> ## Documentation Index
> Fetch the complete documentation index at: https://docs.itoflow.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Decide whether a name improves a book

> Ask Itoflow which of several stocks would do more for a portfolio. The research agent weighs each name's fundamentals beside its effect on the book's return, volatility, drawdown and Sharpe ratio, tested on a holdout period, and names the trade-offs.

A stock can look good alone and do little for your book. Ask Itoflow to weigh each candidate's fundamentals beside what it does to the whole portfolio, in one request.

**What you'll get:** a side-by-side of the candidates on growth, margins, valuation and quality, their effect on the book's risk and return, and the trade-offs between them.

## Try it

> [tab] Ask your AI assistant
>
> With [Itoflow connected to your assistant](https://docs.itoflow.ai/mcp/install.md), paste this into your assistant:
>
> ```text theme={null}
> Use Itoflow to decide which of GOOGL.US and AAPL.US would do more for a book
> that is 70% SPY.US, if added as a 30% sleeve. Compare the two companies on
> growth, margins, valuation and quality. Then measure what each does to the
> book: return, volatility, worst drawdown, Sharpe ratio and correlation with
> the S&P 500, using a shrinkage covariance and a holdout period. Name the
> trade-offs rather than only a winner. Wait for the research to finish, then
> summarize it.
> ```
>
> > [card] [Open in Claude](https://claude.ai/new?q=Use%20the%20Itoflow%20plugin%20\(https%3A%2F%2Fgithub.com%2Fitoflow%2Fskills\)%20for%20this.%20If%20it%20isn't%20installed%20yet%2C%20first%20tell%20me%20how%20to%20install%20it%20and%20sign%20in%20to%20Itoflow%2C%20and%20wait%20until%20I%20confirm.%20Then%3A%0A%0AUse%20Itoflow%20to%20decide%20which%20of%20GOOGL.US%20and%20AAPL.US%20would%20do%20more%20for%20a%20book%20that%20is%2070%25%20SPY.US%2C%20if%20added%20as%20a%2030%25%20sleeve.%20Compare%20the%20two%20companies%20on%20growth%2C%20margins%2C%20valuation%20and%20quality.%20Then%20measure%20what%20each%20does%20to%20the%20book%3A%20return%2C%20volatility%2C%20worst%20drawdown%2C%20Sharpe%20ratio%20and%20correlation%20with%20the%20S%26P%20500%2C%20using%20a%20shrinkage%20covariance%20and%20a%20holdout%20period.%20Name%20the%20trade-offs%20rather%20than%20only%20a%20winner.%20Wait%20for%20the%20research%20to%20finish%2C%20then%20summarize%20it.)
> >
> > Start this in Claude with the Itoflow plugin.
>
> > [card] [Open in ChatGPT](https://chatgpt.com/?q=Use%20the%20Itoflow%20plugin%20\(https%3A%2F%2Fgithub.com%2Fitoflow%2Fskills\)%20for%20this.%20If%20it%20isn't%20installed%20yet%2C%20first%20tell%20me%20how%20to%20install%20it%20and%20sign%20in%20to%20Itoflow%2C%20and%20wait%20until%20I%20confirm.%20Then%3A%0A%0AUse%20Itoflow%20to%20decide%20which%20of%20GOOGL.US%20and%20AAPL.US%20would%20do%20more%20for%20a%20book%20that%20is%2070%25%20SPY.US%2C%20if%20added%20as%20a%2030%25%20sleeve.%20Compare%20the%20two%20companies%20on%20growth%2C%20margins%2C%20valuation%20and%20quality.%20Then%20measure%20what%20each%20does%20to%20the%20book%3A%20return%2C%20volatility%2C%20worst%20drawdown%2C%20Sharpe%20ratio%20and%20correlation%20with%20the%20S%26P%20500%2C%20using%20a%20shrinkage%20covariance%20and%20a%20holdout%20period.%20Name%20the%20trade-offs%20rather%20than%20only%20a%20winner.%20Wait%20for%20the%20research%20to%20finish%2C%20then%20summarize%20it.)
> >
> > Start this in ChatGPT with the Itoflow plugin.
>
> Using another client? Copy the prompt with the button on the code block.
>
> To test against your own book, replace the 70% SPY.US core with the name of one of your saved portfolios.

> [tab] In the Itoflow app
>
> 1. Open [Chat](https://app.itoflow.ai/chat).
> 2. Name the candidates and the book: a saved portfolio, or a mix such as 70% SPY.
> 3. Ask for fundamentals and the effect on the book's risk and return, tested on a holdout period.

## What a result looks like

We ran the prompt above on October 28, 2026. The agent fitted the covariance on three years to October 2024 and held out the two years after. Over the holdout, the GOOGL sleeve raised the book's return by 17.8 points over SPY alone, and AAPL by 4.6. The AAPL book was less volatile and led in the second year. Neither sleeve lowered the book's volatility or worst drawdown against SPY alone. The answer said so, and called its pick of GOOGL a conditional preference, not a forecast.

An earlier run, published in [Combining fundamental quality with quantitative optimization: GOOGL vs AAPL](https://itoflow.ai/blog/googl-wins-aapl-loses-integrated-analysis) on July 9, 2026, ran a similar request with a 30% sleeve on a 70% S\&P 500 core. The S\&P 500 alone had a Sharpe ratio of 1.40. With a GOOGL sleeve it rose to 2.54, and with AAPL to 1.92. GOOGL also led on valuation (27.6 times earnings against 35.6) and margins (37.9% against 27.2%).

The answer named the trade-off too: the AAPL book had the shallower worst drawdown, 9.1% against 12.4%. The post covers two candidates over a few years of daily data, with an index standing in for real holdings. It is not a stock call.

## How it's checked

* **The figures come from code.** The agent writes the code that measures each book, and the system checks that each number in the answer matches what the code produced. See [the research contract](https://docs.itoflow.ai/platform/agent-harness.md#the-research-contract).
* **A holdout period.** The comparison is tested on data the choice didn't use.
* **A second agent reviews it.** The [independent reviewer](https://docs.itoflow.ai/platform/agent-harness.md#independent-review) reads the files, not a summary.

## Limits

* The answer rests on past data and one covariance estimate. It is research, not investment advice.
* Fundamentals come from filings, counted from the day the regulator accepted them.

## Next steps

* [Measure a book's factor risk](https://docs.itoflow.ai/use-cases/measure-factor-risk.md) to see which factors a new name adds.
* [Quant engine and risk model](https://docs.itoflow.ai/platform/quant-engine.md): the portfolio construction methods behind the answer.


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