT 0.000100 0.000006 \n", + "20 ZORA-USD ZORAUSDT 0.000065 0.000013 \n", + "21 XAG-USD XAGUSDT 0.000055 0.000003 \n", + "22 TRUMP-USD TRUMPUSDT 0.000033 0.000001 \n", "\n", - " funding_rate_ts_dt_as funding_rate_as \n", - "0 2026-04-28 16:47:59 0.00010000 \n", - "1 2026-04-28 16:47:59 0.00010000 \n", - "2 NaT NaN \n", - "3 2026-04-28 16:47:59 0.00010000 \n", - "4 2026-04-28 16:47:59 0.00010000 \n", - ".. ... ... \n", - "107 2026-04-28 16:47:59 0.00010000 \n", - "108 2026-04-28 16:47:59 0.00010000 \n", - "109 NaT NaN \n", - "110 2026-04-28 16:47:59 0.00010000 \n", - "111 NaT NaN \n", - "\n", - "[112 rows x 6 columns]" + " net_funding_rate next_funding_at_same_time hourly_dollars_per_1k \n", + "0 -0.000388 False 3.53 \n", + "1 0.000013 False 1.11 \n", + "2 0.000013 False 0.98 \n", + "3 0.000013 False 0.98 \n", + "4 0.000013 False 0.87 \n", + "5 0.000023 False 0.86 \n", + "6 0.000013 False 0.78 \n", + "7 0.000022 False 0.73 \n", + "8 0.000168 False 0.63 \n", + "9 -0.000009 False 0.54 \n", + "10 0.000013 False 0.49 \n", + "11 0.000013 False 0.43 \n", + "12 0.000013 False 0.43 \n", + "13 -0.000022 False 0.39 \n", + "14 -0.000005 False 0.33 \n", + "15 -0.000013 False 0.19 \n", + "16 0.000002 False 0.13 \n", + "17 0.000013 False 0.12 \n", + "18 0.000013 False 0.12 \n", + "19 0.000006 False 0.10 \n", + "20 0.000013 False 0.06 \n", + "21 0.000003 False 0.05 \n", + "22 -0.000001 False 0.03 " ] }, - "execution_count": 70, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "df_extend_current_fr[['USDT_Symbol','funding_rate_ts_dt','funding_rate']].merge(df_aster_current_fr[['symbol','funding_rate_ts_dt','funding_rate']], how='left', left_on='USDT_Symbol', right_on='symbol', suffixes=('_ex','_as'))" + "df_best_fr_rate" ] }, { "cell_type": "code", "execution_count": null, - "id": "63226c64", + "id": "73db21ae", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, "metadata": {}, "outputs": [], "source": [] @@ -2701,7 +863,6 @@ { "cell_type": "code", "execution_count": null, - "id": "37275f59", "metadata": {}, "outputs": [], "source": [] diff --git a/engine_best_funding_rate.py b/engine_best_funding_rate.py new file mode 100644 index 0000000..dd639b3 --- /dev/null +++ b/engine_best_funding_rate.py @@ -0,0 +1,172 @@ +import asyncio +import json +import logging +import os +import time +import traceback +from dataclasses import dataclass, field +from datetime import datetime +from typing import AsyncContextManager + +import pandas as pd +import requests +import valkey +from dotenv import load_dotenv + +# from sqlalchemy.ext.asyncio import create_async_engine + +### Structs ### +@dataclass(kw_only=False) +class Asset_Leverage: + exchange: str + lh_asset: str + rh_asset: str + max_leverage: int + max_notional: float + # max_leverage_notional: list = field(default_factory=list) + +### MANUAL LEVERAGE DATA ### +LEVERAGE_BY_EXCH: list[Asset_Leverage] = [ + Asset_Leverage('ASTER', 'BTC' , 'USDT', 150, 300_000), Asset_Leverage('EXTEND', 'BTC' , 'USD', 50, 4_000_000), + Asset_Leverage('ASTER', 'ETH' , 'USDT', 150, 300_000), Asset_Leverage('EXTEND', 'ETH' , 'USD', 50, 4_000_000), + Asset_Leverage('ASTER', 'LIT' , 'USDT', 50 , 2_500 ), Asset_Leverage('EXTEND', 'LIT' , 'USD', 25, 400_000 ), + Asset_Leverage('ASTER', 'CHIP' , 'USDT', 50 , 5_000 ), Asset_Leverage('EXTEND', 'CHIP' , 'USD', 5 , 100_000 ), + Asset_Leverage('ASTER', 'XAG' , 'USDT', 100, 50_000 ), Asset_Leverage('EXTEND', 'XAG' , 'USD', 10, 1_000_000), + Asset_Leverage('ASTER', '4' , 'USDT', 50 , 5_000 ), Asset_Leverage('EXTEND', '4' , 'USD', 5 , 100_000 ), + Asset_Leverage('ASTER', 'XPT' , 'USDT', 3 , 30_000 ), Asset_Leverage('EXTEND', 'XPT' , 'USD', 5 , 1_000_000), + Asset_Leverage('ASTER', 'XMR' , 'USDT', 50 , 10_000 ), Asset_Leverage('EXTEND', 'XMR' , 'USD', 25, 400_000 ), + Asset_Leverage('ASTER', 'WLFI' , 'USDT', 25 , 104_869), Asset_Leverage('EXTEND', 'WLFI' , 'USD', 10, 250_000 ), + Asset_Leverage('ASTER', 'TRUMP', 'USDT', 50 , 5_567 ), Asset_Leverage('EXTEND', 'TRUMP', 'USD', 25, 400_000 ), + Asset_Leverage('ASTER', 'INIT' , 'USDT', 50 , 5_000 ), Asset_Leverage('EXTEND', 'INIT' , 'USD', 5 , 100_000 ), + Asset_Leverage('ASTER', 'ZORA' , 'USDT', 5 , 100_000), Asset_Leverage('EXTEND', 'ZORA' , 'USD', 5 , 100_000 ), + Asset_Leverage('ASTER', 'ZEC' , 'USDT', 75 , 6_250 ), Asset_Leverage('EXTEND', 'ZEC' , 'USD', 10, 250_000 ), +] +df_leverage_by_exch = pd.DataFrame(LEVERAGE_BY_EXCH) + +### Database ### +# CON: AsyncContextManager | None = None +VAL_KEY = None +VK_OUT = 'fr_engine_best_fund_rate_output' + +### Logging ### +load_dotenv() +LOG_FILEPATH: str = os.getenv("LOGS_PATH") + '/Fund_Rate_Engine_BFR.log' + +### CONSTANTS ### +LOOP_SLEEP_SEC: int = 5 +REFRESH_MKT_INFO_EVERY_SEC: int = 90 +REFRESH_MKT_VOLUME_EVERY_SEC: int = 30 + +### GLOBALS ### +Mkt_Info_Last_Refresh_TS_ms: int +Mkt_Volume_Last_Refresh_TS_ms: int + +### Funcs - Load Data ### +def get_extended_markets_info() -> pd.DataFrame: + global Mkt_Info_Last_Refresh_TS_ms + + r = json.loads(requests.get('https://api.starknet.extended.exchange/api/v1/info/markets').text) + + df = pd.DataFrame(r['data']) + df['funding_rate'] = df['marketStats'].apply(lambda x: x.get('fundingRate',{})) + df['funding_rate_ts'] = df['marketStats'].apply(lambda x: x.get('nextFundingRate',{})) + df['min_order_size'] = df['tradingConfig'].apply(lambda x: x.get('minOrderSize',{})) + df['min_price_change'] = df['tradingConfig'].apply(lambda x: x.get('minPriceChange',{})) + df['max_leverage'] = df['tradingConfig'].apply(lambda x: x.get('maxLeverage',{})) + + Mkt_Info_Last_Refresh_TS_ms = round(datetime.now().timestamp() * 1000) + + print('Extend markets info refreshed successfully') + + return df + +def load_aster_current_fr() -> pd.DataFrame: + df = pd.DataFrame(json.loads(VAL_KEY.get('fund_rate_aster_all'))) + + df = df[['s','E','r','T']].rename({'s':'symbol','E':'funding_rate_updated_ts_ms','r':'funding_rate','T':'next_funding_ts'}, axis=1) + df['funding_rate_updated_dt'] = pd.to_datetime(df['funding_rate_updated_ts_ms'], unit='ms') + df['funding_rate'] = df['funding_rate'].astype(float) + df['time_delta_to_next_funding'] = pd.to_datetime(df['next_funding_ts'], unit='ms') - pd.Timestamp.now() + + return df + +def load_extend_current_fr(df_mkt_stats: pd.DataFrame) -> pd.DataFrame: + df = pd.DataFrame(json.loads(VAL_KEY.get('fund_rate_extended_all'))) + + df = df[['symbol','funding_rate_updated_ts_ms','funding_rate']] + df['funding_rate_updated_dt'] = pd.to_datetime(df['funding_rate_updated_ts_ms'], unit='ms') + df['funding_rate'] = df['funding_rate'].astype(float) + + df = df.merge(df_mkt_stats[['name','assetName','status', 'funding_rate_ts','max_leverage']].rename({'name':'symbol','funding_rate_ts':'next_funding_ts'}, axis=1), on='symbol', how='left') + df = df.loc[df['status']=='ACTIVE',:] + df['USDT_Symbol'] = df['assetName'] + 'USDT' + + df['time_delta_to_next_funding'] = pd.to_datetime(df['next_funding_ts'], unit='ms') - pd.Timestamp.now() + + return df + +async def loop() -> None: + global Mkt_Info_Last_Refresh_TS_ms + + df_extend_mkt_stats = get_extended_markets_info() + try: + while True: + ts_arrival = round(datetime.now().timestamp() * 1000) + if ( ts_arrival - Mkt_Info_Last_Refresh_TS_ms ) > ( REFRESH_MKT_INFO_EVERY_SEC * 1000 ): + df_extend_mkt_stats = get_extended_markets_info() + + df_aster_fr = load_aster_current_fr() + df_extend_fr = load_extend_current_fr(df_mkt_stats=df_extend_mkt_stats) + + df_comb_fr = df_extend_fr.merge(df_aster_fr, left_on='USDT_Symbol', right_on='symbol', how='inner', suffixes=('_ext', '_ast')) + df_comb_fr['next_funding_at_same_time'] = (abs(df_comb_fr['time_delta_to_next_funding_ext'].dt.total_seconds() - df_comb_fr['time_delta_to_next_funding_ast'].dt.total_seconds()) / 60) < 1 + df_comb_fr['net_funding_rate'] = (df_comb_fr[['funding_rate_ext', 'funding_rate_ast']].max(axis=1) - df_comb_fr[['funding_rate_ext', 'funding_rate_ast']].min(axis=1)).where(df_comb_fr['next_funding_at_same_time'], df_comb_fr['funding_rate_ext']) + df_comb_fr['net_funding_rate_abs'] = df_comb_fr['net_funding_rate'].abs() + + ### NET MULT ### + df_comb_fr = df_comb_fr.merge(df_leverage_by_exch.loc[df_leverage_by_exch['exchange']=='EXTEND'], left_on='assetName', right_on='lh_asset').merge(df_leverage_by_exch.loc[df_leverage_by_exch['exchange']=='ASTER'], left_on='assetName', right_on='lh_asset', suffixes=('_ext', '_ast')) + df_comb_fr['net_mult'] = 1 / ( ( 0.5 / df_comb_fr['max_leverage_ext'] ) + ( 0.5 / df_comb_fr['max_leverage_ast'] ) ) + df_comb_fr['net_mult'] = df_comb_fr['net_mult'].round(2) + df_comb_fr['net_mult_x_net_fr_abs'] = df_comb_fr['net_funding_rate_abs'] * df_comb_fr['net_mult'] + + df_best_fr_rate = df_comb_fr[['symbol_ext','symbol_ast','net_mult_x_net_fr_abs','net_funding_rate_abs','net_funding_rate','next_funding_at_same_time']].sort_values(by='net_mult_x_net_fr_abs', ascending=False).reset_index(drop=True) + best_next_funding_pair = {'symbol_aster':df_best_fr_rate['symbol_ast'][0],'symbol_extended':df_best_fr_rate['symbol_ext'][0]} + + VAL_KEY.set(VK_OUT, json.dumps(best_next_funding_pair)) + print(best_next_funding_pair) + time.sleep(LOOP_SLEEP_SEC) + continue + except valkey.exceptions.ConnectionError as e: + logging.info(f"Could not connect to Valkey. Please check the publish server is up; {e}") + except KeyboardInterrupt: + logging.info('ORCHESTRATOR SHUTTING DOWN...') + except Exception as e: + logging.error(traceback.format_exc()) + logging.critical(f'*** ORCHESTRATOR CRASHED: {e}') + + +### STARTUP ### +async def main() -> None: + global VAL_KEY + # global CON + + VAL_KEY = valkey.Valkey(host='localhost', port=6379, db=0, decode_responses=True) + # engine = create_async_engine('mysql+asyncmy://root:pwd@localhost/fund_rate') + + await loop() + +if __name__ == '__main__': + START_TIME = round(datetime.now().timestamp()*1000) + + logging.info(f'Log FilePath: {LOG_FILEPATH}') + + logging.basicConfig( + force=True, + filename=LOG_FILEPATH, + level=logging.INFO, + format='%(asctime)s - %(levelname)s - %(message)s', + filemode='w' + ) + logging.info(f"STARTED: {START_TIME}") + + asyncio.run(main()) \ No newline at end of file diff --git a/engine_dispersion.ipynb b/engine_dispersion.ipynb index 8084eee..ef7cbed 100644 --- a/engine_dispersion.ipynb +++ b/engine_dispersion.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 97, "id": "25697582", "metadata": {}, "outputs": [], @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 98, "id": "cd9ecfde", "metadata": {}, "outputs": [ @@ -46,7 +46,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 99, "id": "60cc2366", "metadata": {}, "outputs": [], @@ -63,7 +63,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 100, "id": "55ae5271", "metadata": {}, "outputs": [], @@ -79,7 +79,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 101, "id": "2b7232e5", "metadata": {}, "outputs": [], @@ -106,8475 +106,70 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 102, "id": "f1174bae", "metadata": {}, "outputs": [], "source": [ "df_fr = funding_rate_hist_extend(market='ETH-USD')\n", "df_fr = pd.DataFrame(df_fr['data']).rename({'m':'market','f':'funding_rate','T':'timestamp'}, axis=1)\n", - "df_fr['timestamp_dt'] = pd.to_datetime(df_fr['timestamp'], unit='ms')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "068a54b6", - "metadata": {}, - "outputs": [], - "source": [ + "df_fr['timestamp_dt'] = pd.to_datetime(df_fr['timestamp'], unit='ms')\n", + "\n", "df_aster_trades_by_sec_maker, df_aster_trades_by_sec_taker = get_24hrs_midbars(\n", " table_name='fr_aster_mkt_trades',\n", ")\n", "\n", "df_extend_trades_by_sec_maker, df_extend_trades_by_sec_taker = get_24hrs_midbars(\n", " table_name='fr_extended_mkt_trades',\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "2862e7e3", - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.plotly.v1+json": { - "config": { - "plotlyServerURL": "https://plot.ly" - }, - "data": [ - { - "hovertemplate": "timestamp_trade_dt=%{x}
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"px.line(df_extend_trades_by_sec_maker, y='qty_sum', template='plotly_dark')" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "56f94403", - "metadata": {}, - "outputs": [], - "source": [ - "df_comb_trades_by_sec = df_aster_trades_by_sec_taker[['price_median']].merge(df_extend_trades_by_sec_maker[['price_median']], left_index=True, right_index=True, suffixes=('_aster','_extend'))" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ + ")\n", + "\n", + "df_comb_trades_by_sec = df_aster_trades_by_sec_taker[['price_median']].merge(df_extend_trades_by_sec_maker[['price_median']], left_index=True, right_index=True, suffixes=('_aster','_extend'))\n", "df_comb_trades_by_sec['ratio'] = df_comb_trades_by_sec['price_median_aster'] / df_comb_trades_by_sec['price_median_extend']" ] }, { "cell_type": "code", - "execution_count": 13, - "id": "663d036f", - "metadata": {}, - "outputs": [], - "source": [ - "# df_comb_trades_by_sec = df_comb_trades_by_sec.reset_index().groupby(pd.Grouper(key='timestamp_trade_dt', freq='h')).agg({'price_median_aster': 'median', 'price_median_extend': 'median', 'ratio': 'median'}) # Resting on the ask (seller is maker): BID [Taker] [Buyer] -- Crossed into --> ASK [Maker] [Seller]" - ] - }, - { - "cell_type": "code", - "execution_count": 14, + "execution_count": 103, "id": "66c5a128", "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "0.6462633451957296" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " Pct Trades w Ratio > 1: 0.6558171745152355\n", + " Pct Trades w Ratio <= 1: 0.34418282548476453\n", + "\n" + ] } ], "source": [ - "len(df_comb_trades_by_sec.loc[df_comb_trades_by_sec['ratio'] > 1]) / len(df_comb_trades_by_sec)" + "print(f'''\n", + " Pct Trades w Ratio > 1: {len(df_comb_trades_by_sec.loc[df_comb_trades_by_sec['ratio'] > 1]) / len(df_comb_trades_by_sec)}\n", + " Pct Trades w Ratio <= 1: {len(df_comb_trades_by_sec.loc[df_comb_trades_by_sec['ratio'] <= 1]) / len(df_comb_trades_by_sec)}\n", + "''')\n" ] }, { "cell_type": "code", - "execution_count": 15, - "id": "a454f3c4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.35373665480427047" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "len(df_comb_trades_by_sec.loc[df_comb_trades_by_sec['ratio'] <= 1]) / len(df_comb_trades_by_sec)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "bf9af769", - "metadata": {}, - "outputs": [], - "source": [ - "min_time = max([round(df_comb_trades_by_sec.index.min().timestamp()*1000), int(round(df_fr['timestamp'].min()))])" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "a0b4ab50", + "execution_count": 104, + "id": "ee0dc256", "metadata": {}, "outputs": [], "source": [ + "min_time = max([round(df_comb_trades_by_sec.index.min().timestamp()*1000), int(round(df_fr['timestamp'].min()))])\n", "df_comb_trades_by_sec_plot = df_comb_trades_by_sec.loc[df_comb_trades_by_sec.index.values.astype(np.int64) > min_time,:]\n", - "df_fr_plot = df_fr.loc[df_fr['timestamp'] > min_time,:]" + "df_fr_plot = df_fr.loc[df_fr['timestamp'] > min_time,:]\n", + "df_fr_plot['funding_rate'] = df_fr_plot['funding_rate'].astype(float)" ] }, { "cell_type": "code", - "execution_count": 18, - "id": "0ed91c0e", - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.microsoft.datawrangler.viewer.v0+json": { - "columns": [ - { - "name": "timestamp_trade_dt", - "rawType": "datetime64[ms]", - "type": "datetime" - }, - { - "name": "price_median_aster", - "rawType": "float64", - "type": "float" - }, - { - "name": "price_median_extend", - "rawType": "float64", - "type": "float" - }, - { - "name": "ratio", - "rawType": "float64", - "type": "float" - } - ], - "ref": 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", 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EokBxPQrXIwOiQB+F61E4AqJAH4XrUbgBokCamZmZWQSiQDMzMzMzBKJA16NwPcoFokC4HoXr0QSiQOxRuB5FBKJAw/UoXI8EokBI4XoULgWiQNejcD0KBaJAexSuR2EFokA9CtejcASiQHoUrkfhAqJA4XoUrscDokBI4XoUrgSiQFK4HoVrAqJAuB6F69EBokAK16Nwvf6hQPYoXI/CAKJAw/UoXA8CokDMzMzMTAKiQBSuR+F6AqJArkfhehQCokAzMzMzMwKiQOJ6FK5HAqJAmpmZmZn/oUD2KFyPQv6hQD0K16Mw/qFAhetRuJ79oUDXo3A9CvuhQClcj8I1+qFApHA9Clf1oUBI4XoULvihQOF6FK7H+aFA9ihcj0L6oUApXI/C9fmhQB+F61E4+6FAhetRuJ75oUAAAAAAAPihQJDC9Sgc+KFAhetRuJ7zoUCPwvUo3PKhQJqZmZmZ86FAkML1KJzxoUAAAAAAAPShQDQzMzOz9aFAZmZmZub1oUA+CtejMPShQPYoXI9C9aFAFK5H4fr0oUDhehSux/ShQEjhehQu9aFAMzMzMzP1oUCuR+F6lPWhQM3MzMzM9KFAMzMzMzPzoUBxPQrXo/KhQArXo3D98qFA9ihcj8LyoUD2KFyPgvChQLgehevR8qFAzczMzMz0oUD2KFyPQvahQAAAAAAA9aFAw/UoXA/0oUAfhetROPShQEjhehQu9KFAhetRuJ7zoUBI4XoULvGhQFyPwvVo8KFAZmZmZmbwoUCuR+F6lPWhQGZmZmZm9KFAhetRuJ70oUC4HoXr0fChQKRwPQqX66FASOF6FO7qoUAAAAAAAOmhQHA9Ctcj6aFAAAAAAADpoUDsUbgexemhQNejcD1K6qFAKVyPwnXpoUC4HoXrUeqhQPYoXI/C5qFA4noUrofloUBI4XoULuWhQNejcD3K5aFA9ihcj8LhoUAzMzMzM9WhQIbrUbge1aFAMzMzMzPXoUAK16NwPdahQNejcD0K1qFAKVyPwnXToUBmZmZm5tGhQML1KFxP1KFAFK5H4frToUCPwvUo3NOhQK5H4XpU2aFAzczMzMzeoUDNzMzMjN6hQAAAAACA3aFAUrgehWvcoUAfhetRON6hQIXrUbge3aFAwvUoXM/coUApXI/CNeChQHsUrkdh36FASOF6FK7eoUC4HoXrEd2hQEjhehRu2qFAwvUoXA/aoUBI4XoULtihQJqZmZkZ2KFA7FG4HgXXoUBSuB6FK9ShQJqZmZkZ1aFAhetRuB7YoUDsUbgeBdihQEjhehSu1qFA4XoUrkfWoUAK16NwPdehQB6F61F42aFAj8L1KFzZoUCkcD0K19ehQMP1KFyP16FAhetRuJ7YoUBmZmZm5tWhQOxRuB4F1aFArkfhehTVoUDsUbgehdehQDMzMzMz16FAexSuR+HWoUAUrkfh+tehQLgehevR3aFApHA9CtfeoUAAAAAAAN2hQFyPwvUo3aFAexSuR2HdoUBcj8L1qNuhQK5H4XqU26FAMzMzM3PaoUApXI/CddqhQML1KFzP2qFAAAAAAADaoUAUrkfh+t2hQArXo3A93aFAAAAAAADfoUCF61G4nuKhQBSuR+E64KFACtejcL3eoUBSuB6Fa9+hQArXo3C94KFAcD0K1+PhoUD2KFyPQuKhQGZmZmZm46FAmpmZmVnloUAzMzMzc+ehQBSuR+H66KFACtejcL3noUC4HoXrUeWhQClcj8L14KFAH4XrUbjeoUCamZmZGd6hQGZmZmZm3KFAUrgehWvYoUA9CtejcNihQIXrUbge2aFAH4XrUTjaoUCPwvUo3NuhQFK4HoXr26FACtejcL3ZoUDD9Shcj9ihQBSuR+H61qFAuB6F69HUoUB7FK5HYdyhQGZmZmZm4aFAcD0K1yPgoUCamZmZGd6hQB+F61E44KFAPQrXo3DhoUBI4XoULuGhQFyPwvVo4KFAKVyPwnXgoUAK16Nwvd6hQD4K16Nw3qFAAAAAAADioUDNzMzMzOOhQNejcD3K5KFAzczMzMzmoUC4HoXrUeahQJqZmZnZ6KFAAAAAAADooUB7FK5HYeShQML1KFxP4aFAw/UoXA/ioUAfhetROOChQOF6FK5H36FAmpmZmZnfoUA+CtejMN6hQB+F61E43aFAZmZmZubeoUDsUbgeheChQIXrUbge4KFAhetRuJ7loUB6FK5HYeyhQBSuR+H66aFAZmZmZqbpoUCamZmZmemhQBSuR+E66aFAKVyPwvXooUDC9Shcz+ahQGZmZmYm4qFAFK5H4freoUDhehSux+ChQOxRuB6F3qFAFK5H4freoUDNzMzMzNuhQOF6FK5H3qFAH4XrUbjfoUCkcD0K19+hQIXrUbge4KFAj8L1KNzfoUApXI/CNd+hQOxRuB4F3qFAZmZmZmbgoUA+CtejcN6hQKRwPQpX3qFASOF6FC7doUD2KFyPwt6hQHA9Ctcj4aFAPQrXo3DhoUCkcD0K1+GhQD4K16Mw4qFAzczMzMzgoUDXo3A9CuGhQB6F61E44KFAmpmZmRngoUDhehSuh+ChQBSuR+H636FAuB6F6xHeoUA9Ctej8NyhQNejcD1K26FAFK5H4TrboUAUrkfhetqhQOxRuB7F1qFAmpmZmZnUoUC4HoXr0dehQJqZmZlZ2KFAUrgehevYoUDhehSux9mhQBSuR+H62aFAAAAAAADXoUBxPQrXI9ahQK5H4XqU1qFAKVyPwvXNoUB7FK5HYc6hQGZmZmZmy6FA4XoUrsfMoUAUrkfhesuhQDMzMzMzyaFAcD0K1+PDoUAK16Nw/buhQM3MzMxMvaFAZmZmZmbBoUCkcD0KV8ChQM3MzMzMvqFA7FG4HgXBoUAzMzMzs8WhQKRwPQpXxaFA4XoUrkfGoUBcj8L1qMWhQKRwPQqXyKFArkfhehTLoUAzMzMzM8qhQBSuR+H6yKFA4XoUrsfJoUDNzMzMTMqhQArXo3A9yaFACtejcD3JoUCPwvUo3MihQHE9CtejyKFAAAAAAADKoUCQwvUoXMehQGZmZmbmxaFAAAAAAADCoUAUrkfhOsShQMP1KFyPwaFA4XoUrsfBoUBmZmZmZsChQEjhehRuu6FArkfhehS+oUD2KFyPQsChQBSuR+E6v6FAXI/C9ejAoUAK16NwPcShQFyPwvWoxaFA9ihcj0LIoUBmZmZmJsehQM3MzMzMx6FAuB6F6xHGoUCF61G4XsihQEjhehQuy6FAMzMzM/PMoUBSuB6F69ChQD0K16Pw0KFAzczMzMzSoUB7FK5H4dShQArXo3B90qFA9ihcj8LSoUDD9ShcD9ShQGZmZmZm0qFAPQrXo/DSoUBI4XoULtOhQD0K16Pw06FAcD0K1+PXoUCQwvUo3NqhQNejcD2K26FAkML1KBzaoUCuR+F6lNmhQIXrUbhe2aFApHA9CtfZoUDNzMzMzNmhQClcj8L11qFAexSuR2HXoUAAAAAAANahQIXrUbge1qFA16NwPYrYoUCF61G4ntqhQM3MzMxM3qFAKVyPwvXeoUBmZmZmZuChQD0K16Nw3KFAFK5H4frdoUDsUbgeBdyhQM3MzMzM2qFAcT0K1yPaoUCPwvUo3NihQOxRuB5F2KFAPQrXo/DgoUB6FK5HYeShQClcj8L136FAmpmZmRnfoUA9CtejcOChQHA9Ctfj36FAFK5H4XrgoUAK16Nwvd2hQK5H4XrU26FAH4XrUTjaoUDD9Shcj9ihQDMzMzOz16FASOF6FC7XoUDXo3A9StehQNejcD0K1qFAkML1KNzWoUAK16Nw/dihQM3MzMzM1aFAzczMzMzWoUCamZmZGdqhQGZmZmbm26FAhetRuB7boUBxPQrXo9uhQMP1KFyP2qFApHA9ClfYoUB7FK5HodehQClcj8L116FAXI/C9ajaoUDsUbgehdmhQGZmZmbm2aFAuB6F69HboUA9CtejcNuhQOxRuB7F2qFAzczMzEzdoUDD9Shcj96hQClcj8J13KFA16NwPcrcoUAUrkfh+tuhQPYoXI9C3KFAmpmZmZnboUAAAAAAAN2hQFK4HoUr3KFArkfhepTaoUBmZmZm5tWhQGZmZmZm16FAzczMzMzUoUCQwvUoHNShQGZmZmZm1qFAmpmZmdnVoUBcj8L1KNWhQB+F61E41KFArkfhehTUoUDNzMzMzNKhQMzMzMyM0aFAMzMzMzPQoUApXI/Cdc2hQK5H4XoUzqFA4XoUrofKoUDhehSux8ihQJqZmZmZyaFAH4XrUbjToUB7FK5HodKhQJqZmZkZ0qFAcT0K1yPXoUApXI/C9dihQHA9Ctej2KFASOF6FK7YoUBcj8L1KNahQJqZmZkZ1aFAFK5H4TrWoUAUrkfh+tOhQBSuR+H606FAAAAAAIDToUDMzMzMTNKhQD0K16Pw0qFAMzMzM7PSoUBSuB6Fa9GhQDMzMzMz0KFAw/UoXI/QoUAfhetRuNKhQM3MzMxM1KFA4XoUrsfToUDC9ShcD9OhQM3MzMzM0qFA7FG4HgXSoUDD9ShcD9KhQFK4HoXr0aFAhetRuN7RoUAAAAAAQNWhQKRwPQoX1qFAAAAAAIDXoUDhehSux9ahQEjhehQu1qFA9ihcj8LVoUCuR+F6FNehQOxRuB4F2KFAMzMzMzPYoUDsUbgehdihQDMzMzMz2KFAAAAAAIDboUBmZmZmZtihQNejcD2K1aFAH4XrUTjXoUA+CtejsNShQM3MzMxM1KFAMzMzMzPQoUDsUbgehc6hQArXo3C9zaFA4XoUrsfNoUDNzMzMTMqhQArXo3C9zKFAj8L1KFzNoUBSuB6Fa8uhQAAAAAAAyqFAj8L1KFzIoUBI4XoULsihQDMzMzMzx6FAZmZmZmbGoUCF61G4nsOhQMzMzMyMw6FASOF6FC7GoUCkcD0KF8ahQLgehetRx6FAPgrXo7DJoUBcj8L1aMmhQFyPwvWoyqFAzczMzMzHoUAfhetRuMShQDMzMzOzwqFA16NwPcrFoUAK16NwvcOhQHA9CtfjwaFAcT0K1yPEoUCF61G43sOhQM3MzMyMxKFAKVyPwrXDoUAehetRuMChQB+F61G4wKFAZmZmZmbAoUDXo3A9Sr+hQHsUrkfhvaFAmpmZmRnCoUBcj8L1qMOhQNejcD2KwKFAzczMzEzBoUD2KFyPQr2hQArXo3D9u6FAmpmZmZm7oUAzMzMzc7yhQIXrUbgevaFAZmZmZma9oUDXo3A9ir6hQFK4HoVrwqFAXI/C9SjCoUB7FK5HYcKhQOF6FK5Hw6FAZmZmZqbFoUDC9Shcz8KhQML1KFzPw6FAH4XrUbjEoUAzMzMzM8ShQJDC9ShcxaFArkfhepTHoUAzMzMzc8ShQClcj8J1xaFAuB6F6xHDoUBSuB6Fa8ShQAAAAACAyqFAuB6F69HLoUDC9Shcz8ihQAAAAACAyaFAzMzMzEzHoUDXo3A9ysWhQK5H4XqUwaFAcT0K16PLoUAK16NwPcqhQBSuR+H6xKFA4XoUrsfEoUBSuB6Fa8ShQLgehevRwKFAKVyPwjXAoUBI4XoUrsGhQLgehetRv6FAcD0K1+O9oUDNzMzMzMKhQHE9CtejwKFArkfhepTEoUBxPQrXo8WhQLgehevRxqFAuB6F69HIoUC4HoXrEcmhQD0K16PwxqFAwvUoXE/HoUAfhetRuMihQD0K16Nwx6FASOF6FC7IoUBmZmZmpsuhQM3MzMwMyaFAkML1KNzLoUDMzMzMzMqhQPYoXI/CyaFA9ihcj8LIoUAehetR+MihQClcj8L1x6FAXI/C9WjHoUBmZmZmpsShQM3MzMwMxaFAUrgehWvFoUAfhetROMKhQM3MzMzMv6FAhetRuJ64oUAAAAAAgLKhQKRwPQoXsaFAKVyPwnWpoUB7FK5HobKhQNejcD0KtaFA9ihcj8K0oUDiehSux7KhQJqZmZkZsKFAUrgehauyoUBI4XoU7rShQIXrUbjetaFAhetRuB62oUDD9ShcD7ahQGZmZmZmtaFAKVyPwvW3oUA0MzMzM7ahQOF6FK6HtqFAwvUoXI+2oUDhehSuR7WhQOF6FK5Hs6FA7FG4HkWyoUDC9Shcj7uhQB6F61E4uqFAj8L1KNyzoUDsUbgeBbmhQBSuR+H6vaFAhetRuJ67oUAK16NwPcChQDMzMzOzwKFA16NwPcrEoUDNzMzMjMWhQJqZmZkZw6FAH4XrUTjBoUBmZmZmpsChQJqZmZmZxqFAAAAAAIDIoUBwPQrXI8qhQClcj8K1yKFAzczMzMzSoUC4HoXrkdahQM3MzMzM06FAMzMzM3PQoUBmZmZmZs6hQOJ6FK4HzKFAj8L1KNzLoUA+CtejsMahQGZmZmZmxaFASOF6FG69oUAAAAAAAL6hQNejcD0KxqFAw/UoXA/GoUCQwvUo3MahQClcj8J1w6FAexSuR2HBoUBcj8L1KL2hQML1KFzPwaFACtejcP2/oUCamZmZmcShQD4K16OwxKFA9ihcj8LBoUC4HoXr0cChQAAAAAAAwKFA4XoUrse9oUCkcD0Kl7+hQAAAAACAwKFAFK5H4bq9oUBcj8L1KL2hQAAAAAAAuaFAexSuR+G9oUBwPQrXY76hQLgehevRuqFAMzMzM/O7oUAUrkfherihQHE9Ctejt6FAwvUoXM+zoUBcj8L1KLahQAAAAACAr6FAXI/C9SiwoUBI4XoULrShQIbrUbgetqFAuB6F6xG2oUA0MzMzM7mhQLgehesRt6FAFK5H4fq0oUCF61G4XrKhQNejcD0KraFAXI/C9aiqoUB7FK5HYayhQLgehetRrKFAFK5H4XquoUB7FK5HYa6hQJqZmZmZr6FAAAAAAMCzoUBmZmZmZrehQB+F61E4u6FAzczMzMy5oUBSuB6Fq7ehQDMzMzOzuKFAj8L1KFy2oUBSuB6Fa7ahQFK4HoVrsqFA4XoUrsevoUDD9ShcD7GhQEjhehSutaFAwvUoXE+1oUCamZmZ2bqhQD0K16NwuqFAPgrXo7C7oUCQwvUo3LuhQFK4HoVrv6FAH4XrUXjDoUD2KFyPwsahQNejcD0KxaFAPgrXozDEoUBmZmZm5sGhQK5H4XqUwKFA9ihcj0K7oUBcj8L1KMChQIXrUbiewKFAFK5H4TrCoUCkcD0K17+hQOF6FK7HwaFAKVyPwvXBoUBmZmZm5sGhQNejcD1Kv6FA9ihcjwLAoUBSuB6Fq8KhQGZmZmamwaFAH4XrUTjBoUC4HoXrUcShQOF6FK7Hw6FAPQrXo/DDoUAehetRuMShQD4K16PwxKFAKVyPwjXEoUD2KFyPwsShQDMzMzMzwqFAj8L1KFzAoUAAAAAAAMChQLgeheuRvqFASOF6FC67oUDsUbgeBb6hQML1KFzPvKFA16NwPcq7oUAzMzMz876hQB+F61G4waFAj8L1KBzBoUDC9Shcz8WhQOxRuB6Fw6FAexSuR+HBoUCamZmZmcChQGZmZmbmwKFAH4XrUTjEoUAUrkfhesWhQD0K16PwxKFAexSuR+HEoUAzMzMzs8ehQBSuR+G6yqFAzczMzMzLoUDNzMzMzMuhQI/C9ShczaFAUrgehWvMoUC4HoXr0cqhQArXo3C9zaFAPQrXo/DMoUDsUbgehcuhQK5H4XqUzKFAKFyPwnXOoUCkcD0KF9ChQEjhehSuyqFAMzMzMzPMoUAehetROMuhQDQzMzPzyqFAZmZmZubJoUAzMzMzs82hQPYoXI/CyaFAAAAAAEDKoUBcj8L1qMihQOJ6FK7Hx6FAuB6F69HKoUBmZmZmJsmhQM3MzMzMxqFAmpmZmZnJoUDsUbgexcyhQML1KFxPzaFA4noUrsfNoUB6FK5HYcyhQDMzMzMzy6FAuB6F6xHLoUCPwvUo3MqhQHE9CtcjyqFAZmZmZubIoUB7FK5H4cqhQHE9CtcjyqFAmpmZmZnHoUCamZmZGcihQI/C9ShcxaFAFK5H4frDoUCkcD0K18WhQBSuR+F6xKFAPQrXo/DFoUBxPQrXI8WhQFyPwvUow6FAexSuRyHFoUDXo3A9SsehQKRwPQqXxaFACtejcD3GoUCPwvUo3MehQFyPwvWoyKFAXI/C9SjIoUB7FK5HIc2hQDMzMzMz1KFAzczMzEzaoUBwPQrX49qhQJDC9Sjc2KFAw/UoXA/boUBxPQrXI9qhQD0K16Nw2aFAhetRuF7aoUDNzMzMDNyhQDQzMzMz2KFAwvUoXE/UoUC4HoXr0dShQAAAAABA1aFApHA9CtfToUCPwvUo3NKhQGZmZmZm0qFAw/UoXA/RoUC4HoXrUdOhQIXrUbie0aFAZmZmZubRoUAUrkfhetGhQKRwPQrXzaFA4XoUrsfMoUDNzMzMzMuhQClcj8I1zqFA9ihcj4LPoUBxPQrXI9ChQFK4HoVr1aFAUrgehWvWoUAAAAAAgNehQBSuR+H62aFAcT0K1yPZoUCkcD0K19mhQJDC9Sgc26FAj8L1KBzeoUAfhetReN+hQD4K16Mw5qFAmpmZmZnmoUBmZmZmZuehQK5H4XoU5KFAcT0K1yPloUAUrkfh+uOhQJqZmZmZ5KFAMzMzMzPloUAzMzMzM+ShQDMzMzMz5KFACtejcH3loUDXo3A9iuWhQML1KFxP46FAcT0K1yPkoUBSuB6F6+ShQDMzMzOz5KFA16NwPQrkoUAUrkfhOuKhQEjhehQu4aFAKVyPwvXfoUDsUbgeheChQGZmZmYm4KFAXI/C9SjioUD2KFyPQuOhQHsUrkdh46FApHA9CpfjoUCPwvUo3OGhQArXo3C94KFA9ihcj0LjoUC4HoXrUeahQM3MzMwM6aFAZmZmZubloUBSuB6F6+KhQLgehetR3qFAFK5H4frfoUCuR+F6FOChQLgehevR3aFAAAAAAMDdoUApXI/C9d2hQClcj8J14KFACtejcH3goUB6FK5HYeShQI/C9Sjc5qFAhutRuB7noUDC9ShcT+ehQClcj8J16KFAMzMzMzPnoUC4HoXr0eehQGZmZmZm6qFAFK5H4frqoUCkcD0KF+uhQD4K16Ow6qFAmpmZmZnqoUA9Ctej8OihQClcj8K16aFANDMzMzProUAUrkfh+umhQBSuR+G66KFApHA9CtfpoUCamZmZ2emhQHE9Ctcj5qFApHA9CtfnoUAK16NwPemhQKRwPQrX56FAzczMzEznoUA9Ctej8OahQOxRuB4F56FA16NwPQrmoUB7FK5H4eShQFyPwvUo5KFAAAAAAEDhoUCamZmZmeKhQJqZmZnZ36FA9ihcj0LfoUAAAAAAgOChQNejcD2K4KFAH4XrUTjgoUDXo3A9CuKhQGZmZmYm4aFA7FG4HsXkoUBxPQrXI+ehQAAAAAAA7aFAmpmZmRnuoUCuR+F61O+hQJqZmZmZ8KFAMzMzMzPvoUDD9ShcD+2hQIbrUbie7KFAZmZmZmbroUBmZmZmJuuhQPYoXI8C66FAcT0K16ProUAzMzMzM+uhQHsUrkfh56FAhetRuJ7poUBI4XoUbuihQIXrUbje6KFA9ihcj0LqoUAzMzMzs+mhQArXo3A95qFAFK5H4frjoUB7FK5HYeWhQK5H4XoU46FA16NwPQrjoUA+CtejcOShQArXo3A95qFAKVyPwvXloUAUrkfheuehQHE9Ctcj5qFAj8L1KFzloUB7FK5HIeWhQD4K16Nw5aFA16NwPQrnoUB7FK5HYeyhQBSuR+F67KFAuB6F61HroUD2KFyPQuyhQHA9Ctfj8qFAXI/C9aj1oUCamZmZmfihQEjhehSu9KFA9ihcj0LyoUDNzMzMzPOhQEjhehQu+KFAAAAAAID8oUA9CtejcP2hQFyPwvWo/KFApHA9Clf9oUCuR+F6lP6hQPYoXI/C/qFASOF6FK78oUBwPQrX4/mhQClcj8L1+qFAKVyPwvX7oUAzMzMz8/uhQArXo3A9/aFAzczMzMz+oUBI4XoULv2hQClcj8L1+aFArkfhehT5oUDiehSuh/ihQNejcD0K+KFAcT0K1yP1oUDD9Shcj/ahQArXo3A99aFAMzMzM7PzoUAUrkfh+vShQOF6FK5H9aFAUrgehev0oUCkcD0KV/WhQHA9Ctdj86FAmpmZmZnzoUBmZmZmZvOhQAAAAAAA8qFApHA9CtfwoUCamZmZGfShQHE9Ctcj8aFAMzMzMzPxoUBSuB6F6++hQAAAAAAA8aFAXI/C9WjwoUAzMzMzM/ChQJqZmZmZ7qFAH4XrUbjuoUC4HoXr0e+hQAAAAACA7qFAzczMzMzyoUD2KFyPgvOhQAAAAADA8qFA9ihcj8LwoUDNzMzMzO6hQOxRuB6F7qFAuB6F69HtoUAUrkfh+u2hQEjhehQu7aFA", 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", "dtype": "f8" }, "yaxis": "y3" } ], "layout": { + "shapes": [ + { + "line": { + "color": "pink", + "dash": "dash" + }, + "type": "line", + "x0": 1, + "x1": 0, + "xref": "paper", + "y0": 1, + "y1": 1, + "yref": "y3" + } + ], "template": { "data": { "bar": [ @@ -13801,10 +5463,10 @@ "fig = go.Figure()\n", "\n", "# Add traces bound to different Y-axes\n", - "fig.add_trace(go.Scatter(x=df_comb_trades_by_sec_plot.index, y=df_comb_trades_by_sec_plot['price_median_aster'], name=\"Aster_Mid\")) # Funding Rate\n", - "fig.add_trace(go.Scatter(x=df_comb_trades_by_sec_plot.index, y=df_comb_trades_by_sec_plot['price_median_extend'], name=\"Extend\", yaxis='y1')) # Ratio\n", - "fig.add_trace(go.Scatter(x=df_fr_plot['timestamp_dt'], y=df_fr_plot['funding_rate'], name=\"FR\", yaxis='y2')) # Ratio\n", - "fig.add_trace(go.Scatter(x=df_comb_trades_by_sec_plot.index, y=df_comb_trades_by_sec_plot['ratio'], name=\"Ratio\", yaxis='y3')) # Funding Rate\n", + "fig.add_trace(go.Scatter(x=df_comb_trades_by_sec_plot.index, y=df_comb_trades_by_sec_plot['price_median_aster'], name=\"Aster_Mid\")) \n", + "fig.add_trace(go.Scatter(x=df_comb_trades_by_sec_plot.index, y=df_comb_trades_by_sec_plot['price_median_extend'], name=\"Extend\", yaxis='y1'))\n", + "fig.add_trace(go.Scatter(x=df_fr_plot['timestamp_dt'], y=df_fr_plot['funding_rate'], name=\"FR\", yaxis='y2', mode='lines+markers'))\n", + "fig.add_trace(go.Scatter(x=df_comb_trades_by_sec_plot.index, y=df_comb_trades_by_sec_plot['ratio'], name=\"Ratio\", yaxis='y3'))\n", "# fig.add_trace(go.Scatter(x=[1, 2, 3], y=[400, 500, 600], name=\"Y3\", yaxis='y3')) # \n", "\n", "fig.update_layout(\n", @@ -13825,17 +5487,17 @@ "# )\n", "# )\n", "\n", - "# fig.add_shape(\n", - "# type=\"line\",\n", - "# x0=0, x1=1,\n", - "# y0=0, y1=0,\n", - "# xref=\"paper\",\n", - "# yref=\"y2\",\n", - "# line=dict(\n", - "# color=\"red\",\n", - "# dash=\"dash\"\n", - "# )\n", - "# )\n", + "fig.add_shape(\n", + " type=\"line\",\n", + " x0=1, x1=0,\n", + " y0=1, y1=1,\n", + " xref=\"paper\",\n", + " yref=\"y3\",\n", + " line=dict(\n", + " color=\"pink\",\n", + " dash=\"dash\"\n", + " )\n", + ")\n", "\n", "# Create a range of hours\n", "start_time = int(min_time)\n", diff --git a/extended.ipynb b/extended.ipynb index f3810ea..66ca28b 100644 --- a/extended.ipynb +++ b/extended.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 9, "id": "6c70a8c3", "metadata": {}, "outputs": [], @@ -27,7 +27,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 12, "id": "ff971ca9", "metadata": {}, "outputs": [], @@ -42,50 +42,46 @@ "CONFIG = MAINNET_CONFIG\n", "\n", "ORDER_MARKET = \"ETH-USD\"\n", - "ORDER_SIDE = OrderSide.BUY\n", "ORDER_QTY = Decimal(\"0.01\")\n", - "ORDER_PRICE = Decimal(\"2200.1\")" + "ORDER_PRICE = Decimal(\"2300.1\")\n", + "ORDER_SIDE = OrderSide.BUY" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 13, "id": "fc2c6d2b", "metadata": {}, - "outputs": [], - "source": [ - "client, trading_client = await extend_auth.create_auth_account_and_trading_client()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c366706f", - "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Error response from https://api.starknet.extended.exchange/api/v1/user/order: {\"status\":\"ERROR\",\"error\":{\"code\":1125,\"message\":\"Invalid price precision\"}}\n" - ] - }, - { - "ename": "ValueError", - "evalue": "Error response from https://api.starknet.extended.exchange/api/v1/user/order: code 400 - {\"status\":\"ERROR\",\"error\":{\"code\":1125,\"message\":\"Invalid price precision\"}}", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mValueError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[4]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m placed_order = await trading_client.place_order(\n\u001b[32m 2\u001b[39m market_name=ORDER_MARKET,\n\u001b[32m 3\u001b[39m amount_of_synthetic=ORDER_QTY,\n\u001b[32m 4\u001b[39m price=ORDER_PRICE,\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniconda3/envs/py_313/lib/python3.13/site-packages/x10/perpetual/trading_client/trading_client.py:101\u001b[39m, in \u001b[36mPerpetualTradingClient.place_order\u001b[39m\u001b[34m(self, market_name, amount_of_synthetic, price, side, taker_fee, post_only, previous_order_id, expire_time, time_in_force, self_trade_protection_level, external_id, builder_fee, builder_id, reduce_only, tp_sl_type, take_profit, stop_loss)\u001b[39m\n\u001b[32m 78\u001b[39m expire_time = utc_now() + timedelta(hours=\u001b[32m1\u001b[39m)\n\u001b[32m 80\u001b[39m order = create_order_object(\n\u001b[32m 81\u001b[39m account=\u001b[38;5;28mself\u001b[39m.__stark_account,\n\u001b[32m 82\u001b[39m market=market,\n\u001b[32m (...)\u001b[39m\u001b[32m 99\u001b[39m stop_loss=stop_loss,\n\u001b[32m 100\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m101\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mawait\u001b[39;00m \u001b[38;5;28mself\u001b[39m.__order_management_module.place_order(order)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniconda3/envs/py_313/lib/python3.13/site-packages/x10/perpetual/trading_client/order_management_module.py:31\u001b[39m, in \u001b[36mOrderManagementModule.place_order\u001b[39m\u001b[34m(self, order)\u001b[39m\n\u001b[32m 28\u001b[39m LOGGER.debug(\u001b[33m\"\u001b[39m\u001b[33mPlacing an order: id=\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[33m\"\u001b[39m, order.id)\n\u001b[32m 30\u001b[39m url = \u001b[38;5;28mself\u001b[39m._get_url(\u001b[33m\"\u001b[39m\u001b[33m/user/order\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m---> \u001b[39m\u001b[32m31\u001b[39m response = \u001b[38;5;28;01mawait\u001b[39;00m send_post_request(\n\u001b[32m 32\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m \u001b[38;5;28mself\u001b[39m.get_session(),\n\u001b[32m 33\u001b[39m url,\n\u001b[32m 34\u001b[39m PlacedOrderModel,\n\u001b[32m 35\u001b[39m json=order.to_api_request_json(exclude_none=\u001b[38;5;28;01mTrue\u001b[39;00m),\n\u001b[32m 36\u001b[39m api_key=\u001b[38;5;28mself\u001b[39m._get_api_key(),\n\u001b[32m 37\u001b[39m )\n\u001b[32m 38\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m response\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniconda3/envs/py_313/lib/python3.13/site-packages/x10/utils/http.py:173\u001b[39m, in \u001b[36msend_post_request\u001b[39m\u001b[34m(session, url, model_class, json, api_key, request_headers, response_code_to_exception)\u001b[39m\n\u001b[32m 171\u001b[39m \u001b[38;5;28;01masync\u001b[39;00m \u001b[38;5;28;01mwith\u001b[39;00m session.post(url, json=json, headers=headers) \u001b[38;5;28;01mas\u001b[39;00m response:\n\u001b[32m 172\u001b[39m response_text = \u001b[38;5;28;01mawait\u001b[39;00m response.text()\n\u001b[32m--> \u001b[39m\u001b[32m173\u001b[39m \u001b[30;43mhandle_known_errors\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43murl\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mresponse_code_to_exception\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mresponse\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mresponse_text\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m 174\u001b[39m response_model = parse_response_to_model(response_text, model_class)\n\u001b[32m 176\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m (response_model.status != ResponseStatus.OK) \u001b[38;5;129;01mor\u001b[39;00m (response_model.error \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m):\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/miniconda3/envs/py_313/lib/python3.13/site-packages/x10/utils/http.py:243\u001b[39m, in \u001b[36mhandle_known_errors\u001b[39m\u001b[34m(url, response_code_handler, response, response_text)\u001b[39m\n\u001b[32m 241\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m response.status > \u001b[32m299\u001b[39m:\n\u001b[32m 242\u001b[39m LOGGER.error(\u001b[33m\"\u001b[39m\u001b[33mError response from \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[33m: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[33m\"\u001b[39m, url, response_text)\n\u001b[32m--> \u001b[39m\u001b[32m243\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mError response from \u001b[39m\u001b[38;5;132;01m{\u001b[39;00murl\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m: code \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mresponse.status\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m - \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mresponse_text\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m)\n", - "\u001b[31mValueError\u001b[39m: Error response from https://api.starknet.extended.exchange/api/v1/user/order: code 400 - {\"status\":\"ERROR\",\"error\":{\"code\":1125,\"message\":\"Invalid price precision\"}}" + "Unclosed client session\n", + "client_session: \n" ] } ], + "source": [ + "client, trading_client = await extend_auth.create_auth_account_and_trading_client()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "07887649", + "metadata": {}, + "outputs": [], + "source": [ + "### Figure out how to flatten small residuals - market order with reduce only?)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "c366706f", + "metadata": {}, + "outputs": [], "source": [ "placed_order = await trading_client.place_order(\n", " market_name=ORDER_MARKET,\n", @@ -98,6 +94,27 @@ ")" ] }, + { + "cell_type": "code", + "execution_count": 15, + "id": "ba85f1e9", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "WrappedApiResponse[PlacedOrderModel](status='OK', data=PlacedOrderModel(id=2049239831434784768, external_id='359148168147219671570709517544221313286652228166698232409514334035033828578'), error=None, pagination=None)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "placed_order" + ] + }, { "cell_type": "code", "execution_count": 5, diff --git a/main.py b/main.py index 5fd1402..ee42aa8 100644 --- a/main.py +++ b/main.py @@ -5,7 +5,6 @@ import math import os import time import traceback -from dataclasses import asdict, dataclass, field from datetime import datetime, timezone from decimal import ROUND_DOWN, Decimal from typing import AsyncContextManager @@ -37,24 +36,30 @@ load_dotenv() LOG_FILEPATH: str = os.getenv("LOGS_PATH") + '/Fund_Rate_Algo.log' ### Algo Config ### -ALGO_CONFIG: structs.Algo_Config = None +ALGO_CONFIG: structs.Algo_Config | None = None MIN_TIME_TO_FUNDING: int -### CONSTANTS ### +### EXCHANGES ### ASTER = structs.Perpetual_Exchange( mult = 150, lh_asset = 'ETH', rh_asset = 'USDT', symbol_asset_separator = '', ) - -EXTEND_LH_ASSET: str = 'ETH' -EXTEND_RH_ASSET: str = 'USD' -EXTEND_TICKER: str = EXTEND_LH_ASSET + '-' + EXTEND_RH_ASSET +EXTEND = structs.Perpetual_Exchange( + mult = 50, + lh_asset = 'ETH', + rh_asset = 'USD', + symbol_asset_separator = '-', +) ### GLOBALS ### -ASTER_MULT = 150 -EXTEND_MULT = 50 +Last_Aster_Fill_Time_Ts: float = 0.00 +Just_Rejected_Or_Expired: bool = False +Best_Symbol_by_Exchange: dict = {} + +# ASTER_MULT = 150 +# EXTEND_MULT = 50 ASTER_MIN_ORDER_QTY = 0.001 EXTEND_MIN_ORDER_QTY = 0.01 @@ -121,7 +126,7 @@ async def get_aster_notional_position(resp: dict | None = None): global ASTER_NOTIONAL_OBJ global ASTER_NOTIONAL_POSITION global ASTER_UNREALIZED_PNL - global ASTER_MULT + global ASTER previous_notional_obj = ASTER_NOTIONAL_OBJ @@ -159,32 +164,31 @@ async def get_aster_notional_position(resp: dict | None = None): previous_notional_position = ASTER_NOTIONAL_POSITION # if not resp: # this can never evaluate - # ASTER_MULT = float(d['leverage']) - # if abs(ASTER_NOTIONAL_POSITION) > ALGO_CONFIG.Max_Target_Notional*1.01: - if abs(ASTER_NOTIONAL_POSITION) > ALGO_CONFIG.Max_Target_Notional*2.01: - logging.info(f'BAD NOTIONAL - ASTER CHANGE: {previous_notional_position} -> {ASTER_NOTIONAL_POSITION}; UR PNL: {ASTER_UNREALIZED_PNL}; MULT: {ASTER_MULT}; d: {d}; resp: {resp}') + # ASTER.mult = float(d['leverage']) + if abs(ASTER_NOTIONAL_POSITION) > ALGO_CONFIG.Config.Max_Target_Notional*ALGO_CONFIG.Config.Max_Order_Over_Notional_Ratio: + logging.info(f'BAD NOTIONAL - ASTER CHANGE: {previous_notional_position} -> {ASTER_NOTIONAL_POSITION}; UR PNL: {ASTER_UNREALIZED_PNL}; MULT: {ASTER.mult}; d: {d}; resp: {resp}') await kill_algo() # if ASTER_NOTIONAL_POSITION != previous_notional_position: - logging.info(f'ASTER NOTIONAL CHANGE: {previous_notional_position:.2f} -> {ASTER_NOTIONAL_POSITION:.2f}; UR PNL: {ASTER_UNREALIZED_PNL:.2f}; MULT: {ASTER_MULT:.0f}; resp: {bool(resp)}') + logging.info(f'ASTER NOTIONAL CHANGE: {previous_notional_position:.2f} -> {ASTER_NOTIONAL_POSITION:.2f}; UR PNL: {ASTER_UNREALIZED_PNL:.2f}; MULT: {ASTER.mult:.0f}; resp: {bool(resp)}') async def get_extend_collateral(): global EXTEND_AVAIL_COLLATERAL get_bals = dict(dict(await EXTEND_CLIENT.account.get_balance()).get('data', {})) - EXTEND_AVAIL_COLLATERAL = get_bals.get('available_for_trade', 0) if get_bals.get('collateral_name', None)==EXTEND_RH_ASSET else 0 + EXTEND_AVAIL_COLLATERAL = get_bals.get('available_for_trade', 0) if get_bals.get('collateral_name', None)==EXTEND.rh_asset else 0 async def get_extend_notional(resp: dict | None = None): global EXTEND_NOTIONAL_OBJ global EXTEND_NOTIONAL_POSITION global EXTEND_UNREALIZED_PNL - global EXTEND_MULT + global EXTEND previous_notional_obj = EXTEND_NOTIONAL_OBJ previous_notional_position = EXTEND_NOTIONAL_POSITION if not resp: resp = dict(await EXTEND_CLIENT.account.get_positions()).get('data', []) - pos_dict = [dict(d) for d in resp if dict(d).get('market') == EXTEND_TICKER] + pos_dict = [dict(d) for d in resp if dict(d).get('market') == EXTEND.symbol] if pos_dict: pos_dict = pos_dict[0] else: @@ -195,7 +199,7 @@ async def get_extend_notional(resp: dict | None = None): pos_dict['timestamp_arrival'] = round(datetime.now().timestamp()*1000) else: - pos_dict = [dict(d) for d in resp if dict(d).get('market') == EXTEND_TICKER] + pos_dict = [dict(d) for d in resp if dict(d).get('market') == EXTEND.symbol] if pos_dict: pos_dict = pos_dict[0] else: @@ -223,12 +227,12 @@ async def get_extend_notional(resp: dict | None = None): logging.info(f'EXTEND BAD SIDE ON POSITION UPDATE: {pos_dict}') EXTEND_NOTIONAL_POSITION = notional_pos_sided - float(EXTEND_UNREALIZED_PNL) - EXTEND_MULT = pos_dict.get('leverage', EXTEND_MULT) - if abs(EXTEND_NOTIONAL_POSITION) > ALGO_CONFIG.Max_Target_Notional*2.01: - logging.info(f'BAD NOTIONAL - EXTEND CHANGE: {previous_notional_position} -> {EXTEND_NOTIONAL_POSITION}; UR PNL: {EXTEND_UNREALIZED_PNL}; MULT: {EXTEND_MULT}; d: {pos_dict}; resp: {resp}') + EXTEND.mult = pos_dict.get('leverage', EXTEND) + if abs(EXTEND_NOTIONAL_POSITION) > ALGO_CONFIG.Config.Max_Target_Notional*ALGO_CONFIG.Config.Max_Order_Over_Notional_Ratio: + logging.info(f'BAD NOTIONAL - EXTEND CHANGE: {previous_notional_position} -> {EXTEND_NOTIONAL_POSITION}; UR PNL: {EXTEND_UNREALIZED_PNL}; MULT: {EXTEND.mult}; d: {pos_dict}; resp: {resp}') await kill_algo() if EXTEND_NOTIONAL_POSITION != previous_notional_position: - logging.info(f'EXTEND NOTIONAL CHANGE: {previous_notional_position} -> {EXTEND_NOTIONAL_POSITION:.2f}; UR PNL: {EXTEND_UNREALIZED_PNL:.2f}; MULT: {EXTEND_MULT:.0f}; resp: {bool(resp)}') + logging.info(f'EXTEND NOTIONAL CHANGE: {previous_notional_position} -> {EXTEND_NOTIONAL_POSITION:.2f}; UR PNL: {EXTEND_UNREALIZED_PNL:.2f}; MULT: {EXTEND.mult:.0f}; resp: {bool(resp)}') ### EXCHANGE INFO ### async def get_aster_exch_info(): @@ -264,7 +268,7 @@ async def aster_cancel_all_orders(): logging.info(f'ASTER CANCEL ALL OPEN ORDERS RESP: {r}') async def extend_cancel_all_orders(): - r = await EXTEND_CLIENT.orders.mass_cancel(markets=[EXTEND_TICKER]) + r = await EXTEND_CLIENT.orders.mass_cancel(markets=[EXTEND.symbol]) logging.info(f'EXTEND CANCEL ALL OPEN ORDERS RESP: {r}') ### KILL ALGO ### @@ -277,29 +281,39 @@ async def kill_algo(): ### ALGO LOOP ### async def run_algo(): + global ASTER + global EXTEND + global ALGO_CONFIG global MIN_TIME_TO_FUNDING global ASTER_OPEN_ORDERS global EXTEND_OPEN_ORDERS + global Last_Aster_Fill_Time_Ts + global Just_Rejected_Or_Expired + global Best_Symbol_by_Exchange try: while True: loop_start = time.time() # print('__________Start___________') ### ALGO CONIFG ### - ALGO_CONFIG = json.loads(VAL_KEY.get('fr_orchestrator_output'), object_hook=lambda d: structs.Algo_Config(**d)) - ALGO_CONFIG.Max_Target_Notional = float(min([ASTER_MULT, EXTEND_MULT]) * ALGO_CONFIG.Target_Open_Cash_Position) + + ALGO_CONFIG = json.loads(VAL_KEY.get('fr_orchestrator_output')) + ALGO_CONFIG = structs.Algo_Config(**ALGO_CONFIG) + ALGO_CONFIG.Config.Max_Target_Notional = float(min([ASTER.mult, EXTEND.mult]) * ALGO_CONFIG.Config.Target_Open_Cash_Position) - MIN_TIME_TO_FUNDING = ALGO_CONFIG.Min_Time_To_Funding_Minutes * 60 * 1000 + MIN_TIME_TO_FUNDING = ALGO_CONFIG.Config.Min_Time_To_Funding_Minutes * 60 * 1000 ### Load Data from Feedhandlers ### + Best_Symbol_by_Exchange = json.loads(VAL_KEY.get('fr_engine_best_fund_rate_output')) + ASTER_FUND_RATE_DICT = json.loads(VAL_KEY.get('fund_rate_aster')) EXTENDED_FUND_RATE_DICT = json.loads(VAL_KEY.get('fund_rate_extended')) ASTER_FUND_RATE = float(ASTER_FUND_RATE_DICT.get('funding_rate', 0)) EXTEND_FUND_RATE = float(EXTENDED_FUND_RATE_DICT.get('funding_rate', 0)) - if ALGO_CONFIG.Flip_Side_For_Testing: + if ALGO_CONFIG.Overrides.Flip_Side_For_Testing: ASTER_FUND_RATE = ASTER_FUND_RATE * -1 EXTEND_FUND_RATE = EXTEND_FUND_RATE * -1 @@ -370,16 +384,20 @@ async def run_algo(): if order_update_status in ['CANCELED','EXPIRED']: logging.info(f'ASTER ORDER CANCELLED or EXPIRED: {order_id}') ASTER_OPEN_ORDERS.pop(idx) + Just_Rejected_Or_Expired = True + utils.send_tg_alert(f'FR_ALGO - ASTER REJECTED ({order_id})') elif order_update_status in ['PARTIALLY_FILLED']: logging.info(f'ASTER ORDER PARTIALLY FILLED: {order_id}') - await get_aster_collateral() - await get_aster_notional_position() + # await get_aster_collateral() + await get_aster_notional_position(resp=ASTER_WS_POS_UPDATES) + Last_Aster_Fill_Time_Ts = datetime.now().timestamp()*1000 utils.send_tg_alert(f'FR_ALGO - ASTER PARTIALLY FILLED ({order_id})') elif order_update_status in ['FILLED']: logging.info(f'ASTER ORDER FILLED: {order_id}') ASTER_OPEN_ORDERS.pop(idx) - await get_aster_collateral() - await get_aster_notional_position() + # await get_aster_collateral() + await get_aster_notional_position(resp=ASTER_WS_POS_UPDATES) + Last_Aster_Fill_Time_Ts = datetime.now().timestamp()*1000 utils.send_tg_alert(f'FR_ALGO - ASTER FILLED ({order_id})') else: logging.critical(f'EXTEND ORDER STATUS CHG TO UNEXPECTED VALUE, KILLING... ({order_id}): {order_orig_status} -> {order_update_status}') @@ -401,6 +419,8 @@ async def run_algo(): if order_update_status in ['CANCELLED','EXPIRED','REJECTED']: logging.info(f'EXTEND ORDER CANCELLED, REJECTED or EXPIRED: {order_id}') EXTEND_OPEN_ORDERS.pop(idx) + Just_Rejected_Or_Expired = True + utils.send_tg_alert(f'FR_ALGO - EXTEND REJECTED ({order_id})') elif order_update_status in ['PARTIALLY_FILLED']: logging.info(f'EXTEND ORDER PARTIALLY FILLED: {order_id}') await get_extend_collateral() @@ -416,10 +436,20 @@ async def run_algo(): logging.critical(f'EXTEND ORDER STATUS CHG TO UNEXPECTED VALUE, KILLING... ({order_id}): {order_orig_status} -> {order_update_status}') + # if Best_Symbol_by_Exchange['symbol_aster'] != ASTER.symbol: + # if abs( ASTER_NOTIONAL_POSITION ) > 0 or abs( EXTEND_NOTIONAL_POSITION ) > 0: + # print('Symbol switch - Flattening Positions') + # ALGO_CONFIG.Overrides.Flatten_Open_Positions = True + # else: + # print(f'Balances Flattened - Updating to Trade New Symbol: ASTER.symbol -> {Best_Symbol_by_Exchange['symbol_aster']}') + # # ASTER.symbol = Best_Symbol_by_Exchange['symbol_aster'] + # # EXTEND.symbol = Best_Symbol_by_Exchange['symbol_extended'] + + + min_between_fundings = round((abs(ASTER_FUND_RATE_TIME - EXTEND_FUND_RATE_TIME) / 1000 / 60)) FUNDINGS_AT_SAME_TIME_NEXT_HR = min_between_fundings < 5 - if ( abs(ASTER_FUND_RATE) > abs(EXTEND_FUND_RATE) ) and FUNDINGS_AT_SAME_TIME_NEXT_HR: ALPHA_EXCH = 'ASTER' ALPHA_FUND_RATE = ASTER_FUND_RATE @@ -429,20 +459,20 @@ async def run_algo(): if ALPHA_FUND_RATE < 0: ALPHA_CARRY_SIDE = 'BUY' - ALPHA_TGT_NOTIONAL = ALGO_CONFIG.Max_Target_Notional + ALPHA_TGT_NOTIONAL = ALGO_CONFIG.Config.Max_Target_Notional else: ALPHA_CARRY_SIDE = 'SELL' - ALPHA_TGT_NOTIONAL = ALGO_CONFIG.Max_Target_Notional*-1 + ALPHA_TGT_NOTIONAL = ALGO_CONFIG.Config.Max_Target_Notional*-1 def calc_next_net_fund_rate(FUNDINGS_AT_SAME_TIME_NEXT_HR: bool) -> float: if FUNDINGS_AT_SAME_TIME_NEXT_HR: - return ASTER_FUND_RATE + EXTEND_FUND_RATE + return max([ASTER_FUND_RATE, EXTEND_FUND_RATE]) - min([ASTER_FUND_RATE, EXTEND_FUND_RATE]) else: return EXTEND_FUND_RATE NEXT_NET_FUNDING_RATE = calc_next_net_fund_rate(FUNDINGS_AT_SAME_TIME_NEXT_HR) - Flags.NET_FUNDING_IS_ZERO = ( NEXT_NET_FUNDING_RATE >= ( (ALGO_CONFIG.Min_Fund_Rate_Pct_To_Trade*-1) / 100) ) and ( NEXT_NET_FUNDING_RATE <= ( ALGO_CONFIG.Min_Fund_Rate_Pct_To_Trade / 100 ) ) - if Flags.NET_FUNDING_IS_ZERO or ALGO_CONFIG.Flatten_Open_Positions: + Flags.NET_FUNDING_IS_ZERO = ( NEXT_NET_FUNDING_RATE >= ( (ALGO_CONFIG.Config.Min_Fund_Rate_Pct_To_Trade*-1) / 100) ) and ( NEXT_NET_FUNDING_RATE <= ( ALGO_CONFIG.Config.Min_Fund_Rate_Pct_To_Trade / 100 ) ) + if Flags.NET_FUNDING_IS_ZERO or ALGO_CONFIG.Overrides.Flatten_Open_Positions: ALPHA_TGT_NOTIONAL = 0.00 # if ASTER_OPEN_ORDERS or EXTEND_OPEN_ORDERS: # logging.info('NET FUNDING = 0.00; Cancelling Open Orders! then Waiting...') @@ -507,26 +537,26 @@ async def run_algo(): ASTER_TGT_TAIL_ORDERABLE = abs(ASTER_TGT_TAIL_BASE_QTY) >= MAX_MIN_ORDER_QTY EXTEND_TGT_TAIL_ORDERABLE = abs(EXTEND_TGT_TAIL_BASE_QTY) >= MAX_MIN_ORDER_QTY - Hedge_Ratio = abs(( abs( max([abs(float(EXTEND_NOTIONAL_POSITION)), 0.01]) / max([abs(float(ASTER_NOTIONAL_POSITION)), 0.01]) ) - 1 ) * 100) + # Hedge_Ratio = abs(( abs( max([abs(float(EXTEND_NOTIONAL_POSITION)), 0.01]) / max([abs(float(ASTER_NOTIONAL_POSITION)), 0.01]) ) - 1 ) * 100) + Hedge_Ratio = abs( ( EXTEND_NOTIONAL_POSITION + ASTER_NOTIONAL_POSITION ) / ASTER_NOTIONAL_POSITION ) * 100 Currently_Hedged = Hedge_Ratio < 1.00 def print_summary(use_logging: bool = False): OUT: print | logging.info = logging.info if use_logging else print OUT(f''' - LOOP SLEEP (SEC): {ALGO_CONFIG.Loop_Sleep_Sec} - FLIP SIDES FOR TESTING?: {ALGO_CONFIG.Flip_Side_For_Testing}; ASTER ORDER ENABLED? {ALGO_CONFIG.Allow_Ordering_Aster}; EXTEND ORDER ENABLED? {ALGO_CONFIG.Allow_Ordering_Extend} + LOOP SLEEP (SEC): {ALGO_CONFIG.Config.Loop_Sleep_Sec} + FLIP SIDES FOR TESTING?: {ALGO_CONFIG.Overrides.Flip_Side_For_Testing}; ASTER ORDER ENABLED? {ALGO_CONFIG.Overrides.Allow_Ordering_Aster}; EXTEND ORDER ENABLED? {ALGO_CONFIG.Overrides.Allow_Ordering_Extend} {pd.to_datetime(ASTER_FUND_RATE_TIME, unit='ms')} ({(pd.to_datetime(ASTER_FUND_RATE_TIME, unit='ms')-datetime.now()):}) | {pd.to_datetime(EXTEND_FUND_RATE_TIME, unit='ms')} ({(pd.to_datetime(EXTEND_FUND_RATE_TIME, unit='ms')-datetime.now()):}) ASTER: {ASTER_FUND_RATE:.6%} [{ASTER_FUND_RATE*10_000:.2f}bps] [{ASTER_FUND_RATE*1_000_000:.0f}pips] | EXTEND: {EXTEND_FUND_RATE:.6%} [{EXTEND_FUND_RATE*10_000:.2f}bps] [{EXTEND_FUND_RATE*1_000_000:.0f}pips] ASTER: {'LONG PAYS SHORT' if ASTER_FUND_RATE > 0 else 'SHORT PAYS LONG'} | EXTEND: {'LONG PAYS SHORT' if EXTEND_FUND_RATE > 0 else 'SHORT PAYS LONG'} - ASTER: [ Available Collateral: {ASTER_AVAIL_COLLATERAL:.4f} ] | EXTEND: [ Available Collateral: {EXTEND_AVAIL_COLLATERAL:.4f} ] ASTER: [ Notional Position $ : {ASTER_NOTIONAL_POSITION:.4f} ] | EXTEND: [ Notional Position $ : {EXTEND_NOTIONAL_POSITION:.4f} ] SAME TIME? : {FUNDINGS_AT_SAME_TIME_NEXT_HR} [ Minutes Between Fundings: {min_between_fundings} ] - NET FUNDING : {NEXT_NET_FUNDING_RATE:.6%} [{NEXT_NET_FUNDING_RATE*10_000:.2f}bps] [{NEXT_NET_FUNDING_RATE*1_000_000:.0f}pips]; Is Zero?: {Flags.NET_FUNDING_IS_ZERO} [Min: {ALGO_CONFIG.Min_Fund_Rate_Pct_To_Trade}] + NET FUNDING : {NEXT_NET_FUNDING_RATE:.6%} [{NEXT_NET_FUNDING_RATE*10_000:.2f}bps] [{NEXT_NET_FUNDING_RATE*1_000_000:.0f}pips]; Is Zero?: {Flags.NET_FUNDING_IS_ZERO} [Min: {ALGO_CONFIG.Config.Min_Fund_Rate_Pct_To_Trade}] ALPHA SIDE : {ALPHA_EXCH} [{ALPHA_CARRY_SIDE}] - TGT NOTIONAL: $ {abs(ALPHA_TGT_NOTIONAL):.2f}; Flatten Open Positions Flag? {ALGO_CONFIG.Flatten_Open_Positions} + TGT NOTIONAL: $ {abs(ALPHA_TGT_NOTIONAL):.2f}; Flatten Open Positions Flag? {ALGO_CONFIG.Overrides.Flatten_Open_Positions} ASTER: {ASTER_NOTIONAL_POSITION:.4f} -> {ASTER_TGT_NOTIONAL:.2f} [ Remain: {ASTER_TGT_TAIL:.4f} ] | EXTEND: {EXTEND_NOTIONAL_POSITION:.4f} -> {EXTEND_TGT_NOTIONAL:.2f} [ Remain: {EXTEND_TGT_TAIL:.4f} ] ASTER: {ASTER_TGT_NOTIONAL:.2f} - {ASTER_NOTIONAL_POSITION:.2f} + {ASTER_UNREALIZED_PNL:.2f} = {ASTER_TGT_TAIL:2f} | EXTEND: {EXTEND_TGT_NOTIONAL:.2f} - {EXTEND_NOTIONAL_POSITION:.2f} + {EXTEND_UNREALIZED_PNL:.2f} = {EXTEND_TGT_TAIL:2f} @@ -543,35 +573,38 @@ async def run_algo(): --- EXTEND OPEN ORDERS --- {EXTEND_OPEN_ORDERS} ''') + # ASTER: [ Available Collateral: {ASTER_AVAIL_COLLATERAL:.4f} ] | EXTEND: [ Available Collateral: {EXTEND_AVAIL_COLLATERAL:.4f} ] # Try Making Hedge Order Contingent on Alpha Order Fills (Basically Hedge has to wait for sig Diff in Balance to order.) would improve when extended is thin (Overnight). - if ALGO_CONFIG.Log_Summary_Each_Loop: + if ALGO_CONFIG.Logging.Log_Summary_Each_Loop: print_summary(use_logging=True) - if ALGO_CONFIG.Print_Summary_Each_Loop: + if ALGO_CONFIG.Logging.Print_Summary_Each_Loop: print_summary(use_logging=False) # print_summary() + ### ROUTES ### # MIN_EXPECTED_ALPHA_TO_TRADE = 0.0001 MIN_EXPECTED_ALPHA_TO_TRADE = -0.000001 # ALPHA RATIO CHECK - if not( ( Expected_Alpha_w_Taker > MIN_EXPECTED_ALPHA_TO_TRADE ) or ( ASTER_OPEN_ORDERS or EXTEND_OPEN_ORDERS ) or ALGO_CONFIG.Flatten_Open_Positions ): - # logging.info(f'Alpha Ratio too low ({ALPHA_RATIO:.8f}) and no Open Orders...') + if not( ( Expected_Alpha_Net_FR_w_Taker > MIN_EXPECTED_ALPHA_TO_TRADE ) or ( ASTER_OPEN_ORDERS or EXTEND_OPEN_ORDERS or Just_Rejected_Or_Expired or ALGO_CONFIG.Overrides.Flatten_Open_Positions) ): + if ALGO_CONFIG.Logging.Print_Summary_Each_Loop: + print(f'Alpha Ratio too low ({ALPHA_RATIO:.8f}) and no Open Orders...') pass - elif ( Expected_Alpha_w_Taker <= MIN_EXPECTED_ALPHA_TO_TRADE ) and ( ASTER_OPEN_ORDERS or EXTEND_OPEN_ORDERS ) and Currently_Hedged: + elif ( Expected_Alpha_Net_FR_w_Taker <= MIN_EXPECTED_ALPHA_TO_TRADE ) and ( ASTER_OPEN_ORDERS or EXTEND_OPEN_ORDERS ) and Currently_Hedged: await aster_cancel_all_orders() await extend_cancel_all_orders() logging.info('Expected_Alpha went away with open orders...cancelling since we are currently hedged...') - time.sleep( (1/1000)*100 ) # 100ms wait for ws cancel response + # time.sleep( (1/1000)*100 ) # 100ms wait for ws cancel response else: # logging.info(f'*** Alpha Ratio HIT - LETS ORDER: {ALPHA_RATIO:.8f}') # ASTER - if ASTER_TGT_TAIL_ORDERABLE and ALGO_CONFIG.Allow_Ordering_Aster: + if ASTER_TGT_TAIL_ORDERABLE and ALGO_CONFIG.Overrides.Allow_Ordering_Aster: symbol = ASTER.symbol side = 'BUY' if ASTER_TGT_TAIL_BASE_QTY > 0.00 else 'SELL' qty = str(abs(ASTER_TGT_TAIL_BASE_QTY)) - price = ASTER_TOB_PX - ALGO_CONFIG.Price_Worsener_Aster if side == 'BUY' else ASTER_TOB_PX + ALGO_CONFIG.Price_Worsener_Aster + price = ASTER_TOB_PX - ALGO_CONFIG.Config.Price_Worsener_Aster if side == 'BUY' else ASTER_TOB_PX + ALGO_CONFIG.Config.Price_Worsener_Aster - if abs( ( float(ASTER_TGT_TAIL_BASE_QTY)*float(price) ) + ASTER_NOTIONAL_POSITION ) > ALGO_CONFIG.Max_Target_Notional*1.01: + if abs( ( float(ASTER_TGT_TAIL_BASE_QTY)*float(price) ) + ASTER_NOTIONAL_POSITION ) > ALGO_CONFIG.Config.Max_Target_Notional*ALGO_CONFIG.Config.Max_Order_Over_Notional_Ratio: logging.info(f'TRYING TO ORDER OVER MAX NOTIOANL - ASTER: {ASTER_NOTIONAL_POSITION} + {float(ASTER_TGT_TAIL_BASE_QTY)*float(price)} (qty: {float(ASTER_TGT_TAIL_BASE_QTY):.2f}; px: {float(price):.2f})') await kill_algo() if ASTER_OPEN_ORDERS: @@ -622,6 +655,7 @@ async def run_algo(): order_resp['original_price'] = price order_resp['order_status'] = order_resp['status'] ASTER_OPEN_ORDERS.append(order_resp) + Just_Rejected_Or_Expired = False utils.send_tg_alert(f'FR_ALGO - ASTER Order ({order_resp['orderId']}). Start_$: {ASTER_NOTIONAL_POSITION:.2f}; Value: {float(ASTER_TGT_TAIL_BASE_QTY)*float(price):.2f}; Price: {float(price):.2f}') logging.info(f'ASTER ORDER PLACED SUCCESS: {order_resp}') print_summary(use_logging=True) @@ -634,13 +668,20 @@ async def run_algo(): await aster_cancel_all_orders() # EXTEND - if EXTEND_TGT_TAIL_ORDERABLE and ALGO_CONFIG.Allow_Ordering_Extend: - symbol = EXTEND_TICKER + if EXTEND_TGT_TAIL_ORDERABLE and ALGO_CONFIG.Overrides.Allow_Ordering_Extend: + Time_Since_Last_Aster_Fill_ms = ( datetime.now().timestamp()*1000 ) - Last_Aster_Fill_Time_Ts + if Time_Since_Last_Aster_Fill_ms > ( 1000 * ALGO_CONFIG.Config.Switch_To_Taker_Seconds ): # Change to allow taker orders if its been more than x seconds + post_only = False + price = EXTEND_TOB_PX - ALGO_CONFIG.Config.Price_Worsener_Extend if side == 'BUY' else EXTEND_TOB_PX + ALGO_CONFIG.Config.Price_Worsener_Extend + else: + post_only = True + price = EXTEND_TOB_PX + + symbol = EXTEND.symbol side = OrderSide.BUY if EXTEND_TGT_TAIL_BASE_QTY > 0.00 else OrderSide.SELL qty = Decimal(str(abs(EXTEND_TGT_TAIL_BASE_QTY))) - price = EXTEND_TOB_PX - ALGO_CONFIG.Price_Worsener_Extend if side == 'BUY' else EXTEND_TOB_PX + ALGO_CONFIG.Price_Worsener_Extend - if abs( ( float(EXTEND_TGT_TAIL_BASE_QTY)*float(price) ) + EXTEND_NOTIONAL_POSITION ) > ALGO_CONFIG.Max_Target_Notional*1.01: + if abs( ( float(EXTEND_TGT_TAIL_BASE_QTY)*float(price) ) + EXTEND_NOTIONAL_POSITION ) > ALGO_CONFIG.Config.Max_Target_Notional*ALGO_CONFIG.Config.Max_Order_Over_Notional_Ratio: logging.info(f'TRYING TO ORDER OVER MAX NOTIOANL - EXTEND: {EXTEND_NOTIONAL_POSITION:.2f} + {float(EXTEND_TGT_TAIL_BASE_QTY)*float(price):.2f} (qty: {float(EXTEND_TGT_TAIL_BASE_QTY):.2f}; px: {float(price):.2f})') await kill_algo() if EXTEND_OPEN_ORDERS: @@ -667,17 +708,20 @@ async def run_algo(): logging.info('EXTEND OPEN ORDER NO PX CHG; SKIPPING') else: try: + taker_fee = taker_fee=Decimal("0.00000") if post_only else Decimal("0.00025") order_resp = await EXTEND_CLIENT.place_order( market_name=symbol, amount_of_synthetic=qty, price=price, side=side, - taker_fee=Decimal("0.00025"), + taker_fee=taker_fee, previous_order_id=open_order_id, + post_only=post_only, ) except Exception as e: logging.error(f'EXTEND ORDER PLACEMENT FAILED - RESP: {order_resp}') logging.error(f'EXTEND ORDER PLACEMENT FAILED: {e}') + logging.error(f'EXTEND ORDER PLACEMENT FAILED - POSTED: market_name:{symbol}, amount_of_synthetic:{qty}, price:{price}, side:{side},taker_fee:{taker_fee}, previous_order_id:{open_order_id}, post_only:{post_only}') logging.error(traceback.format_exc()) order_resp_dict = dict(order_resp) @@ -694,6 +738,7 @@ async def run_algo(): order_dict['side'] = str(side) EXTEND_OPEN_ORDERS.append(order_dict) + Just_Rejected_Or_Expired = False utils.send_tg_alert(f'FR_ALGO - EXTEND Order ({order_dict.get('id', None)}). Start_$: {EXTEND_NOTIONAL_POSITION:.2f}; Value: {float(EXTEND_TGT_TAIL_BASE_QTY)*float(price):.2f}; Price: {float(price):.2f}') logging.info(f'EXTEND ORDER PLACED SUCCESS: {order_dict}') print_summary(use_logging=True) @@ -710,8 +755,8 @@ async def run_algo(): if ASTER_OPEN_ORDERS or EXTEND_OPEN_ORDERS: continue else: - time.sleep(ALGO_CONFIG.Loop_Sleep_Sec) - # print(f'_____ End No Open Orders _____ (Algo Engine ms: {(time.time() - loop_start)*1000:.2f}); Sleeping for sec: {ALGO_CONFIG.Loop_Sleep_Sec:.0f}') + time.sleep(ALGO_CONFIG.Config.Loop_Sleep_Sec) + # print(f'_____ End No Open Orders _____ (Algo Engine ms: {(time.time() - loop_start)*1000:.2f}); Sleeping for sec: {ALGO_CONFIG.Config.Loop_Sleep_Sec:.0f}') except KeyboardInterrupt: logging.info('CANCELLING OPEN ORDERS') @@ -736,10 +781,15 @@ async def main(): engine = create_async_engine('mysql+asyncmy://root:pwd@localhost/fund_rate') with open('algo_config.json', 'r', encoding='utf-8') as file: - ALGO_CONFIG = json.load(file, object_hook=lambda d: structs.Algo_Config(**d)) - ALGO_CONFIG.Max_Target_Notional = float(min([ASTER_MULT, EXTEND_MULT]) * ALGO_CONFIG.Target_Open_Cash_Position) + ALGO_CONFIG = json.load(file) + ALGO_CONFIG = structs.Algo_Config(**ALGO_CONFIG) - VAL_KEY.set('fr_orchestrator_output', json.dumps(asdict(ALGO_CONFIG))) + # with open('algo_config.json', 'r', encoding='utf-8') as file: + # ALGO_CONFIG = json.load(file, object_hook=lambda d: structs.Algo_Config(**d)) + + ALGO_CONFIG.Config.Max_Target_Notional = float(min([ASTER.mult, EXTEND.mult]) * ALGO_CONFIG.Config.Target_Open_Cash_Position) + + VAL_KEY.set('fr_orchestrator_output', json.dumps(ALGO_CONFIG.model_dump())) async with engine.connect() as CON: ### ASTER SETUP ### diff --git a/modules/structs.py b/modules/structs.py index d2bf0b3..88d31d1 100644 --- a/modules/structs.py +++ b/modules/structs.py @@ -3,25 +3,39 @@ from dataclasses import dataclass, field from typing import Any import valkey +from pydantic import BaseModel - -@dataclass(kw_only=True) -class Algo_Config: - Config_Updated_Timestamp: int +# @dataclass(kw_only=True) +class Algo_Config_Overrides(BaseModel): Allow_Ordering_Aster: bool Allow_Ordering_Extend: bool + Flatten_Open_Positions: bool + Flip_Side_For_Testing: bool + +# @dataclass(kw_only=True) +class Algo_Config_Config(BaseModel): Loop_Sleep_Sec: int + Max_Order_Over_Notional_Ratio: float Max_Target_Notional: float Min_Time_To_Funding_Minutes: int Min_Fund_Rate_Pct_To_Trade: float Price_Worsener_Aster: float Price_Worsener_Extend: float + Switch_To_Taker_Seconds: int Target_Open_Cash_Position: int - - Log_Summary_Each_Loop: bool = False - Print_Summary_Each_Loop: bool = False - Flatten_Open_Positions: bool = False - Flip_Side_For_Testing: bool = False + +# @dataclass(kw_only=True) +class Algo_Config_Logging(BaseModel): + Log_Summary_Each_Loop: bool + Print_Summary_Each_Loop: bool + +# @dataclass(kw_only=True) +class Algo_Config(BaseModel): + Updated_Timestamp: int + Config: Algo_Config_Config + Logging: Algo_Config_Logging + Overrides: Algo_Config_Overrides + @dataclass(kw_only=True) class Flags: diff --git a/requirements.txt b/requirements.txt index 4a4d001..b44e6de 100644 --- a/requirements.txt +++ b/requirements.txt @@ -22,4 +22,5 @@ nicegui # grpcio-tools==1.76.0 x10-python-trading-starknet eth-keys -eth-account \ No newline at end of file +eth-account +pydantic \ No newline at end of file diff --git a/ws_aster_fund_rate_all.py b/ws_aster_fund_rate_all.py new file mode 100644 index 0000000..023a4cc --- /dev/null +++ b/ws_aster_fund_rate_all.py @@ -0,0 +1,110 @@ +import asyncio +import json +import logging +import socket +import traceback +from datetime import datetime, timezone +from typing import AsyncContextManager +import math + +import numpy as np +import pandas as pd +import requests.packages.urllib3.util.connection as urllib3_cn # type: ignore +from sqlalchemy import text +import websockets +from sqlalchemy.ext.asyncio import create_async_engine +import valkey +import os +from dotenv import load_dotenv +import modules.utils as utils + +### Allow only ipv4 ### +def allowed_gai_family(): + return socket.AF_INET +urllib3_cn.allowed_gai_family = allowed_gai_family + +### Database ### +USE_DB: bool = False +USE_VK: bool = True +VK_FUND_RATE_ALL = 'fund_rate_aster_all' + +CON: AsyncContextManager | None = None +VAL_KEY = None + +### Logging ### +load_dotenv() +LOG_FILEPATH: str = os.getenv("LOGS_PATH") + '/Fund_Rate_Aster_FR_ALL.log' + +### Globals ### +WSS_URL = "wss://fstream.asterdex.com/ws/!markPrice@arr" + + +### Websocket ### +async def ws_stream(): + async for websocket in websockets.connect(WSS_URL): + logging.info(f"Connected to {WSS_URL}") + try: + async for message in websocket: + if isinstance(message, str): + try: + data = json.loads(message) + if data: + VAL_KEY.set(VK_FUND_RATE_ALL, json.dumps(data)) + # print(f'VK_SAVED: {len(data)}') + continue + else: + logging.info(f'Initial or unexpected data struct, skipping: {data}') + continue + except (json.JSONDecodeError, ValueError): + logging.warning(f'Message not in JSON format, skipping: {message}') + continue + else: + raise ValueError(f'Type: {type(data)} not expected: {message}') + except websockets.ConnectionClosed as e: + logging.error(f'Connection closed: {e}') + logging.error(traceback.format_exc()) + continue + except Exception as e: + logging.error(f'Connection closed: {e}') + logging.error(traceback.format_exc()) + +### Startup ### +async def main(): + global VAL_KEY + global CON + + if USE_VK: + VAL_KEY = valkey.Valkey(host='localhost', port=6379, db=0) + else: + VAL_KEY = None + logging.warning("VALKEY NOT BEING USED, NO DATA WILL BE PUBLISHED") + + if USE_DB: + engine = create_async_engine('mysql+asyncmy://root:pwd@localhost/fund_rate') + async with engine.connect() as CON: + # await create_rtds_btcusd_table(CON=CON) + await ws_stream() + else: + CON = None + logging.warning("DATABASE NOT BEING USED, NO DATA WILL BE RECORDED") + await ws_stream() + + +if __name__ == '__main__': + START_TIME = round(datetime.now().timestamp()*1000) + + logging.info(f'Log FilePath: {LOG_FILEPATH}') + + logging.basicConfig( + force=True, + filename=LOG_FILEPATH, + level=logging.INFO, + format='%(asctime)s - %(levelname)s - %(message)s', + filemode='w' + ) + logging.info(f"STARTED: {START_TIME}") + + try: + asyncio.run(main()) + except KeyboardInterrupt: + logging.info("Stream stopped") \ No newline at end of file diff --git a/ws_extended_fund_rate_all.py b/ws_extended_fund_rate_all.py new file mode 100644 index 0000000..8e7a369 --- /dev/null +++ b/ws_extended_fund_rate_all.py @@ -0,0 +1,133 @@ +import asyncio +import json +import logging +import socket +import traceback +from datetime import datetime, timezone +from typing import AsyncContextManager +import math + +import numpy as np +import pandas as pd +import requests.packages.urllib3.util.connection as urllib3_cn # type: ignore +from sqlalchemy import text +import websockets +from sqlalchemy.ext.asyncio import create_async_engine +import valkey +import os +from dotenv import load_dotenv +import modules.utils as utils + +### Allow only ipv4 ### +def allowed_gai_family(): + return socket.AF_INET +urllib3_cn.allowed_gai_family = allowed_gai_family + +### Database ### +USE_DB: bool = False +USE_VK: bool = True +VK_FUND_RATE = 'fund_rate_extended' +VK_FUND_RATE_ALL = 'fund_rate_extended_all' + +CON: AsyncContextManager | None = None +VAL_KEY = None + +### Logging ### +load_dotenv() +LOG_FILEPATH: str = os.getenv("LOGS_PATH") + '/Fund_Rate_Extended_FR_ALL.log' + +### Globals ### +WSS_URL = "wss://api.starknet.extended.exchange/stream.extended.exchange/v1/funding/" +LOCAL_FUNDING_RATES = [] + +def time_round_down(dt, interval_mins=5) -> int: # returns timestamp in seconds + interval_secs = interval_mins * 60 + seconds = dt.timestamp() + rounded_seconds = math.floor(seconds / interval_secs) * interval_secs + + return rounded_seconds + +### Websocket ### +async def ws_stream(): + global LOCAL_FUNDING_RATES + + async for websocket in websockets.connect(WSS_URL): + logging.info(f"Connected to {WSS_URL}") + try: + async for message in websocket: + ts_arrival = round(datetime.now().timestamp()*1000) + if isinstance(message, str): + try: + data = json.loads(message) + if data.get('data', None) is not None: + # print(f'FR: {data}') + # fr_next_update_ts = (time_round_down(dt=datetime.now(timezone.utc), interval_mins=60)+(60*60))*1000 + fr_update = { + 'sequence_id': data['seq'], + 'timestamp_arrival': ts_arrival, + 'timestamp_msg': data['ts'], + 'symbol': data['data']['m'], + 'funding_rate': float(data['data']['f']), + 'funding_rate_updated_ts_ms': data['data']['T'], + # 'next_funding_time_ts_ms': fr_next_update_ts, + } + LOCAL_FUNDING_RATES = utils.upsert_list_of_dicts_by_id(LOCAL_FUNDING_RATES, fr_update, id='symbol', seq_check_field='sequence_id') + VAL_KEY.set(VK_FUND_RATE_ALL, json.dumps(LOCAL_FUNDING_RATES)) + # print(f'VK_SAVED: {data}') + continue + else: + logging.info(f'Initial or unexpected data struct, skipping: {data}') + continue + except (json.JSONDecodeError, ValueError): + logging.warning(f'Message not in JSON format, skipping: {message}') + continue + else: + raise ValueError(f'Type: {type(data)} not expected: {message}') + except websockets.ConnectionClosed as e: + logging.error(f'Connection closed: {e}') + logging.error(traceback.format_exc()) + continue + except Exception as e: + logging.error(f'Connection closed: {e}') + logging.error(traceback.format_exc()) + +### Startup ### +async def main(): + global VAL_KEY + global CON + + if USE_VK: + VAL_KEY = valkey.Valkey(host='localhost', port=6379, db=0) + else: + VAL_KEY = None + logging.warning("VALKEY NOT BEING USED, NO DATA WILL BE PUBLISHED") + + if USE_DB: + engine = create_async_engine('mysql+asyncmy://root:pwd@localhost/fund_rate') + async with engine.connect() as CON: + # await create_rtds_btcusd_table(CON=CON) + await ws_stream() + else: + CON = None + logging.warning("DATABASE NOT BEING USED, NO DATA WILL BE RECORDED") + await ws_stream() + + +if __name__ == '__main__': + START_TIME = round(datetime.now().timestamp()*1000) + + logging.info(f'Log FilePath: {LOG_FILEPATH}') + + logging.basicConfig( + force=True, + filename=LOG_FILEPATH, + level=logging.INFO, + format='%(asctime)s - %(levelname)s - %(message)s', + filemode='w' + ) + logging.info(f"STARTED: {START_TIME}") + + try: + asyncio.run(main()) + except KeyboardInterrupt: + logging.info("Stream stopped") \ No newline at end of file