Opportunity Radar Built By Traders, For Traders

This is the story of us building Candlestick.io.

9X Is Just The Begining

Our story with blockchain data analytics starts at the end of 2020. Nearly missed the whole DeFi summer, we’ve caught on $BADGER (& $DIGG). That’s when we realized the value of on-chain data is beyond the fundamental analysis — it adds greater value to the technical trading analytics.

Long story short, we entered $BADGER at $4 and exited at around $40 (9x) by analyzing the holder amount for entry and monitoring large LP movements for an exit. The entry at token holder number dropped from 4k to 2k, which was a deadly signal for most people in the trading groups we joined because it literally means early holders/airdrop receivers don’t care about anything but quick profit. But the unique number of addresses that provided liquidity and staked showed extraordinary growth — turns out the significant drop in holders was due to holders sending all tokens to DEX pools.

Meanwhile, we started monitoring the positions of different addresses, following the actions of major holders to know when are they selling. Started with excel and a few Etherscan tables for token transfer, we also built a sketchy Dune to level up our weapons.

(A forked version of Dune Analytics we made)

Infinite Intels with Decoded On-Chain Data

Then we realized it is the perfect timing to unlock the value of on-chain data, especially with our “Proof of Work”. AMM, liquidity mining, yield farming, L2, all these innovative products/mechanisms had “stole” all the major trading/financial activities from CEXs’ black boxes to the public ledger. DEXs already had more trading volume than CEXs, plus they were faster, safer (think QuadrigaCX), and more transparent (think Okex). All these on-chain activities stored & accessible by anyone are the new gold mines.

  1. Moving forward, we tried to discover more with fully decoded on-chain data:
  2. What kind of addresses is buying/selling? Are they whale or small retail?
  3. Are the large holders selling off when the price driving up? Or are they still holding?
  4. Do insider traders exist? Did someone accumulate a token right before the good news is announced or dump it before something bad happened?
  5. Is a token being manipulated? Are there real trading orders or market-making?
  6. Are there any “signals” for a perfect buy or sell timing? What contributes to the signals?

Turns out it gets more insightful after digging deeper, you get to see the full picture by seeing as a whole and also looking at small groups (Whales/VCs/Elite Traders, etc.). So we started working in 2 directions.

Stay On Top Of The Market

1. Finding the right indicator for trading actions. We use machine learning to find correlations between token prices and different datasets created based on on-chain activities. We created a lot of metrics based on traditional stock trading as well as innovated on-chain methods only available with web 3. Eventually, 60 out of 100+ metrics were chosen to be on Candlestick as our algorithms show them more relevant to price changes. Just to name a few:

  • Net Buy Value

It means there are more tokens that were brought than were sold if the Net Buy is positive. Very great indicator for entry & exit timing.

  • Net Add Liquidity

Monitor liquidity movements for tokens. Seeing a significant liquidity change on a token? Something is happening, you know if it is good or bad, you just don’t know exactly what it is yet.

Saw $FTM removed from DEXs 2 days before Andre Cronje’s announcement to leave? You sold at the peak!

A great amount of $FTM was removed 2 days before AC’s announcement to leave.
  • Average HODL Price & Position Cost Distribution

Knowing the average holding price of the whole market could definitely help you evaluate your positions. What about knowing the price support line and resistance line? Very clear right!

  • Turnover Rate

The Turnover Rate can reflect the activity status of traders. The all-time high peak of turnovers appears before a token reaches the price peak.

Keeping Up With The Smart Money

2. Identifying the Smarter Minority (Smart Money) so that they could work for us. Believe it or not, there’s a reason a whale becomes a whale — whether he/she is smarter, has a better network, or has higher-level information. They called it asymmetric information. Know what they are doing, we become part of them.

There is so much information that we could get when analyzing the activities of an address at different levels.

  • The total value of holdings & distributions
  • Trading & costs of positions
  • Defi activities (LPs, farming, lending, etc.)
  • Funds moving into CEXs

For example, We went through 5,433,370 addresses that traded on Ethereum DEX and built models based on profits, buy/sell ratios, realized & unrealized gains and win rate, etc. to generate the “Smart Dex Traders” group. Guess which one of the followings is labeled as “Smart Dex Trader” on Candlestick?

Yes, all the above are of the 800+ Smart DEX Traders our model found (but in different segments). Our Smart Money Mode is a feature that applies Smart Address Lists to our charts to track their behaviors — see they are working for us!

Candlestick is launched! It took us 8 months from concept to shipping the beta. There are way more difficulties than we expected. As an early bird, now you can enjoy full access to all functions including 60+ token signals, real-time Smart Money movement, 40+ exclusive metric analytics & Gem Explore with 60% off.

It’s just a simple story of how a group of guys turned our own research & analysis into a powerful tool, not only for ourselves but for our users.

But nothing is more exciting than seeing a bull born in a bear market right?