The Power-Law Mystery of Corn and Bitcoin

2026-06-18 14:44 127 views US Stock Trending News
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Can Corn Predict Bitcoin? This Mysterious Pattern Makes Farmers Consider Buying Crypto

When it comes to measuring Bitcoin's value, what comes to mind first? Is it the fluctuating dollar price, the gold it's often compared to, or the ebb and flow between Bitcoin and the Nasdaq index?

But you may never guess that someone recently turned their attention to – corn.

Yes, you read that right. The corn from your breakfast flakes, the popcorn downstairs, even the cornfield near your home.

The 'Unexpected Discovery' in Corn Prices

Kevin Kimle, founder of US agricultural Bitcoin company BitCorn, recently conducted a rather interesting study. He found that since 2013, there has been a stable mathematical pattern called 'power-law relationship' between Bitcoin and US corn prices.

What is a power-law relationship? In simple terms, the amount of corn one Bitcoin can buy has been steadily growing along a predictable curve over time, rather than fluctuating randomly.

Kimle's research shows the model exponent is 5.03, with R² reaching 0.91. This sounds technical, but in plain language: this mathematical model can explain about 91% of the Bitcoin-corn price ratio changes over the past 13 years. 91%! This is already a quite astonishing number.

In the financial field, even those professional quantitative fund teams dare not claim they can predict over 90% of price movements.

Why Corn? Not Beef or Wheat?

You might ask, why use corn to price Bitcoin? Isn't gold, the dollar, or even housing prices more common?

There's deep reasoning here. Kimle believes using physical commodities like corn as a reference can cleverly filter out the interference of currency depreciation and inflation. No matter whether you hold dollars, euros, or yen, they all continuously depreciate, a known fact of the global monetary system. But corn? It's a real agricultural product; its price reflects real supply and demand.

For example, with $100 in 1980, you could buy 100 ears of corn in a supermarket; now maybe only 20. But if in 1980, you used 1 Bitcoin to buy corn (Bitcoin didn't exist then, but let's assume), now that same Bitcoin could buy dozens or even hundreds of times more corn.

This is the charm of using corn as a reference – it filters out the interference of currency depreciation, letting you see Bitcoin's 'real purchasing power' growth trajectory.

Bitcoin's 'Corn Purchasing Power': Underestimated?

Kimle's research goes beyond historical data compilation; he built a Z-Score model to judge whether Bitcoin is 'overpriced' or 'underpriced' relative to corn prices.

According to this model, during the FTX collapse at the end of 2022, Bitcoin's Z value relative to corn fell to an extreme negative value of -1.84, meaning Bitcoin's corn purchasing power was far below the long-term trend, an excellent buying opportunity. Kimle even believes that was one of the best times for agricultural producers to allocate Bitcoin using agricultural income.

As of June 2026, the model shows the current Z value is about -0.68, not extremely undervalued but still below the long-term average. In other words, from the perspective of corn purchasing power, Bitcoin is currently in a 'slightly discounted' state.

Why Should Farmers Consider Allocating Bitcoin?

You might think asking corn farmers to buy Bitcoin sounds a bit far-fetched. But Kimle believes it's actually a rational asset allocation strategy for the agricultural industry.

Agriculture is a typical capital-intensive industry. What do farmers face long-term? Rising seed, fertilizer, and equipment costs, unpredictable weather and pests, and sharp fluctuations in agricultural product prices. In such an environment, inflation and currency depreciation are farmers' biggest headaches.

Kimle's suggestion: for any capital-intensive agricultural enterprise, allocating part of operating profits to Bitcoin is not speculation but a structural asset allocation choice. Just as you can't put all eggs in one basket, farmers can't rely solely on corn prices for income.

BitCorn was founded precisely to promote the combination of agriculture with Bitcoin infrastructure, providing new wealth management tools for farmers and agricultural enterprises.

Why Is Power-Law Theory Popular?

In fact, using power-law theory to analyze Bitcoin is not unique to Kimle. In recent years, the 'Bitcoin power-law theory' has gained many supporters in the crypto field.

Korok Ray, an associate professor at Texas A&M University's Mays Business School, believes that Bitcoin's fixed total supply of 21 million is an important reason for the power-law model's long-term effectiveness.

Ray explained a very interesting perspective: the core force driving the power-law model is the FOMO cycle.

Think about it: when gold prices rise, miners increase production, increasing market supply, thereby relatively suppressing gold's rise. But Bitcoin is different; its issuance speed is entirely controlled by the protocol. No matter how high the price goes, miners cannot increase supply by raising production.

This 'verifiable scarcity' creates a sustained expectation among market participants: 'There will always be someone who bought before you, and they bought when supply was greater and price was lower.'

This long-standing expectation drives Bitcoin's price to rise along a trajectory similar to a power-law curve.

Opponents Say: Bitcoin Is Not Natural Science

However, there's no free lunch; the market never gives anyone accurate predictions.

Adrian Morris, deputy head of digital asset recovery at Grant Thornton, openly criticized this view. He believes treating Bitcoin as a physical system following natural laws is itself a 'category error'.

Morris's point is sharp: 'Bitcoin should be understood as a complex socio-technical system.'

What does that mean? Bitcoin's price is not determined by some natural law but is influenced by many factors: economic environment, regulatory policies, geopolitics, investor sentiment, and capital flows. These variables are too complex for a single mathematical formula to encompass.

According to Morris: 'As part of the global financial network, Bitcoin's price behavior is far more complex than a physical system.'

Can Corn Really Predict Bitcoin's Future?

To be honest, the answer is probably no.

Kimle himself is actually cautious: He does not believe corn prices will determine or predict Bitcoin's future trajectory. Instead, corn is just a reference, a simple yardstick to measure changes in Bitcoin's purchasing power.

Why choose corn? Precisely because there's no direct link between corn and Bitcoin. Corn prices are mainly determined by agricultural factors like weather, acreage, yield, and global demand, almost no direct connection to the crypto market. Because of this 'irrelevance', corn can become an ideal benchmark to help investors filter out currency depreciation noise and observe Bitcoin's genuine long-term value growth.

But even though this pattern has persisted for over 13 years, no one can guarantee it will remain effective in the future. After all, patterns are only patterns because they can be broken under extreme circumstances.

For ordinary investors, the 'Bitcoin and corn' story provides a fresh perspective, an interesting thinking tool. But it can never replace comprehensive analysis of macroeconomics, market sentiment, and crypto industry fundamentals.

Next time you buy Bitcoin, maybe you'll think about corn prices. After all, this golden grain is telling a fascinating story between the digital world and the real economy in its unique way.

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  1. CONNECT:[ UseTime:0.001010s ] mysql:host=127.0.0.1;port=3306;dbname=cjgpcs;charset=utf8mb4
  2. SHOW FULL COLUMNS FROM `g3ys_config` [ RunTime:0.002527s ]
  3. SELECT `value` FROM `g3ys_config` WHERE `name` = 'timezone' AND `subsite_id` = '27' LIMIT 1 [ RunTime:0.000743s ]
  4. SHOW FULL COLUMNS FROM `g3ys_route` [ RunTime:0.002487s ]
  5. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '27' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000750s ]
  6. SHOW FULL COLUMNS FROM `g3ys_theme` [ RunTime:0.002735s ]
  7. SELECT `paginator` FROM `g3ys_theme` WHERE `module` = 'home' AND `name` = 'green' AND `subsite_id` = '27' LIMIT 1 [ RunTime:0.000728s ]
  8. SHOW FULL COLUMNS FROM `g3ys_lang` [ RunTime:0.003447s ]
  9. SELECT * FROM `g3ys_lang` WHERE `subsite_id` = 27 AND ( ( LOWER(name) = 'en-us' ) OR `subtag` = 'en-us' ) AND `status` = 1 ORDER BY `id` ASC LIMIT 1 [ RunTime:0.001167s ]
  10. SHOW FULL COLUMNS FROM `g3ys_member` [ RunTime:0.004071s ]
  11. SELECT * FROM `g3ys_member` WHERE `id` = 0 AND `subsite_id` = '27' LIMIT 1 [ RunTime:0.001067s ]
  12. SHOW FULL COLUMNS FROM `g3ys_document` [ RunTime:0.003744s ]
  13. SELECT `id`,`document_type` FROM `g3ys_document` WHERE `subsite_id` = 27 AND `name` = 'corn-bitcoin-power-law-purchasing-power' AND `status` IN ('1','2') LIMIT 1 [ RunTime:0.001029s ]
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  15. SHOW TABLES LIKE 'g3ys_document_article' [ RunTime:0.002469s ]
  16. SHOW FULL COLUMNS FROM `g3ys_document_article` [ RunTime:0.001611s ]
  17. SELECT * FROM `g3ys_document_article` WHERE `document_id` = '4872' LIMIT 1 [ RunTime:0.000746s ]
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  19. SELECT * FROM `g3ys_total` WHERE `target_id` = '4872' LIMIT 1 [ RunTime:0.000901s ]
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  23. SHOW FULL COLUMNS FROM `g3ys_document_article_lang` [ RunTime:0.002389s ]
  24. SHOW TABLES LIKE 'g3ys_category_lang' [ RunTime:0.002405s ]
  25. SHOW FULL COLUMNS FROM `g3ys_category_lang` [ RunTime:0.001913s ]
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  27. SELECT * FROM `g3ys_total` WHERE `target_id` = '4872' LIMIT 1 [ RunTime:0.001102s ]
  28. UPDATE `g3ys_total` SET `view_total` = `view_total` + 1 WHERE `target_id` = '4872' [ RunTime:0.002597s ]
  29. SHOW FULL COLUMNS FROM `g3ys_record` [ RunTime:0.004377s ]
  30. SELECT `id` FROM `g3ys_record` WHERE `subsite_id` = '27' AND `type` = 'article' AND `url` = 'https://www.thaifarm.asia/corn-bitcoin-power-law-purchasing-power' AND `create_time` >= 1788520462 AND ( `visitor_id` = '8fa85e1c811cc0a6191a219182dd78b7' OR `session_id` = '0a991afe568e61429060fc7462c83c17' ) LIMIT 1 [ RunTime:0.001544s ]
  31. INSERT INTO `g3ys_record` SET `subsite_id` = '27' , `uid` = '0' , `visitor_id` = '8fa85e1c811cc0a6191a219182dd78b7' , `session_id` = '0a991afe568e61429060fc7462c83c17' , `type` = 'article' , `target_id` = '4872' , `target_type` = 0 , `category_id` = '1255' , `title` = 'The Power-Law Mystery of Corn and Bitcoin' , `url` = 'https://www.thaifarm.asia/corn-bitcoin-power-law-purchasing-power' , `path` = '/corn-bitcoin-power-law-purchasing-power' , `query_string` = '' , `referer` = '' , `referer_domain` = '' , `source_type` = 'direct' , `source_domain` = '' , `search_engine` = '' , `search_keyword` = '' , `utm_source` = '' , `utm_medium` = '' , `utm_campaign` = '' , `utm_term` = '' , `utm_content` = '' , `ip` = '216.73.216.196' , `user_agent` = 'Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)' , `device_type` = 'pc' , `browser` = '其他' , `browser_version` = '' , `os` = '其他' , `os_version` = '' , `language` = '' , `is_spider` = 0 , `spider_name` = '' , `status_code` = 200 , `country` = '' , `province` = '' , `city` = '' , `district` = '' , `isp` = '' , `region_code` = '' , `geo_status` = 0 , `geo_time` = 0 , `create_time` = 1788520522 , `update_time` = 1788520522 [ RunTime:0.003380s ]
  32. SHOW FULL COLUMNS FROM `g3ys_comment` [ RunTime:0.003265s ]
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  34. SELECT * FROM `g3ys_document` WHERE `category_id` = 1255 AND `subsite_id` = 27 AND `pid` = '0' AND `status` = '1' AND ( ( sort > 0) or ( sort = 0 and id < 4872) ) ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.001975s ]
  35. SELECT * FROM `g3ys_document` WHERE `category_id` = 1255 AND `subsite_id` = 27 AND `pid` = '4871' AND `status` = '1' ORDER BY `sort` ASC,`id` DESC LIMIT 1 [ RunTime:0.001488s ]
  36. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '27' AND `lang` = 'en-US' AND `document_id` = '4871' [ RunTime:0.008516s ]
  37. SELECT * FROM `g3ys_document` WHERE `category_id` = 1255 AND `subsite_id` = 27 AND `pid` = '4872' AND `status` = '1' AND `document_type` = 0 ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.001710s ]
  38. SELECT * FROM `g3ys_document` WHERE `category_id` = 1255 AND `subsite_id` = 27 AND `pid` = '0' AND `status` = '1' AND `document_type` = 0 AND ( ( sort>0 and sort <= 0 and id!=4872) or ( sort = 0 and id > 4872) ) ORDER BY `sort` DESC,`id` ASC LIMIT 1 [ RunTime:0.001239s ]
  39. SELECT * FROM `g3ys_document_article_lang` WHERE `subsite_id` = '27' AND `lang` = 'en-US' AND `document_id` = '4930' [ RunTime:0.012346s ]
  40. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '27' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001680s ]
  41. SELECT * FROM `g3ys_total` WHERE `target_id` = '4872' LIMIT 1 [ RunTime:0.000969s ]
  42. SHOW FULL COLUMNS FROM `g3ys_ad_location` [ RunTime:0.003627s ]
  43. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-detail-full' AND `subsite_id` = '27' AND `status` = 1 LIMIT 1 [ RunTime:0.001222s ]
  44. SHOW FULL COLUMNS FROM `g3ys_ad` [ RunTime:0.004824s ]
  45. SELECT * FROM `g3ys_ad` WHERE `subsite_id` = '27' AND `ad_location_id` = '27' AND `status` = 1 AND `device` IN ('all','pc') AND ( `start_time` = 0 OR `start_time` <= 1788520522 ) AND ( `end_time` = 0 OR `end_time` >= 1788520522 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.001390s ]
  46. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.002726s ]
  47. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 27 AND `subsite_id` = '27' AND `lang` = 'en-US' [ RunTime:0.000813s ]
  48. SHOW FULL COLUMNS FROM `g3ys_ad_lang` [ RunTime:0.002017s ]
  49. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '27' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000851s ]
  50. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '27' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000690s ]
  51. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '27' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000691s ]
  52. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '27' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000749s ]
  53. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '27' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000910s ]
  54. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '27' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001045s ]
  55. SELECT * FROM `g3ys_ad_location` WHERE `name` = 'ad-right' AND `subsite_id` = '27' AND `status` = 1 LIMIT 1 [ RunTime:0.001130s ]
  56. SELECT * FROM `g3ys_ad` WHERE `subsite_id` = '27' AND `ad_location_id` = '29' AND `status` = 1 AND `device` IN ('all','pc') AND ( `start_time` = 0 OR `start_time` <= 1788520522 ) AND ( `end_time` = 0 OR `end_time` >= 1788520522 ) ORDER BY `sort` DESC,`id` DESC [ RunTime:0.001570s ]
  57. SELECT * FROM `g3ys_ad_lang` WHERE `ad_id` = 29 AND `subsite_id` = '27' AND `lang` = 'en-US' [ RunTime:0.000808s ]
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  59. SELECT * FROM `g3ys_tags` WHERE `subsite_id` = 27 AND `status` = 1 ORDER BY `sort` DESC,`id` DESC LIMIT 15 [ RunTime:0.001762s ]
  60. SHOW FULL COLUMNS FROM `g3ys_tags_lang` [ RunTime:0.002947s ]
  61. SELECT * FROM `g3ys_tags_lang` WHERE `tags_id` IN (747,746,745,744,743,742,741,740,739,738,737,736,735,734,733) AND `subsite_id` = 27 AND `lang` = 'en-US' [ RunTime:0.002234s ]
  62. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '27' AND `category_id` = '2055' AND `lang` = 'en-US' LIMIT 1 [ RunTime:0.001782s ]
  63. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '27' AND `category_id` = '2056' AND `lang` = 'en-US' LIMIT 1 [ RunTime:0.000874s ]
  64. SELECT * FROM `g3ys_category_lang` WHERE `subsite_id` = '27' AND `category_id` = '2057' AND `lang` = 'en-US' LIMIT 1 [ RunTime:0.000878s ]
  65. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '27' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.001017s ]
  66. SELECT * FROM `g3ys_route` WHERE ( `subsite_id` = '27' OR `subsite_id` = '0' ) AND `module` = 'home' AND `status` = 1 ORDER BY `sort` DESC,`id` ASC [ RunTime:0.000925s ]
0.527663s