Esempio n. 1
0
def triggeredUp(symbObj, curPrice, buyPrice, closePrice, maxPrice, sellUpDn,
                latestTrades):
    global gainers
    print("Starting thread for " + symbObj['symbol'])

    while ((curPrice / buyPrice >= maxPrice / buyPrice * sellUpDn
            or curPrice / closePrice >= maxPrice / closePrice * sellUpDn)
           and a.timeTillClose() >= 30):
        curPrice = a.getPrice(symbObj['symbol'])
        maxPrice = max(maxPrice, curPrice)
        print(symbObj['symbol'] + " - " + str(round(curPrice / buyPrice, 2)) +
              ":" + str(round(maxPrice / buyPrice * sellUpDn, 2)) + " - " +
              str(round(curPrice / closePrice, 2)) + ":" +
              str(round(maxPrice / closePrice, 2)))
        a.o.time.sleep(3)

    print(a.createOrder("sell", symbObj['qty'], symbObj['symbol']))
    latestTrades[symbObj['symbol']] = {
        "tradeDate": str(a.o.dt.date.today()),
        "tradeType": "sell",
        "buyPrice": 0,  #reset the avgBuyPrice to 0 after a sell
        "shouldSell": False
    }
    with open(a.o.c['latestTradesFile'], "w") as f:
        f.write(a.o.json.dumps(latestTrades, indent=2))
    #remove from gainers in case it sells after updateStockList has run
    if (symbObj['symbol'] in gainers):
        gainers.remove(symbOjb['symbol'])
Esempio n. 2
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def check2buy(latestTrades, minBuyPow, buyPowMargin, minDolPerStock):
    usableBuyPow = float(
        a.getAcct()['buying_power'])  #init as the current buying power
    if (
            buyPowMargin < 1
    ):  #buyPowMargin MUST BE GREATER THAN 1 in order for it to work correctly
        raise (
            "Error: withdrawlable funds margin is less than 1. Multiplier must be >=1"
        )

    if (
            usableBuyPow >= minBuyPow * buyPowMargin
    ):  #if we have more buying power than the min plus some leeway, then reduce it to hold onto that buy pow
        print(f"Can safely withdrawl ${round(minBuyPow,2)}")
        usableBuyPow = usableBuyPow - minBuyPow * buyPowMargin  #subtract the minBuyPow plus the margin
    elif (usableBuyPow > minBuyPow
          and usableBuyPow < minBuyPow * buyPowMargin):
        usableBuyPow = 0  #stop trading if we've started to eat into the margin, that way we don't overshoot

    if (len(gainers) > 0):
        dolPerStock = max(
            minDolPerStock, usableBuyPow / len(gainers)
        )  #if buyPow>(minDolPerStock*len(gainers)) then divvy up buyPow over gainers
    else:
        dolPerStock = minDolPerStock

    i = 0  #index of gainers
    stocksBought = 0  #number of stocks bought

    stocks2buy = int(usableBuyPow / dolPerStock)  #number of stocks to buy

    while (stocksBought < stocks2buy and i < len(gainers)):
        symb = gainers[i]  #candidate stock to buy
        #TODO: in this conditional, also check that the gain isn't greater than ~75% of sellUp (e.g. must be <1.15 if sellUp=1.2)
        if (symb not in [
                t.getName() for t in threading.enumerate()
        ]):  #make sure the stock isn't trying to be sold already
            try:  #check when it was traded last
                lastTradeDate = a.o.dt.datetime.strptime(
                    latestTrades[symb]['tradeDate'], '%Y-%m-%d').date()
                lastTradeType = latestTrades[symb]['tradeType']
                try:
                    avgBuyPrice = latestTrades[symb]['buyPrice']
                except Exception:
                    avgBuyPrice = 0
            except Exception:
                lastTradeDate = a.o.dt.datetime.today().date(
                ) - a.o.dt.timedelta(1)
                lastTradeType = "NA"
                avgBuyPrice = 0

            #for some reason this check was being bypassed. This should be resolved in the updateStockList function where it removes any prospective stock to be bought from the list if it was sold today
            if (lastTradeType != "sell"
                    or lastTradeDate < a.o.dt.datetime.today().date()
                ):  #make sure we didn't sell it today already
                if (a.isAlpacaTradable(symb)
                    ):  #make sure it's tradable on the market
                    curPrice = a.getPrice(symb)
                    if (curPrice > 0):
                        shares2buy = int(dolPerStock / curPrice)
                        orderText = a.createOrder("buy", shares2buy, symb,
                                                  "market", "day")
                        #make sure it actually executed the order, then increment
                        if (orderText.endswith('accepted')):
                            print(orderText)
                            #record the transaction
                            latestTrades[
                                symb] = {  #set the avgBuyPrice to the average of the currentPrice and the previous avg (unless the prev avg<=0)
                                    "tradeDate":
                                    str(a.o.dt.date.today()),
                                    "tradeType":
                                    "buy",
                                    "buyPrice": (curPrice + avgBuyPrice) /
                                    (1 + avgBuyPrice > 0),
                                    "shouldSell":
                                    False
                                }
                            with open(a.o.c['latestTradesFile'], "w") as f:
                                f.write(a.o.json.dumps(latestTrades, indent=2))
                            stocksBought += 1
                        i += 1  #try the next stock
                    else:
                        i += 1  #try the next stock
                else:
                    i += 1  #try the next stock
            else:
                i += 1  #try the next stock
        else:
            i += 1  #try the next stock

    print("Done buying")
Esempio n. 3
0
def check2sell(symList, latestTrades, mainSellDn, mainSellUp, sellUpDn):
    print(
        "symb\tinit jump\tpred jump (+/- 3wks)\tchg from buy\tchg from close\tsell points"
    )
    print(
        "----\t---------\t--------------------\t------------\t--------------\t-----------"
    )
    for e in symList:
        #if(a.isAlpacaTradable(e['symbol'])): #just skip it if it can't be traded - skipping this for slower connections & to save a query
        try:
            lastTradeDate = a.o.dt.datetime.strptime(
                latestTrades[e['symbol']]['tradeDate'], '%Y-%m-%d').date()
            lastTradeType = latestTrades[e['symbol']]['tradeType']
            avgBuyPrice = float(
                e['avg_entry_price']
            )  #if it doesn't exist, default to the avg buy price over all time - it's important to keep a separate record to reset after a sell rather than over all time
        except Exception:
            lastTradeDate = a.o.dt.date.today() - a.o.dt.timedelta(1)
            lastTradeType = "NA"
            avgBuyPrice = float(e['avg_entry_price'])

        try:
            shouldSell = latestTrades[e['symbol']]['shouldSell']
        except Exception:  #in the event it doesn't exist, don't worry about it
            shouldSell = False

        #if marked to sell, sell regardless of price immediately
        if (shouldSell):
            print(e['symbol'] + " marked for immediate sale.")
            print(a.createOrder("sell", e['qty'], e['symbol']))
            latestTrades[e['symbol']] = {
                "tradeDate": str(a.o.dt.date.today()),
                "tradeType": "sell",
                "buyPrice": 0,
                "shouldSell": False
            }
            with open(a.o.c['latestTradesFile'], "w") as f:
                f.write(a.o.json.dumps(latestTrades, indent=2))

        elif (
                lastTradeDate < a.o.dt.date.today() or lastTradeType == "sell"
                or float(a.getPrice(e['symbol'])) / avgBuyPrice >= 1.75
        ):  #prevent selling on the same day as a buy (only sell if only other trade today was a sell or price increased substantially)
            buyPrice = avgBuyPrice
            closePrice = float(e['lastday_price'])
            #curPrice = float(e['current_price'])
            curPrice = a.getPrice(e['symbol'])
            maxPrice = 0
            buyInfo = a.o.goodBuy(e['symbol'], 260)

            try:
                lastJump = a.o.dt.datetime.strptime(buyInfo, "%m/%d/%Y").date()
                #adjust selling targets based on date to add a time limit

                #sellUp change of 0 if <=5 weeks after initial jump, -.05 for every week after 6 weeks for a min of 1
                sellUp = round(
                    max(
                        1, mainSellUp - .05 * max(
                            0,
                            int((a.o.dt.date.today() -
                                 (lastJump + a.o.dt.timedelta(6 * 7))).days /
                                7))), 2)
                #sellDn change of 0 if <=5 weeks after initial jump, +.05 for every week after 6 weeks for a max of 1
                sellDn = round(
                    min(
                        1, mainSellDn + .05 * max(
                            0,
                            int((a.o.dt.date.today() -
                                 (lastJump + a.o.dt.timedelta(6 * 7))).days /
                                7))), 2)

                totalChange = round(curPrice / buyPrice, 2)
                dayChange = round(curPrice / closePrice, 2)
                print(
                    f"{e['symbol']}\t{lastJump}\t{lastJump+a.o.dt.timedelta(5*7)}\t\t{bcolor.FAIL if totalChange<1 else bcolor.OKGREEN}{totalChange}{bcolor.ENDC}\t\t{bcolor.FAIL if dayChange<1 else bcolor.OKGREEN}{dayChange}{bcolor.ENDC}\t\t{sellUp} & {sellDn}"
                )
            except Exception:
                print(e['symbol'] + " - " + buyInfo)
                sellUp = mainSellUp
                sellDn = mainSellDn

            #cut the losses if we missed the jump or if the price dropped too much
            if (buyPrice == 0 or curPrice / buyPrice <= sellDn
                    or buyInfo == "Missed jump"):
                print("Lost it on " + e['symbol'])
                print(a.createOrder("sell", e['qty'], e['symbol']))
                latestTrades[e['symbol']] = {
                    "tradeDate": str(a.o.dt.date.today()),
                    "tradeType": "sell",
                    "buyPrice": 0,
                    "shouldSell": False
                }
                with open(a.o.c['latestTradesFile'], "w") as f:
                    f.write(a.o.json.dumps(latestTrades, indent=2))

            #use e['lastday_price'] to get previous close amount ... or curPrice/float(e['lastday_price'])>=sellUpFromYesterday
            elif (curPrice / buyPrice >= sellUp
                  or curPrice / closePrice >= sellUp):
                if (
                        not e['symbol']
                        in [t.getName() for t in threading.enumerate()]
                ):  #if the thread is not found in names of the running threads, then start it (this stops multiple instances of the same stock thread)
                    print("Trigger point reached on " + e['symbol'] +
                          ". Seeing if it will go up...")
                    triggerThread = threading.Thread(
                        target=triggeredUp,
                        args=(e, curPrice, buyPrice, closePrice, maxPrice,
                              sellUpDn, latestTrades))  #init the thread
                    triggerThread.setName(
                        e['symbol'])  #set the name to the stock symb
                    triggerThread.start()  #start the thread
Esempio n. 4
0
def check2buyDJ(latestTrades, pos, minBuyPow, buyPowMargin, minDolPerStock):

    pQty = {e['symbol']: e['qty']
            for e in pos}  #isolate just the held stock and the # of shares
    usableBuyPow = float(
        a.getAcct()['cash'])  #init as the current buying power

    if (
            buyPowMargin < 1
    ):  #buyPowMargin MUST BE GREATER THAN 1 in order for it to work correctly
        raise (
            "Error: withdrawlable funds margin is less than 1. Multiplier must be >=1"
        )

    if (
            usableBuyPow >= minBuyPow * buyPowMargin
    ):  #if we have more buying power than the min plus some leeway, then reduce it to hold onto that buy pow
        print(f"Can safely withdrawl ${round(minBuyPow,2)}")
        usableBuyPow = usableBuyPow - minBuyPow * buyPowMargin  #subtract the minBuyPow plus the margin
    elif (usableBuyPow > minBuyPow
          and usableBuyPow < minBuyPow * buyPowMargin):
        usableBuyPow = 0  #stop trading if we've started to eat into the margin, that way we don't overshoot

    if (len(gainers) > 0):
        #TODO: investigate this delaration?
        dolPerStock = max(
            minDolPerStock, usableBuyPow / len(gainers)
        )  #if buyPow>(minDolPerStock*len(gainers)) then divvy up buyPow over gainers
    else:
        dolPerStock = minDolPerStock

    i = 0  #index of gainers
    stocksBought = 0  #number of stocks bought

    stocks2buy = int(usableBuyPow / dolPerStock)  #number of stocks to buy
    gainerList = list(
        gainers
    )  #Shuffle the list to avoid scanning from the top down every loop (must be a list rather than dict)
    random.shuffle(gainerList)
    while (stocksBought < stocks2buy and i < len(gainers)):
        symb = gainerList[i]  #candidate stock to buy
        #TODO: in this conditional, also check that the gain isn't greater than ~75% of sellUp (e.g. must be <1.15 if sellUp=1.2)

        if (
                symb not in [t.getName() for t in threading.enumerate()]
                and gainers[symb]['algo'] == "DJ"
        ):  #make sure the stock isn't trying to be sold already and that the algorithm is doubleJump
            try:  #check when it was traded last
                lastTradeDate = a.o.dt.datetime.strptime(
                    latestTrades['doubleJump'][symb]['tradeDate'],
                    '%Y-%m-%d').date()
                lastTradeType = latestTrades['doubleJump'][symb]['tradeType']
                try:
                    avgBuyPrice = latestTrades['doubleJump'][symb]['buyPrice']
                except Exception:
                    avgBuyPrice = 0
            except Exception:
                lastTradeDate = a.o.dt.datetime.today().date(
                ) - a.o.dt.timedelta(1)
                lastTradeType = "NA"
                avgBuyPrice = 0

            #for some reason this check was being bypassed. This should be resolved in the updateStockList function where it removes any prospective stock to be bought from the list if it was sold today
            if (lastTradeType != "sell"
                    or lastTradeDate < a.o.dt.datetime.today().date()
                ):  #make sure we didn't sell it today already
                # if(a.isAlpacaTradable(symb)): #make sure it's tradable on the market (optional check?)
                [curPrice, mktCap] = a.getPrice(
                    symb, True
                )  #market cap is needed because we don't want to buy too much of the company that the pattern would no longer hold
                sharesHeld = 0 if (symb not in pQty) else float(
                    pQty[symb]
                )  #get the shares held of a certain stock (if we have it)
                if (curPrice > 0):
                    #calc outstanding shares, reduce to our acceptable holding % of shares, account for currently held shares (don't let it go negative). If within that range, then just look at the divvied cash
                    shares2buy = min(
                        max(
                            int(mktCap / curPrice *
                                float(a.o.c['Buy Params']['maxVolPerc']) -
                                sharesHeld), 0), int(dolPerStock / curPrice))
                    #shares2buy = int(dolPerStock/curPrice) #outdated # of shares to buy (does not account for marketCap)
                    orderText = a.createOrder("buy", shares2buy, symb,
                                              "market", "day")
                    #make sure it actually executed the order, then increment
                    if (orderText.endswith('accepted')):
                        print(orderText)
                        #record the transaction
                        latestTrades['doubleJump'][
                            symb] = {  #set the avgBuyPrice to the average of the currentPrice and the previous avg (unless the prev avg<=0)
                                "tradeDate":
                                str(a.o.dt.date.today()),
                                "tradeType":
                                "buy",
                                "buyPrice": (curPrice + avgBuyPrice) /
                                (1 + avgBuyPrice > 0),
                                "shouldSell":
                                False
                            }
                        with open(a.o.c['File Locations']['latestTradesFile'],
                                  "w") as f:
                            f.write(a.o.json.dumps(latestTrades, indent=2))
                        stocksBought += 1
                    i += 1  #try the next stock
                else:
                    i += 1  #try the next stock
                # else:
                # i += 1 #try the next stock
            else:
                i += 1  #try the next stock
        else:
            i += 1  #try the next stock

    print("Done buying")
Esempio n. 5
0
def check2sellDJ(symList, latestTrades, mainSellDn, mainSellUp, sellUpDn):
    global jumpDates
    print(
        "symb\tchg from buy\tchg from close\tsell points\tinit jump\tpred jump (+/- 3wks)"
    )
    print(
        "----\t------------\t--------------\t-----------\t---------\t--------------------"
    )
    for e in symList:
        #if(a.isAlpacaTradable(e['symbol'])): #just skip it if it can't be traded - skipping this for slower connections & to save a query
        try:
            lastTradeDate = a.o.dt.datetime.strptime(
                latestTrades['doubleJump'][e['symbol']]['tradeDate'],
                '%Y-%m-%d').date()
            lastTradeType = latestTrades['doubleJump'][
                e['symbol']]['tradeType']
            avgBuyPrice = float(
                e['avg_entry_price']
            )  #if it doesn't exist, default to the avg buy price over all time - it's important to keep a separate record to reset after a sell rather than over all time
        except Exception:
            lastTradeDate = a.o.dt.date.today() - a.o.dt.timedelta(1)
            lastTradeType = "NA"
            avgBuyPrice = float(e['avg_entry_price'])

        try:
            shouldSell = latestTrades['doubleJump'][e['symbol']]['shouldSell']
        except Exception:  #in the event it doesn't exist, don't worry about it
            shouldSell = False

        #if marked to sell, sell regardless of price immediately
        if (shouldSell):
            print(e['symbol'] + " marked for immediate sale.")
            print(a.createOrder("sell", e['qty'], e['symbol']))
            latestTrades['doubleJump'][e['symbol']] = {
                "tradeDate": str(a.o.dt.date.today()),
                "tradeType": "sell",
                "buyPrice": 0,
                "shouldSell": False
                #TODO: add isTradable:date
                #TODO: add sharesHeld:##
            }
            with open(a.o.c['File Locations']['latestTradesFile'], "w") as f:
                f.write(a.o.json.dumps(latestTrades, indent=2))

        elif (
                lastTradeDate < a.o.dt.date.today() or lastTradeType == "sell"
                or float(a.getPrice(e['symbol'])) / avgBuyPrice >= 1.75
        ):  #prevent selling on the same day as a buy (only sell if only other trade today was a sell or price increased substantially)
            buyPrice = avgBuyPrice
            closePrice = float(e['lastday_price'])
            #curPrice = float(e['current_price'])
            curPrice = a.getPrice(e['symbol'])
            maxPrice = 0

            #setup jump dates/info about the held positions (reset in markandupdate() and at the beginning of the program)
            if (e['symbol'] not in jumpDates
                    and e['symbol'] in latestTrades['doubleJump']
                ):  #only update if not already present
                jumpDates[e['symbol']] = a.o.goodBuy(e['symbol'], 260)
            #TODO: add another check here that if it does have an error, try updating it again (especially if few points available)
            #elif(jumpDates[e['symbol']]!= <some date format>): then do the thing also
#        jumpDates[e['symbol']] = a.o.goodBuy(e['symbol'],260)
            buyInfo = jumpDates[e[
                'symbol']]  #TODO: phase out buyInfo in lieu of just jumpDates index
            totalChange = round(curPrice / buyPrice, 2)
            dayChange = round(curPrice / closePrice, 2)

            try:
                lastJump = a.o.dt.datetime.strptime(buyInfo, "%m/%d/%Y").date()
                #adjust selling targets based on date to add a time limit

                #after some weeks since the initial jump, the sell values should reach 1 after some more weeks
                #piecewise function: if less than time to start squeezing, remain constant, else start squeezing linearily per day
                sellUp = mainSellUp if (
                    a.o.dt.date.today() < lastJump + a.o.dt.timedelta(
                        float(a.o.c['Sell Params']['startSqueeze']) * 7)
                ) else mainSellUp - (mainSellUp - 1) * (
                    a.o.dt.date.today() - (lastJump + a.o.dt.timedelta(
                        float(a.o.c['Sell Params']['startSqueeze']) * 7))
                ).days / (float(a.o.c['Sell Params']['squeezeTime']) * 7)

                sellDn = mainSellDn if (
                    a.o.dt.date.today() < lastJump + a.o.dt.timedelta(
                        float(a.o.c['Sell Params']['startSqueeze']) * 7)
                ) else mainSellDn - (mainSellDn - 1) * (
                    a.o.dt.date.today() - (lastJump + a.o.dt.timedelta(
                        float(a.o.c['Sell Params']['startSqueeze']) * 7))
                ).days / (float(a.o.c['Sell Params']['squeezeTime']) * 7)

                #sellUp change of 0 if <=5 weeks after initial jump, -.05 for every week after 6 weeks for a min of 1
                # sellUp = round(max(1,mainSellUp-.05*max(0,int((a.o.dt.date.today()-(lastJump+a.o.dt.timedelta(6*7))).days/7))),2)
                #sellDn change of 0 if <=5 weeks after initial jump, +.05 for every week after 6 weeks for a max of 1
                # sellDn = round(min(1,mainSellDn+.05*max(0,int((a.o.dt.date.today()-(lastJump+a.o.dt.timedelta(6*7))).days/7))),2)

                print(
                    f"{e['symbol']}\t{bcolor.FAIL if totalChange<1 else bcolor.OKGREEN}{totalChange}{bcolor.ENDC}\t\t{bcolor.FAIL if dayChange<1 else bcolor.OKGREEN}{dayChange}{bcolor.ENDC}\t\t{round(sellUp,2)} & {round(sellDn,2)}\t{lastJump}\t{lastJump+a.o.dt.timedelta(5*7)}\t"
                )
            except Exception:
                sellUp = mainSellUp
                sellDn = mainSellDn
                print(
                    f"{e['symbol']}\t{bcolor.FAIL if totalChange<1 else bcolor.OKGREEN}{totalChange}{bcolor.ENDC}\t\t{bcolor.FAIL if dayChange<1 else bcolor.OKGREEN}{dayChange}{bcolor.ENDC}\t\t{round(sellUp,2)} & {round(sellDn,2)}\t{buyInfo}"
                )

            #cut the losses if we missed the jump or if the price dropped too much
            if (
                    buyPrice == 0 or curPrice / buyPrice <= sellDn
                    or buyInfo == "Missed jump"
            ):  #TODO: ensure that the stock is part of the DJ algo (should actually also check in the main algo rather then here, though might be good to check both?
                print("Lost it on " + e['symbol'])
                print(a.createOrder("sell", e['qty'], e['symbol']))
                latestTrades['doubleJump'][e['symbol']] = {
                    "tradeDate": str(a.o.dt.date.today()),
                    "tradeType": "sell",
                    "buyPrice": 0,
                    "shouldSell": False
                }
                with open(a.o.c['File Locations']['latestTradesFile'],
                          "w") as f:
                    f.write(a.o.json.dumps(latestTrades, indent=2))

            #use e['lastday_price'] to get previous close amount ... or curPrice/float(e['lastday_price'])>=sellUpFromYesterday
            elif (curPrice / buyPrice >= sellUp
                  or curPrice / closePrice >= sellUp):
                if (
                        not e['symbol']
                        in [t.getName() for t in threading.enumerate()]
                ):  #if the thread is not found in names of the running threads, then start it (this stops multiple instances of the same stock thread)
                    print("Trigger point reached on " + e['symbol'] +
                          ". Seeing if it will go up...")
                    triggerThread = threading.Thread(
                        target=triggeredUpDJ,
                        args=(e, curPrice, buyPrice, closePrice, maxPrice,
                              sellUpDn, latestTrades))  #init the thread
                    triggerThread.setName(
                        e['symbol'])  #set the name to the stock symb
                    triggerThread.start()  #start the thread
Esempio n. 6
0
def algo12():
    #TODO: fix sellAll instances so that it will only record in the event that we actually made trades
    f = open("algo12.txt", "r")  #contains json info regarding trading
    j = a.json.loads(f.read())
    f.close()

    symb = j['symb']
    d = j["periodDateStart"].split("-")
    periodStartDate = date(int(d[0]), int(d[1]), int(d[2]))
    periodStartVal = float(j["periodPortStart"])

    d = j["lastTradeDate"].split("-")
    lastTradeDate = date(int(d[0]), int(d[1]), int(d[2]))
    lastSellPrice = float(j["lastSellPrice"])
    maxPrice = 0
    # minPrice = 100000 #may be used later in trying to get the best buy
    currentPrice = 0
    shares2buy = 0
    buyPrice = 0

    period = 10  #length of period (d)
    sellUp = 5
    sellUpDn = 3
    sellDn = 16
    # buyDnUp = 1
    portGain = 20
    portLoss = 25

    timeFromClose = 300  #seconds from close to start analyzing to buy
    timeSinceStart = 300  #seconds from start to analyze to sell (before infrequent checking)

    shortTime = 2
    medTime = 20
    longTime = 60 * 10

    while True:
        #while the market is still alive
        print("\nMarket is alive")
        print("Today is " + str(date.today()) + ", the period start date is " +
              str(periodStartDate))
        print("Day " + str(nwd(periodStartDate, date.today()) - 1) + " of " +
              str(period))
        while (nwd(periodStartDate, date.today()) - 1 < period):
            #while within the period
            print("We're within the period.")

            [openTime, closeTime] = a.openCloseTimes(str(
                date.today()))  #get the open and close times of today

            while (a.marketIsOpen() and date.today() > lastTradeDate):
                #while the market is open on a given day (that we haven't traded yet)
                print("\nMarket is open, and no trades made yet")
                print("Time is: " + str(a.dt.now()))

                if (
                        a.getShares(symb) > 0
                ):  #only check to sell if we have shares in the first place
                    print("We have shares")
                    buyPrice = a.getBuyPrice(
                        symb)  #set var to avoid lots of redundant calls
                    while ((a.dt.now() - openTime).seconds < timeSinceStart):
                        #while we're near the open time
                        currentPrice = a.getPrice(
                            symb)  #set var to avoid lots of redundant calls
                        print(
                            str((a.dt.now() - openTime).seconds) +
                            "s since open | stock change " +
                            str(round((currentPrice / buyPrice - 1) *
                                      100, 2)) + "%")
                        #check frequently to sell
                        if (currentPrice > buyPrice * (1 + sellUp / 100)):
                            #if the stock price has reached the sell limit
                            print("Stock has reached limit - up " + str(
                                round(100 *
                                      (currentPrice / buyPrice - 1), 2) + "%"))
                            maxPrice = max(maxPrice, currentPrice)
                            if (currentPrice <= maxPrice *
                                (1 - sellUpDn / 100)):
                                print("Sell up conditions met.")
                                if (a.sellAll(0)):
                                    #set trade flag
                                    lastTradeDate = date.today()
                                    lastSellPrice = currentPrice
                                    j['lastTradeDate'] = str(lastTradeDate)
                                    j['lastSellPrice'] = lastSellPrice
                            time.sleep(
                                shortTime)  #we're excited, so check often
                        else:
                            time.sleep(medTime)  #only check every so often

                if (lastTradeDate < date.today()):
                    portVal = float(a.getAcct()['portfolio_value'])
                    print("Checking portfolio status")
                    if (portVal > periodStartVal * (1 + portGain / 100)
                            or portVal < periodStartVal *
                        (1 - portLoss / 100)):
                        print("Portfolio won or lost - " +
                              str(round(portVal / periodStartVal, 2)) + "%")
                        if (a.sellAll(0)):
                            periodStartDate = a.date.today()
                            periodStartVal = portVal
                            lastTradeDate = a.date.today()
                            lastSellPrice = a.getPrice(symb)
                            j['lastTradeDate'] = str(lastTradeDate)
                            j['lastSellPrice'] = lastSellPrice
                            j['periodStartDate'] = periodStartDate
                            j['poeriodPortStart'] = periodStartVal

                            #record the end of the period data
                            portVal = float(a.getAcct()['portfolio_value'])
                            print("Portfolio Value: $" +
                                  str(round(portVal, 2)))
                            f = open("alpacaPortValues.txt", "a")
                            f.write("\n" + str(date.today()) + "," +
                                    str(portVal))
                            f.close()

                            print("Starting period over.")
                        break
                    else:
                        print("Portfolio change: " + str(
                            round((portVal / periodStartVal - 1) * 100, 2)) +
                              "%")
                else:
                    break

                if (lastTradeDate < date.today()):
                    print("No trades made yet today.")
                    while (a.timeTillClose() <= timeFromClose):
                        #while we're close to the end of the day
                        print("Close to closing | " + str(a.dt.now()) + " / " +
                              str(closeTime))
                        #buy if no shares held, or sell if it reaches the sellUp % method
                        currentPrice = a.getPrice(symb)
                        maxPrice = 0

                        if (a.getShares(symb) == 0):
                            print("No shares held. Buying.")
                            #include buyDnUp & minPrice here
                            shares2buy = int(
                                float(a.getAcct()['buying_power']) /
                                currentPrice)
                            print(
                                a.createOrder("buy", shares2buy, symb,
                                              "market", "day"))
                            lastTradeDate = a.date.today()
                            j['lastTradeDate'] = str(lastTradeDate)
                            break
                        elif (currentPrice >= a.getBuyPrice(symb) *
                              (1 + sellUp / 100)):
                            print("Shares still held, and price is going up")
                            while (currentPrice >= maxPrice * (1 - sellUpDn)
                                   and a.timeTillClose() > shortTime * 2):
                                print("Time left: " + str(a.timeTillClose(
                                )) + "s | Stock change: " + str(
                                    round(currentPrice /
                                          a.getBuyPrice(symb), 2) - 1) + "%")
                                currentPrice = a.getPrice(symb)
                                maxPrice = max(maxPrice, currentPrice)
                                time.sleep(shortTime)
                            if (
                                    currentPrice >= maxPrice * (1 - sellUpDn)
                            ):  #if the price is still up (hasn't started dropping yet), then wait till next morning to sell
                                print(
                                    "Price is still up, but market is closing. Will continue tomorrow."
                                )
                            else:
                                if (a.sellAll(0)):
                                    lastTradeDate = a.date.today()
                                    lastSellPrice = currentPrice
                                    j['lastTradeDate'] = str(lastTradeDate)
                                    j['lastSellPrice'] = lastSellPrice
                                break

                        time.sleep(medTime)

                    #if we're at any other time of the day
                    #check slow - only sell
                    if (lastTradeDate < a.date.today()
                            and a.getShares(symb) > 0):
                        if (a.getPrice(symb) >= a.getBuyPrice(symb) *
                            (1 + sellUp / 100)):
                            print("Price going up")
                            maxPrice = 0
                            while (currentPrice >= maxPrice *
                                   (1 - sellUpDn / 100)):
                                currentPrice = a.getPrice(symb)
                                maxPrice = max(maxPrice, currentPrice)
                                print("Current Price: " + str(currentPrice) +
                                      ", Max Price: " + str(maxPrice))
                                time.sleep(shortTime)
                            if (a.sellAll(0)):
                                lastSellPrice = currentPrice
                                lastTradeDate = a.date.today()
                                j['lastTradeDate'] = str(lastTradeDate)
                                j['lastSellPrice'] = lastSellPrice
                            break
                    time.sleep(
                        min(longTime, abs(a.timeTillClose() - timeFromClose))
                    )  #in case we're too close to the closing time, we don't want to overrun it
                else:
                    break

            # set values and wait for the market to open again
            print("Done trading for the day.")
            f = open("algo12.txt", "w")
            f.write(a.json.dumps(j))
            f.close()
            maxPrice = 0
            currentPrice = 0
            shares2buy = 0
            print("Current Time: " + str(a.marketTime()))
            print("Will resume in " + str(a.timeTillOpen()) + " seconds")
            time.sleep(a.timeTillOpen())

        #sell all at end of period and reset values
        print("End of period. Selling all and resetting.")
        if (a.sellAll(0)):  #sell everything at the end of the period
            #record the end of the period data
            portVal = float(a.getAcct()['portfolio_value'])
            print("Portfolio Value: $" + str(round(portVal, 2)))
            f = open("alpacaPortValues.txt", "a")
            f.write("\n" + str(date.today()) + "," + str(portVal))
            f.close()

            #record the trading info
            lastTradeDate = date.today()
            j['lastTradeDate'] = str(lastTradeDate)
            j['periodDateStart'] = str(date.today())
            j['periodPortStart'] = a.getAcct()['portfolio_value']
            maxPrice = 0
            currentPrice = 0
            shares2buy = 0
            f = open("algo12.txt", "w")
            f.write(a.json.dumps(j))
            f.close()
        print("Current Time: " + str(a.marketTime()))
        print("Will resume in " + str(a.timeTillOpen()) + " seconds")
        time.sleep(a.timeTillOpen())
    '''
Esempio n. 7
0
def algo11():

    #initial conditions
    symb = 'xspa'  #symbol to work with
    timeLimit = 10  #trading days since start to stop
    startDate = date(2020, 5, 6)  #day first started investing
    startPortVal = float(
        a.getAcct()['portfolio_value'])  #starting portfolio value

    #selling constants (%)
    portSellUp = 20
    portSellDn = 25
    stockSellDn = 16
    stockSellUp = 2
    stockSellUpDn = 1

    #timing constants (s)
    countdown = 10
    longwait = 60 * 10
    shortWait = 30

    #variables
    tradeMadeToday = False  #flag if a trade has been made today
    currentPortVal = 0
    currentStockVal = 0
    sellPrice = 0  #price stocks sold at - $/share
    shares2buy = 0  #number of shares to buy in a given order

    #this assumes that shares are held of the stock 'symb', or no shares are held at all
    while (True):
        maxStockVal = 0  #additional variable to set/reset after the time limit/period
        #additional functionailty to choose new stocks on some cirteria should go here

        #at this point, all of the money should be in buying power

        #make sure that the shares are held in the correct stock, if not, prompt to sell
        if (a.getShares(symb) == 0 and not tradeMadeToday):
            if (
                    len(a.getPos())
            ):  #this shouldn't ever happen, but just in case, we error check
                print(str(a.getPos()).replace(',', '\n') + "\n")
                print("Error: Shares already held other than " + symb)
                if (
                        not a.sellAll(1)
                ):  #prompt user to sell all - returns 0 if cancelled, 1 if finished selling
                    sys.exit(
                        "Only shares of '" + symb +
                        "' are valid. Please sell all to proceed."
                    )  #restart if cancelled - program probably won't work otherwise
            else:  #this should happen the most often - if we're sure no stocks are held, then we can buy some
                if (not a.marketIsOpen()
                    ):  #wait until open, if it's not already
                    print("Waiting till open to buy.")
                    time.sleep(a.timeTillOpen())
                shares2buy = int(
                    float(acctInfo['buying_power']) / a.getPrice(symb))
                print(a.createOrder("buy", shares2buy, symb, "market", "day"))
                tradeMadeToday = True
                startDate = date.today()

#at this point, we should have as many shares as we can afford

        while (nwd(startDate, date.today()) <=
               timeLimit):  #as long as we're in the time limit
            if (not tradeMadeToday and a.marketIsOpen()):
                currentStockVal = a.getPrice(
                    symb)  # if(a.getShares(symb)) else currentStockVal = 0 #
                if (currentStockVal <
                    (a.getBuyPrice(symb) * (1 - stockSellDn / 100))):
                    print("Lost the stock")
                    a.sellAll(0)
                    sellPrice = a.getPrice(symb)
                    tradeMadeToday = True

                elif (currentStockVal >=
                      (a.getBuyPrice(symb) * (1 + stockSellUp / 100))
                      and a.getBuyPrice(symb) > 0):
                    print("Won the stock")
                    while (currentStockVal >
                           (maxStockVal * (1 - stockSellUpDn / 100))):
                        time.sleep(shortwait)
                        currentStockVal = a.getPrice(symb)
                        maxStockVal = max(maxStockVal, currentStockVal)
                        print("Current Stock Value: " + str(currentStockVal) +
                              ", Sell price:" + str(maxStockVal *
                                                    (1 - stockSellUpDn / 100)))
                    a.sellAll(0)
                    tradeMadeToday = True

                acctInfo = a.getAcct()
                currentPortVal = float(acctInfo['portfolio_value'])
                if (currentPortVal <= startPortVal * (1 - portSellDn / 100)):
                    print("Lost the portfolio")
                    a.sellAll(0)
                    sellPrice = a.getPrice(symb)
                    # tradeMadeToday = True
                    break

                elif (currentPortVal >= startPortVal * (1 + portSellUp / 100)):
                    print("Won the portfolio!")
                    a.sellAll(0)
                    sellPrice = a.getPrice(symb)
                    # tradeMadeToday = True
                    break

            if (not tradeMadeToday and a.getShares(symb) == 0):
                print("No trades today, and no shares held, so we're buying.")
                shares2buy = int(
                    float(acctInfo['buying_power']) / a.getPrice(symb))
                print(a.createOrder('buy', shares2buy, symb, 'market', 'day'))

            if (a.marketIsOpen() and not tradeMadeToday
                ):  #this enforces 1 trade per day only during market open
                print(
                    "Market is open, and no trades made today - Current Portfolio Value Change: "
                    + str(a.getPortfolioChange(startPortVal)) + "%")
                time.sleep(longwait)
            else:
                print(str(timeTillOpen()) + " seconds till open. Be patient.")
                time.sleep(timeTillOpen() - countdown)
                tradeMadeToday = False  #reset for the start of a new day
                for i in range(countdown, 0, -1):
                    print(i)
                    time.sleep(1)
                print("Welcome to day " + str(nwd(startDate, date.today())) +
                      " of " + str(timeLimit) +
                      " - Current Portfolio Value: " +
                      a.getAcct()['portfolio_value'] + " | " +
                      str(a.getPortfolioChange(startPortVal)) +
                      "% from start of period.")

        print("End of Period. Selling all and starting over.")
        a.sellAll(0)
        tradeMadeToday = True
        startPortVal = float(a.getAcct()['portfolio_value'])
        startDate = date.today()
Esempio n. 8
0
def algo10():

    symb = 'SD'  #ticker symbol
    length = 10  #days to hold out for
    sellUp = 9  #sell if the stock is up this far
    sellDn = 19  #sell if the stock falls this far

    # startPortfolio = float(a.getAcct()["portfolio_value"]) #portfolio balance at the beginning
    startPortfolio = 100.0

    portfolioGain = 20  #if portfolio value gains by this %, sell and wait till end of period
    portfolioLoss = 50  #if portfolio value falls by this %, sell and wait till end of period
    buyPrice = a.getBuyPrice(symb)  #init last buy price
    sellPrice = 0  #init last sell price

    sharesHeld = a.getShares(symb)  #get current held shares of the stock

    # startDate = date(2020,4,27)
    marketTime = a.marketTime()  #do this to reduce number of API calls
    startDate = date(marketTime[0], marketTime[1],
                     marketTime[2])  #date of initial investments
    today = date(marketTime[0], marketTime[1],
                 marketTime[2])  #date to be contiuously updated
    # filename = "/srv/http/portfolio.json" #used on the serve to display public data

    while ((today - startDate).days <= length):  #while within the period
        # marketTime = a.marketTime()
        # today = date(marketTime[0],marketTime[1],marketTime[2]) #set today
        print("Day " + str((today - startDate).days) + " of " +
              str(length))  #show the current day
        # f = open(filename,'w') #open the json file to write to
        # f.write(a.json.dumps({"portfolioIncrease":float(a.getAcct()["portfolio_value"])/startPortfolio, "period":length,"daysIn":(today-startDate).days})) #write the json data for the server
        # f.close()  #close the json file
        tradeMade = 0  #reset daily trade counter
        if (a.marketIsOpen()):

            #check portfolio value
            if (float(a.getAcct()["portfolio_value"]) >=
                ((1 + portfolioGain / 100) * startPortfolio)):
                sellPrice = a.getPrice(symb)
                a.sellAll(0)
                tradeMade = 1
                print("Win Time: " + str(today - startDate) + " days")
                sharesHeld = a.getShares(symb)
                break
            elif ((float(a.getAcct()["portfolio_value"]) <=
                   (1 - portfolioLoss / 100)) and (sharesHeld > 0)):
                print(
                    "Portfolio Failed at " + str(a.marketTime()) +
                    " - Current Value: " +
                    a.getAcct()["portfolio_value"])  #let me know what happened
                sellPrice = a.getPrice(symb)
                a.sellAll(0)
                tradeMade = 1
                sharesHeld = a.getShares(symb)

            #check stock value
            sharesHeld = a.getShares(symb)  #get currently held shares
            stockVal = a.getPrice(symb)  # get the stock's current value
            if (
                    a.getShares(symb) == 0 and stockVal >= sellPrice
            ):  #if we don't have shares, and and the price has increased since the last sale, buy
                buyPrice = int(
                    float(a.getAcct()['buying_power']) /
                    stockVal)  #set "buy price", this is actually shares to buy
                print(a.createOrder("buy", buyPrice, symb, "market",
                                    "day"))  #may have to make a limit buy
                buyPrice = float(
                    a.getBuyPrice(symb))  #get actual price bought at
            elif (
                    sharesHeld > 0
                    and (stockVal >=
                         (1 + sellUp / 100) * buyPrice or stockVal <=
                         (1 - sellDn / 100) * buyPrice)
            ):  #if shares are held and their value is sufficiently different to sell
                if (not tradeMade):  #if a trade hasn't been made yet today
                    if (today == startDate):  #on the first day we buy
                        #buy as much as we can afford
                        if (sharesHeld == 0):  #if no shares held, buy some
                            sharesHeld = int(
                                float(a.getAcct()['buying_power']) /
                                a.getPrice(symb)
                            )  #set # of shares to purchase based on price and current buying power
                            print(
                                a.createOrder(
                                    "buy", sharesHeld, symb, "market",
                                    "day"))  #may have to make a limit buy
                            buyPrice = float(a.getBuyPrice(
                                symb))  #get actual price bought at
                            sharesHeld = a.getShares(
                                symb)  #get actual shares held
                            tradeMade = 1  #indicate that a trade has been made today
                    else:  #it's not the first day anymore
                        #check portfolio value
                        if (float(a.getAcct()["portfolio_value"]) >=
                            ((1 + portfolioGain / 100) * startPortfolio)
                            ):  #if portfolio reached target gain
                            sellPrice = a.getPrice(symb)  #get appx sell price
                            a.sellAll(0)  #sell everything
                            tradeMade = 1  #set the flag
                            print("Win Time: " + str(today - startDate) +
                                  " days")
                            sharesHeld = a.getShares(
                                symb
                            )  #update to actual shares held (should be 0)
                            break  #stop the loop
                        elif ((float(a.getAcct()["portfolio_value"]) <=
                               (1 - portfolioLoss / 100))
                              and (sharesHeld > 0)):  #if portfolio lost :(
                            print(
                                "Portfolio lost too much. Selling out until we recover."
                            )
                            sellPrice = a.getPrice(symb)  #get appx sell price
                            a.sellAll(0)  #sell everything
                            sharesHeld = a.getShares(
                                symb)  #get the shares held
                            tradeMade = 1  #set the flag

                        #check stock value
                        stockVal = a.getPrice(
                            symb)  # get the stock's current value
                        sharesHeld = a.getShares(symb)  #update shares held
                        if (
                                sharesHeld == 0 and stockVal >= sellPrice
                        ):  # if we don't have shares and the price has increased from the last sale (i.e. has recovered from a slide)
                            buyPrice = int(
                                float(a.getAcct()['buying_power']) /
                                stockVal)  #this is actually shares to buy
                            print(
                                a.createOrder(
                                    "buy", buyPrice, symb, "market",
                                    "day"))  #may have to make a limit buy
                            buyPrice = float(a.getBuyPrice(
                                symb))  #get actual price bought at
                        elif (
                                sharesHeld > 0 and
                            (stockVal >=
                             (1 + sellUp / 100) * buyPrice or stockVal <=
                             (1 - sellDn / 100) * buyPrice)
                        ):  #if we have shares and it's greater or less than our initial buying price
                            print("Lost the stock :/") if stockVal <= (
                                1 - sellDn / 100) * buyPrice else print(
                                    "Won the stock :)")
                            a.sellAll(0)  #sell everything
            else:  #market closed
                print("Done trading for the day.")

            time.sleep(60 * 15)
            print(
                str(a.marketTime()) + " - portfolio Value: " +
                a.getAcct()["portfolio_value"])
        print(str(round(timeTillOpen() / 60, 2)) + " minutes till open.")

        time.sleep(60 * 30) if timeTillOpen() > (60 * 30) else time.sleep(60 *
                                                                          5)