The Effects of Liquidity in the Entry and Exit Criteria of Leveraged Bitcoin Tokens
The Effects of Liquidity in the Entry and Exit Criteria of Leveraged Bitcoin Tokens
Christian L. Groves (@Groves, The Don), IMC Level 4
Cryptocurrency Investing Campus - The Real World (“TRW”)
Adam’s Investing Masterclass
Professor Adam
02 November 2024
*THE FINDINGS OF THIS RESEARCH PAPER ARE NOT INTENDED TO BE FOR THOSE WHO HAVE NOT YET COMPLETED IMC LEVEL 3 AND HAVE OBTAINED IMC LEVEL 4. ONLY PAST LEVEL 3 WILL YOU HAVE A FULL UNDERSTANDING OF THE RESULTS.*
Author Note
Christian Groves (@Groves, The Don), Adam’s Investing Masterclass, TRW.
I would like to thank Professor Adam, the Investing Captains, and the Investing Masters, especially @Randy_S | Crypto Captain, @Natt | 𝓘𝓜𝓒 𝓖𝓾𝓲𝓭𝓮, and @Stefan Stojanovic for helping me through the IMC exam and IMC levels, and @IRS`⚖️for creating some of my favourite indicator inputs for my systems.
Correspondence concerning this article should be addressed via Direct Message in TRW to @Groves, The Don.
Abstract
This research paper aims to discover whether the entry criteria of “long” signals from only the MTPI and LTPI are optimal, or if additional factors can improve the quality and returns of signals, specifically, Global Liquidity.
Four different methods have been studied: 1) MTPI only, 2) LTPI only, 3) MTPI and LTPI, and 4) MTPI, LTPI, and Liquidity TPI. A more in-depth description of the individual entry and exit criteria for each of the methods will be explained in the analysis and results of each respective method.
The best method found for the leveraged tokens, both 3x and 4x, was Strategy 4. The best method found for spot holdings was Strategy 2, with Strategy 4 very close behind. Strategy 1 and Strategy 3 were found to be incompetent compared to Strategy 2 and Strategy 4.
The Effects of Liquidity in the Entry and Exit Criteria of Leveraged Bitcoin Tokens
Tradingview was used to map the entry and exit dates based on the systems’ individual signals. The characteristics of the leveraged tokens are what was described by Toros Finance’s “Leveraged Tokens Overview” at the time of this writing. Google Sheets was used to manage and record data. coincodex was used to retrieve historical price data for BTC from 01 January 2018 to 31 October 2024 (the timeframe of the project). Google Colab was used for the calculations of daily returns within a selected signal period, daily leverage updating during the signal period, leverage rebalancing – if necessary – during the signal period, cumulative daily returns during the signal period, and cumulative period returns for 3x leverage, 4x leverage, and spot.
Strategy 1: MTPI Only
Criteria
Entry: MTPI signals “long”.
Exit: MTPI signals “short/no position”
Full Data (image below)
Data Summary
During the timeframe of this study, the MTPI Only Strategy had 17 entries and exits. The returns were as follows:
Spot: 11,3784x (1.137,84%)
3x: 234,5617x (23.456,17%)
4x: 156,9535x (15.695,35%)
Analysis
Due to the quickened signal changes of the MTPI, there are significantly more drawdown periods than with the other Strategies, especially during the bear markets. Due to the nature of leveraged tokens, even “slight” drawdowns have an incredible effect on the value of the holdings, especially when selling for a loss.
Conclusion
The sensitivity of the MTPI causes more signals, which is not necessarily a good aspect when running a strategy for leveraged tokens.
Strategy 2: LTPI Only
Criteria
Entry: LTPI signals “long”.
Exit: LTPI signals “short/no position”
Full Data (image below)
Data Summary
During the timeframe of this study, the LTPI Only Strategy had seven entries and exits. The returns were as follows:
Spot: 29,8148x (2.981,48%)
3x: 3.105,8439x (310.584,39%)
4x: 3.711,3341x (371.133,41%)
Analysis
Due to the slower signal changes of the LTPI, this strategy captured the highest probability trends compared to the MTPI Strategy. This style of signals matches much better with leveraged tokens, as there were far fewer realised losses.
Conclusion
The higher conviction trend signals with the LTPI, though slower, are of very high quality, which is exceptionally important with a leveraged token strategy to avoid significant losses.
Strategy 3: MTPI and LTPI
Criteria
Entry: MTPI is “long”, and LTPI is “long”
Exit: MTPI is “short/no position”, or LTPI is “short/no position”, or MTPI and LTPI are “short/no position”
Full Data (image below)
Data Summary
During the timeframe of this study, the MTPI and LTPI Strategy had 12 entries and exits. The returns were as follows:
Spot: 17,5478x (1.754,78%)
3x: 1.168,7925x (116.879,25%)
4x: 1.675,3862x (167.538,62%)
Analysis
Combining the quickness of the MTPI with the conviction of the LTPI seemed like a good idea prior to running the tests, but it failed to outperform the LTPI Only Strategy. Because only one of the systems has to flip short/no position, the quickness of the MTPI hinders the LTPI’s higher-probability long-trend continuations.
It seems to perform better than the MTPI Only Strategy because it does not fire during bear markets, leading to less losses.
Conclusion
Combining the MTPI with the LTPI prevents false positive signals during bear markets, but it allows for false negatives during strong bull markets, significantly reducing potential profits.
Strategy 4: MTPI, LTPI, and Liquidity TPI
Criteria
Entry: At least two of the three TPIs signals “long”. Which two of the three does not matter.
Exit: At least two of the three TPIs signals “short/no position”. Which two of the three does not matter.
Full Data (image below)
Data Summary
During the timeframe of this study, the MTPI, LTPI, and Liquidity TPI Strategy had nine entries and exits. The returns were as follows:
Spot: 27,7159x (2.771,59%)
3x: 4.909,2913x (490.929,13%)
4x: 9.769,7174x (976.971,74%)
Analysis
Global liquidity is a clear driver of the cryptocurrency market. It seems that this can be used in a leverage token system to provide more signals without losing their quality. The LTPI prevents firing in the bear markets, the MTPI ensures quicker entries, and the Liquidity signals provide confluence to some of the “difficult” times of market direction. In this study, it outperformed any other system in the leveraged tokens returns.
Conclusion
The higher conviction trend signals with the LTPI, though slower, are of very high quality, which is exceptionally important with a leveraged token strategy to avoid significant losses.
Final Results
Strategy 4 – the MTPI, LTPI, and Liquidity TPI Strategy – proved to be the best choice for a leveraged token system. The MTPI alone is too sensitive in bear markets, as it tends to have a couple of costly false positives, the LTPI is great, and even the best, for a spot positions Strategy, but is not quite quick enough to capture early trend shifts. The MTPI and LTPI Strategy fails to stay “long” during the longer, parabolic trends with sharp pullbacks, which cost potential profits in the parabolic stage of the bull markets.
The most significant conclusion from this study is that even through major drawdowns in a bull market, so long as the systems you are using continue to remain long, it is better to hold the leveraged tokens rather than capitulate, especially if your systems are robust.
Strategy 4 was best for leverage.
Strategy 2 was best for spot.
Disclaimers
The findings in this study were conducted using a personally created LTPI, MTPI, and Liquidity TPI, not the systems of Professor Adam. An additional note for the LTPI, due to difficulties in finding all of the information for the true LTPI to backtest with, this testing was completed using the TOTAL input for the full LTPI system. I believe that using the full LTPI system for forward testing will provide higher quality entries and exits due to the full range of market inputs included in such a system (not advice). The only cryptocurrency this was tested for was Bitcoin, using Tradingview’s INDEX:BTCUSD ticker. Ethereum and Solana have not been tested at the time of writing. The calculations were completed with a personally coded system in Python in Google Colab to increase accuracy and efficiency. The calculations for leverage in the context of this paper were completed with the 3x and 4x Toros leveraged tokens; the webpage with Toros’s description will be included in References. The calculations in the coded system take into account the respective rebalancing ranges, as described on Toros’s website; however, due to the constraint of resources (i.e.: not having access to a supercomputer), the rebalancing does not occur intraday as it may with Toros. Rebalancing fees are not taken into account. The effects of this for the purpose of this research project are at worst minor, if not negligible, as the exact returns of each strategy is not the point of concern. Historical Bitcoin price information used in this project is from 01 January 2018 to 31 October 2024. This will be considered the initial timeframe of the project prior to any updates that may occur.
*THIS RESEARCH IS NOT INTENDED TO BE FINANCIAL ADVICE. USE THE FINDINGS OF THIS PAPER AT YOUR OWN DISCRETION, PREFERABLY AS CONFLUENCE TO YOUR ALREADY-CREATED, ROBUST SYSTEMS. ALWAYS DO YOUR OWN RESEARCH BEFORE ENTERING A POSITION.*
*I RESERVE THE RIGHT TO DENY A RESPONSE TO ANY QUESTION THAT DEMONSTRATES THE LACK OF FUNDAMENTAL KNOWLEDGE REQUIRED TO PERFORM SUCH A SYSTEM.*
References
CoinCodex. (n.d.). Bitcoin (BTC) Historical Data. CoinCodex. Retrieved November 2, 2024, from https://coincodex.com/crypto/bitcoin/historical-data/
Toros Finance. (n.d.). Bitcoin Bull 3x | Toros. Retrieved November 2, 2024, from https://toros.finance/vault/0xb03818de4992388260b62259361778cf98485dfe
Toros Finance. (n.d.). Bitcoin Bull 4x | Toros. Retrieved November 2, 2024, from https://toros.finance/vault/0x11b55966527ff030ca9c7b1c548b4be5e7eaee6d
Toros Finance. (2024, October 4). Leveraged Tokens Overview. Retrieved November 2, 2024, from https://docs.toros.finance/leveraged-tokens/leveraged-tokens-overview
Tradingview. (n.d.). BTCUSD. Retrieved November 2, 2024, from https://www.tradingview.com/chart/ipH0WohG/?symbol=INDEX%3ABTCUSD