bigbucks-port 0.0.3

A package used for portfolio analysis in Fintech512

Introduction

This package is used for portfolio analysis in FINTECH 512 Bigbucks project. This package also depends on the bigbucks_db package to interact with the supabase database and Alpha Vantage.

Connect to supabase and alpha Vantage

# Connect to supabase
SUPABASE_URL = ""
KEYS = ""
objs = Table_View(SUPABASE_URL, KEYS)

# Connect to Alpha Vantage
STOCK_API_KEYS = ""
objs_realtime = Buy_And_Sell(STOCK_API_KEYS)

Import package

from bigbucks_port.portfolio import *

Functions

• Get the current portfolio holdings for user. It returns a json list includes the stock symbol, number of shares and price per share (weighted by historical cost) Note: If you want to get all the stocks for all the users, set id=None. Same for other functions below.

holding = current_holding(objs,6)

Example output:

[{"stock_symbol":"AAPL","num_shares":0,"pv":0.0,"price per share":null},{"stock_symbol":"IBM","num_shares":100,"pv":13107.0007324219,"price per share":131.0700073242}]

• Calculate the expected return, std and covariance of portfolio The statistics are calculated based on the historical data. Note: It returns 4 values, the fourth one is the json list with expected return and std for each stock and the rest 3 are used in later functions.

er,std,covar,er_std_json = er_covar(objs,6)

Example output of er_std_json

{"mean":{"AAPL":0.2318697889,"IBM":-0.0075799068},"std":{"AAPL":0.3361717704,"IBM":0.2759977582}}

• Get the risk and return for a list of portfolios with randomly generated weights

# N: number of portfolios generated
return_risk = rand_scatter(5,objs,6)

Example output

{"mean": [0.13009300157209497, 0.02497749995225248, 0.16554410436129516, 0.14454572030763208, 0.10086096141188186], "std": [0.06705431545265916, 0.0656856601122741, 0.07160084144613905, 0.0686922284906061, 0.06474888518469718]}

• Get the risk and return for the efficient frontier

return_risk = frontier(objs,6)

Example output

{"mean": [],"std":[]}

• Get the optimal portfolio given a risk free rate

opt = optimize_port(0.0025,objs,6)

Example output

{"opt mean": 0.2318697888966346, "opt std": 0.08412521675427394, "opt sharpe": 2.7265283555418782}

• Get the risk and return for the current portfolio Note: weight is calculated by the current holding

risk_return = cur_risk_return(0.0025,objs,6)

Example output

{'mean': -0.007579906778486523, 'std': 0.06906698680510652, 'sharpe': -0.1459439197330273}

• Calculate the holding period return and balance

holding_stat = holding_return(objs,6,objs_realtime)

Example output

# PV: the market value of all cash and stocks in the account
# Cash: cash remained in the account balance
{'PV': 1000000.0, 'Cash': 986892.9992675781, 'Holding period return': 0.0}