Kalpi

What is Kalpi?

Kalpi is a rule-based investing platform that helps you build stock portfolios, backtest them, and then invest using predefined rules rather than discretionary choices. Its core purpose is to turn portfolio decisions into data-driven strategies you can test and repeat.

Rather than relying on emotions during the decision process, Kalpi focuses on creating custom stock baskets from strategy rules and using backtesting to evaluate those rules before using them in a live portfolio context.

Key Features

• Rule-based portfolio construction: Create custom stock baskets using explicit rules, making the selection logic clear and repeatable.
• Portfolio backtesting: Test rule-based portfolios against historical data to understand how the strategy might have performed before committing capital.
• Strategy-first workflow: Organize investing around a strategy that can be updated and re-evaluated, rather than a one-off set of picks.
• Emotion-reduction through predefined rules: Use the same rule set to guide portfolio decisions, aiming to minimize discretionary changes.

How to Use Kalpi

1. Define your portfolio rules: Specify the criteria or logic for how you want stocks selected.
2. Build a basket from those rules: Use Kalpi to assemble the portfolio based on your strategy inputs.
3. Backtest the portfolio: Run a backtest to evaluate how your rule set performed historically.
4. Use the strategy going forward: Once the rules are set, use the portfolio approach as your investing plan.

Use Cases

• Testing a new stock-selection rule: Build a basket using a specific rule, backtest it, and iterate on the rules if the results don’t match your expectations.
• Maintaining consistency in portfolio decisions: Use the same rule set over time to reduce the impact of day-to-day emotional decisions.
• Creating custom portfolios for different goals: Set up distinct rule-based baskets (for example, different selection criteria) and evaluate each through backtesting.
• Comparing strategy variations: Modify one part of the rule logic, backtest the updated portfolio, and compare outcomes across variations.

FAQ

Is Kalpi only for backtesting, or can it be used to invest?

Kalpi is presented as a platform to both build and backtest stock portfolios, and to invest using the resulting rule-based approach.

What does “rule-based investing” mean in Kalpi?

In Kalpi’s context, it refers to defining portfolio construction logic as rules that determine which stocks are included, rather than making purely discretionary picks.

Do I need to know how to code to use Kalpi?

The provided information does not specify whether coding is required. If you need a particular requirement, check Kalpi’s documentation or onboarding details on the site.

What kind of output should I expect from backtesting?

Backtesting is used to evaluate how your rule-based portfolio might have performed historically. The exact metrics or format are not detailed in the provided content.

Alternatives

• Spreadsheet-based rule systems: If you prefer manual control, you can encode selection rules in spreadsheets and use separate backtesting workflows; the tradeoff is more manual setup and less integrated portfolio tooling.
• Dedicated backtesting platforms: Some tools focus primarily on strategy backtesting; they may require additional work to translate results into an investing workflow.
• Portfolio management tools with scripted strategies: Instead of a rule-based investing workflow focused on strategy creation and testing, these tools may emphasize portfolio tracking and rebalancing, with strategy automation handled differently.
• Quant-style research environments: General research environments can be used to implement and test strategies, but may be less tailored to building and investing in stock baskets from rule inputs.