Automated Stock Portfolio Week 8: Losses, Lessons, and New Strategies

What happens when an automated options portfolio prints losses for eight straight weeks live: do you quit, or do you stay loyal to the plan? The eighth weekly session of the Option Alpha team revolves around exactly that question, with September closing in the red and hopes shifting to October. In the session recording on youtube.com the speakers openly share both the results and the updates published that same morning.

The OA Portfolio is an automated stock portfolio that executes defined strategies without human hands; the team deliberately kept position size at 1x during the first weeks to observe the system. At viewers request, a new live tracking screen now shows every open position in real time. How bot-based automatic trading is set up is explained in plain language on the bot introduction page on optionalpha.com, and that structure forms the backbone of the portfolio.

The weekly results table mirrors the whole of September; the portfolio is broadly underwater and trading inside a drawdown. The speakers show the table without hiding anything, counting strategy by strategy what lost and how much. That transparency looks like a deliberate choice to defend automated investing discipline, because even with ugly numbers the system visibly obeyed its rules.

Gold trades lead the losses; one position held for about twenty-two days closes with an eleven-hundred-dollar loss. A single-day trade adds an eight-hundred-fifty-dollar loss and weighs the weekly balance further down. This losing streak in gold stands out as the weakest link of the portfolio.

Trades That Softened the Losses

The savior of the day is a long-waited long put on the S&P, whose thirteen-hundred-dollar gain softens the weekly bill. Another remarkable trade comes from the gamma-adjusting strategy built as an iron butterfly ; the position between 7700 and 7670 closes in the morning with a one-hundred-ninety-dollar profit while sitting in maximum-loss territory. The index cratering right after the exit shows how timely that early close was.

The picture darkens again that same afternoon; a gold position that looked like a winner in the morning reverses direction and dives into the close, ending at maximum loss. Another gamma-adjusted trade closes with a five-hundred-thirty-dollar loss. Fortunately the sandwich strategy saves the day with a sixteen-hundred-dollar gain and goes down as the brightest trade of the week.

In the morning adjustments, the most consistent recent trade, the 145 PM sandwich, is scaled up five times; the position carrying about sixteen hundred dollars of credit against nine hundred dollars of risk closes at full profit. The rarely trading flatfly strategy gets its risk lifted from five hundred to six hundred dollars as well. The team openly defends the logic of scaling winners and pruning losers.

The headline lesson of the week is that nobody touched a position by hand throughout September; the speakers admit they used to cut losers too early far too often. A promise made in front of the community keeps the hands-off discipline intact. Trusting past results and staying loyal to the plan becomes the philosophical backbone of this portfolio experiment.

Power Portfolio and the New Breakout Strategy

The morning releases center on the Power Portfolio, aiming to combine different symbols, strategies, and expirations into one long-term plan. The goal is to lower volatility, raise profit potential, and reduce dependence on any single strategy. The background of this multi-leg vision is told at length in the August feature roundup on optionalpha.com, which hints at where the portfolio is heading.

The newly added opening range breakout strategy is designed to work alongside the afternoon paycheck strategy; it shows two trades in backtesting but only one fills live. The gap is explained by the GEX filter , which blocks the trade whenever buying-side gamma stacks up one hundred percent across every strike. The logic of catching the first momentum burst after the stock market open is illustrated with examples in the opening range guide on optionalpha.com, giving a reason behind the strategy choice.

To prevent collisions, Wednesdays and Thursdays are removed from the list, so the zero-day put strategy and the new breakout strategy cannot cancel each other out. Since one winning while the other loses would raise internal portfolio swings, the simplification reads as sensible. The team stresses that dropping days looks small yet moves the bottom line meaningfully.

The most striking novelty of the day is the strategy optimizer; a strategy first runs with no filters to produce a huge dataset, and then the automatic analysis scans entry ranges, indicators, moving averages, and reward-risk bands one by one. The screen showing day by day and threshold by threshold what worked best turns trial and error into a system. How a backtesting setup over three years of one-minute data is built is summarized in the backtester introduction on optionalpha.com, revealing where the data richness comes from.

Screening Results and Bot Novelties

An already optimized strategy serves as the example; starting from thirty-one thousand in returns against a nineteen-hundred drawdown, simply removing Thursdays lifts the return-to-drawdown figure from sixteen hundred to eighteen hundred. Win rates between ninety-five and one hundred percent show how selective the strategy becomes. The speaker concedes he would never have thought of that filter himself, crediting the automatic analysis.

Two practical novelties arrive on the bot side as well; loops cycling through symbols gain a branching decision keyed to a specific symbol such as SPX. A new risk filter also skips any trade when a major event could strike during the life of the position. Both touches bring the rigid rules of automation a little closer to market reality.

Small gaps between backtests and the live bot get their turn on the table; a trade the test takes can be missed by the bot because gamma data shifts within split seconds, and that is treated as normal. The single-trade difference seen in the afternoon paycheck strategy is explained exactly this way. The team presents the new breakout strategy, which mirrors bot behavior one to one, as the fix for that problem.

Questions, Research Context, and the October Plan

The Q and A segment debates the warning flag on the Gold Rush 2X strategy and a tiny sample of only forty-one trades, stressing how dangerous it is to generalize from few fills. Power seven templates are noted as updated while the paycheck side gets no update. Community questions stand out as the most productive part, raising the transparency of the live experiment.

Setting what the session teaches next to independent research completes the picture; the rules of the zero-day put credit spread showing promising results over the last two years are demonstrated with historical tests in the strategy review on alphacrunching.com, confirming the zero-day preference of the portfolio. Running opening range breakouts profitably with credit spreads is proven with concrete coded examples in the research piece on quantish.io, supporting the breakout pick. The math of market-maker delta hedging and gamma adjustment is explained step by step in the gamma guide on tradealgo.com, clarifying the theory behind the butterfly trades. How dealer gamma positioning shapes intraday support and resistance is laid out with its formula in the GEX definition on flashalpha.com, making the logic of the filter understandable.

Heading into October the plan sharpens; scaled-up winning strategies, the added breakout strategy, and rules sieved through the smart screen make the portfolio more selective. The speakers repeat their belief that past results will reassert themselves and renew the pledge to stay hands-off. The coming weeks will show whether these updates can close out the drawdown.