# Decompose fund performance attribution. AI Agent Connect

> Accelerator Performance Attribution helps you break down how a fund's returns are generated. This MCP calculates core attribution metrics like Alpha, Selection, and Coaching effects. You can determine if a fund's success comes from simply picking winners or from actively coaching them. It also pulls historical benchmark data for accurate comparisons, making it essential for serious fund analysis.

## Overview
- **Category:** finance
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_9BENOeRex09IbkhdimMO01QOkkhKOIWb7jz51oYw/ai-agent-connect
- **Tags:** performance, attribution, alpha, fund-analysis, venture-capital

## Description

Understanding why a fund performs well is complex. It's not enough to know the total return; you need to know the source. This MCP provides the analytical tools to attribute venture capital fund performance to specific accelerator drivers. You can calculate Alpha, Selection, and Coaching effects, giving you a clear picture of the fund's true impact. Need context? You can pull historical sector and vintage benchmarks to normalize your findings. This lets you move past simple return percentages and get to the root cause of success, whether it's superior deal flow, strong operational support, or just market timing.

## Tools

### calculate_selection_vs_coaching
Isolates whether the fund's success is due to "picking winners" (Selection) or "making winners" (Coaching)

### get_sector_vintage_benchmark
Retrieves the baseline performance for a specific sector and year

### analyze_performance_drivers
Calculates core attribution metrics (Alpha, Selection, and Coaching) to determine the accelerator's total impact

## Prompt Examples

**Prompt:** 
```
Calculate the performance drivers for a fund with 25% returns, 40% accelerator deal flow, 15% support value, 10% non-accelerator return in the SaaS sector for 2022.
```

**Response:** 
```
The total Alpha from the accelerator is 15%, with a Selection Effect of 6% and a Coaching Effect of 9%.
```

**Prompt:** 
```
Is the fund's success driven more by picking winners or making winners if selection alpha is 5% and coaching alpha is 10%?
```

**Response:** 
```
The success is driven 33.3% by selection and 66.7% by coaching, with a selection-to-coaching ratio of 0.5.
```

**Prompt:** 
```
What was the benchmark return for the Fintech sector in 2021?
```

**Response:** 
```
The benchmark return for the Fintech sector in 2021 was 12.5%.
```

## Capabilities

### Calculate Alpha effects
The AI uses this MCP to determine the overall performance impact of the accelerator.

### Compare selection vs. coaching
It calculates the ratio to see if the fund succeeded by picking winners or making them.

### Get historical benchmarks
The AI retrieves baseline performance data for any specific sector and year.

## Use Cases

### Reviewing a Fund's Track Record
You can run an analysis to see if the fund's returns were driven by the quality of deals picked or the support provided.

### Benchmarking a Sector
Need to know how a specific sector performed in 2021? Use the MCP to retrieve the exact historical benchmark return.

### Comparing Investment Strategies
Run attribution on two different funds to see which strategy—picking winners or coaching winners—yielded better results.

### Due Diligence
Use the MCP during due diligence to validate a fund's claims of success by calculating its true Alpha.

## Benefits

- It separates raw returns into Alpha, Selection, and Coaching effects, giving you a precise measure of impact.
- You determine if a fund's success relies on picking winners or actively developing them.
- The MCP pulls historical benchmarks, allowing you to compare current performance against established sector averages.

## How It Works

Connect your preferred AI client to the Vinkius catalog. You simply prompt your agent with the fund's performance data and the sector details. The MCP then runs the necessary calculations and returns the full attribution report.

1. Connect your AI client to the Vinkius catalog and select this MCP.
2. Provide the fund's performance metrics and the target sector/year in your prompt.
3. The MCP executes the necessary tools, like analyze_performance_drivers.
4. Your agent receives the full breakdown, showing Alpha, Selection, and Coaching effects.

## Frequently Asked Questions

**What is Alpha in this context?**
Alpha is a core attribution metric that measures the total impact of the accelerator on the fund's performance. It helps you understand the overall boost the program provided.

**Does this MCP tell me if the fund is good?**
It doesn't give a simple yes or no. It gives you the data to decide. You can determine if the success is due to picking winners or making winners, which is a much deeper insight.

**Can I compare different sectors?**
Yes. You can use the MCP to retrieve the baseline performance for a specific sector and year, allowing you to normalize and compare different industries accurately.

**What kind of data do I need to provide?**
You need to provide the fund's performance metrics, including deal flow, support value, and non-accelerator returns, along with the sector and year for analysis.

**Is this MCP only for venture capital?**
While it focuses on VC attribution, the core metrics—Alpha, Selection, and Coaching—are general financial tools for decomposing investment returns.