Category Archives: Trading

Bitcoin Cash Price Technical Analysis – BCH/USD Approaching Short-term Break

Key Points Bitcoin cash price is consolidating above the $320 support area against the US Dollar. There is a short-term contracting triangle forming with resistance near $335 on the hourly chart of BCH/USD (data feed from Kraken). The price might dip once more before moving higher above the $330-340 levels. Bitcoin cash price is moving … Continue reading Bitcoin Cash Price Technical Analysis – BCH/USD Approaching Short-term Break

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Bitcoin Cash Price Technical Analysis – BCH/USD Back To Square One

Key Points Bitcoin cash price declined sharply from $390 and traded towards $300 against the US Dollar. A major bullish trend line with support at $310 prevented declines on the hourly chart of BCH/USD (data feed from Kraken). The price is now back in the bearish zone below the $350 resistance level. Bitcoin cash price … Continue reading Bitcoin Cash Price Technical Analysis – BCH/USD Back To Square One

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AVATRADE: LE OPINIONI E LE RECENSIONI SUL TRADING DI CRIPTOVALUTE

In questa guida parleremo delle Avatrade opinioni e recensioni del trading criptovalute che da sempre ha offerto assieme ad oltre 2000 altri asset e sottostanti.

Avatrade è una piattaforma di trading CFD molto popolare in Europa e oltrettutto è regolamentata e autorizzata a fornire i suoi servizi anche in Italia perchè è registrata CONSOB.

Avatrade Europe LTD è autorizzata dalla Banca di Irlanda in Europa.

Tramite la piattaforma di trading criptovalute di Avatrade puoi operare la compravendita di molte criptovalute.

>> continua a leggere qui i vantaggi di fare trading criptovalute con Avatrade

Originally published at www.lecriptovalute.org.

Bitcoin Cash Price Technical Analysis – BCH/USD Burst Above $350

Key Points Bitcoin cash price surged higher and broke an important resistance at $350 against the US Dollar. This week’s highlighted contracting triangle pattern with resistance at $320 was broken on the hourly chart of BCH/USD (data feed from Kraken). The price is now placed well above the $350 level and eying more gains in … Continue reading Bitcoin Cash Price Technical Analysis – BCH/USD Burst Above $350

The post Bitcoin Cash Price Technical Analysis – BCH/USD Burst Above $350 appeared first on NEWSBTC.

ETH/USD on 18 October 2017

Analysis

  • ETH/USD has been moving in a downward channel but it might be running out of steam
  • Bullish divergence on Stochastic indicator: price moved lower to test $310 but Stoch actually rose up
  • RSI also showed oversold signal twice
  • These indicated that $310 will be a strong support level for ETH/USD

Suggestion

  • The market will probably test $310 again. Look for more bullish signals for a long trade
  • If $310 is penetrated, it will easily fall to $300 or even lower

Want to diversify your cryptocurrency portfolio? Visit our website to learn more! Please also join our telegram chat for daily updates!


ETH/USD on 18 October 2017 was originally published in Cryptomover on Medium, where people are continuing the conversation by highlighting and responding to this story.

24hr Crypto Market Round Up

24hr Crypto Market Round Up

The Top 10 by market Cap in the last 24hrs of trading has seen some interesting developments

Bitcoin (BTC) Rocketed up 7.53% to smash the $5000 mark @ $5178

Trends showed us it was on the cards but was a little faster than most expected.

Ether (ETH) followed suit and passed the $300 dollar mark once again @ $307 up 2.18%

Ripple (XRP) had a wobble with a 1.87% dip to $0.2603784

Bitcoin Cash (BCH) also slipped down 1.57% @ $313.28

LiteCoin (LTC) gained up 2.67% @ $51.90

DASH up a further 1.58% @ $296.82

NEM dropped against the dollar by 2.60% @ $0.212789

NEO lost value down 4.58%$29.44

IOTA down 2.29%@ $0.462828 & Monero up 0.93%@ $88.09

Keep up to date with all things Crypto with our blog @blog.cryptonetix.com/

24hr Crypto Market Round Up

24hr Crypto Market Round Up

The Top 10 by market Cap in the last 24hrs of trading has seen some interesting developments

Bitcoin (BTC) Rocketed up 7.53% to smash the $5000 mark @ $5178

Trends showed us it was on the cards but was a little faster than most expected.

Ether (ETH) followed suit and passed the $300 dollar mark once again @ $307 up 2.18%

Ripple (XRP) had a wobble with a 1.87% dip to $0.2603784

Bitcoin Cash (BCH) also slipped down 1.57% @ $313.28

LiteCoin (LTC) gained up 2.67% @ $51.90

DASH up a further 1.58% @ $296.82

NEM dropped against the dollar by 2.60% @ $0.212789

NEO lost value down 4.58%$29.44

IOTA down 2.29%@ $0.462828 & Monero up 0.93%@ $88.09

Keep up to date with all things Crypto with our blog @blog.cryptonetix.com/

Billionaire Hedge Fund Legend Novogratz: Bitcoin Price En Route to $25,000

Mike Novogratz, the hedge fund legend and former executive at Fortress, have stated in an interview with CNBC that the Bitcoin price is heading towards $25,000. Rise in Demand For Bitcoin From Institutional Investors Novogratz emphasized that the demand for Bitcoin and the cryptocurrency in general from large-scale retail traders and institutional investors is rising … Continue reading Billionaire Hedge Fund Legend Novogratz: Bitcoin Price En Route to $25,000

The post Billionaire Hedge Fund Legend Novogratz: Bitcoin Price En Route to $25,000 appeared first on NEWSBTC.

Cryptocurrency market manipulation. Part 2 — manipulator, crowd, punctures.

First, let’s see who this mythical manipulator is. A manipulator is just a big player who has such a resource (money) that allows him to move the price of an asset to the right side or keep the asset at the right level while making sales/purchases. Everything depends on the market, the liquidity of the asset, its price and quantity.

For example, John issued his coins in the amount of 100 pieces at a price of 1 dollar apiece and brought them to the stock exchange. All coins belong to John, and he and his friends begin to resell them to each other, pushing the price up to 2, 5, 10 dollars. John is a manipulator specifically in this coin, he can move it as he wants and where he wants. The only problem is that nobody needs the coin and John s going out of business.

Bitcoin, Ethereum and other popular coins with a capitalization of tens of billions of dollars are very different story. There in a role of a manipulator can be an investment fund, just a large investor, Vitalik Buterin :), etc., those who have the same tens of billions of dollars. At the same time, it should be noted again that the market of cryptocurrency relative to the world financial markets is insignificant. Large stock markets of stocks and bonds have portfolios that are many times higher than the value of all cryptocurrencies for today and, therefore, if they want they will draw any graph they want to. They will set absolutely any price in absolutely any asset in the cryptocurrency world.

These funds are constantly in the search mode of profit, and we are sure that they have already come to the cryptocurrency market. The main technology of their work is to force the crowd to sell at low prices and buy at high prices. For this they use various techniques and algorithms of psychological impact:

Puncture — a sharp and very strong price movement in any direction, with a rapid subsequent recovery.

A vivid example of such manipulation was the collapse of Ethereum on the GDAX exchange on June 21, 2017, when the price dropped to the level of $ 0.1 per coin. Of course, the exchange said that it was a technical failure, but it’s hard to believe. This exchange provided loans to its participants in the marginal trade, was aware of all the positions of its customers and their level of the debt burden. Firstly the fall of the asset to almost 0 led to the massive margin-call of those who used to trade borrowed funds and, consequently, to automatically sell all their assets, and secondly to the triggering of stop-losses for those who were reinsured from falling prices and again selling all of their assets. This decline was made possible because the large player simply drastically poured into the market a huge number of coins, fulfilling all bids for the purchase. From the side, it may seem that he lost money selling coins of $ 200, $ 100, $ 50, $ 10, but this is far from the case since he bought them back much more and at much lower prices. It is worth noting that in this case only investors from this exchange have been affected, and such a puncture became possible due to the relatively low liquidity of a specific asset specifically on this exchange at a particular time.

The conclusion is that on a thin and relatively illiquid cryptocurrency market don’t work with borrowed funds (don’t use margin), do not place automatic stop-loss, and manage the portfolio manually.

This was an example of purely technical impact for momentary gain. From the psychological point of view, punctures are made to expand the range of the usual, psychologically important, for the crowd prices for the asset. When the crowd no longer believes in the possible growth or drop in prices to some level, manipulator using colossal means (sometimes even at a loss) makes a puncture and shows that the price is possible. After the expansion of the range, as a rule, the crowd begins to move the asset to its specified goal, because it no longer seems unattainable. Imagine that tomorrow you will be shown the price of Ethereum in the area of 600–700 dollars, albeit very briefly, and all news portals will blow about it nonstop. Don’t you want to buy everything for 300 now? :) While the crowd starts to sweep everything on the way to $ 600, a large player will gradually sell out his giant portfolio, fixing profits, and then repeat everything exactly the opposite.

If you have any questions — don’t hesitate to write us at https://t.me/fidcomRu or info@fidcom.net

Join our ICO https://fidcom.net


Cryptocurrency market manipulation. Part 2 — manipulator, crowd, punctures. was originally published in Fidcom on Medium, where people are continuing the conversation by highlighting and responding to this story.

Cryptocurrency market manipulation. Part 2 — manipulator, crowd, punctures.

First, let’s see who this mythical manipulator is. A manipulator is just a big player who has such a resource (money) that allows him to move the price of an asset to the right side or keep the asset at the right level while making sales/purchases. Everything depends on the market, the liquidity of the asset, its price and quantity.

For example, John issued his coins in the amount of 100 pieces at a price of 1 dollar apiece and brought them to the stock exchange. All coins belong to John, and he and his friends begin to resell them to each other, pushing the price up to 2, 5, 10 dollars. John is a manipulator specifically in this coin, he can move it as he wants and where he wants. The only problem is that nobody needs the coin and John s going out of business.

Bitcoin, Ethereum and other popular coins with a capitalization of tens of billions of dollars are very different story. There in a role of a manipulator can be an investment fund, just a large investor, Vitalik Buterin :), etc., those who have the same tens of billions of dollars. At the same time, it should be noted again that the market of cryptocurrency relative to the world financial markets is insignificant. Large stock markets of stocks and bonds have portfolios that are many times higher than the value of all cryptocurrencies for today and, therefore, if they want they will draw any graph they want to. They will set absolutely any price in absolutely any asset in the cryptocurrency world.

These funds are constantly in the search mode of profit, and we are sure that they have already come to the cryptocurrency market. The main technology of their work is to force the crowd to sell at low prices and buy at high prices. For this they use various techniques and algorithms of psychological impact:

Puncture — a sharp and very strong price movement in any direction, with a rapid subsequent recovery.

A vivid example of such manipulation was the collapse of Ethereum on the GDAX exchange on June 21, 2017, when the price dropped to the level of $ 0.1 per coin. Of course, the exchange said that it was a technical failure, but it’s hard to believe. This exchange provided loans to its participants in the marginal trade, was aware of all the positions of its customers and their level of the debt burden. Firstly the fall of the asset to almost 0 led to the massive margin-call of those who used to trade borrowed funds and, consequently, to automatically sell all their assets, and secondly to the triggering of stop-losses for those who were reinsured from falling prices and again selling all of their assets. This decline was made possible because the large player simply drastically poured into the market a huge number of coins, fulfilling all bids for the purchase. From the side, it may seem that he lost money selling coins of $ 200, $ 100, $ 50, $ 10, but this is far from the case since he bought them back much more and at much lower prices. It is worth noting that in this case only investors from this exchange have been affected, and such a puncture became possible due to the relatively low liquidity of a specific asset specifically on this exchange at a particular time.

The conclusion is that on a thin and relatively illiquid cryptocurrency market don’t work with borrowed funds (don’t use margin), do not place automatic stop-loss, and manage the portfolio manually.

This was an example of purely technical impact for momentary gain. From the psychological point of view, punctures are made to expand the range of the usual, psychologically important, for the crowd prices for the asset. When the crowd no longer believes in the possible growth or drop in prices to some level, manipulator using colossal means (sometimes even at a loss) makes a puncture and shows that the price is possible. After the expansion of the range, as a rule, the crowd begins to move the asset to its specified goal, because it no longer seems unattainable. Imagine that tomorrow you will be shown the price of Ethereum in the area of 600–700 dollars, albeit very briefly, and all news portals will blow about it nonstop. Don’t you want to buy everything for 300 now? :) While the crowd starts to sweep everything on the way to $ 600, a large player will gradually sell out his giant portfolio, fixing profits, and then repeat everything exactly the opposite.

If you have any questions — don’t hesitate to write us at https://t.me/fidcomRu or info@fidcom.net

Join our ICO https://fidcom.net


Cryptocurrency market manipulation. Part 2 — manipulator, crowd, punctures. was originally published in Fidcom on Medium, where people are continuing the conversation by highlighting and responding to this story.

Exogenous Crypto Doom Scenarios

This is a short thought experiment on doom scenarios surrounding (the value of) crypto coins. This thought experiment will exclusively focus on exogenous doom scenarios. Endogenous Doom scenarios are thus not included. Examples of endogenous threats are the loss of keys, loss of sufficient backups, death without will and ability of your loved ones to retrieve coins etc (see Pamela Morgan for endogenous risk reduction @pamelawjd) . The thought experiment on exogenous doom scenarios is useful so you are mentally prepared and know what to do when disaster strikes. This prevents you from just standing there with your thumb up your ass. Every doom scenario is briefly described and a few tips are given on how to reduce involved risks. TL;DR tips in bullet points below every doom scenario.

Don’t do it.

Doom scenario #1: Exchange hack, exit scam, etc.

When an exchange is hacked or exit scams, a lot of users are effected. Likely the users end up paying for a hack and/or exit scam. This means you should not have all your coins in one exchange. Also try to split your Exchange Balance across multiple exchanges to minimize impact. Moreover you should transfer a large portion of your coins to a hardware wallet and thus not have them on an exchange anyway. Even when your exchange is not directly involved in a hack or exit scam, you will likely still feel the pain. Prices are likely to drop across the board. Standard Stop Loss (limit!) trading practices should minimize this risk.

· Don’t have all your coins on exchanges, store a large fraction on a hardware wallet. (e.g. ledger

· Spread your Exchange Balance across multiple exchanges to decrease impact.

Doom scenario #2: Instant worldwide ban of crypto exchanges

In this scenario governments across the world ban crypto exchanges and seize all funds. This could be combined with declaring crypto currencies illegal. All funds on exchanges are lost and prices plummet across the board. Crypto trading will likely instantly move to darknet exchanges and platforms like localbitcoins* (https://localbitcoins.com/?ch=gg93). In this scenario you lose everything you had on crypto exchanges. Because of the global ban and difficulty trading coins stored elsewhere, prices will likely plummet. Be prepared for heavy losses on the value of your coins stored in hardware wallets due to falling prices. No exchange hedge can currently protect you against this since they will also be affected (business case for doom scenarios insurance contracts!). Make sure to choose coins with the greatest liquidity and belief system behind them when you store keys on a hardware wallet. These coins are likely to retain more of their value than the long tail of crypto during a similar scenario (credit @twobitidiot).

· Don’t have all your money on an exchange

· Make sure to store coins with the greatest liquidity and belief system on a hardware wallet. e.g: Leder Wallet*.

Doom scenario #3: Flash crash or general market crash

An exchange flash crash can cause you to get terrible execution from a Stop Loss market order. This risk can be limited by setting a Stop Loss Limit order. If you margin trade a position, this will possibly not save you due to position liquidation. Make sure to trade on exchanges with the biggest market depth. Also make sure to not use too high a margin to decrease the chances of getting liquidated. When a general market crash occurs, your hardware wallet stored coins’ value suffers. To limit your losses you could hedge your position (i.e. open a short position equivalent to the value of your hardware wallet coins) .

· Trade on exchanges with biggest market depth

· Don’t trade on (high) margin.

· Hedge your hardware wallet balance with a short position; e.g. a futures contract short*.

Doom scenario #4: Global power outage due to solar flares, total nuclear destruction, etc.

Pack your sh*t, including your hardware wallet(s) plus survival kit and keep yourself and your loved ones safe. Seriously, there are bigger things to worry about right now.

“RUN! I’ll stop them with my hardware wallet”

Twitter: @JroenvdH

*Affiliate links, tips are not build around them! Sign up via another buddy for all I care.

What happened last week?

What happened last week? Steal Your Bitcoins Through Google Ads, Goldman Sachs & BTC, Disney Built a Blockchain

Bitcoiners beware — Google is allowing malicious “phishing” sites to create ads that appear right there in your search results. If you’re a newcomer to Bitcoin, or don’t carefully check the URLs of every site you visit, you could lose your money.

The Chinese government will likely resume cryptocurrency trading in the upcoming months with necessary Know Your Customer (KYC) and Anti-Money Laundering (AML) systems in place. Earlier this week, Xinhua, the state-owned news publication of China, revealed that the Chinese government is concerned with criminal activities surrounding cryptocurrencies such as bitcoin.

Taiwan Follows Bitcoin-Friendly Japan, Avoids China & Korea ICO Bans. Taiwan will not regulate against initial coin offerings (ICOs) and cryptocurrencies like bitcoin and will avoid the hardline stance taken by the likes of China and South Korea. In significant news today, Taiwan’s Financial Supervisory Commission chairman Wellington Koo has told a joint session of the parliament and the cabinet today that Taiwan will not follow the paths of China and South Korea in an outright ban on crypto-related activity.

Malware That Hijacks Your Computer to Mine Cryptocurrency Is Swarming Across the Internet. Last month, visitors of BitTorrent search engine/piracy website The Pirate Bay noticed their central processing unit (CPU) usage spike. An increasing number of websites are turning the computers of unsuspecting visitors into cryptocurrency miners. Aside from slowing down CPU performance, these tools violate the privacy of users.

Bitcoin.org has threatened to publicly denounce companies that support SegWit2x and have not committed to treating the competing blockchains as separate cryptocurrencies in the event of a chain split. On Thursday, Bitcoin.org published a blog post revealing that it will publicly denounce supporters of the controversial SegWit2x hard fork on October 11.

Goldman Sachs to Start Trading Bitcoin Directly. According to the Wall Street Journal, Goldman Sachs is debating a new trading platform that would be in the business of selling and buying bitcoin, and possibly other digital currencies. If Goldman Sachs follows through with their plans, then they would be the first major Wall Street firm to deal with bitcoin directly.

South Korean authorities have confirmed that hackers from North Korea targeted bitcoin exchanges in the country in multiple attempts to steal the cryptocurrency.The Republic of Korea’s National Police Agency (NPA) has published details of its investigation surrounding several claims of cybersecurity incidents involving hackers from North Korea.

Dragonchain? Disney Built a Blockchain — Can It Compete With Ethereum? From animatronics to digital animation, the Walt Disney Company has long been a pioneer in emerging technology. And blockchain technology is no exception.In 2014, Disney’s tech-focused Seattle office started building what’s now known as Dragonchain, a blockchain protocol designed to allow for more data privacy than is possible on other enterprise-oriented blockchains like Ethereum.

Do you have some feedback for us? Leave us your comment below or you can write on our Twitter or Facebook page.

Do not forget to join our new next generation Bitcoin trading platform NakamotoX now and win awesome prizes. More on: https://nakamotox.com/

What happened last week?

What happened last week? Steal Your Bitcoins Through Google Ads, Goldman Sachs & BTC, Disney Built a Blockchain

Bitcoiners beware — Google is allowing malicious “phishing” sites to create ads that appear right there in your search results. If you’re a newcomer to Bitcoin, or don’t carefully check the URLs of every site you visit, you could lose your money.

The Chinese government will likely resume cryptocurrency trading in the upcoming months with necessary Know Your Customer (KYC) and Anti-Money Laundering (AML) systems in place. Earlier this week, Xinhua, the state-owned news publication of China, revealed that the Chinese government is concerned with criminal activities surrounding cryptocurrencies such as bitcoin.

Taiwan Follows Bitcoin-Friendly Japan, Avoids China & Korea ICO Bans. Taiwan will not regulate against initial coin offerings (ICOs) and cryptocurrencies like bitcoin and will avoid the hardline stance taken by the likes of China and South Korea. In significant news today, Taiwan’s Financial Supervisory Commission chairman Wellington Koo has told a joint session of the parliament and the cabinet today that Taiwan will not follow the paths of China and South Korea in an outright ban on crypto-related activity.

Malware That Hijacks Your Computer to Mine Cryptocurrency Is Swarming Across the Internet. Last month, visitors of BitTorrent search engine/piracy website The Pirate Bay noticed their central processing unit (CPU) usage spike. An increasing number of websites are turning the computers of unsuspecting visitors into cryptocurrency miners. Aside from slowing down CPU performance, these tools violate the privacy of users.

Bitcoin.org has threatened to publicly denounce companies that support SegWit2x and have not committed to treating the competing blockchains as separate cryptocurrencies in the event of a chain split. On Thursday, Bitcoin.org published a blog post revealing that it will publicly denounce supporters of the controversial SegWit2x hard fork on October 11.

Goldman Sachs to Start Trading Bitcoin Directly. According to the Wall Street Journal, Goldman Sachs is debating a new trading platform that would be in the business of selling and buying bitcoin, and possibly other digital currencies. If Goldman Sachs follows through with their plans, then they would be the first major Wall Street firm to deal with bitcoin directly.

South Korean authorities have confirmed that hackers from North Korea targeted bitcoin exchanges in the country in multiple attempts to steal the cryptocurrency.The Republic of Korea’s National Police Agency (NPA) has published details of its investigation surrounding several claims of cybersecurity incidents involving hackers from North Korea.

Dragonchain? Disney Built a Blockchain — Can It Compete With Ethereum? From animatronics to digital animation, the Walt Disney Company has long been a pioneer in emerging technology. And blockchain technology is no exception.In 2014, Disney’s tech-focused Seattle office started building what’s now known as Dragonchain, a blockchain protocol designed to allow for more data privacy than is possible on other enterprise-oriented blockchains like Ethereum.

Do you have some feedback for us? Leave us your comment below or you can write on our Twitter or Facebook page.

Do not forget to join our new next generation Bitcoin trading platform NakamotoX now and win awesome prizes. More on: https://nakamotox.com/

Stochastic Optimal Control and Optimization of Trading Algorithms

Although quant funds are quite common these days, for most people they’re still “black boxes” that do some “advanced math” or “machine learning” or even “artificial intelligence” inside. In one of our previous articles, we have shown our trading system (you can read it here: ) In one of the future articles we may show how we build and test our predictive, or “alpha” models (yes, that includes advanced statistics and machine learning techniques). In this article, we’ll show you how we can optimize execution of trading algorithms and what kind of optimization tasks arise. There will be some advanced math, but we’ll try to keep it simple in the beginning and move to more advanced models.

Dynamic Programming Principle and the Hamilton-Jacobi-Bellman (HJB) equation

Let’s assume we have a plane(or a rocket) flying from point A to point B, but as there’s lots of turbulence on the way, it can’t move in a straight line, as it’s constantly tossed in random directions. Control systems have to adjust trajectory (“control policy”) all the time, and since the amount of fuel is limited, it has to be done in an optimal way. The dynamic programming method breaks this decision problem into smaller subproblems. Richard Bellman’s principle of optimality describes how to do this:

An optimal policy has the property that whatever the initial state and initial decision are, the remaining decisions must constitute an optimal policy with regard to the state resulting from the first decision.

Basically, that means that part of the optimal trajectory is also an optimal trajectory: if the bold line between C and D wasn’t an optimal trajectory, we should’ve substituted it with some other (dashed) line. That is why such problems are usually solved backwards in time: if we’re at some (random) point C’ near C, we know how to get to C, and so on.

Mathematically, the problem could be formulated like this:

we need to minimize the value function:

over the time period [0,T], where C[ ] is the scalar cost rate function and D[ ] is a function that gives the economic value or utility at the final state, x(t) is the system state vector,x(0) is assumed given, and u(t) for 0≤tT is the control vector that we are trying to find.

The system must also be subject to terminal condition:

In general, the goal of stochastic control problems is to maximize(minimize) some expected profit(cost) function by choosing an optimal strategy which itself affects the dynamics of the underlying stochastic system. Let’s have a look at some classic toy problems:

-The Merton Problem

The agent is trying to maximize the expected utility of future wealth by trading a risky asset and a risk-free bank account. The agent’s actions affect her wealth, but at the same time, the random dynamics in traded asset modulate agent’s wealth in a stochastic manner. Or more strictly, agent is trying to maximize expectation of U(X), where X — agent’s wealth — is modeled as:

where W is a Brownian motion, used to model price of a risky asset:

where π is a self-financing trading strategy, μ is expected compounded rate of growth of the traded asset and r is compounded rate of return of the risk-free bank account.

-The Optimal Liquidation Problem

Suppose that our alpha model signals us that it’s profitable to liquidate a large number N of coins at price St and we wish to do so by the end of the day at time T. Realistically, market does not have infinite liquidity, so it can’t absorb a large sell order at the best available price, which means we will walk the order book or even move the market and execute an order at a lower price (subject to market impact denoted as ‘h’ below). Hence, we should spread this out over time, and solve a stochastic control problem. We may also have a sense of urgency, represented by penalising utility function for holding non-zero invenotry throughout the strategy. Let νt denote the rate at which agent sells her coins at time t. Agent’s value function will look like:

where dQ=-νtdt — agent’s inventory, dS — coin price (as in Merton’s problem above), S’t=St-h(νt) — execution price and dX=νtS’tdt — agent’s cash.

-The Optimal Entry-Exit Problem for Statistical Arbitrage

Suppose we have two co-integrated assets A and B (or, in trivial case, one asset on different exchanges) and have a long-short portfolio which is linear combination of these two assets. Optimal strategy should determine when to enter and exit such a portfolio and we can pose this problem as an optimal stopping problem. We can model the dynamics of the εt, co-integration factor of these assets, as

where W is a standard Brownian motiom, κ is a rate of mean-reversion, θ is the level that the process mean-reverts to and σ is the volatility of the process. The agent’s performance, for example, for exiting the long position can be written as

where c is the transaction cost for selling the portfolio, ρ represents urgency, usually given by the cost of margin trade and E[ ] denotes expectation conditional on εt= ε.

The value function will seek for the optimal stopping time when unwinding the position (long portfolio) maximizes the performance criteria. Alternatively, we can find performance criteria for entering long position, and finally, criteria for entering and exiting short positions.

There are, of course, many more optimal stochastic control problems in trading and almost any execution algorithm can be optimised using similar principles. Performance of two algorithms based on exact same signals may vary greatly, which is why it is not enough to have just a good “alpha” model that generates accurate predictions.

As a group of “quants” with academic background in Numerical Methods, Computational Mathematics, Game Theory and hands-on experience in High Frequency Trading and Machine Learning, our interest was in exploring opportunities in cryptocurrency markets, with the goal of exploiting various market inefficiencies to generate steady absolute returns (not correlated with market movements) with low volatility, or simply put, steady profit without major drawdowns. For more information please visit http://www.TensorBox.com and if you like what we do you can participate in our Initial Token Offering.

Stochastic Optimal Control and Optimization of Trading Algorithms

Although quant funds are quite common these days, for most people they’re still “black boxes” that do some “advanced math” or “machine learning” or even “artificial intelligence” inside. In one of our previous articles, we have shown our trading system (you can read it here: ) In one of the future articles we may show how we build and test our predictive, or “alpha” models (yes, that includes advanced statistics and machine learning techniques). In this article, we’ll show you how we can optimize execution of trading algorithms and what kind of optimization tasks arise. There will be some advanced math, but we’ll try to keep it simple in the beginning and move to more advanced models.

Dynamic Programming Principle and the Hamilton-Jacobi-Bellman (HJB) equation

Let’s assume we have a plane(or a rocket) flying from point A to point B, but as there’s lots of turbulence on the way, it can’t move in a straight line, as it’s constantly tossed in random directions. Control systems have to adjust trajectory (“control policy”) all the time, and since the amount of fuel is limited, it has to be done in an optimal way. The dynamic programming method breaks this decision problem into smaller subproblems. Richard Bellman’s principle of optimality describes how to do this:

An optimal policy has the property that whatever the initial state and initial decision are, the remaining decisions must constitute an optimal policy with regard to the state resulting from the first decision.

Basically, that means that part of the optimal trajectory is also an optimal trajectory: if the bold line between C and D wasn’t an optimal trajectory, we should’ve substituted it with some other (dashed) line. That is why such problems are usually solved backwards in time: if we’re at some (random) point C’ near C, we know how to get to C, and so on.

Mathematically, the problem could be formulated like this:

we need to minimize the value function:

over the time period [0,T], where C[ ] is the scalar cost rate function and D[ ] is a function that gives the economic value or utility at the final state, x(t) is the system state vector,x(0) is assumed given, and u(t) for 0≤tT is the control vector that we are trying to find.

The system must also be subject to terminal condition:

In general, the goal of stochastic control problems is to maximize(minimize) some expected profit(cost) function by choosing an optimal strategy which itself affects the dynamics of the underlying stochastic system. Let’s have a look at some classic toy problems:

-The Merton Problem

The agent is trying to maximize the expected utility of future wealth by trading a risky asset and a risk-free bank account. The agent’s actions affect her wealth, but at the same time, the random dynamics in traded asset modulate agent’s wealth in a stochastic manner. Or more strictly, agent is trying to maximize expectation of U(X), where X — agent’s wealth — is modeled as:

where W is a Brownian motion, used to model price of a risky asset:

where π is a self-financing trading strategy, μ is expected compounded rate of growth of the traded asset and r is compounded rate of return of the risk-free bank account.

-The Optimal Liquidation Problem

Suppose that our alpha model signals us that it’s profitable to liquidate a large number N of coins at price St and we wish to do so by the end of the day at time T. Realistically, market does not have infinite liquidity, so it can’t absorb a large sell order at the best available price, which means we will walk the order book or even move the market and execute an order at a lower price (subject to market impact denoted as ‘h’ below). Hence, we should spread this out over time, and solve a stochastic control problem. We may also have a sense of urgency, represented by penalising utility function for holding non-zero invenotry throughout the strategy. Let νt denote the rate at which agent sells her coins at time t. Agent’s value function will look like:

where dQ=-νtdt — agent’s inventory, dS — coin price (as in Merton’s problem above), S’t=St-h(νt) — execution price and dX=νtS’tdt — agent’s cash.

-The Optimal Entry-Exit Problem for Statistical Arbitrage

Suppose we have two co-integrated assets A and B (or, in trivial case, one asset on different exchanges) and have a long-short portfolio which is linear combination of these two assets. Optimal strategy should determine when to enter and exit such a portfolio and we can pose this problem as an optimal stopping problem. We can model the dynamics of the εt, co-integration factor of these assets, as

where W is a standard Brownian motiom, κ is a rate of mean-reversion, θ is the level that the process mean-reverts to and σ is the volatility of the process. The agent’s performance, for example, for exiting the long position can be written as

where c is the transaction cost for selling the portfolio, ρ represents urgency, usually given by the cost of margin trade and E[ ] denotes expectation conditional on εt= ε.

The value function will seek for the optimal stopping time when unwinding the position (long portfolio) maximizes the performance criteria. Alternatively, we can find performance criteria for entering long position, and finally, criteria for entering and exiting short positions.

There are, of course, many more optimal stochastic control problems in trading and almost any execution algorithm can be optimised using similar principles. Performance of two algorithms based on exact same signals may vary greatly, which is why it is not enough to have just a good “alpha” model that generates accurate predictions.

As a group of “quants” with academic background in Numerical Methods, Computational Mathematics, Game Theory and hands-on experience in High Frequency Trading and Machine Learning, our interest was in exploring opportunities in cryptocurrency markets, with the goal of exploiting various market inefficiencies to generate steady absolute returns (not correlated with market movements) with low volatility, or simply put, steady profit without major drawdowns. For more information please visit http://www.TensorBox.com and if you like what we do you can participate in our Initial Token Offering.

Bitcoin Price Weekly Analysis – BTC/USD To Surpass $4600

Key Points Bitcoin price is back in the bullish zone and might soon break the $4600 level against the US Dollar. There is a crucial contracting triangle pattern forming with support at $4320 on the 4-hours chart of BTC/USD (data feed from SimpleFX). The pair might continue to move higher and remains a buy on … Continue reading Bitcoin Price Weekly Analysis – BTC/USD To Surpass $4600

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Covesting, Copy-trading Platform announces PreICO. Talented Traders Wanted!

Every successful trader comes to a point where he feels confident to manage client’s money. Crypto currency traders are not an exception. Setting up an infrastructure for accepting investments, registering a fund and building necessary relationships with exchanges could be time and money consuming. It takes hard work, costs and many years of effort to … Continue reading Covesting, Copy-trading Platform announces PreICO. Talented Traders Wanted!

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Bitcoin Cash Targeting Below $350: BCH Price Analysis

Bitcoin Cash price is finding no edge to grab on while the price continues to decline as this is written. Despite its very promising start when it launched which showed a very solid value surging, the price now is acting totally in contrary as what holders were hoping. For quite some time BCH price against the US Dollar was hovering between the major levels of $400.00 and $600.00 before and after...

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Ripple Price Technical Analysis – XRP/USD Breaks Key Resistance

Key Highlights Ripple price surged higher and broke a major resistance near $0.2150 against the US Dollar. There are two connecting bullish trend lines forming with support at $0.2100 and $0.2010 on the hourly chart of the XRP/USD pair (data source from Kraken). The price might continue to gain pace and it could even break … Continue reading Ripple Price Technical Analysis – XRP/USD Breaks Key Resistance

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Ethereum Price Technical Analysis – ETH/USD Remains Range Bound

Key Highlights ETH price is trading in a range with resistance near the $302-304 levels against the US Dollar. There is a key bullish trend line forming with support at $297 on the hourly chart of ETH/USD (data feed via SimpleFX). The price is now above $295 and the 100 hourly simple moving average, which … Continue reading Ethereum Price Technical Analysis – ETH/USD Remains Range Bound

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Analysis of Request Network

Most of the hyped blockchain related projects have big names in their team or advisory board. Request network is an outsider on this aspect: a small and young team for a seemingly nice and promising project. Let’s see what they got under the hood and if you should FLIP or HODL in October.

What is Request Network

Request is meant to be a decentralized system that enables quick and secure online payments, invoicing and accounting. You can think of it as a fully featured online payment solution that bridges multiple blockchains to allow traditional online commerce to be easily made with cryptocurrencies.

So it is not limited to a bunch of tools for e-commerce. To ensure that the transactions are not only technically but also commercially secure for all the parties (i.e. to exclude scams from the network), they propose what they call smart audits. The smart audit feature is using the benefits of a transparent and immutable blockchain to store commercial data. This data can be used by anyone wanting to act as an audit node. This way, the whole Request network can keep its commercial integrity by decentralizing commercial trust. In the yellow paper, the financial auditing is summarized to those three objectives:

  • Ensure adequate procedures are in place to achieve optimized results (internal management)
  • Verify that the company is in compliance with the competent authorities
  • Protect commercial players from the risk of fraudulent practices

In a few words, Request can be compared to a decentralized and transparent Paypal, or even credit card network, that would propose efficient B2C and B2B commercial exchange protocols.

How it works

So, the concept of Request is already very appealing regarding what it will allow on the accounting part. Companies or projects can decide what they want to share on the network and it’s already fair at this stage because they can hardly lie about it (blockchain motherfuckers). You can add to this that they’ll have to face competing audit nodes as well as the Request proprietary reputation system, which creates a safe ecosystem for buyers and sellers without having to rely on a centralized entity that imposes its own rules while getting all the fees.

Now that we are on it, let’s talk about the money. Decentralized incentivization is the other very interesting part of Request. First, you need to know that the Request network will be composed of 3 layers:

  • The Core layer is basically the blockchain and the main Request smart contracts.
  • The Extensions layer is the open layer on which developers will be able to implant payment modules like billing or invoicing systems.
  • The Applications layer is the off-chain layer. This layer serves to bridge existing or new systems with the Request network.

As it is a fully decentralized system, every type of participant will be able to get a remuneration based on the provided service. For example, if you develop an extension, you will be remunerated by the fees that are linked to the use of the extension (more on this below). You could specialize in auditing and set your prices relatively to how serious is your activity. The reputation system is also something that will affect a company’s finances. The whitepaper says that “members of the network with the best reputation will be able to receive cost reductions or access to custom extensions”.

The most interesting part of this is probably how the fees work on the core and extensions levels. To incentivize holders, fees are divided like this: “Each time a charge is applied, it is allocated between the REQ token holders (70%) and the extension developer (30%)”. This system is further described in the whitepaper like this: “Since the security of the network is paramount, the 30% returned to the creator of the extension will be shared with the bug hunters at a rate of 5% to 10% per security flaw. The reason why the REQ token holders are the most interested in this model is that the extensions developers won’t have to market their extensions, but the community will have an interest in making the extensions known in this ecosystem”.

This is a great idea that not only allows interest rates for token holders, as if you had a savings account in a traditional bank, but also invites holders to actually do something to justify those interests. The only downside of that seemingly brilliant idea is that they don’t explain how they are linking developers work to token holders, or, put in other words, how the network will discern “active” and “lazy” holders (I mean, I hope it will in some way).

Another thing about how Request is intended to work, and which looks very promising, is that it is not advertised as a system built from scratch to revolutionize the whole financial world alone. Request is a “brick” that will be built to function with other already functional “bricks”. There are three announced partnerships. Civic system will be used as a secure and efficient identity plugin to enhance “Reputation, Accounting, Audit and Trust from the payer”. Aragon will be used for its governance protocol and 0x will be the cross-currency settlement brick. Unfortunately, the whitepaper doesn’t tell us yet what connection Request has with each respective team. Is that brick system just an idea or are they cooperating in some way? Impossible to say.

ICO characteristics

Start October 13

End October 17

Total supply 1 000 000 000 REQ tokens

Conversion rate 1 ETH = 5 000 REQ

Soft cap / Hard cap 100 000 ETH D

istribution 50% investors — 20% early investors — 15% development — 15% team.

Use of funds 55% developement — 15% research — 15% marketing — 10% operations — 5% legal.

To summarize, they are seeking for 30 million $USD for 50 % of the tokens, which is ok for that kind of project. In a recent blog post, they said that the REQ tokens are going to be released 1 week after the beginning of the crowdsale, which is a very good news for flippers.

Team

I would say that the team composition is ok while not being a big asset for a project of this size. They seem to be skilled individuals and it is good to know that they already worked together, because they actually all come from another project called Moneytis. Since Moneytis is a working product in the financial domain, we can say that they all have a relevant experience. The downside of this is that the team seriously lacks diversity (same schools, same professional experience) and that they may suffer from being very new to the game (Moneytis started in 2014 and Request in 2017).

They also maybe lack blockchain related expertise but we are pretty confident about their ability to get the things right on this matter when they will be funded. Finally, only one advisor (a good one, though) is a bit uncanny. More advisors from financial, accounting or banking industry would have been better, especially with this young team profile.

Roadmap

Let’s distinct two roadmaps here. There is the project roadmap and the ICO roadmap. The project roadmap is pretty clear and it is cool to see that the first working product is expected to be released as soon as Q4 2017. Note that some code is already available on Github (see Useful links section below). The development should take place and even end during 2018, since the last step is said to be achieved during Q4 2018. This sounds awesome but seems to be also slightly too optimistic.

Now the ICO roadmap. As we are writing those lines, the whitelist period initially planned from 13rd to 30th of September has been shortened due to the massive amount of registrations they received. However, you can still subscribe to the waiting list here. You still have a chance because many participants may not pass the next step. During the October 2–7 period, it will be the registration phase. The registration phase is a KYC (Know Your Customer) process so 1 whitelist address = 1 Ethereum address = 1 real person. We can read the following in one of their blog posts: “Details we will need: passport, selfie with passport, one ethereum wallet address, full name, birth date, and nationality”.

After that, the final step will be the ICO itself during the October 13–17 period. It will last 4 days and the amount you can send will be limited so each participant has the same opportunity. The formula is “individual cap = total public cap / number of approved registrants”.

Interview with the Co-Founder & CFO

FlipHodl — Can you develop on your distribution model regarding fees? In the whitepaper you say “Each time a charge is applied, it is allocated between the REQ token holders (70%) and the extension developer (30%)”. You later say that you do this because “the community will have an interest in making the extensions known in this ecosystem”. Will promoting holders win the same than “lazy” holders? How do you know who promoted what?

Christophe Lassuyt — There is no “promoter” status but the community will have an interest in the fact that the network is used.

You all come from Moneytis, which is a quite recent project (started in 2014). You all started to work on the Request project this year (2017). How will you address the challenges posed by a market largely controlled by financial and state monopolies as a young team?

Mark Z, Strip founders and Vitalik Buterin are young too. We don’t think the age is a good criteria.

Can you explain more in detail your relation with 0x and Aragon? Are your teams in contact with each other and, if yes, what is the nature of your relationship/partnership as of today?

We are in touch with 0x, the0cean and radar relay for our inter-currencies feature. The interest of the blockchain world is that you can work with a project without needing an agreement.

Our advice

So the idea of Request is good and the whole thing is nicely presented. The concepts are well described in the various documents, which shows that we face a competent team not only in the financial domain but also in the marketing and community management ones. We express some reservations on the technical and business aspects though. It is indeed a very complex project and we think that they are a bit optimistic if they think that they’ll be able to provide a final working product by the end of 2018 with no real connection or advisory board in the financial domain.

Partnerships with 0x, Aragon and Civic should be a strength, but it’s hard to determine their level of implication on that matter. We didn’t really saw any endorsement from those teams, which is a bit worrisome. Actually, the word stuffing is a bit obvious in the whitepaper, there are big names and concepts everywhere but no key partnership announced and no key player supporting the project yet.

We think it is a very good FLIPPING opportunity, so we’ll give an 8 because the hype is very good, the parameters of the ICO are decent, there is not a lot of big or similar ICOs in October and the Request team seems to manage their project quite seriously. We are a little more reserved on the HODL side and we’ll limit our mark to 6 because, despite the nice ideas they bring to us today, we think the team has yet to prove that they can handle such a challenge.

Was this article useful to you? Consider tipping us!

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Analysis of Request Network

Most of the hyped blockchain related projects have big names in their team or advisory board. Request network is an outsider on this aspect: a small and young team for a seemingly nice and promising project. Let’s see what they got under the hood and if you should FLIP or HODL in October.

What is Request Network

Request is meant to be a decentralized system that enables quick and secure online payments, invoicing and accounting. You can think of it as a fully featured online payment solution that bridges multiple blockchains to allow traditional online commerce to be easily made with cryptocurrencies.

So it is not limited to a bunch of tools for e-commerce. To ensure that the transactions are not only technically but also commercially secure for all the parties (i.e. to exclude scams from the network), they propose what they call smart audits. The smart audit feature is using the benefits of a transparent and immutable blockchain to store commercial data. This data can be used by anyone wanting to act as an audit node. This way, the whole Request network can keep its commercial integrity by decentralizing commercial trust. In the yellow paper, the financial auditing is summarized to those three objectives:

  • Ensure adequate procedures are in place to achieve optimized results (internal management)
  • Verify that the company is in compliance with the competent authorities
  • Protect commercial players from the risk of fraudulent practices

In a few words, Request can be compared to a decentralized and transparent Paypal, or even credit card network, that would propose efficient B2C and B2B commercial exchange protocols.

How it works

So, the concept of Request is already very appealing regarding what it will allow on the accounting part. Companies or projects can decide what they want to share on the network and it’s already fair at this stage because they can hardly lie about it (blockchain motherfuckers). You can add to this that they’ll have to face competing audit nodes as well as the Request proprietary reputation system, which creates a safe ecosystem for buyers and sellers without having to rely on a centralized entity that imposes its own rules while getting all the fees.

Now that we are on it, let’s talk about the money. Decentralized incentivization is the other very interesting part of Request. First, you need to know that the Request network will be composed of 3 layers:

  • The Core layer is basically the blockchain and the main Request smart contracts.
  • The Extensions layer is the open layer on which developers will be able to implant payment modules like billing or invoicing systems.
  • The Applications layer is the off-chain layer. This layer serves to bridge existing or new systems with the Request network.

As it is a fully decentralized system, every type of participant will be able to get a remuneration based on the provided service. For example, if you develop an extension, you will be remunerated by the fees that are linked to the use of the extension (more on this below). You could specialize in auditing and set your prices relatively to how serious is your activity. The reputation system is also something that will affect a company’s finances. The whitepaper says that “members of the network with the best reputation will be able to receive cost reductions or access to custom extensions”.

The most interesting part of this is probably how the fees work on the core and extensions levels. To incentivize holders, fees are divided like this: “Each time a charge is applied, it is allocated between the REQ token holders (70%) and the extension developer (30%)”. This system is further described in the whitepaper like this: “Since the security of the network is paramount, the 30% returned to the creator of the extension will be shared with the bug hunters at a rate of 5% to 10% per security flaw. The reason why the REQ token holders are the most interested in this model is that the extensions developers won’t have to market their extensions, but the community will have an interest in making the extensions known in this ecosystem”.

This is a great idea that not only allows interest rates for token holders, as if you had a savings account in a traditional bank, but also invites holders to actually do something to justify those interests. The only downside of that seemingly brilliant idea is that they don’t explain how they are linking developers work to token holders, or, put in other words, how the network will discern “active” and “lazy” holders (I mean, I hope it will in some way).

Another thing about how Request is intended to work, and which looks very promising, is that it is not advertised as a system built from scratch to revolutionize the whole financial world alone. Request is a “brick” that will be built to function with other already functional “bricks”. There are three announced partnerships. Civic system will be used as a secure and efficient identity plugin to enhance “Reputation, Accounting, Audit and Trust from the payer”. Aragon will be used for its governance protocol and 0x will be the cross-currency settlement brick. Unfortunately, the whitepaper doesn’t tell us yet what connection Request has with each respective team. Is that brick system just an idea or are they cooperating in some way? Impossible to say.

ICO characteristics

Start October 13

End October 17

Total supply 1 000 000 000 REQ tokens

Conversion rate 1 ETH = 5 000 REQ

Soft cap / Hard cap 100 000 ETH D

istribution 50% investors — 20% early investors — 15% development — 15% team.

Use of funds 55% developement — 15% research — 15% marketing — 10% operations — 5% legal.

To summarize, they are seeking for 30 million $USD for 50 % of the tokens, which is ok for that kind of project. In a recent blog post, they said that the REQ tokens are going to be released 1 week after the beginning of the crowdsale, which is a very good news for flippers.

Team

I would say that the team composition is ok while not being a big asset for a project of this size. They seem to be skilled individuals and it is good to know that they already worked together, because they actually all come from another project called Moneytis. Since Moneytis is a working product in the financial domain, we can say that they all have a relevant experience. The downside of this is that the team seriously lacks diversity (same schools, same professional experience) and that they may suffer from being very new to the game (Moneytis started in 2014 and Request in 2017).

They also maybe lack blockchain related expertise but we are pretty confident about their ability to get the things right on this matter when they will be funded. Finally, only one advisor (a good one, though) is a bit uncanny. More advisors from financial, accounting or banking industry would have been better, especially with this young team profile.

Roadmap

Let’s distinct two roadmaps here. There is the project roadmap and the ICO roadmap. The project roadmap is pretty clear and it is cool to see that the first working product is expected to be released as soon as Q4 2017. Note that some code is already available on Github (see Useful links section below). The development should take place and even end during 2018, since the last step is said to be achieved during Q4 2018. This sounds awesome but seems to be also slightly too optimistic.

Now the ICO roadmap. As we are writing those lines, the whitelist period initially planned from 13rd to 30th of September has been shortened due to the massive amount of registrations they received. However, you can still subscribe to the waiting list here. You still have a chance because many participants may not pass the next step. During the October 2–7 period, it will be the registration phase. The registration phase is a KYC (Know Your Customer) process so 1 whitelist address = 1 Ethereum address = 1 real person. We can read the following in one of their blog posts: “Details we will need: passport, selfie with passport, one ethereum wallet address, full name, birth date, and nationality”.

After that, the final step will be the ICO itself during the October 13–17 period. It will last 4 days and the amount you can send will be limited so each participant has the same opportunity. The formula is “individual cap = total public cap / number of approved registrants”.

Interview with the Co-Founder & CFO

FlipHodl — Can you develop on your distribution model regarding fees? In the whitepaper you say “Each time a charge is applied, it is allocated between the REQ token holders (70%) and the extension developer (30%)”. You later say that you do this because “the community will have an interest in making the extensions known in this ecosystem”. Will promoting holders win the same than “lazy” holders? How do you know who promoted what?

Christophe Lassuyt — There is no “promoter” status but the community will have an interest in the fact that the network is used.

You all come from Moneytis, which is a quite recent project (started in 2014). You all started to work on the Request project this year (2017). How will you address the challenges posed by a market largely controlled by financial and state monopolies as a young team?

Mark Z, Strip founders and Vitalik Buterin are young too. We don’t think the age is a good criteria.

Can you explain more in detail your relation with 0x and Aragon? Are your teams in contact with each other and, if yes, what is the nature of your relationship/partnership as of today?

We are in touch with 0x, the0cean and radar relay for our inter-currencies feature. The interest of the blockchain world is that you can work with a project without needing an agreement.

Our advice

So the idea of Request is good and the whole thing is nicely presented. The concepts are well described in the various documents, which shows that we face a competent team not only in the financial domain but also in the marketing and community management ones. We express some reservations on the technical and business aspects though. It is indeed a very complex project and we think that they are a bit optimistic if they think that they’ll be able to provide a final working product by the end of 2018 with no real connection or advisory board in the financial domain.

Partnerships with 0x, Aragon and Civic should be a strength, but it’s hard to determine their level of implication on that matter. We didn’t really saw any endorsement from those teams, which is a bit worrisome. Actually, the word stuffing is a bit obvious in the whitepaper, there are big names and concepts everywhere but no key partnership announced and no key player supporting the project yet.

We think it is a very good FLIPPING opportunity, so we’ll give an 8 because the hype is very good, the parameters of the ICO are decent, there is not a lot of big or similar ICOs in October and the Request team seems to manage their project quite seriously. We are a little more reserved on the HODL side and we’ll limit our mark to 6 because, despite the nice ideas they bring to us today, we think the team has yet to prove that they can handle such a challenge.

Was this article useful to you? Consider tipping us!

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Ethereum: 0xfC6b5409Eb81D2E71CA1D44D2f047a7553978D19

Zcash Uniquest Choice as a Bitcoin Alternative: Edward Snowden

Edward Snowden – NSA whitleblower who weighed in on anonymity-centric virtual currencies, naming Zcash the “most interesting Bitcoin Alternative”. The former U.S. intelligence contractor that leaked out National Security Agency (NSA) data showcasing that the agency was taking notes (spying) on citizens that were not part of any investigations, is now serving as the president of...

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[Enigma Catalyst] 暗号通貨におけるマーコウィッツのポートフォリオ最適化の有効性について

Catalystを使用した現代ポートフォリオ理論の応用

皆さん、こんにちは!本記事は、Catalystプラットフォーム上で開発された暗号通貨トレーディングストラテジーにフォーカスを当てた記事の第2回目となります。今回もCatalystコミュニティのメンバーの方に寄稿して頂きました。本記事をお読み頂いた後に、フィードバックを残して頂けると幸いです。また、Catalystのアルファ版がリリースされていますので、ぜひ一度お試しになってご意見等をSlackコミュニティでお聞かせください!

Rodrigo Gomez-Grassi氏による寄稿

マーコウィッツと現代ポートフォリオ理論

メキシコ中央銀行で3年間ポートフォリオマネージャーを務めてきましたが、そこではマーコウィッツのポートフォリオ最適化モデルの構築と実装がポートフォリオの構築プロセスにとって欠かすことのできないものでした。このことは、従来型のアセットマネージャーのほとんどに当てはまります(例えば、中央銀行、年金基金、政府系ファンド、ソブリン・ウエルス・ファンドなど)。

この最適化理論は、現代ポートフォリオ理論(Modern Portfolio Theory, MPT)をベースにしています。「この理論では、投資リスクとリターンを単独で見るべきではなく、投資によってポートフォリオ全体のリスクとリターンがどのような影響を受けるのかによって評価すべきであるとされています。MPTでは、ある特定のリスク水準に対してリターンを最大化させるような複数のアセットからなるポートフォリオを構築することができるということが示されています。」(Investpediaより引用)

このモデルでは、選択したアセットのリターン実績がメインの入力となります。このモデルは、期待リターンとして各アセットの平均リターンを使用しています。このようなデータを使って、全てのアセット間の相関関係が計算されます。そして、その相関関係はポートフォリオ全体のリスク予測水準またはその標準偏差を決定するために使用されます。このような相関関係は、-1と1の間の数値で表されます。1に近い数値ほどアセットは同じ方向に動く傾向があり、0に近い数値ほどアセット間に関係がないということが示されます。また、-1に近い数値ほどアセットは反対方向に動く傾向があるということが示されます。

このモデルのパラメーターは、ポートフォリオ内の各アセットの個々の重みであり、その値はパーセントで表されることになります。大抵の場合、最適化した結果が実行可能なポートフォリオとなるように、ポートフォリオマネージャーはこのようなパラメーターに対して制約を加えることになります。通常、そのような制約として、重みがマイナスとならないようにしたり(つまり、ショートポジションがない)、重みの合計が100%になるようにする(つまり、現金の余りやレバレッジがない)といったようなことが行われます。ポートフォリオマネージャーの目的などに応じて、その他の制約を課すことも可能です。

このモデルでは上記のようなことを全て考慮に入れ、リターン水準に対する期待リスク水準が最小になるようなポートフォリオを見つけるまで、あらゆるポートフォリオの重みを何千回も繰り返し試行します。最適ポートフォリオのセットによって、効率化フロンティア(Efficient Frontier)と呼ばれるものが形成されることになります。このフロンティア内で、モデルはシャープ・レシオが最大となるポートフォリオを見つけることもできます。つまり、リスク単位当たりのリターンの高いポートフォリオを見つけることができるのです。

Catalystによるマーコウィッツモデルのバックテスト

本記事の最初の方で述べたように、マーコウィッツの最適化モデルは、従来型のアセット(国債、社債、外貨、株式など)に対して投資を行うようなアセットマネージャーのポートフォリオ構築プロセスにとっては欠かせないものになっています。しかし、暗号通貨は従来のアセットとは異なります。このような理由から、このモデルが暗号通貨という資産区分においてどのように機能するかを実験して確認てみたいと考えました。

この実験では、1トークン当たり1ドル以上の価格を持ち、2016年1月1日以前の取引履歴を利用することが可能な暗号通貨を使用することにしました。そしてそのような暗号通貨の中から、時価総額の高い5つの暗号通貨を使用することにしました。その5つの暗号通貨とは、ビットコイン、イーサリアム、ライトコイン、ダッシュ、モネロです。データとして過去180日間という枠組みの価格データを使用し、30日毎の調整期間を設定しました。つまり、アルゴリズムの実行開始時とその後の30日毎に、モデルは過去180日間のリターンに関するデータを使用し、効率化フロンティアの計算を行います。最終的に、調整期間毎にシャープ・レシオが最大となるポートフォリオの重みを得るようにモデルをプログラミングしました。このモデルのPythonコードはGitHub上で確認することができます。

私の元々の関心は、アセット間の相関関係にありました。多様化で大きなメリットを享受するためには、アセットに正の低い相関または負の相関がなければなりません。暗号通貨間に強い相関があった場合、マーコウィッツの最適化モデルは暗号通貨だけで構成されるポートフォリオには実用的ではないということになります。しかし、今回はそのようなケースではありませんでした。実際、下の表で示すように、相関の多くは0.5を下回っていました。

暗号通貨の相関マトリクス

2017年8月29日時点での過去180日間のデータを使用して計算

この結果によって、マーコウィッツのモデルは個々の資産に価値を付与し、リスク調整の観点からアセット単独の時や等金額ポートフォリオの時よりも高いパフォーマンスを示すということが分かります。しかし、結果について詳細に検討していく前に、まずは最大シャープ・レシオを使って各アセットとポートフォリオの期待リターンと期待リスクの簡単な分析をお示ししたいと思います。その結果は、以下の表の通りとなりました。

各再調整期間のアセットのサマリーデータ。単純化するために、リスクフリーレートを0%としてシャープ・レシオの計算を行っています。

アセット単独での特徴と各アセット間の相関関係を用いることによって、ポートフォリオの期待リターンと期待リスクを計算することができます。しかし、結果を実行可能なポートフォリオのみに制限するために、重みがマイナスにならず、重みの合計が100%となるような制約を加えました。その後、50,000通りのランダムなポートフォリオを生成し、そのリターンとリスク・プロファイルを計算しました。各リスク水準で期待リターンが最大となるポートフォリオでは、効率化フロンティア(Efficient Frontier)と呼ばれるものが生成されることになります。効率化フロンティア内には、リスク単位当たりの期待リターンが最大となるようなポートフォリオが存在します。これが、最大シャープポートフォリオ(Maximum Sharpe Portfolio)となります。

50,000通りのランダムポートフォリオの期待リターンと期待リスクの結果は、以下のグラフで示される通りとなりました。最大シャープ・レシオは青色の点で示されています。

ランダムポートフォリオと効率的フロンティア。2017年8月29日時点の過去180日間のデータで計算。

このモデルでは、上図の緑色で示されているようなシャープ・レシオの高いアセットほどポートフォリオ内に占める割合が大きくなり、マイナスや比較的低いシャープ・レシオのアセットは避けられるようになります。このモデルで計算される最適なポートフォリオの重みは、この洞察と一致しているということが分かります。このような重みの結果は、以下のグラフで示されています。

このようなポートフォリオの最適な重みを利用して、Catalystでストラテジーのバックテストを行いました。その際、テスト用に過去1年間のデータ(2017年1月1日~2017年9月19日までのデータ)を使用しました。またそれとは別に、同じアセットを使用して等金額ポートフォリオのバックテストも行い、追加で各アセット毎の長期保有ストラテジーのバックテストも行いました。その後、各ストラテジーの年換算利回りの平均と標準偏差を計算しました。以下の表が、その結果を要約したものとなります。

結果の要約

この結果から分かるように、最適化されたポートフォリオは素晴らしい結果を示しました。106%の標準偏差で359.6%もの年換算利回りを達成しており、シャープ・レシオの値は3.4となっています。このシャープ・レシオは非常に高い値であり、主要な資産区分(債券や株式など)への投資では通常このような値を得ることは困難であると考えられています。しかし、他のポートフォリオなどと比較した場合、最適化されたポートフォリオは最高のパフォーマンスを示すストラテジーではありませんでした。今回の結果では、等金額ポートフォリオが最も優れたパフォーマンスを示すということが分かりました。

さらに驚くべきことに、単一アセット(ETHおよびDASH)の長期保有ストラテジーでも「最適ポートフォリオ」よりもパフォーマンスの優れたものが2つありました。このような結果は、MPTや多様化のメリットの考えとは一致しないものです。この結果に対する説明としては、暗号通貨はまだ成熟しきった資産区分ではなく、そのためアセット間の相関はポートフォリオの標準偏差を予測するのに十分なほど安定していないということが考えられます。

本記事は、MITスローン経営大学院のMBA候補生であるRodrigo Gomez-Grassi氏によって執筆されました。

本記事は皆さんのご期待に沿えるものとなったでしょうか?Catalystを使い始める準備はできましたか?ぜひCatalystのアルファ版を一度お試しください。そしてSlackコミュニティでご意見をお聞かせください。それでは幸運を祈ります。良いトレーディング生活を!

免責事項 — 本記事の内容はあくまで情報提供を目的としたものです。有価証券の売買や投資ストラテジーの実装を推奨するものではありません。

[Enigma Catalyst] 暗号通貨におけるマーコウィッツのポートフォリオ最適化の有効性について

Catalystを使用した現代ポートフォリオ理論の応用

皆さん、こんにちは!本記事は、Catalystプラットフォーム上で開発された暗号通貨トレーディングストラテジーにフォーカスを当てた記事の第2回目となります。今回もCatalystコミュニティのメンバーの方に寄稿して頂きました。本記事をお読み頂いた後に、フィードバックを残して頂けると幸いです。また、Catalystのアルファ版がリリースされていますので、ぜひ一度お試しになってご意見等をSlackコミュニティでお聞かせください!

Rodrigo Gomez-Grassi氏による寄稿

マーコウィッツと現代ポートフォリオ理論

メキシコ中央銀行で3年間ポートフォリオマネージャーを務めてきましたが、そこではマーコウィッツのポートフォリオ最適化モデルの構築と実装がポートフォリオの構築プロセスにとって欠かすことのできないものでした。このことは、従来型のアセットマネージャーのほとんどに当てはまります(例えば、中央銀行、年金基金、政府系ファンド、ソブリン・ウエルス・ファンドなど)。

この最適化理論は、現代ポートフォリオ理論(Modern Portfolio Theory, MPT)をベースにしています。「この理論では、投資リスクとリターンを単独で見るべきではなく、投資によってポートフォリオ全体のリスクとリターンがどのような影響を受けるのかによって評価すべきであるとされています。MPTでは、ある特定のリスク水準に対してリターンを最大化させるような複数のアセットからなるポートフォリオを構築することができるということが示されています。」(Investpediaより引用)

このモデルでは、選択したアセットのリターン実績がメインの入力となります。このモデルは、期待リターンとして各アセットの平均リターンを使用しています。このようなデータを使って、全てのアセット間の相関関係が計算されます。そして、その相関関係はポートフォリオ全体のリスク予測水準またはその標準偏差を決定するために使用されます。このような相関関係は、-1と1の間の数値で表されます。1に近い数値ほどアセットは同じ方向に動く傾向があり、0に近い数値ほどアセット間に関係がないということが示されます。また、-1に近い数値ほどアセットは反対方向に動く傾向があるということが示されます。

このモデルのパラメーターは、ポートフォリオ内の各アセットの個々の重みであり、その値はパーセントで表されることになります。大抵の場合、最適化した結果が実行可能なポートフォリオとなるように、ポートフォリオマネージャーはこのようなパラメーターに対して制約を加えることになります。通常、そのような制約として、重みがマイナスとならないようにしたり(つまり、ショートポジションがない)、重みの合計が100%になるようにする(つまり、現金の余りやレバレッジがない)といったようなことが行われます。ポートフォリオマネージャーの目的などに応じて、その他の制約を課すことも可能です。

このモデルでは上記のようなことを全て考慮に入れ、リターン水準に対する期待リスク水準が最小になるようなポートフォリオを見つけるまで、あらゆるポートフォリオの重みを何千回も繰り返し試行します。最適ポートフォリオのセットによって、効率化フロンティア(Efficient Frontier)と呼ばれるものが形成されることになります。このフロンティア内で、モデルはシャープ・レシオが最大となるポートフォリオを見つけることもできます。つまり、リスク単位当たりのリターンの高いポートフォリオを見つけることができるのです。

Catalystによるマーコウィッツモデルのバックテスト

本記事の最初の方で述べたように、マーコウィッツの最適化モデルは、従来型のアセット(国債、社債、外貨、株式など)に対して投資を行うようなアセットマネージャーのポートフォリオ構築プロセスにとっては欠かせないものになっています。しかし、暗号通貨は従来のアセットとは異なります。このような理由から、このモデルが暗号通貨という資産区分においてどのように機能するかを実験して確認てみたいと考えました。

この実験では、1トークン当たり1ドル以上の価格を持ち、2016年1月1日以前の取引履歴を利用することが可能な暗号通貨を使用することにしました。そしてそのような暗号通貨の中から、時価総額の高い5つの暗号通貨を使用することにしました。その5つの暗号通貨とは、ビットコイン、イーサリアム、ライトコイン、ダッシュ、モネロです。データとして過去180日間という枠組みの価格データを使用し、30日毎の調整期間を設定しました。つまり、アルゴリズムの実行開始時とその後の30日毎に、モデルは過去180日間のリターンに関するデータを使用し、効率化フロンティアの計算を行います。最終的に、調整期間毎にシャープ・レシオが最大となるポートフォリオの重みを得るようにモデルをプログラミングしました。このモデルのPythonコードはGitHub上で確認することができます。

私の元々の関心は、アセット間の相関関係にありました。多様化で大きなメリットを享受するためには、アセットに正の低い相関または負の相関がなければなりません。暗号通貨間に強い相関があった場合、マーコウィッツの最適化モデルは暗号通貨だけで構成されるポートフォリオには実用的ではないということになります。しかし、今回はそのようなケースではありませんでした。実際、下の表で示すように、相関の多くは0.5を下回っていました。

暗号通貨の相関マトリクス

2017年8月29日時点での過去180日間のデータを使用して計算

この結果によって、マーコウィッツのモデルは個々の資産に価値を付与し、リスク調整の観点からアセット単独の時や等金額ポートフォリオの時よりも高いパフォーマンスを示すということが分かります。しかし、結果について詳細に検討していく前に、まずは最大シャープ・レシオを使って各アセットとポートフォリオの期待リターンと期待リスクの簡単な分析をお示ししたいと思います。その結果は、以下の表の通りとなりました。

各再調整期間のアセットのサマリーデータ。単純化するために、リスクフリーレートを0%としてシャープ・レシオの計算を行っています。

アセット単独での特徴と各アセット間の相関関係を用いることによって、ポートフォリオの期待リターンと期待リスクを計算することができます。しかし、結果を実行可能なポートフォリオのみに制限するために、重みがマイナスにならず、重みの合計が100%となるような制約を加えました。その後、50,000通りのランダムなポートフォリオを生成し、そのリターンとリスク・プロファイルを計算しました。各リスク水準で期待リターンが最大となるポートフォリオでは、効率化フロンティア(Efficient Frontier)と呼ばれるものが生成されることになります。効率化フロンティア内には、リスク単位当たりの期待リターンが最大となるようなポートフォリオが存在します。これが、最大シャープポートフォリオ(Maximum Sharpe Portfolio)となります。

50,000通りのランダムポートフォリオの期待リターンと期待リスクの結果は、以下のグラフで示される通りとなりました。最大シャープ・レシオは青色の点で示されています。

ランダムポートフォリオと効率的フロンティア。2017年8月29日時点の過去180日間のデータで計算。

このモデルでは、上図の緑色で示されているようなシャープ・レシオの高いアセットほどポートフォリオ内に占める割合が大きくなり、マイナスや比較的低いシャープ・レシオのアセットは避けられるようになります。このモデルで計算される最適なポートフォリオの重みは、この洞察と一致しているということが分かります。このような重みの結果は、以下のグラフで示されています。

このようなポートフォリオの最適な重みを利用して、Catalystでストラテジーのバックテストを行いました。その際、テスト用に過去1年間のデータ(2017年1月1日~2017年9月19日までのデータ)を使用しました。またそれとは別に、同じアセットを使用して等金額ポートフォリオのバックテストも行い、追加で各アセット毎の長期保有ストラテジーのバックテストも行いました。その後、各ストラテジーの年換算利回りの平均と標準偏差を計算しました。以下の表が、その結果を要約したものとなります。

結果の要約

この結果から分かるように、最適化されたポートフォリオは素晴らしい結果を示しました。106%の標準偏差で359.6%もの年換算利回りを達成しており、シャープ・レシオの値は3.4となっています。このシャープ・レシオは非常に高い値であり、主要な資産区分(債券や株式など)への投資では通常このような値を得ることは困難であると考えられています。しかし、他のポートフォリオなどと比較した場合、最適化されたポートフォリオは最高のパフォーマンスを示すストラテジーではありませんでした。今回の結果では、等金額ポートフォリオが最も優れたパフォーマンスを示すということが分かりました。

さらに驚くべきことに、単一アセット(ETHおよびDASH)の長期保有ストラテジーでも「最適ポートフォリオ」よりもパフォーマンスの優れたものが2つありました。このような結果は、MPTや多様化のメリットの考えとは一致しないものです。この結果に対する説明としては、暗号通貨はまだ成熟しきった資産区分ではなく、そのためアセット間の相関はポートフォリオの標準偏差を予測するのに十分なほど安定していないということが考えられます。

本記事は、MITスローン経営大学院のMBA候補生であるRodrigo Gomez-Grassi氏によって執筆されました。

本記事は皆さんのご期待に沿えるものとなったでしょうか?Catalystを使い始める準備はできましたか?ぜひCatalystのアルファ版を一度お試しください。そしてSlackコミュニティでご意見をお聞かせください。それでは幸運を祈ります。良いトレーディング生活を!

免責事項 — 本記事の内容はあくまで情報提供を目的としたものです。有価証券の売買や投資ストラテジーの実装を推奨するものではありません。

Meet the Enigma Dev Team — and Join Us

An introduction to the Enigma developers, and how you can get involved

Hi to all from Enigma! As we all continue to work on the Catalyst product and reconcile our token sale, we wanted to take a moment to properly introduce the main developers behind Enigma. A later post will focus on the other members of our core team that are working hard to scale our project, platform, partners, and community.

Thanks again for following Enigma. If you’re interested in joining our team and helping us build the future of crypto trading and data, please read additional info at the end of this post.

Guy Zyskind

Guy Zyskind

Guy is the CEO and co-founder of Enigma. He is a long time tinkerer, most comfortable sitting at the intersection of entrepreneurship and research. Prior to Enigma, Guy was a graduate student at MIT researching and teaching blockchain technology. Guy has authored several academic papers around cryptocurrencies, including the Enigma white paper (downloaded over 100K times) and “Decentralizing Privacy: Using Blockchain to Protect Personal Data”, which is one of the most cited papers in the space. Previously, Guy led the development of several start-up companies. Most notably, he was the Chief Technology Officer at Athena Wisdom (now Endor), an MIT Media Lab spin-off company involving Big Data Analytics and Network Science. Guy holds a M.S. from MIT and a B.S. in Electrical Engineering and Computer Science from Tel-Aviv University.

Victor Grau Serrat

Victor Grau Serrat

Victor speaks many languages, both natural languages and programming languages. As a senior developer at Enigma, he predominantly codes in Python, which is the language of choice for Catalyst, an algorithmic trading platform and Enigma’s first product. Having learnt version control software in the early days of Subversion, now he heavily relies on Github to manage the development of open-sourced Catalyst and other Enigma repositories. With a Master’s in Electrical and Computer Engineering from the University of Maryland, Victor brings more than fifteen years experience in software development that includes developing electronic medical records with JavaServer Pages, firmware engineering of WiFi drivers in embedded systems using C for high latency networks, and interactive online ads programmed in Flash and ActionScript. For 7+ years, Victor was the co-director of MIT D-Lab, a research and academic program at the intersection of technology innovation, social entrepreneurship and global poverty. Under his leadership, the D-Lab’s academic offerings quadrupled and its staff and operational budget grew tenfold. Victor also previously created his own algorithmic trading platform that traded live with a leading exchange, and he’s finally found his tribe in joining the Enigma team to develop Catalyst.

Frederic Fortier

Frederic Fortier

Frederic is a senior software developer specializing in finance. Prior to joining Enigma, he designed and implemented several enterprise applications for some of North America’s largest financial institutions. He primarily develops software in Python, but also has deep expertise with Java and JavaScript. Passionate about the financial markets, he has been trading equities and options since the dawn of online brokerage. His idea of fun is to read research papers on quantitative trading, trying to put them into practice. Over the years, he has live-traded several profitable strategies. His platform of choice is Zipline, which he knows inside and out. He joined Enigma partly to scratch his own itch, which is to build a high-grade quantitative trading platform for cryptocurrencies. He holds double degrees in Computer Science and Finance, as well as a Master of Science in E-Commerce from the Université de Sherbrooke.

Would you like to join our developers in building Catalyst and the Enigma data marketplace protocol? We are actively hiring for the following roles:

Data Engineer

A finder of needles in a virtual haystack, you will comb your way through the web, markets and social networks, crawling and curating intelligence around the cryptocurrency ecosystem. Solid knowledge of Python and data-driven frameworks such as Pandas is required. Experience in scaling big data systems, handling high-throughput queries in a real-time manner, is a big plus.

Data Scientist

Your thirst for knowledge is insatiable. You see patterns everywhere you look, and enjoy turning raw datasets into useful insights. Proficiency in Python and ML libraries (e.g., TensorFlow) is required, as well as previous quant experience and understanding of financial markets.

Fullstack Developer

A jack of all trades, you’re a dev ninja that can speak both front-end and back-end. Experience in React, NodeJS and MongoDB is required. A good inclination towards good UI/UX is a significant advantage, as well as any design skills.

If you’re interested in any of these roles, send us an email at jobs@enigma.co. Include your resume and a bit of information about yourself and why you’re excited about Enigma. We are working hard to bring our visions for Enigma and Catalyst to life — help us build the future of crypto trading and data!

With excitement,

The Enigma Team

Our community Telegram — https://t.me/enigmacatalyst

Our community Discord —https://discordapp.com/invite/SJK32GY

Our Twitter — https://www.twitter.com/enigmampc


Meet the Enigma Dev Team — and Join Us was originally published in Catalyst on Medium, where people are continuing the conversation by highlighting and responding to this story.

Meet the Enigma Dev Team — and Join Us

An introduction to the Enigma developers, and how you can get involved

Hi to all from Enigma! As we all continue to work on the Catalyst product and reconcile our token sale, we wanted to take a moment to properly introduce the main developers behind Enigma. A later post will focus on the other members of our core team that are working hard to scale our project, platform, partners, and community.

Thanks again for following Enigma. If you’re interested in joining our team and helping us build the future of crypto trading and data, please read additional info at the end of this post.

Guy Zyskind

Guy Zyskind

Guy is the CEO and co-founder of Enigma. He is a long time tinkerer, most comfortable sitting at the intersection of entrepreneurship and research. Prior to Enigma, Guy was a graduate student at MIT researching and teaching blockchain technology. Guy has authored several academic papers around cryptocurrencies, including the Enigma white paper (downloaded over 100K times) and “Decentralizing Privacy: Using Blockchain to Protect Personal Data”, which is one of the most cited papers in the space. Previously, Guy led the development of several start-up companies. Most notably, he was the Chief Technology Officer at Athena Wisdom (now Endor), an MIT Media Lab spin-off company involving Big Data Analytics and Network Science. Guy holds a M.S. from MIT and a B.S. in Electrical Engineering and Computer Science from Tel-Aviv University.

Victor Grau Serrat

Victor Grau Serrat

Victor speaks many languages, both natural languages and programming languages. As a senior developer at Enigma, he predominantly codes in Python, which is the language of choice for Catalyst, an algorithmic trading platform and Enigma’s first product. Having learnt version control software in the early days of Subversion, now he heavily relies on Github to manage the development of open-sourced Catalyst and other Enigma repositories. With a Master’s in Electrical and Computer Engineering from the University of Maryland, Victor brings more than fifteen years experience in software development that includes developing electronic medical records with JavaServer Pages, firmware engineering of WiFi drivers in embedded systems using C for high latency networks, and interactive online ads programmed in Flash and ActionScript. For 7+ years, Victor was the co-director of MIT D-Lab, a research and academic program at the intersection of technology innovation, social entrepreneurship and global poverty. Under his leadership, the D-Lab’s academic offerings quadrupled and its staff and operational budget grew tenfold. Victor also previously created his own algorithmic trading platform that traded live with a leading exchange, and he’s finally found his tribe in joining the Enigma team to develop Catalyst.

Frederic Fortier

Frederic Fortier

Frederic is a senior software developer specializing in finance. Prior to joining Enigma, he designed and implemented several enterprise applications for some of North America’s largest financial institutions. He primarily develops software in Python, but also has deep expertise with Java and JavaScript. Passionate about the financial markets, he has been trading equities and options since the dawn of online brokerage. His idea of fun is to read research papers on quantitative trading, trying to put them into practice. Over the years, he has live-traded several profitable strategies. His platform of choice is Zipline, which he knows inside and out. He joined Enigma partly to scratch his own itch, which is to build a high-grade quantitative trading platform for cryptocurrencies. He holds double degrees in Computer Science and Finance, as well as a Master of Science in E-Commerce from the Université de Sherbrooke.

Would you like to join our developers in building Catalyst and the Enigma data marketplace protocol? We are actively hiring for the following roles:

Data Engineer

A finder of needles in a virtual haystack, you will comb your way through the web, markets and social networks, crawling and curating intelligence around the cryptocurrency ecosystem. Solid knowledge of Python and data-driven frameworks such as Pandas is required. Experience in scaling big data systems, handling high-throughput queries in a real-time manner, is a big plus.

Data Scientist

Your thirst for knowledge is insatiable. You see patterns everywhere you look, and enjoy turning raw datasets into useful insights. Proficiency in Python and ML libraries (e.g., TensorFlow) is required, as well as previous quant experience and understanding of financial markets.

Fullstack Developer

A jack of all trades, you’re a dev ninja that can speak both front-end and back-end. Experience in React, NodeJS and MongoDB is required. A good inclination towards good UI/UX is a significant advantage, as well as any design skills.

If you’re interested in any of these roles, send us an email at jobs@enigma.co. Include your resume and a bit of information about yourself and why you’re excited about Enigma. We are working hard to bring our visions for Enigma and Catalyst to life — help us build the future of crypto trading and data!

With excitement,

The Enigma Team

Our community Telegram — https://t.me/enigmacatalyst

Our community Discord —https://discordapp.com/invite/SJK32GY

Our Twitter — https://www.twitter.com/enigmampc


Meet the Enigma Dev Team — and Join Us was originally published in Catalyst on Medium, where people are continuing the conversation by highlighting and responding to this story.

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