{"id":797,"date":"2026-07-29T23:47:33","date_gmt":"2026-07-30T03:47:33","guid":{"rendered":"https:\/\/www.tiingo.com\/blog\/immortalizing-our-history-through-blockchain\/"},"modified":"2026-07-29T23:47:33","modified_gmt":"2026-07-30T03:47:33","slug":"immortalizing-our-history-through-blockchain","status":"publish","type":"post","link":"https:\/\/www.tiingo.com\/blog\/immortalizing-our-history-through-blockchain\/","title":{"rendered":"Immortalizing Our History Through Blockchain"},"content":{"rendered":"
\n

A note from Rishi:<\/strong> This piece first appeared in Chainlink Today, which has since shut down. I’m republishing it here because it covers what I still think is one of the most important problems we have to solve in data, and the last few years have only made it more urgent. We are now in an age where AI systems are trained on historical data and used to test future policy decisions. If the underlying record is wrong, or quietly rewritten, then every model and every decision built on top of it inherits that error and nobody can see where it came from. The integrity of the record is the whole foundation.<\/p>\n<\/blockquote>\n

In 2017, I received an email asking for a meeting to talk about market data. I initially thought it would be a standard sales meeting, but soon it became clear that it was anything but.<\/p>\n

When I met my contact in a nondescript coffee shop in downtown New York City, he told me a story about market data that has stuck with me ever since.<\/p>\n

Prior to 9\/11, a well-known large financial firm was located in a building adjacent to the World Trade Center. While their building was not attacked during the events that transpired on 9\/11, the collapse of the WTC blew out the buildings of their nearby office, destroying nearly everything in their path and scattering rubble everywhere.<\/p>\n

The namesake family who still ran this particular financial firm was looking to salvage what they could amongst the debris. During the course of this recovery, they came across old market data tape drives from the 1960s onward.<\/p>\n

The patriarch (still head of the financial firm) was planning to throw out those tapes until the youngest and “IV” in their family line told him to wait. “IV” understood the power of data and insisted that rather than throw away the tapes, they should convert them to a more modern, digital format.<\/p>\n

My contact then shared with me a small sample of the data, and I was awestruck. I was looking at 1969 tick data for an American icon: Ford. This was data that almost nobody alive today had seen before.<\/p>\n

I then realized the gravity of the story I had just heard: had “IV” not convinced his father to save the tapes, this piece of financial history would have been lost forever, disappearing into the ethers of knowledge that once was.<\/p>\n

The fragility of financial history<\/h2>\n

Each day in the course of running Tiingo.com, a platform built on providing clean, reliable financial data, I am continually reminded of the fragility of financial data. And I don’t just mean single points of failure from non-redundant data storage, but also conflicting information about what has happened on any given day.<\/p>\n

Our success stems from people testing our data and discovering its cleanliness for themselves. What they don’t see is the massive behind-the-scenes cleaning effort demanded by data sources that continuously conflict.<\/p>\n

For example, in 2020 there was a stretch of two to three months when 6% to 8% of data points among centralized U.S. equity exchange data providers disagreed on open, high, low, and closing prices as well as volumes. Not edge cases. Household names, on ordinary days.<\/p>\n

Since 2014 (when we launched our firm), tracking these discrepancies and their causes has been relatively easy compared to tracking data from years ago.<\/p>\n

Why does this matter? Because, each day, we gatekeep the history of data as we go through painstaking lengths to verify older data. If a customer raises a questionable data point regarding information that appeared as recently as 2005, for example, we then proceed to comb over financial filings as well as our own news database of over 70 million articles in search of any reason that the price discrepancy may exist.<\/p>\n

This process quickly becomes incredibly labor intensive, sometimes taking between two to six hours to trace down a single price discrepancy. In some cases, nothing we find can explain the price discrepancy, so we are forced to accept that the price movement may be real based on circumstantial evidence and our evolving understanding of market dynamics at the time.<\/p>\n

These are the cases that keep us up at night. And then I am forced to ask the question:<\/p>\n

“What if there is a better way to record financial history?”<\/em><\/p>\n

What we built on our own side of the problem<\/h2>\n

Long before this had anything to do with blockchains, it forced us to solve a smaller version of the same problem internally. For over a decade we have kept an auditable trail of unadjusted data. Every time our system adjusts or unadjusts a price, it captures the delta, and no human at Tiingo can overwrite or erase what was there before. The record of what we thought a price was, and when we thought it, survives.<\/p>\n

That matters more than it sounds. A lot of public sources have quietly gotten worse at this over the years, to the point where most data labeled “unadjusted” out in the world has actually been adjusted for splits already, or is simply inconsistent from one day to the next. If your own history can be silently rewritten, you cannot answer a question about a 2005 price at all, and you certainly cannot prove your answer. Our end-of-day history reaches back to 1962<\/a>, and I have come to think of maintaining it as custodial work more than product work.<\/p>\n

An immutable internal record is the same idea as an immutable public one, only at a smaller scale and with one company as the trusted party. Which raises the obvious question about whether the trusted party needs to be a company at all.<\/p>\n

Why blockchain answers this<\/h2>\n

Blockchain solves this not-so-rhetorical question by allowing data to exist openly for everyone in a redundant way that also immutably records history. One location being attacked will not destroy data, and those in charge of data cannot accidentally (or purposefully) change historical data points.<\/p>\n

Blockchain and oracle networks<\/a> like Chainlink<\/a> create a real-time mapping of our history. Moreover, Chainlink Price Feeds don’t ignore price variations, but rather map them with full transparency.<\/p>\n

This is why Tiingo’s data is on-chain in three different ways. We run our own Chainlink node<\/a>, publishing cryptographically signed end-of-day US equity prices. We also supply data to other node operators, who combine our data with other sources into aggregated feeds. And our data is now available through Chainlink’s DataLink<\/a> service as well. Each route cements the same history a little more permanently.<\/p>\n

Nobody knew this data would matter<\/h2>\n

In the infancy of the stock market, we could not fathom what data would be used for. In fact, I asked “IV” of the aforementioned financial firm: “Why didn’t the exchanges have this old tick data?”<\/p>\n

His response was that stock exchanges did not anticipate that the data would be useful, and in the 1960s-80s, they contracted data storage to an outside firm. Both the exchange and the firm did not think data that old would be useful, so they decided to throw it out.<\/p>\n

Read that again. The people holding that 1969 tick data made a reasonable-sounding judgment that nobody would ever want it, and threw it out on purpose.<\/p>\n

If there’s anything to be learned from this story and applied to crypto markets in their infancy, it’s that it is our responsibility to future generations to ensure that this financial history is recorded in both its glory and volatility. This financial price data may one day be used for financial modeling and gaining insight into what makes a successful crypto project stand out.<\/p>\n

This data will also be used to better understand our society and how to build projects with longevity. Yet we probably cannot even fathom all the ways this data will be used 100 years from now, and that is exactly why it is our job to ensure the data remains clean, accurate, and available for future generations to build a more stable, prosperous, and equitable world.<\/p>\n

We have been at this since 2014. We are a team of artists, engineers, and algorithmic traders, some of us former professional photographers, some of us having run trading algorithms managing hundreds of millions of dollars, and we built the company on the belief that love is the right way to conduct business. If preserving the record is a problem you care about too, I would genuinely like to hear about it: rishi@tiingo.com.<\/p>\n","protected":false},"excerpt":{"rendered":"

A note from Rishi: This piece first appeared in Chainlink Today, which has since shut down. I’m republishing it here because it covers what I still think is one of the most important problems we have to solve in data, and the last few years have only made it more urgent. We are now in […]<\/p>\n","protected":false},"author":1,"featured_media":798,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"osom_blocks_metabox":"","inline_featured_image":false,"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","footnotes":""},"categories":[7],"tags":[],"class_list":["post-797","post","type-post","status-publish","format-standard","has-post-thumbnail","category-market-data","entry"],"yoast_head":"\nImmortalizing Our History Through Blockchain | Tiingo<\/title>\n<meta name=\"description\" content=\"A 2017 meeting, 1969 Ford tick data recovered after 9\/11, and why the record of financial history needs to be immutable.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" 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