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      "body": "@@ -4083,14 +4083,118 @@\n the \n+%5B\n part-2\n+%5D(https://steemit.com/programming/@omkardash/optimizing-crypto-investments-implementation-using-python)\n  of \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/@OmkarDash/crypto-portfolio-optimization-python-9d38e9ebe6be",
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      "body": "In this post, I will go into the details of a portfolio optimization that yielded 406% returns over a 180 days period, on paper, with a Sharpe ratio of 4.69. The [first post](https://steemit.com/cryptocurrency/@omkardash/maximizing-risk-adjusted-returns-on-crypto-investments) in this series introduces you to the conceptual underpinnings and the context of what I am tried to demonstrate here.\n\nData Acquisition is the obvious first step - I’ve used Coincap.io API for data acquisition purposes. (I have tried CoinMarketCap and CryptoCompare previously, but I find Coincap’s API to be better for acquiring historical data.)\n\n![](https://steemitimages.com/DQmSe4qX9jMr2KFbZC3zmFo7htJDE1hWT4yDByz9CwMESPF/image.png)\n\nI’m focussed on cryptos with large market cap — greater than USD 5 Billion. In the second data acquisition step, I extract historical data (180 days) from another [Coincap API](http://coincap.io/history/180day/), and hold the data in a master dataframe.\n\n![](https://steemitimages.com/DQmRGnmA6gk6gnKQVfXRXAavehB1otCeeEQBe69CtNowtga/image.png)\n\nOnce I have the historical data for the selected coins in a dataframe, the data needs to be cleaned & transformed. Returns and covariance are then calculated.\n\n![](https://steemitimages.com/DQmQyancTwhxdympvjqxTc21RHxFFS8MyFgwm52Anwu6kax/image.png)\n\nAfter the returns & covariance are calculated, I implement the core of MPT to optimize the portfolio.\n\n![](https://steemitimages.com/DQmUx5VZFNsBL1uYnZaQYVKsncnBAwT2nzURyhbyqnpbxMi/image.png)\n\nVisualization of Efficient frontier :\n![](https://steemitimages.com/DQmPKDMcrXSwGainHUK3Np6YepmPVCc7abwGtHGaoWPbdeH/image.png)\n![](https://steemitimages.com/DQmYghA9Nj4xe4WBMDvBshYJZDdkkW1ES9ASWWxvjvKVpRj/image.png)\n\nThe goal of this portfolio optimization technique was to find the portfolio that maximizes return and minimizes volatility, which is measured as Sharpe ratio. The weights of the coins, with highest sharpe ratio is below:\n\n![](https://steemitimages.com/DQmeg1Jacckb9rsDCtckbyFA3JsFwo8US7mrttNgtfD7Kvq/image.png)\n\nIn summary, allocating investments in a manner below is the most optimized portfolio — 406% returns\n\n![](https://steemitimages.com/DQmUi1sRGGckvtkfMtLCG4mzSyaj2c1ManBHNeeBWiyknEE/image.png)\n\n[Assumptions of MPT](http://education.howthemarketworks.com/glossary/modern-portfolio-theory-mpt/)\n\n• Asset returns are normally distributed random variables.\n• Investors attempt to maximize economic market returns.\n• Investors are rational and avoid risk when possible.\n• Investors all have access to the same sources of information for investment decisions.\n• Investors share similar views on expected returns.\n• Taxes and brokerage commissions are not considered.\n• Investors are not large enough players in the market to influence the price.\n• Investors have unlimited access to borrow (and lend) money at the risk-free rate.\n\n**Crypto markets are extremely volatile. Please do your own research & invest at your own risk. All the views expressed in this post are my own and do not represent my current or past employers. The post should not be construed as financial advice.**\n\n[Jupyter Notebook with Python Implementation](https://github.com/omkardash/crypto-portfolio-optimization/blob/master/crypto-portfolio-optimization.ipynb)",
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      "author": "omkardash",
      "body": "That's my post, robot!",
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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/@OmkarDash/crypto-portfolio-optimization-39bc6cb64c7c",
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      "body": "After the hack of Mt.Gox, I had lost interest in Bitcoin & Cryptocurrencies until the spring of 2016 when I got a chance to take a deeper dive into the world of Blockchain and Distributed Ledger Technologies. Fast forward to the present-day, and I’ve worked on some exciting projects using Hyperledger Fabric, Ethereum, and Corda. While I was at it, I happened to stumble upon Coinbase. Trading accounts on exchanges followed rather quickly. Before I understood where this was all going, I was partaking in ICOs & IBOs — it was all moving at a breathtaking pace.\n\n>Veni, Vidi, VC.\n\nI’m a sucker for adrenaline and that’s unmistakably counterproductive for the crypto-trading game. I decided to catch a breather during my vacation in December 2017 and take a fresh look at how the cryptocurrency markets are playing out. \n\nUntil I figured it out, I decided I would just **HODL**.\n\nIn the meanwhile, Robo-advisors had fascinated me sufficiently that I finally found time to explore [Wealthfront](https://wlth.fr/2vs4FyI).\n\nIf you have not checked it out yet, you sure should. You are not very likely to regret it and to sweeten the deal, you will also get your first $15,000K managed for free. (But please DYOR).\n\nAs I saw it, automatic investing using AI was all fine and dandy, but there was a different itch I had to scratch — I had to know more about how all of these worked under the hood. I couldn’t let it be a black box that magically arrives at the best investment strategy for my risk appetite. So, one night, I decided to finally peruse the whitepaper on the Wealthfront investment methodology. I thus got introduced to Markowitz’s Modern Portfolio Theory. One thing led to another, and I ended up implementing MPT (however limited in efficiency it may be) for optimization of a crypto portfolio.\n\nThe idea behind MPT in English is this: \nYou want to invest some of your disposable money in the crypto market, but you know zilch about the state of the crypto markets. Your friend from high school, who has been smoking some funny stuff lately, strongly recommends you buy some ``$BTC``. The nerdiest guy on the block, who has been buying mining racks and shoving it all down in the basement of his mother’s house, strongly believes your best bet is ``$ETH``. And then, there’s the guy who thinks that the Big Brother is watching all of us all the time and even holds back from using Tor due to the fear of the egotistical giraffe thinks you must be buying nothing but ``$XMR`` and ``$XVG``. As if these friends weren’t enough you have listened to experts who feed off of their collective intelligence to predict how Ripple,``$XRP``, is going to create waves in 2018. \n\nWell, that’s too much to process. So, let’s break it down.\n\nThe relationship between risk and return is not something you discovered while sipping your coffee this morning. If you demand higher returns, you must take greater risks. If you know what your goals in terms of returns are, then half the battle is won because all you have to do now is find a way to minimize the risks for that target return. In other words, you want to make enough money to buy that Lambo, but you want to do it in a way that minimizes the chance of making you look like, well, the guy who lost money in the crypto market.\n\nSo, here’s what we do: We select a bunch of coins as potential candidates for investment. By representing the historical RoI of each coin as a random variable, we estimate two parameters — covariance and mean return, for the variable. For a given risk level, our goal is to maximize the return, by selecting the optimal combination of coins. We find that by solving an optimization problem.\n\n![](https://steemitimages.com/DQmQ4KZ72WjtW2GCne4ZfqJiXyGxAzpkt7iFxRsE9kMfKEc/image.png)\n\nThe optimal allocation of investments dollars over 14 large cap crypto-assets (market cap > USD 5B), based on price data from last 180 days gathered from exchanges is below:\n\n\n---\n\nThe plot for finding the efficient frontier:\n![](https://steemitimages.com/DQmfRCY8vSRZNuy8T635tWaGXABAzKZatmDgBprNnc6URYM/image.png)\n\nIn the part-2 of this series, I will get into the details of the implementation.",
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