{ "docId": "019f6b8f-19e2-72df-8c4b-aa621c5e9c8a", "docSlug": "jarvis-followon-pro-rata", "documentTitle": "followon pro rata", "authorId": "followon-pro-rata", "authorName": null, "documentKindSlug": "deck", "documentKindLabel": "Deck", "sourceTypeSlug": "investor_relations", "sourceTypeLabel": "Investor relations", "presentationDate": null, "orientation": null, "aspectRatio": null, "pageNumber": 7, "pageCount": 10, "prevPage": 6, "nextPage": 8, "slideType": "other", "function": "analyze_data", "density": "overcrowded", "nDataPoints": 0, "notes": "The slide discusses simulation clusters (large, red circle, green circle) and the power law of early-stage investments.", "elementsJson": null, "metadataConfidence": 0.9, "imagePath": null, "slideHref": "/slides/019f6b8f-19e2-72df-8c4b-aa621c5e9c8a/7", "deckHref": "/decks/019f6b8f-19e2-72df-8c4b-aa621c5e9c8a", "deckJsonHref": "/decks/019f6b8f-19e2-72df-8c4b-aa621c5e9c8a.json", "deckAnchorHref": "/decks/019f6b8f-19e2-72df-8c4b-aa621c5e9c8a#slide-7", "components": [ { "bbox": { "h": 0.15, "w": 0.9, "x": 0.05, "y": 0.12 }, "kind": "paragraph", "text": "The large cluster at the lower left represents the typical performance of the two strategies; the points in that cluster come from the bulk of simulations that never consider an investment in the seed stage of AngelList's best-performing investment. Observe that in that cluster, Always has returns that have higher variance, while Never has more well-behaved performance. This is consistent with the power law of early-stage investment returns rewarding making more, putatively independent, investments.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "41aed98d-6535-440d-b1c0-6cc0f9f3b113", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.18, "w": 0.9, "x": 0.05, "y": 0.45 }, "kind": "paragraph", "text": "Finally, the smallest cluster, in the green circle, are those simulations where Always has typical performance but Never does well. These are the simulations where following on to a prior investment precludes Always from making the original investment into the best-performing company on the platform. This green circle is a graphical depiction of one of our key findings: that there exists an opportunity cost of doing follow-on investments. This is closely related to the power law of early-stage investment returns, which as a general rule suggests that having more winning early-stage investments is always better from the perspective of risk-adjusted returns.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "4cd3ebf3-03f6-4a57-a2a7-e113457d4098", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.15, "w": 0.9, "x": 0.05, "y": 0.28 }, "kind": "paragraph", "text": "The smaller cluster in the red circle at right are simulations where Never performs well but Always performs even better. This cluster is entirely due to Always putting additional capital into the Series A of the best-performing company on the AngelList platform, which company raised a convertible instrument that converted at a modest, roughly 10% return to a Series A before going on to a better than 100x unrealized return after its first priced equity round.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "81f3aade-4c49-4f4f-adbb-18ed7e540b8e", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.05, "w": 0.9, "x": 0.05, "y": 0.9 }, "kind": "paragraph", "text": "For investors who are not capital constrained and who plan to make a number of investments large enough that following on does not significantly affect the number of early stage investments they make, there are", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "982d8533-f1ac-44cd-bd06-bab4600a7978", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.05, "y": 0.65 }, "kind": "paragraph", "text": "Our experimental results are ambiguous as to whether Double's outperformance of Always in the head-to-head and median measures is because it makes more investments (like Never) or because its selection of follow-on investments is superior to Always. To study this issue we consider those follow-on investments with valuation changes in the table below:", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "a96ddc14-e929-4b50-962b-951a41802533", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.05, "y": 0.75 }, "kind": "paragraph", "text": "Compared to the universe of all follow-on investments, the Series A investments that followed the doubling of a convertible have a higher median, lower mean, and identical fraction of \"Went to Zero\" investments. Investor preferences for mean or median return would seem to support either of these strategies, and it does not seem reasonable to reject either one out of hand based on these results.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "b1191d9e-0023-4aef-82b7-1706aeb61dee", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.03, "w": 0.2, "x": 0.05, "y": 0.85 }, "kind": "title", "text": "Discussion", "attrs": null, "subkind": "headline", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "85aa746a-f8f7-46b2-a6f0-b353a3036dde", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.03, "w": 0.5, "x": 0.05, "y": 0.05 }, "kind": "title", "text": "Othman - Should Seed Investors Follow On?", "attrs": null, "subkind": "headline", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "ee58e29c-8f5c-4d20-9a29-17eabb1a578b", "frameworkName": null, "frameworkSlug": null } ], "metrics": [], "tools": [], "frameworks": [], "arcBeats": [ { "to": 9, "from": 6, "beatId": "df214c8c-58e1-4676-8454-88cc51badb52", "arcName": "Problem-Agitate-Solution", "arcSlug": "problem-agitate-solution", "beatName": "Solution", "beatSlug": "problem-agitate-solution-solution-provide-relief", "evidence": "The deck provides key takeaways and a comparison table to offer a solution to the problem.", "position": 2, "confidence": 0.8, "parentBeatName": "Resolution", "parentBeatSlug": "resolution" } ], "loops": [ { "to": 8, "from": 6, "name": "Mece Breakdown", "slug": "40-mece-breakdown", "bestFor": "Problem structuring, ensuring completeness, strategic analysis", "matchId": "97efb20c-70aa-4bdc-a925-4eb23cf5a42c", "evidence": "The deck uses a comparison table to break down the decision into manageable parts.", "position": 1, "objective": "to break down the decision into manageable parts", "structure": "The Whole -> Category A (distinct) -> Category B (distinct) -> Category C (distinct) -> Complete Coverage", "confidence": 0.7, "description": "Divide a complex topic into mutually exclusive, collectively exhaustive categories" } ], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }