The AI Oracle Speaks (and We Raise a Skeptical Eyebrow)

So, the digital muse has deigned to bestow upon us a curated list of trading strategies. One can almost hear the synthesized trumpets heralding this wisdom from the silicon heavens. Five distinct approaches, each presented with the crisp, almost unsettling, clarity of a freshly printed user manual. One might be tempted to leap directly into coding these algorithmic panaceas. One might.

Let's dissect this digital offering with the requisite dose of skepticism, shall we?

1. Day Trading: The RSI and MACD Tango. Ah, the classics. Buy low (according to one lagging indicator), sell high (according to another). Throw in a moving average for good measure – because why not? The exit rule helpfully suggests selling when the buying signal reverses. Profound. And a 2% stop-loss? Boldly limiting the potential for minor fluctuations to… well, stop you out.

2. Swing Trading: Embracing the Bouncing Bands and Magic Numbers. Bollinger Bands, those ever-so-predictive envelopes of volatility. Buy at the bottom, naturally, just as it reverses (because catching the exact bottom is a well-known novice trick that works consistently). Exit at a Fibonacci level – because markets respect arbitrary mathematical sequences, apparently. And a trailing stop-loss? A commendable feature, assuming the market politely trends in your favor without those pesky retracements.

3. Scalping: The High-Frequency Hustle with VWAP and Stochastic. Trading around the Volume Weighted Average Price with the Stochastic Oscillator as your momentum whisperer. Buy on bullish momentum above VWAP, sell when it’s… overbought. Groundbreaking. Tight stop-losses and high-frequency trades – a recipe for excitement, if not necessarily consistent profitability, especially when factoring in those oh-so-negligible transaction costs.

4. Breakout Trading: Riding the Explosive Volume (or Lack Thereof). Buy when price leaps valiantly above resistance on surging volume (assuming that surge is genuine and not a fleeting anomaly). Sell when the momentum wanes or it dips below the newfound support (which, incidentally, might be as ephemeral as the initial breakout). A stop-loss just below the breakout level – strategically placed for maximum pain on a false break.

5. Arbitrage Trading: The Holy Grail of Risk-Free Profit (Narrative Alert: Sarcasm Imminent). Buy on one exchange, sell on another due to price discrepancies. Sounds delightfully simple. The risk management caveat about transaction fees and withdrawal delays is almost endearing in its understatement. One might also consider the milliseconds that high-frequency behemoths have a distinct advantage in exploiting such fleeting opportunities.

So, here we have it. A starter pack of algorithmic aspirations, courtesy of the digital assistant. It provides a direction, a set of keywords to begin the coding journey. And that, perhaps, is its primary utility. We shall, of course, subject these suggested strategies to the rigorous scrutiny of the "Algorithmic Autopsy." We will translate these seemingly straightforward rules into the unforgiving logic of code and then confront them with the cold, hard data of historical markets.

Consider this the initial reconnaissance. The real work – the coding, the backtesting, the inevitable disillusionment, and hopefully, some genuine learning – is yet to come. Stay tuned as we take these theoretical blueprints and see if they hold up under the harsh realities of algorithmic trading.