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      "body": "We’ve been so focused on the Protos ICO (underway now see protos.tokenhub.com for more), we haven’t shared much about our technology roadmap.\n\nWe’d like to change that.\n\nOver the next few days we will be sharing our roadmap and vision for pursuing the creation of a project that we’re currently calling PRTS2, a crypto multi-manager trading platform.\n\n**About PRTS2**\n\nPRTS2 will be a multi-manager crypto trading platform, and associated utility token for use on the platform.\n\nWe intend to build an ecosystem that will provide the necessary tools to develop quant trading strategies for cryptoassets and to make that toolset accessible to anyone. Investors in the Protos fund will have a unique position to benefit from the innovation generated in the ecosystem.\n\nAll Protos token holders will get an airdrop of PRTS2 to join our ecosystem when the platform launches (expected Q2–2018)\n\n**Why build a crypto multi manager platform?**\n\nWe believe the crypto market is maturing fast. This poses an interesting challenge for anyone investing in the space.\n\nWhile we believe that we bring the right degree of quant trading experience, market knowledge and technology expertise to remain at the forefront in the field, we also believe that an outsized degree of innovation will come from individuals or teams of traders and technologists from all over the world. We believe that this innovation remains locked unless rightly triggered.\n\nHow do we follow through on our intention to offer our token holders what we believe to be the potential to achieve the best risk adjusted return on their token investment, if we don’t have all the best minds in the world working towards that same goal?\n\nIt is clear to us that tapping into, and supporting this crowd wisdom is an important component of a successful strategy moving forward.\n\n**In the future how many tokens will be traded by humans?**\n\nWe think that, in the near future, the best brains to make trading decisions will be machines.\n\nBased on our experience in traditional markets, machine and deep learning algorithms have outpaced trading algorithms based on traditional statistics.\n\nIn the expected exponential improvements of artificial intelligence, we believe that alpha will be driven by early access to advances in these technologies which lead the way in algorithmic trading.\n\n**We believe the future of trading is human and machine.**\n\nWe believe that, to be successful in this new market, investment funds need the best minds working towards building the best algorithms to provide the best returns.\n\nWe believe it’s this pairing, of crowd wisdom, brilliant minds and leading edge algorithms, which is the key to ensure that Protos will constantly facilitate optimal returns to the PRTS Tokenholders, and be a positive force in bringing about a more decentralized future.\n\n**But developing quant strategies in a decentralized way is challenging**\n\n1. Access to data — Lack of data that can be used for meaningful backtesting limits participation\n\n2. Custodial challenges — Securing crypto while ensuring enough liquidity so that that tokens can be flexibly traded on exchanges is a challenge.\n\n3. Incentives and attribution — Defining the right Incentive structures needed to get the smartest people working in the same direction, requires careful consideration.\n \nWe believe we have solutions for the above challenges and are excited to share more of our plan to develop a decentralized active trading strategy creation platform.\n\nOver the next few days we expect to share our roadmap and vision to create a toolbox that enables anyone to develop quant trading strategies for cryptoassets.\n\nWe hope we can count on your input.\n\n\nLearn more about Protos — protos.tokenhub.com\nJoin our Telegram Channel — https://t.me/ProtosCrypto\n\n\n---\n\nProtos is an actively managed tokenized hedge fund. We’re passionate about encouraging crypto adoption by providing a global onramp to blockchain asset investment. Our ICO public sale ends soon. Visit protos.tokenhub.com to register or learn more.",
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      "body": "Congratulations @jsloss! You have completed some achievement on Steemit and have been rewarded with new badge(s) :\n\n[![](https://steemitimages.com/70x80/http://steemitboard.com/notifications/firstpost.png)](http://steemitboard.com/@jsloss) You published your First Post\n[![](https://steemitimages.com/70x80/http://steemitboard.com/notifications/firstcomment.png)](http://steemitboard.com/@jsloss) You made your First Comment\n[![](https://steemitimages.com/70x80/http://steemitboard.com/notifications/firstvoted.png)](http://steemitboard.com/@jsloss) You got a First Vote\n\nClick on any badge to view your own Board of Honor on SteemitBoard.\nFor more information about SteemitBoard, click [here](https://steemit.com/@steemitboard)\n\nIf you no longer want to receive notifications, reply to this comment with the word `STOP`\n\n> By upvoting this notification, you can help all Steemit users. Learn how [here](https://steemit.com/steemitboard/@steemitboard/http-i-cubeupload-com-7ciqeo-png)!",
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      "body": "Thanks Robot, that is indeed the original post. Well done! \n\n:)",
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      "body": "Hi! I am a robot. I just upvoted you! I found similar content that readers might be interested in:\nhttps://medium.com/@philippkallerhoff/can-a-common-hedge-fund-strategy-be-applied-to-bitcoin-to-drastically-reduce-investment-risk-12bc1c0eb7a6",
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      "permlink": "can-a-common-hedge-fund-strategy-be-applied-to-bitcoin-to-drastically-reduce-investment-risk",
      "title": "Can a Common Hedge Fund Strategy Be Applied to Bitcoin to Drastically Reduce Investment Risk?",
      "body": "*Blockchain assets are volatile, often have limited liquidity and represent higher risk than most investments. They’ve also appreciated in value at a staggering rate. So we asked ourselves, could a common hedge fund strategy, when applied to the bitcoin market, allow us to successfully limit our risk while still participating in the upside?*\n\nBlockchain assets emerged as a new asset class lately and are traded frequently on various online exchanges. Bitcoin is the most prominent example and the most valuable at the time of writing with a market cap of more than 50 billion USD.\n\nThe total market cap now exceeds 100 billion and includes more than 1000 different blockchain assets. The total trading volume exceeds 2 billion USD per day.\n\nThis market has seen tremendous interest as some of these assets have increased over 10 times in a short period of time.\nFor example, Ethereum has increased more than 24 times on 6/30/17 compared to one year ago. Hence an investor of 1000 USD a year ago would now own Ethereum worth 24’000 USD and could buy himself a new car.\n\n<h2>But that interest comes with risk</h2>\n\nMost of the blockchains are released by startups at an early stage leading to significant risk in investing in this new asset class as some of the startups will undoubtedly fail.\n\nThe risk doesn’t end there, as some of the assets have very limited liquidity, which results in massive price increases and sometimes even larger price drops.\n\nAdditionally, one could fear that the blockchain bubble bursts. In particular, the risk — measured by volatility — in this new asset class is far bigger than in the classic asset classes like equities or bonds. Both Bitcoin and Ethereum have a volatility of more than 100% over the last year, whereas the S&P 500 Index has a long run volatility of around 16%.\n\n<h2>How Risk is Managed in Traditional Markets</h2>\n\nIdeally, one could participate in the upside of blockchain assets such as bitcoin, but be protected on the downside. In traditional markets one could achieve that by buying a call option.\nA call option is the right to buy a particular underlying asset at a certain time for a certain price from the seller. The result is that the buyer of this option is only participating in the upside of the underlying, but not if the price of the underlying falls. Of course, the buyer has to pay a fee for that (premium).\n\nThe figure below shows the payoff and profit profile for the buyer, depending on the price of the underlying at the expiration date for the call option.\n\n![](https://steemitimages.com/DQmNTMARAfu7S2pQxbpK2FG2VAekpXvftUYqdwMwCJgQ33h/image.png)\n\n<h2>Risk Mitigation Tools Are Limited in Crypto</h2>\n\nUnfortunately, call options are not readily available for blockchain assets. There is not yet a provider of these options and options are inherently difficult to trade as well.\n\nSeveral other strategies exist to evade financial risk. Fundamental analysis, delving into a detailed analysis of the cryptocurrency such as revenues, adoption level, governmental models, development strategies etc. might help to find risky investments. However, these markets lack the underlying data required to make such judgements with confidence.\n\nSo, what tools do we have to limit our risk?\n\n<h2>Managed Future or Commodity Trading Advisors at work</h2>\n\nHedge funds have developed a strategy that is only based on the price history of an asset and works similar or sometimes even better than just buying a call option.\n\nThe strategy is called trend-following and is in fact one of the largest strategies in the hedge fund space. Hedge funds using trend-following, also called momentum strategies, have existed for over 50 years and have grown to approximately $320 Billion of assets under management.\n\n<h2>So we wanted to know, could this strategy be applied to bitcoin trading to replicate a call option?</h2>\n\nTrend-following strategies have been shown to have a similar result as call-options. Hurst, Ooi and Pedersen (2013) used a simple price momentum strategy and applied this strategy across asset classes of equities, bonds, fiat currencies and commodities. The strategy proposes to buy an asset, if the return of this asset is positive over the last m days. Hurst, Ooi and Pedersen (2013) suggest to use m between 30 and 360 calendar days.\n\nWe applied this simple momentum strategy to the bitcoin market price and chose m arbitrarily as 60 days. We calculated the 60 day return for each day in the past. If the return was positive, we would assume that we would have bought bitcoins. If the return was zero or negative, we assume that we would have not kept a position in bitcoin.\n\n<h2>The Result?</h2>\n\nHow would this strategy have done since inception of bitcoin? The figure below shows the rolling returns of this strategy for different bitcoin returns.\n\nFor example if the bitcoin market price increased 200% over 60 days, then the momentum strategy made about 200% as well. However, if bitcoin lost 50% in 60 days, then the momentum strategy lost on average only 10%.\n\n![](https://steemitimages.com/DQmaHC59yfZMPUNviXBrbW91gwNVFwiy9Gd72XAX9TzCPnm/image.png)\n\nOur research shows that momentum strategies from financial markets can be applied to bitcoin trading.\nWith this strategy, an investor would have participated in the large upside of bitcoin, but not so much in the drawdowns of bitcoin of more than 90%.\n\nThe strategy returns similar profits if the bitcoin price moves up significantly, but does not lose nearly as much in a down market. In other words, the strategy returned a similar profit as a simple bitcoin investment, but reduced the risk. In statistical terms, the strategy increased the Sharpe ratio by about 50%.\n\n<h2>So What’s the Catch?</h2>\n\nThe investor pays a price for this protection.\n\nFirst, the investor has to watch the bitcoin market on a daily basis and invest his time. Secondly, his risk is not zero if the bitcoin market sells off, but limited to an average of about 10% and sometimes even higher. Thirdly, the investor does not fully participate in bitcoin if the market price reverses quickly. The investor would sell his position in a sell-off, but would only get back into bitcoin after it has retraced from the low.\n\nSeveral extensions to this strategy have been proposed. For example, trading several blockchain assets at the same time would improve the investment performance. The most common approach is weighting these investments according to the volatility of each market (see Hurst, Ooi and Pedersen, 2013).\n\nAlso, several pitfalls of such a strategy are recorded in financial markets and it remains to be seen if these apply to blockchain asset trading as well. Viebig, Kallerhoff and Tschunko (2013) showed that these strategies do not fare well, if the market moves sideways, but with a high volatility. In fact, in this research we excluded the time frame of March/April 2014, where bitcoin showed exactly this type of pattern.\n\nThis analysis is based only on price data. Future work should incorporate other technical data sources such as volumes and order books to analyze the price movements of blockchain assets. Above that other data sources and maybe even new valuation models will be necessary to trade blockchain assets from a fundamental view.\n\n<h2>Conclusion</h2>\n\nThe volatility and higher risk profile of blockchain assets led us to wonder, could we apply a common hedge fund strategy to limit our risk while still participating in most of the upside. We tested a common hedge fund strategy called trend-following to limit our downside risk, but still participate in the upside of cryptocurrencies.\n\nWe applied this strategy to bitcoin as an example and found that this strategy works well. If bitcoin rallied over 200%, this strategy would have returned almost the same. However, if bitcoin sold off 50%, this strategy would have only lost an average of around 10%. This is almost like a call option, where you only participate in the upside of the investment, but on the other hand you have to pay a premium. This premium would be around 10% in our example.\n\nIdeally this strategy is applied on a wide range of different cryptocurrency assets to improve and lower the premium even further. Other strategies to mitigate the risk of investing in cryptocurrencies might be to take a more fundamental approach. However, the detailed and comparable data across cryptocurrencies is not yet available.\n\n<h2>About the Author</h2>\n\nDr. Philipp Kallerhoff is Founder and General Partner at Protos Cryptocurrency Asset Management. He is a senior portfolio manager and data scientist in the fintech and hedge fund industry for over 10 years. He managed hedge funds, most recently under UCITS IV and SICAV SIF at Harcourt Investment Consulting across asset classes and was a co-founder of Jumiya Inc., a big data startup in Silicon Valley. He is an alumnus of Singularity University and holds University degrees in Engineering, Psychology and Physics and PhD in Computational Neuroscience from the Technical University Berlin.\n\nReferences\n\nHurst, Brian, Yao Hua Ooi, and Lasse Heje Pedersen. “Demystifying managed futures.” Journal of Investment Management 11.3 (2013): 42–58.\nViebig, Kallerhoff, Tschunko. “Commodity Trading Advisors (CTAs): When do the money machines fail?.” Corporate Finance 05 (2016): 150–161.",
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