Not-sold Insider Holdings Effect

1from AlgorithmImports import *
2import pandas as pd
3from io import StringIO
4#endregion
5
6class NotSoldInsiderHoldingsEffect(QCAlgorithm):
7
8def Initialize(self):
9self.SetStartDate(2010, 1, 1)
10self.SetCash(100000)
11
12self.last_date = None
13
14self.insiders_by_symbol = {}    # storing list of insiders keyed by symbols for trading
15self.managed_queue = []
16
17self.holding_period = 12        # holding each stock for 12 months
18
19self.insiders_trading = {}      # list of insiders data keyed by date
20
21sp100_stocks = ['AAPL','MSFT','AMZN','FB','BRKB','GOOGL','GOOG','JPM','JNJ','V','PG','XOM','UNH','BAC','MA','T','DIS','INTC','HD','VZ','MRK','PFE','CVX','KO','CMCSA','CSCO','PEP','WFC','C','BA','ADBE','WMT','CRM','MCD','MDT','BMY','ABT','NVDA','NFLX','AMGN','PM','PYPL','TMO','COST','ABBV','ACN','HON','NKE','UNP','UTX','NEE','IBM','TXN','AVGO','LLY','ORCL','LIN','SBUX','AMT','LMT','GE','MMM','DHR','QCOM','CVS','MO','LOW','FIS','AXP','BKNG','UPS','GILD','CHTR','CAT','MDLZ','GS','USB','CI','ANTM','BDX','TJX','ADP','TFC','CME','SPGI','COP','INTU','ISRG','CB','SO','D','FISV','PNC','DUK','SYK','ZTS','MS','RTN','AGN','BLK']
22
23for symbol in sp100_stocks:
24    data = self.AddEquity(symbol, Resolution.Daily)
25    data.SetLeverage(10)
26    data.SetFeeModel(CustomFeeModel())
27
28    csv_string_file = self.Download(f'data.quantpedia.com/backtesting_data/economic/insiders_trading/{symbol}.csv')
29    if csv_string_file == "":
30        continue
31    
32    parser = lambda x: pd.datetime.strptime(x, "%Y-%m-%d")
33    df = pd.read_csv(StringIO(csv_string_file), sep=';', parse_dates=['Tran.Date'], date_parser=parser)
34    
35    # this is only possible, because index consists of numbers in sequence
36    for index in range(df.shape[0]):
37        date = df.loc[index, 'Tran.Date'].date()
38        
39        data_dict = df.loc[index, ['Symbol', 'Filer Name', 'Relation', 'Action']].to_dict()
40        
41        if date not in self.insiders_trading:
42            self.insiders_trading[date] = []
43        self.insiders_trading[date].append(data_dict)
44        
45        if self.last_date is None or self.last_date < date:
46            self.last_date = date
47   
48self.recent_month = -1
49self.sold_shares_previous_month = {}    # monthly stored sellers
50self.is_already_insider_by_symbol = {}  # store every insider in any company
51
52def OnData(self, data):
53current_date = self.Time.date()
54
55if current_date in self.insiders_trading:
56    curr_date_data = self.insiders_trading[current_date]
57    
58    for insider_dict in curr_date_data:
59        symbol = insider_dict['Symbol']
60        insider_name = insider_dict['Filer Name']
61        relation = insider_dict['Relation'].lower()
62        trade = insider_dict['Action'].lower()
63        
64        # insider sold his/her holdings
65        if symbol in self.insiders_by_symbol and trade == 's' and insider_name in self.insiders_by_symbol[symbol]:
66            # store name of insider who sold shares during current month
67            if symbol not in self.sold_shares_previous_month:
68                self.sold_shares_previous_month[symbol] = []
69            self.sold_shares_previous_month[symbol].append(insider_name)
70            
71            # not deleting name - insider is still active but he will be counted out from trading for the next month
72            # self.insiders_by_symbol[symbol].remove(insider_name)
73            # if len(self.insiders_by_symbol[symbol]) == 0:
74            #     del self.insiders_by_symbol[symbol]
75        
76        # check if insider is officer or director in this company and made buy or sell
77        if ('officer' in relation or 'director' in relation) and (trade in ['s', 'b']):
78            for is_insider_already_symbol in self.is_already_insider_by_symbol:
79                # check wheter insider is also insider in other company and not counted in trading collection
80                if is_insider_already_symbol != symbol and insider_name in self.is_already_insider_by_symbol[is_insider_already_symbol]:
81                    if symbol not in self.insiders_by_symbol:
82                        self.insiders_by_symbol[symbol] = []
83                    self.insiders_by_symbol[symbol].append(insider_name)
84                    break
85                
86            if symbol not in self.is_already_insider_by_symbol:
87                self.is_already_insider_by_symbol[symbol] = []
88            # store insider name for one symbol
89            if insider_name not in self.is_already_insider_by_symbol[symbol]:
90                self.is_already_insider_by_symbol[symbol].append(insider_name)
91
92if self.Time.month == self.recent_month:
93    return    
94self.recent_month = self.Time.month
95
96long = []
97
98long_length = 0
99
100# create new portfolio part for trade
101for symbol, insiders_list in self.insiders_by_symbol.items():
102    if symbol in data and data[symbol]:
103        last_price = data[symbol].Value
104        
105        # seller will be counted out from trading for the next month
106        n_of_sellers_last_month = len(self.sold_shares_previous_month[symbol]) if symbol in self.sold_shares_previous_month else 0
107        symbol_diff_occurences = len(insiders_list) - n_of_sellers_last_month
108        
109        long_length += symbol_diff_occurences
110        
111        long.append((symbol, symbol_diff_occurences, last_price))
112
113# clear previous month's sells
114self.sold_shares_previous_month.clear()
115
116# stop trading at the end of the date
117if self.last_date <= current_date:
118    self.insiders_by_symbol.clear()
119
120long_symbol_q = []
121
122if long_length != 0:
123    for symbol, diff_occ, price in long:
124        # calculate portfolio weight for curr symbol
125        weight = self.Portfolio.TotalPortfolioValue / self.holding_period / long_length * diff_occ
126        long_symbol_q.append((symbol, np.floor(weight / price)))
127
128    self.managed_queue.append(RebalanceQueueItem(long_symbol_q))
129
130# rebalance portfolio
131remove_item = None
132
133for item in self.managed_queue:
134    if item.holding_period == self.holding_period: # all portfolio parts are held for n months
135        for symbol, quantity in item.opened_symbol_q:
136            self.MarketOrder(symbol, -quantity)
137                    
138        remove_item = item
139    
140    # trade execution    
141    if item.holding_period == 0: # all portfolio parts are held for n months
142        opened_symbol_q = []
143        
144        for symbol, quantity in item.opened_symbol_q:
145            if symbol in data and data[symbol]:
146                self.MarketOrder(symbol, quantity)
147                opened_symbol_q.append((symbol, quantity))
148                    
149        # only opened orders will be closed        
150        item.opened_symbol_q = opened_symbol_q
151        
152    item.holding_period += 1
153    
154# need to remove closed part of portfolio after loop. Otherwise it will miss one item in self.managed_queue
155if remove_item:
156    self.managed_queue.remove(remove_item)
157
158class RebalanceQueueItem():
159def __init__(self, symbol_q):
160# symbol/quantity collections
161self.opened_symbol_q = symbol_q  
162self.holding_period = 0
163
164# Custom fee model
165class CustomFeeModel(FeeModel):
166def GetOrderFee(self, parameters):
167fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
168return OrderFee(CashAmount(fee, "USD"))