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

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

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!!!")

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