Esempio n. 1
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    def _process_forex(self, row : Dict[str, str]) ->Trade:
        date_time = datetime.strptime(row["Date/Time"],
                                      '%Y-%m-%d, %H:%M:%S')  # 2019-07-01, 14:48:19
        price: float = float(row["T. Price"].replace(",", ""))
        quantity: float = float(row["Quantity"].replace(",", ""))
        proceeds: float = float(row["Proceeds"].replace(",", ""))
        commission: float = float(row["Comm in AUD"].replace(",", ""))
        symbol: str = str(row["Symbol"])
        currency: str = str(row["Currency"])
        asset_category: str = str(row["Asset Category"].upper())

        # Fix strange Interactive Brokers convention of setting AUD as quanity and USD amount as proceeds.
        # Possibly a result of indirect quoting. Swapping quantity/proceeds and AUD.USD to USD.AUD.
        if symbol == "AUD.USD":
            return Trade("USD.AUD",
                                asset_category,
                                date_time,
                                1 / price,  # NB: converted to USD.AUD.
                                # This is a bit of a hack as there should be a conversion class to
                                # handle this. Keep as market convention quote, convert all floats to
                                # Amounts which contain Currency and have a translater divide or
                                # multiply as required to convert.
                                "AUD",  # Hack: Report seems to use USD?
                                proceeds,
                                Amount(commission, "AUD"),
                                'BROKER_REPORT')
        else:
            raise NotImplementedError(
                "Only AUD.USD currency trades implemented as I am unsure how IB treats other currencies.")
Esempio n. 2
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 def _process_trade(self, row : Dict[str, str]) -> Trade:
     date_time = datetime.strptime(row["Date/Time"],
                                   '%Y-%m-%d, %H:%M:%S')  # 2019-07-01, 14:48:19
     #price: float = float(row["T. Price"].replace(",", "")) # Cannot use as contracts might have multipliers.
     quantity: float = float(row["Quantity"].replace(",", ""))
     proceeds: float = float(row["Notional Value"].replace(",", ""))
     commission: float = float(row["Comm/Fee"].replace(",", ""))
     symbol: str = str(row["Symbol"])
     currency: str = str(row["Currency"])
     asset_category: str = str(row["Asset Category"]).upper()
     effective_price = abs(proceeds / quantity)
     return Trade(symbol,
                  asset_category,
                  date_time,
                  effective_price,
                  currency,
                  quantity,
                  Amount(commission, currency),
                  'BROKER_REPORT')
Esempio n. 3
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def open_new_trade(user, currency):
    """
    Returns a new trade
    """
    user = get_user(msg=user)

    affiliate = get_affiliate(user.chat)
    if affiliate != None:
        affiliate = affiliate.id

    trade = Trade(
        id=generate_id(),
        seller=user.id,
        currency=currency,
        payment_status=False,
        created_at=str(datetime.now()),
        updated_at=str(datetime.now()),
        is_open=True,
        affiliate_id=affiliate,
    )

    session.add(trade)
    session.commit()
import pandas as pd
import json
import datetime
from model import Pair, Trade
fp = open("input_csv/ed_trade_data.json")
jsondata = json.load(fp)
pairlist = jsondata.keys()

total_data = []
for i in pairlist:
    pair = Pair(i)
    pair_data = jsondata[str(pair)]
    trades = []
    for j in pair_data:
        trade = Trade(i, j)
        trades.append(trade)
    total_data.append(trades)
print pd.DataFrame(total_data)
Esempio n. 5
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import pandas as pd
import json
import datetime
from model import Pair, Trade
fp = open("input_csv/ed_trade_data.json")
jsondata = json.load(fp)
pairlist = jsondata.keys()

y = {
    u'amount':
    u'510',
    u'amountBase':
    u'0.01377',
    u'buyer':
    u'0x13e2c5f84bce6ff7b9068313b21729dc8fd55d5a',
    u'seller':
    u'0x96e1e7ba823796772bbda5c2abe81c8556b5e937',
    u'tokenAddr':
    u'0x814964b1bceaf24e26296d031eadf134a2ca4105',
    u'txHash':
    u'0x122b9d6932b50d748d7848aae071cf41f7df8baa1400472dbcc4182bf3287478'
}

b = Trade('ETH_NEWB', y)
print b
    def calculate_proceeds(
            self, trades: List[TranslatedTrade]) -> List[TranslatedTrade]:
        matched_trades: List[MatchedInventory[
            TranslatedTrade]] = self.inventory_accountant.match_trades(trades)
        proceed_trades: List[TranslatedTrade] = list(trades)
        for matched_trade in matched_trades:
            if matched_trade.buy_trade.currency != 'AUD':
                # Estimate gain/loss in foreign currency.
                price_difference = matched_trade.sell_trade.price - matched_trade.buy_trade.price
                proceeds = matched_trade.quantity * price_difference

                # Create effective trade to account for FX flow from foreign asset sale.
                # ATO translates all foreign assets to AUD for tax purposes on trade. If there is a foreign
                # currency gain/loss then the fx cost base is the ATO fx rate at sale.
                proxy_trade = Trade(matched_trade.sell_trade.currency + '.AUD',
                                    'FOREX', matched_trade.sell_trade.date,
                                    matched_trade.sell_trade.exchange_rate,
                                    'AUD', proceeds, Amount(0, 'AUD'),
                                    'SALE_PROCEEDS')

                # Set the FX rate/price to the ATO-based FX rate used on selling the underlying asset.
                taxable_proxy_trade = TranslatedTrade(
                    proxy_trade, matched_trade.sell_trade.exchange_rate, 1, 0,
                    'AUD')
                proceed_trades.append(taxable_proxy_trade)

            #And again for the buy commission
            if matched_trade.buy_trade.commission.currency != 'AUD':
                proportion_matched = matched_trade.quantity / abs(
                    matched_trade.buy_trade.quantity)
                proxy_trade = Trade(
                    matched_trade.buy_trade.currency + '.AUD', 'FOREX',
                    matched_trade.buy_trade.date,
                    matched_trade.buy_trade.exchange_rate, 'AUD',
                    proportion_matched *
                    matched_trade.buy_trade.commission.value, Amount(0, 'AUD'),
                    'COMMISSION')
                taxable_proxy_trade = TranslatedTrade(
                    proxy_trade,
                    proportion_matched * matched_trade.buy_trade.exchange_rate,
                    1, 0, 'AUD')
                proceed_trades.append(taxable_proxy_trade)

            # And one mroe for the sell commission
            if matched_trade.sell_trade.commission.currency != 'AUD':
                proportion_matched = matched_trade.quantity / abs(
                    matched_trade.sell_trade.quantity)
                proxy_trade = Trade(
                    matched_trade.sell_trade.currency + '.AUD', 'FOREX',
                    matched_trade.sell_trade.date,
                    matched_trade.sell_trade.exchange_rate, 'AUD',
                    proportion_matched *
                    matched_trade.sell_trade.commission.value,
                    Amount(0, 'AUD'), 'COMMISSION')
                taxable_proxy_trade = TranslatedTrade(
                    proxy_trade, proportion_matched *
                    matched_trade.sell_trade.exchange_rate, 1, 0, 'AUD')
                proceed_trades.append(taxable_proxy_trade)

        # Static method to help with sorting
        def get_date(t: Trade) -> datetime:
            return t.date

        sorted_trades = sorted(proceed_trades, key=get_date)

        return sorted_trades
Esempio n. 7
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    return q

def read_trade_price():
    """ Get Trade Price from input """
    trade_price = float(0)
    while(True):
        q = raw_input("Enter trade price:")
        try:
            trade_price = float(q)
            break
        except:
            print("Invalid trade price.  Try again.")
    return trade_price

if __name__ == '__main__':
    print('Please select stocks from '+(",".join(symbol_list)))
    trades = []
    while(True):
        symbol = read_stock_symbol()
        market_price = read_trade_price()
        q = read_trade_quantity()
        
        current_stock = service.get_stock_by_symbol(symbol)
        
        trades.append(Trade(trade_count.next(), time.time(), current_stock.id, q, market_price, "BUY"))

        print("PE Ratio for "+symbol+":"+str(round(service.get_pe_ratio(market_price, symbol),3 )))
        print("Dividend yield for "+symbol+":"+str(round(service.get_dividend_yeild(market_price, symbol), 3)))
        print("VSMP for "+symbol+":"+str(round(service.get_volume_weighted_stock_price(trades, current_stock.id),3)))
        print("Geometric Mean for "+symbol+":"+str(round(service.get_geometric_mean(trades, current_stock.id), 3)))
        print("\n")