Slow Stochastic Oscillator
Smoothed version of the stochastic oscillator that reduces false signals and noise.
Export Optimization Code
Advanced Options & Examples
Optimization Output Example
Example output from running the optimization code above on a year of S&P data.
Period: 19
Model: SimpleMovingAverage
Oversold threshold: 50
Overbought threshold: 84
Best Slow Stochastic values: [29.04536316035683, 29.024778730753603, 27.712118166355456, ...]
Analysis
The optimized Slow Stochastic Oscillator parameters generate different trading signals compared to the default settings. A trading simulation was conducted to evaluate the effectiveness of both parameter sets. Both strategies started with an initial capital of $1000 and invested 20% of the remaining capital on each trade.
Long positions were opened when the Slow Stochastic fell below the oversold level and closed when it rose above the overbought level. Short positions were opened when the Slow Stochastic rose above the overbought level and closed when it fell below the oversold level.
The results are shown in the tables below. The optimized Slow Stochastic strategy yielded a loss of $26.23, with a $188.52 open position. While this performed better than the default Slow Stochastic strategy which resulted in a loss of $83.81 (with a $173.70 open position), both strategies struggled in this particular market condition.
Optimized Trading Simulation
- SideLONG
- Shares0.0334
- Entry$5872.16
- Value$188.52
Default Trading Simulation
- SideLONG
- Shares0.0308
- Entry$6025.99
- Value$173.70
Trading Simulation Code
For those who want to run their own simulation to compare results.
use centaur_technical_indicators::momentum_indicators::bulk::{slow_stochastic, stochastic_oscillator};
use centaur_technical_indicators::ConstantModelType;
fn simulate_trading(best_indicator: &[f64], best_period: usize, close: &[f64], best_oversold: usize, best_overbought: usize) {
// --- TRADING SIMULATION CODE ---
println!("
--- Trading Simulation ---");
let initial_capital = 1000.0;
let mut capital = initial_capital;
let investment_pct = 0.20;
struct Position {
entry_price: f64,
shares: f64,
}
let mut open_long: Option<Position> = None;
let mut open_short: Option<Position> = None;
// Print table header
println!("{:<5} | {:<19} | {:<10} | {:<10} | {:<12} | {:<15} | {:<10}",
"Day", "Event", "Stochastic", "Price", "Shares", "Capital", "P/L");
println!("{}", "-".repeat(95));
for i in 0..best_indicator.len() {
let price_index = i + best_period;
if price_index >= close.len() { break; }
let stoch_val = best_indicator[i];
let current_price = close[price_index];
let day = price_index;
// --- Handle Long Position ---
if let Some(long_pos) = open_long.take() {
if stoch_val > best_overbought as f64 {
let sale_value = long_pos.shares * current_price;
let profit = sale_value - (long_pos.shares * long_pos.entry_price);
capital += sale_value;
println!("{:<5} | {:<19} | {:<10.2} | ${:<9.2} | {:<12.4} | ${:<14.2} | ${:<9.2}",
day, "Sell (Close Long)", stoch_val, current_price, long_pos.shares, capital, profit);
} else {
open_long = Some(long_pos); // Put it back if not selling
}
} else if stoch_val < best_oversold as f64 && open_short.is_none() { // Don't buy if short is open
let investment = capital * investment_pct;
let shares_bought = investment / current_price;
open_long = Some(Position { entry_price: current_price, shares: shares_bought });
capital -= investment;
println!("{:<5} | {:<19} | {:<10.2} | ${:<9.2} | {:<12.4} | ${:<14.2} | {}",
day, "Buy (Open Long)", stoch_val, current_price, shares_bought, capital, "-");
}
// --- Handle Short Position ---
if let Some(short_pos) = open_short.take() {
if stoch_val < best_oversold as f64 {
let cost_to_cover = short_pos.shares * current_price;
let profit = (short_pos.shares * short_pos.entry_price) - cost_to_cover;
capital += profit; // Add profit to capital
println!("{:<5} | {:<19} | {:<10.2} | ${:<9.2} | {:<12.4} | ${:<14.2} | ${:<9.2}",
day, "Cover (Close Short)", stoch_val, current_price, short_pos.shares, capital, profit);
} else {
open_short = Some(short_pos); // Put it back if not covering
}
} else if stoch_val > best_overbought as f64 && open_long.is_none() { // Don't short if long is open
let short_value = capital * investment_pct;
let shares_shorted = short_value / current_price;
open_short = Some(Position { entry_price: current_price, shares: shares_shorted });
// Capital doesn't change when opening a short, it's held as collateral
println!("{:<5} | {:<19} | {:<10.2} | ${:<9.2} | {:<12.4} | ${:<14.2} | {}",
day, "Short (Open Short)", stoch_val, current_price, shares_shorted, capital, "-");
}
}
println!("
--- Final Results ---");
if let Some(pos) = open_long {
println!("Simulation ended with an OPEN LONG position:");
println!(" - Shares: {:.4}", pos.shares);
println!(" - Entry Price: ${:.2}", pos.entry_price);
let last_price = close.last().unwrap_or(&0.0);
let current_value = pos.shares * last_price;
capital += current_value;
println!(" - Position value at last price (${:.2}): ${:.2}", last_price, current_value);
}
if let Some(pos) = open_short {
println!("Simulation ended with an OPEN SHORT position:");
println!(" - Shares: {:.4}", pos.shares);
println!(" - Entry Price: ${:.2}", pos.entry_price);
let last_price = close.last().unwrap_or(&0.0);
let cost_to_cover = pos.shares * last_price;
let pnl = (pos.shares * pos.entry_price) - cost_to_cover;
capital += pnl;
println!(" - Unrealized P/L at last price (${:.2}): ${:.2}", last_price, pnl);
}
let final_pnl = capital - initial_capital;
println!("
Initial Capital: ${:.2}", initial_capital);
println!("Final Capital: ${:.2}", capital);
println!("Total P/L: ${:.2}", final_pnl);
}
fn main() {
// Fetch data and perform optimization as shown in the optimization code above
simulate_trading(&best_slow_stochastics, best_period, &close, best_oversold, best_overbought);
// Compare with default parameters
let default_stochastics = stochastic_oscillator(&close, 14);
let default_slow_stochastics = slow_stochastic(&default_stochastics, ConstantModelType::SimpleMovingAverage, 3);
simulate_trading(&default_slow_stochastics, 3, &close, 20, 80);
}