Stock Market

Trading Simulation

Stock Market

Trading Simulation

股票模擬交易－均值回歸策略

均值回歸策略

Mean Reversion Startegy

均值回歸策略

Mean Reversion Startegy

EBBS AND FLOWS

均值回歸策略

Mean Reversion Startegy

均值回歸策略

Mean Reversion Startegy

對於長遠股市我們用 0.15% 來交易

對於上漲波動股市我們用 1.5% 來交易

均值回歸策略

Mean Reversion Startegy

1.在波動市場中保持穩定

均值回歸策略

Mean Reversion Startegy

1.在波動市場中保持穩定

2.實際運用

import matplotlib.pyplot as plt

for _ in range(1, days):
    change = random.uniform(-2, 2) 
    new_price = prices[-1] * (1 + change / 100)
    prices.append(new_price)

for i in range(1, days):
    today = prices[i]
    yesterday = prices[i-1]
    change_pct = (today - yesterday) / yesterday * 100
    #if ahhhhhhhhh find reset point
    if change_pct < -1.5 and cash >= today:
        shares += 1
        cash -= today
        history.append(f"Day {i}: Bought at {today:.2f}")

    elif change_pct > 1.5 and shares > 0:
        shares -= 1
        cash += today
        history.append(f"Day {i}: Sold at {today:.2f}")

portfolio_value = cash + shares * prices[-1]
#剩餘的本金加股票的價值

import matplotlib.pyplot as plt

問題

import yfinance as yf
import matplotlib.pyplot as plt

TICKER     = 'AAPL'
PERIOD     = '1mo'
INTERVAL   = '30m'
THRESHOLD  = 0.0015 # 0.15%
INITIAL_CAPITAL = 10000.0

data = yf.download(TICKER, period=PERIOD, interval=INTERVAL)
prices = data['Close'].values
dates  = data.index

position = True
buy_price = float(prices[0])
sell_price = None
capital = 0.0
quantity = INITIAL_CAPITAL / buy_price
buy_signals = [dates[0]]
sell_signals = []

for i in range(1, len(prices)):
    p = float(prices[i])
    current_date = dates[i]
    #check the reset point if avilable ahhhh no
    if position:
        if p >= buy_price * (1 + THRESHOLD):
            sell_price = p
            capital = quantity * sell_price
            quantity = 0.0
            position = False
            sell_signals.append(current_date)
            print(f"SELL at ${p:.2f} on {current_date}")
    else:
        if p <= sell_price * (1 - THRESHOLD):
            buy_price = p
            quantity = capital / buy_price
            capital = 0.0
            position = True
            buy_signals.append(current_date)
            print(f"BUY  at ${p:.2f} on {current_date}")

final_value = capital + quantity * float(prices[-1])

plt.figure(figsize=(14,6))
plt.plot(dates, prices, label=f'{TICKER} Close', color='blue')
plt.plot(buy_signals,  data['Close'].loc[buy_signals],  '^', markersize=10, color='green', label='Buy')
plt.plot(sell_signals, data['Close'].loc[sell_signals], 'v', markersize=10, color='red',   label='Sell')
plt.title(f'{TICKER} Price with 0.15% Reversion Strategy (1m)\nFinal Portfolio Value: ${final_value:,.2f}')
plt.xlabel('Date')
plt.ylabel('Price (USD)')
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.show()

print(f"\nFinal Portfolio Value: ${final_value:,.2f}")
print("class dismissed!!!")

import yfinance as yf
import matplotlib.pyplot as plt

TICKER     = 'AAPL'
PERIOD     = '1mo'
INTERVAL   = '30m'
THRESHOLD  = 0.0015 # 0.15%
INITIAL_CAPITAL = 10000.0

data = yf.download(TICKER, period=PERIOD, interval=INTERVAL)
prices = data['Close'].values
dates  = data.index

position = True
buy_price = float(prices[0])
sell_price = None
capital = 0.0
quantity = INITIAL_CAPITAL / buy_price
buy_signals = [dates[0]]
sell_signals = []

for i in range(1, len(prices)):
    p = float(prices[i])
    current_date = dates[i]
    #check the reset point if avilable ahhhh no
    if position:
        if p >= buy_price * (1 + THRESHOLD):
            sell_price = p
            capital = quantity * sell_price
            quantity = 0.0
            position = False
            sell_signals.append(current_date)
            print(f"SELL at ${p:.2f} on {current_date}")
    else:
        if p <= sell_price * (1 - THRESHOLD):
            buy_price = p
            quantity = capital / buy_price
            capital = 0.0
            position = True
            buy_signals.append(current_date)
            print(f"BUY  at ${p:.2f} on {current_date}")

final_value = capital + quantity * float(prices[-1])

plt.figure(figsize=(14,6))
plt.plot(dates, prices, label=f'{TICKER} Close', color='blue')
plt.plot(buy_signals,  data['Close'].loc[buy_signals],  '^', markersize=10, color='green', label='Buy')
plt.plot(sell_signals, data['Close'].loc[sell_signals], 'v', markersize=10, color='red',   label='Sell')
plt.title(f'{TICKER} Price with 0.15% Reversion Strategy (1m)\nFinal Portfolio Value: ${final_value:,.2f}')
plt.xlabel('Date')
plt.ylabel('Price (USD)')
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.show()

print(f"\nFinal Portfolio Value: ${final_value:,.2f}")
print("class dismissed!!!")

pip install yfinance

plt.plot
(buy_signals,  data['Close'].loc[buy_signals],  '^', 
 markersize=10, color='green', label='Buy')
plt.plot
(sell_signals, data['Close'].loc[sell_signals], 'v', 
 markersize=10, color='red',   label='Sell')

plt.plot
(buy_signals,  data['Close'].loc[buy_signals],  '^', 
 markersize=10, color='green', label='Buy')
plt.plot
(sell_signals, data['Close'].loc[sell_signals], 'v', 
 markersize=10, color='red',   label='Sell')

plt.plot
(buy_signals,  data['Close'].loc[buy_signals],  '^', 
 markersize=10, color='green', label='Buy')
plt.plot
(sell_signals, data['Close'].loc[sell_signals], 'v', 
 markersize=10, color='red',   label='Sell')

RESET POINT

本金分配

RESET POINT

~~本金分配~~ -> random 每筆投資

RAND_T

import random
import matplotlib.pyplot as plt

days = 100
initial_price = 100
prices = [initial_price]

for _ in range(1, days):
    change = random.uniform(-2, 2) 
    new_price = prices[-1] * (1 + change / 100)
    prices.append(new_price)

cash = 1000
shares = 0
history = []

for i in range(1, days):
    today = prices[i]
    yesterday = prices[i-1]
    change_pct = (today - yesterday) / yesterday * 100
    #if ahhhhhhhhh find reset point
    if change_pct < -1.5 and cash >= today:
        shares += 1
        cash -= today
        history.append(f"Day {i}: Bought at {today:.2f}")

    elif change_pct > 1.5 and shares > 0:
        shares -= 1
        cash += today
        history.append(f"Day {i}: Sold at {today:.2f}")

portfolio_value = cash + shares * prices[-1]
print("\n".join(history))
print(f"\nFinal Portfolio Value: ${portfolio_value:.2f}")

plt.plot(prices, label="Stock Price")
plt.title(portfolio_value)# i need title

plt.xlabel("Day")
plt.ylabel("Price ($)")
plt.grid(True)
plt.legend()
plt.show()

APPL_1mo (0.15%)

import yfinance as yf
import matplotlib.pyplot as plt

TICKER     = 'AAPL'
PERIOD     = '1mo'
INTERVAL   = '30m'
THRESHOLD  = 0.0015 # 0.15%
INITIAL_CAPITAL = 10000.0

data = yf.download(TICKER, period=PERIOD, interval=INTERVAL)
prices = data['Close'].values
dates  = data.index

position = True
buy_price = float(prices[0])
sell_price = None
capital = 0.0
quantity = INITIAL_CAPITAL / buy_price
buy_signals = [dates[0]]
sell_signals = []

for i in range(1, len(prices)):
    p = float(prices[i])
    current_date = dates[i]
    #check the reset point if avilable ahhhh no
    if position:
        if p >= buy_price * (1 + THRESHOLD):
            sell_price = p
            capital = quantity * sell_price
            quantity = 0.0
            position = False
            sell_signals.append(current_date)
            print(f"SELL at ${p:.2f} on {current_date}")
    else:
        if p <= sell_price * (1 - THRESHOLD):
            buy_price = p
            quantity = capital / buy_price
            capital = 0.0
            position = True
            buy_signals.append(current_date)
            print(f"BUY  at ${p:.2f} on {current_date}")

final_value = capital + quantity * float(prices[-1])

plt.figure(figsize=(14,6))
plt.plot(dates, prices, label=f'{TICKER} Close', color='blue')
plt.plot(buy_signals,  data['Close'].loc[buy_signals],  '^', markersize=10, color='green', label='Buy')
plt.plot(sell_signals, data['Close'].loc[sell_signals], 'v', markersize=10, color='red',   label='Sell')
plt.title(f'{TICKER} Price with 0.15% Reversion Strategy (1m)\nFinal Portfolio Value: ${final_value:,.2f}')
plt.xlabel('Date')
plt.ylabel('Price (USD)')
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.show()

print(f"\nFinal Portfolio Value: ${final_value:,.2f}")
print("class dismissed!!!")

APPL_4/8 (1.5%)

import yfinance as yf
import matplotlib.pyplot as plt

TICKER     = 'AAPL'
PERIOD     = '1mo'  
INTERVAL   = '30m'
THRESHOLD  = 0.015 # 1.5% (adjustable)
INITIAL_CAPITAL = 10000.0
START_DATE = '2025-04-08' 

data = yf.download(TICKER, start=START_DATE, period=PERIOD, interval=INTERVAL)

data = data[data.index.hour >= 19]

prices = data['Close'].values
dates  = data.index

position = True
buy_price = float(prices[0])
sell_price = None
capital = 0.0
quantity = INITIAL_CAPITAL / buy_price
buy_signals = [dates[0]]
sell_signals = []

for i in range(1, len(prices)):
    p = float(prices[i])
    current_date = dates[i]
    # Check the reset point if available(no
    if position:
        if p >= buy_price * (1 + THRESHOLD):
            sell_price = p
            capital = quantity * sell_price
            quantity = 0.0
            position = False
            sell_signals.append(current_date)
            print(f"SELL at ${p:.2f} on {current_date}")
    else:
        if p <= sell_price * (1 - THRESHOLD):
            buy_price = p
            quantity = capital / buy_price
            capital = 0.0
            position = True
            buy_signals.append(current_date)
            print(f"BUY  at ${p:.2f} on {current_date}")

final_value = capital + quantity * float(prices[-1])

plt.figure(figsize=(14, 6))
plt.plot(dates, prices, label=f'{TICKER} Close', color='blue')
plt.plot(buy_signals, data['Close'].loc[buy_signals], '^', markersize=10, color='green', label='Buy')
plt.plot(sell_signals, data['Close'].loc[sell_signals], 'v', markersize=10, color='red', label='Sell')
plt.title(f'{TICKER} Price with 1.5% Reversion Strategy (0408-19:00)\nFinal Portfolio Value: ${final_value:,.2f}')
plt.xlabel('Date')
plt.ylabel('Price (USD)')
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.show()

print(f"\nFinal Portfolio Value: ${final_value:,.2f}")
print("class dismissed!!!")