Position Sizing Before Everything

def fixed_fractional_size(account, risk_pct, entry, stop):
    """
    account  : total portfolio value in ₹
    risk_pct : e.g., 0.01 for 1%
    entry    : entry price per share
    stop     : stop-loss price per share
    """
    max_loss   = account * risk_pct
    risk_per_share = abs(entry - stop)
    
    if risk_per_share == 0:
        raise ValueError("Entry and stop cannot be the same")
    
    shares     = int(max_loss / risk_per_share)
    pos_value  = shares * entry
    pct_capital = (pos_value / account) * 100
    
    return {
        'shares':      shares,
        'pos_value':   pos_value,
        'pct_capital': round(pct_capital, 1),
        'max_loss':    shares * risk_per_share,
    }

import numpy as np
import pandas as pd

def vol_target_size(portfolio, annual_vol_target, returns_series, price):
    """
    portfolio         : total portfolio value in ₹
    annual_vol_target : e.g., 0.15 for 15%
    returns_series    : pd.Series of daily % returns (last 20 days)
    price             : current stock price
    """
    daily_vol_target = annual_vol_target / np.sqrt(252)
    
    # Rolling 20-day realised vol
    sigma = returns_series.tail(20).std()
    
    if sigma == 0:
        return 0
    
    position_value = portfolio * (daily_vol_target / sigma)
    shares = int(position_value / price)
    
    return {
        'shares':         shares,
        'position_value': shares * price,
        'stock_daily_vol': f"{sigma*100:.2f}%",
        'pct_capital':    round((shares * price / portfolio) * 100, 1),
    }

def kelly_fraction(win_rate, reward_risk_ratio, fraction=0.5):
    """
    win_rate          : e.g., 0.55 for 55%
    reward_risk_ratio : e.g., 1.5 means risk 1 to make 1.5
    fraction          : 0.5 = half Kelly (recommended)
    """
    p = win_rate
    q = 1 - p
    b = reward_risk_ratio
    
    full_kelly = (p * b - q) / b
    
    if full_kelly <= 0:
        return {
            'full_kelly': full_kelly,
            'use_fraction': 0,
            'note': "Negative Kelly — no edge, do not trade this setup"
        }
    
    adjusted = full_kelly * fraction
    
    return {
        'full_kelly':      round(full_kelly * 100, 1),  # %
        'half_kelly':      round(adjusted * 100, 1),    # %
        'recommendation':  f"Risk {round(adjusted * 100, 1)}% per trade",
        'note': f"Full Kelly is {round(full_kelly*100,1)}% — use {int(fraction*100)}% of that"
    }