Stock Market Simulation? Pfft. This is MARKET CRASH SIMULATION! 🚨💥

Welcome to the Wildest Portfolio Ride of Your Life 🎢💥

Buckle up, because this rollercoaster was definitely designed by a caffeine-fueled dev with zero bug fixes and lots of chaos! Watch your portfolio dive faster than your morning coffee disappears and your code breaks after a midnight commit. Buy high, sell low? Nah, here we do buy panic, sell chaos — the market’s so buggy it’s basically a free fall simulator with random spikes and faceplants. 😎💸

I keep changing the price random change code but still:

The Code Saga: Take 4 🚀 (Or maybe the “Why is this still so wild?” edition)

DateTime now = DateTime.Now;

double timeFactor = 0.05 * Math.Sin(now.Second * Math.PI / 100);

int chance = rand.Next(100);
double percentChange = 0;

double baseDrift = 0.0005;

if (chance < 2)
    percentChange = 0.8 + rand.NextDouble() * 0.4;
else if (chance < 6)
    percentChange = 0.3 + rand.NextDouble() * 0.2;
else if (chance < 12)
    percentChange = -0.4 - rand.NextDouble() * 0.3;
else if (chance < 40)
    percentChange = -0.1 - rand.NextDouble() * 0.1;
else
    percentChange = (rand.NextDouble() - 0.5) * 0.02;

percentChange += baseDrift + timeFactor;

double price = lastPrice * (1 + percentChange);

if (price < 1)
    price = 1;

int index = chart1.Series["Series1"].Points.AddXY(now, price);

chart1.Series["Series1"].Points[index].Color = price >= lastPrice ? Color.Green : Color.Red;

lastPrice = price;

if (chart1.Series["Series1"].Points.Count > 30)
    chart1.Series["Series1"].Points.RemoveAt(0);

var area = chart1.ChartAreas["MainArea"];
area.AxisX.Minimum = chart1.Series["Series1"].Points[0].XValue;
area.AxisX.Maximum = chart1.Series["Series1"].Points[chart1.Series["Series1"].Points.Count - 1].XValue;

UpdateWorthLabel();
UpdateWalletLabel();

lbl_how_much_wortyh.Text = lastPrice.ToString("C2");

Result

The Comeback: Take 6 or 7 — Smoother Chaos Edition 🎯

DateTime now = DateTime.Now;

// Smoothed time factor using total seconds with sine for more continuous oscillation
double timeFactor = 0.03 * Math.Sin(now.TimeOfDay.TotalSeconds * Math.PI / 30);

// Volatility factor that slightly varies over time to simulate market mood changes
double volatility = 0.01 + 0.02 * Math.Sin(now.TimeOfDay.TotalMinutes);

// Base drift to simulate general market trend (can be positive or negative)
double baseDrift = 0.0003; 

// Random chance for bigger jumps or drops
int chance = rand.Next(100);
double percentChange = 0;

if (chance < 3) // rare big jump up
    percentChange = 0.6 + rand.NextDouble() * 0.5;
else if (chance < 8) // moderate jump up
    percentChange = 0.2 + rand.NextDouble() * 0.3;
else if (chance < 15) // moderate drop
    percentChange = -0.4 - rand.NextDouble() * 0.25;
else if (chance < 45) // small drop
    percentChange = -0.12 - rand.NextDouble() * 0.08;
else // usual minor fluctuation
    percentChange = (rand.NextDouble() - 0.5) * volatility;

// Combine all factors with base drift and time oscillation for smooth random walk
percentChange += baseDrift + timeFactor;

// Calculate new price and ensure it doesn’t fall below 1
double price = lastPrice * (1 + percentChange);
if (price < 1)
    price = 1;

// Add new price point to chart
int index = chart1.Series["Series1"].Points.AddXY(now, price);

// Color the point green if price increased or red if decreased
chart1.Series["Series1"].Points[index].Color = price >= lastPrice ? Color.Green : Color.Red;

// Update lastPrice for next iteration
lastPrice = price;

// Keep only last 30 points to keep chart neat
if (chart1.Series["Series1"].Points.Count > 30)
    chart1.Series["Series1"].Points.RemoveAt(0);

// Update X-axis range dynamically
var area = chart1.ChartAreas["MainArea"];
area.AxisX.Minimum = chart1.Series["Series1"].Points[0].XValue;
area.AxisX.Maximum = chart1.Series["Series1"].Points[chart1.Series["Series1"].Points.Count - 1].XValue;

// Update UI labels
UpdateWorthLabel();
UpdateWalletLabel();

lbl_how_much_wortyh.Text = lastPrice.ToString("C2");

Result

So... What’s Next? 🔮

Add news-driven volatility spikes: simulate “breaking news” that causes massive sudden jumps or drops.
Implement volume-based effects: bigger trades move the market more.
Try mean reversion: prices tend to bounce back to an average over time (for some sanity).
Add seasonality or periodic events — like earnings reports or holidays messing with the market mood.
And of course, more memes and chaos! Because if your portfolio isn't making you sweat, is it even real?