Define trade signals using TS models:
➡️ Mean reversion strategies - Time series model identifies when asset is oversold → Buy in
➡️ Momentum strategies - forecast assets price if it performs well → Buy in

Common time series models:
➡️ ARIMA model - explain the connection between a time series, its lagged values, and error for non-seasonal trends
➡️ GARCH model - model the variance or volatility of a time series
➡️ Exponential smoothing model - model using recent data for forecasts

7️⃣Paper trade - Test live using paper account
8️⃣Deploy & monitor - Start with small very capital, monitor performance

4️⃣ Evaluate model - Evaluate different TS models (🧵🪡) on unseen data
5️⃣ Generate signals - Generate forecasts and define trade signals (🧵🪡)
6️⃣ Backtest - Simulate trade with historical data

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If you find the way out, turn them into code and live it, you can still make a fortune using $1,000 in a long run. Remember compound returns is your friend!

If don’t have a systematic way to bet the market, more capital is the best way to ruin your wealth

The truth is - allocating more capital for your trading doesn’t necessary mean you will earn more money

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I tried to backtest this pattern: short the stock once this pattern detected. The truth is, it is a 43% win rate strategy, and it is a losing money strategy in long run.

✅ Listen to nobody
✅ Learn Python and backtest yourself
✅ Build a systematic way to validate anything