Market Making and Liquidity for cryptocurrencies and other digital assets and topics

Algorithmic Trading – A complete guide

What is algorithmic trading?

 

Algorithmic Trading in simple words is to use computer programs to automate the process of trading (buying and selling) financial instruments (stocks, FX pairs, Cryptocurrency, options). These computer programs are coded to trade based on the input that has been defined for them. Inputs could be based on the aimed strategy to take advantage of different market behaviors such as the specific change of a price could trigger the algorithms to make some specific trades, or other factors like volume, time or sophisticated algorithms that trade based on trading indicators. 

Algorithmic trading strategies and backtesting

 

Almost all trading ideas are first converted to a trading strategy and coded into an algorithm that then comes to life and ready for execution. Most algorithmic trading strategies are created on the basis of wide trading knowledge on the financial market combined with quantitative analysis and modeling, later the strategies are given to quants programmers who will convert the strategy to executable algorithms. 

 It is widely common to perform testing on trading strategies before they go live on the market, this practice is known as Backtesting. This is where the algorithm is being tested on historical data to check the algorithm and apply further modifications. 

The main idea behind Backtesting is to evaluate the performance of the algorithmic strategy to see if the strategy is behaving the way it was programmed and check the profitability of it using real market data. 

For more sophisticated algorithms and firms with more advanced tools, algorithmic strategies perform on what so-called paper trading, where the strategy performs virtual trading without committing any commercial value (trading without money). 

The most popular programming languages used to write algorithmic trading strategies are JAVA, Python, and C++. Matlab is also a good tool with a wide range of analytic tools to plot and analyze algorithmic strategies. 

Who uses algorithmic trading?

 

By far the most common fans of performing trades algorithmically are larger financial institutions as well as investment banks alongside Hedge Funds, pension funds, broker-dealer, market makers. 

 

Some well-known algorithmic strategies:

 

On a broad sense most commonly used algorithmic strategies are Momentum strategies, as the names indicate the algorithm start execution based on a given spike or given moment. The algorithm basically detects the moment (e.g spike) and executed by and sell order as to how it has been programmed. 

One another popular strategy is Mean-Reversion algorithmic strategy. This algorithm assumes that prices usually deviate back to its average. 

A more sophisticated type of algorithmic trading is market making strategy, these algorithms are known as liquidity providers. Market Making strategies aim to supply buy and sell orders in order to fill the order book and make a certain instrument in a market more liquid. Market Making strategies are designed to capture the spread between buying and selling price and ultimately decrease the spread. 

Another advanced and complex algorithmic strategy is Arbitrage algorithms. These algorithms are designed to detect mispricing and spread inefficiencies among different markets. Basically, Arbitrage algorithms find the different prices among two different markets and buy or sell orders to take advantage of the price difference. 

Among big investment banks and hedge funds trading with high frequency is also a popular practice. A great deal of all trades executed globally is done with high-frequency trading. The main aim of high-frequency trading is to perform trades based on market behaviors as fast and as scalable as possible. Though, high-frequency trading requires solid and somewhat expensive infrastructure. Firms that would like to perform trading with high frequency need to collocate their servers that run the algorithm near the market they are executing to minimize the latency as much as possible. 

Algorithmic Trading Software

 

Based on the given use case like the size of orders, customizability and experience level there are options available for algorithmic trading software. Larger firms like hedge funds, investment banks or proprietary trading firms use rather more tailored custom-built and advanced tools. When it comes to more individual traders or quants with less capital to trade they will rather use more readymade algorithmic strategies, some on the cloud, some stand-alone. 

The most common features of algorithmic trading software are ways to analyze profit/loss of an algorithm on a live market data. There are different protocols available to get, process and send orders from software to market, such as TCP/IP, webhooks, FIX and etc. One important factor for this data processing from receiving to processing and pushing order is measured with latency. Latency is the time-delay introduced to the movement of data from points to points. Considering the changes in price in the market the lower obtained latency the better software reacts to market events hence a faster reaction. 

Backtesting is another useful feature that should be included in algorithmic trading software, usually, this software allows traders to apply their algorithmic trading strategies and test it with historical data to evaluate the profitability of their strategies. 

Pros and cons of algorithmic trading

 

Just like any other choice, there are pros and cons to using algorithmic trading strategies and automating the process of trading. Let’s get down with the pros. Based on many expert opinions in investments human emotions could be toxic and faulty when it comes to trading, one perhaps most acknowledged pros of Algorithmic Trading is taking away human emotions and errors out of trading.

Another huge advantage of algorithmic trading is the increase of speed in action of execution to the market as well as possibilities to test strategies using Backtesting and paper-trading in a simulated manner. Testing algorithmic strategies determine the viability of the idea behind trading strategies.

Another vastly discussed advantage of algorithmic trading is risk diversification. Algorithmic trading allows traders to diversify themselves across man accounts, strategies or market at any given time. The act of diversification will spread the risk of different market instruments and hedge them against their losing positions. 

Making trading automatically using algorithmic trading decreases the operational costs of performing large volumes of trade in a short period of time. 

There are also a few other advantages such as automation in the allocation of assets, keeping a consistent discipline in trading and faster execution.

Now let’s get on with some of the cons of using algorithmic trading. Perhaps one very discussed issue with using algorithmic trading is constant monitoring of the strategies which to some traders could be a bit stressful since the human control in algorithmic trading is much less. Though it is widely common to have lost control features included in strategies and algorithmic trading software (automated and manual ones). 

For most individual traders having enough resources could be another disadvantage of algorithmic trading. The algorithmic trading itself reduces the cost of executing large orders but it could come expensive as it requires initial infrastructure such as the software cost or the server cost.

 

Pros Cons
Emotionless trading Needs for monitoring 
Less error Technological infrastructure 
Higher trading speed Programming skills required for updating strategies
Backtesting and paper trading
Risk diversification 
Lower operational costs 
Consistent trading discipline 

 

Algorithmic trading in Cryptocurrency

 

Unlike more mature instruments like stocks, options or CFDs, the Cryptocurrency market is quite volatile. Typically higher volatility leads to more frequent jumps in the price of instruments, higher and lower. Hence, some professional traders find this amusing and opportunistic to make the most of the profits.  

Generally, for Cryptocurrency traders, there are plenty of cloud-based solutions using trading bots, though for very professional and institutional traders this may not flexible enough. There are few algorithmic trading platforms for cryptocurrencies which can utilize the need for more sophisticated and institutional traders. 

 

Algorithmic Trading Trends:

 

On average 80% of the daily traders across the US are done by algorithmic trading and machines. Though the volume of the algorithmic trading can change based on the volatility in the market. According to J.P. Morgan, fundamental discretionary traders are accounted for only 10% of trading volume in stocks. This is the traditional way of checking the companies business performance and their outlook before deciding whether to buy or sell a position. 

 

The growth in the number of algorithmic trading since last year comes close to 47% and there is 41% growth in the number of users executing their trades algorithmically. Mobile also plays an important role in the tools provided there is around 54% growth in trading FX algorithmically using mobile devices. 

New technologies, Artificial Intelligence, Machine Learning, Blockchain:

 

According to another J.P. Morgan research, Artificial Intelligence and Machine learning are predicted to be the most influential for shaping the future of trading. Based on this analysis Artificial Intelligence and Machine Learning will influence the future of trading by 57% and 61% in the next three years.  

Interestingly this report states that Natural Language Processing alone will count to 5% of the change in the next 12 months and up to 9% in the next three years. 

J.P. Morgan report shows that around 68% of the traders believe that Artificial Intelligence and Machine Learning provide deep data analytics. Around 62% believe that Artificial Intelligence and Machine Learning optimize trade execution and 49% of traders believe that Artificial Intelligence and Machine Learning represents an opportunity to hone their trading decisions. 

The same report indicates that Blockchain within the next 12 months will influence the trading up to 9% and 19% within the next three years. Within the same report, the usage of mobile trading applications is to influence the trading market up to 28% within the next 12 months and 11% within the next 3 years. 

Now Crypto. Lessons learned from over 10 years of developing trading software

By Michal Rozanski, CEO at Empirica.

Reading news about crypto we regularly see the big money inflow to new companies with a lot of potentially breakthrough ideas. But aside from the hype from the business side, there are sophisticated technical projects going on underneath.

And for new cryptocurrency and blockchain ideas to be successful, these projects have to end with the delivery of great software systems that scale and last. Because we have been building these kinds of systems for the financial markets for over 10 years we want to share a bit of our experience.

Read more on how Empirica delivers its trading software development services

“Software is eating the world”. I believe these words by Marc Andreessen. And now the time has come for financial markets, as technology is transforming every corner of the financial sector. Algorithmic trading, which is our speciality, is a great example. Other examples include lending, payments, personal finance, crowdfunding, consumer banking and retail investments. Every part of the finance industry is experiencing rapid changes triggered by companies that propose new services with heavy use of software.

If crypto relies on software, and there is so much money flowing into crypto projects, what should be looked for when making a trading software project for cryptocurrency markets? Our trading software development projects for the capital and crypto markets as well as building our own algorithmic trading platform has taught us a lot. Now we want to share our lessons learned from these projects.

 

  1. The process – be agile.

Agile methodology is the essence of how software projects should be made. Short iterations. Frequent deliveries. Fast and constant feedback from users. Having a working product from early iterations, gives you the best understanding of where you are now, and where you should go.

It doesn’t matter if you outsource the team or build everything in-house; if your team is local or remote. Agile methodologies like Scrum or Kanban will help you build better software, lower the overall risk of the project and will help you show the business value sooner.

 

  1. The team – hire the best.

A few words about productivity in software industry. The citation is from my favourite article by Robert Smallshire ‘Predictive Models of Development Teams and the Systems They Build’ : ‘… we know that on a small 10 000 line code base, the least productive developer will produce about 2000 lines of debugged and working code in a year, the most productive developer will produce about 29 000 lines of code in a year, and the typical (or average) developer will produce about 3200 lines of code in a year. Notice that the distribution is highly skewed toward the low productivity end, and the multiple between the typical and most productive developers corresponds to the fabled 10x programmer.’.

I don’t care what people say about lines of code as a metric of productivity. That’s only used here for illustration.

The skills of the people may not be that important when you are building relatively simple portals with some basic backend functionality. Or mobile apps. But if your business relies on sophisticated software for financial transactions processing, then the technical skills of those who build it make all the difference.

And this is the answer to the unasked question why we in Empirica are hiring only best developers.

We the tech founders tend to forget how important it is to have not only best developers but also the best specialists in the area which we want to market our product. If you are building an algo trading platform, software for market makers or trading bots, you need quants. If you are building banking omnichannel system, you need bankers. Besides, especially in B2B world, you need someone who will speak to your customers in their language. Otherwise, your sales will suck.

And finally, unless you hire a subcontractor experienced in your industry, your developers will not understand the nuances of your area of finance.

 

  1. The product – outsource or build in-house?

If you are seriously considering building a new team in-house, please read the points about performance and quality, and ask yourself the question – ‘Can I hire people who are able to build systems on required performance and stability levels?’. And these auxiliary questions – can you hire developers who really understand multithreading? Are you able to really check their abilities, hire them, and keep them with you? If yes, then you have a chance. If not, better go outsource.

And when deciding on outsourcing – do not outsource just to any IT company hoping they will take care. Find a company that makes systems similar to what you intend to build. Similar not only from a technical side but also from a business side.

Can outsourcing be made remotely without an unnecessary threat to the project? It depends on a few variables, but yes. Firstly, the skills mentioned above are crucial; not the place where people sleep. Secondly, there are many tools to help you make remote work as smooth as local work. Slack, trello, github, daily standups on Skype. Use it. Thirdly, find a team with proven experience in remote agile projects. And finally – the product owner will be the most important position for you to cover internally.

And one remark about a hidden cost of in-house development, inseparably related to the IT industry – staff turnover costs. Depending on the source of research, turnover rates for software developers are estimated at 25% to even 38%. That means that when constructing your in-house team, every fourth or even every third developer will not be with you in a year from now. Finding a good developer – takes months. Teaching a new developer and getting up to speed – another few months. When deciding on outsourcing, you are also outsourcing the cost and stress of staff turnover.

 

  1. System’s performance.

For many crypto projects, especially those related with trading,  system’s performance is crucial. Not for all, but when it is important, it is really important. If you are building a lending portal, performance isn’t as crucial. Your customers are happy if they get a loan in a few days or weeks, so it doesn’t matter if their application is processed in 2 seconds or in 2 minutes. If you are building an algo trading operations or bitcoin payments processing service, you measure time in milliseconds at best, but maybe even in nanoseconds. And then systems performance becomes a key input to the product map.

95% of developers don’t know how to program with performance in mind, because 95% of software projects don’t require these skills. Skills of thinking where bytes of memory go, when they will be cleaned up, which structure is more efficient for this kind of operation on this type of object. Or the nightmare of IT students – multithreading. I can count on my hands as to how many people I know who truly understand this topic.

 

  1. Stability, quality and level of service.

Trading understood as an exchange of value is all about the trust. And software in crypto usually processes financial transactions in someway.

Technology may change. Access channels may change. You may not have the word ‘bank’ in your company name, but you must have its level of service. No one in the world would allow someone to play with their money. Allowing the risk of technical failure may put you out of business. You don’t want to spare on technology. In the crypto sapce there is no room for error.

You don’t achieve quality by putting 3 testers behind each developer. You achieve quality with processes of product development. And that’s what the next point is about.

 

  1. The DevOps

The core idea behind DevOps is that the team is responsible for all the processes behind the development and continuous integration of the product. And it’s clear that agile processes and good development practices need frequent integrations. Non-functional requirements (stability and performance) need a lot of testing. All of this is an extra burden, requiring frequent builds and a lot of deployments on development and test machines. On top of that there are many functional requirements that need to be fulfilled and once built, kept tested and running.

On many larger projects the team is split into developers, testers, release managers and system administrators working in separate rooms. From a process perspective this is an unnecessary overhead. The good news is that this is more the bank’s way of doing business, rarely the fintech way. This separation of roles creates an artificial border when functionalities are complete from the developers’ point of view and when they are really done – tested, integrated, released, stable, ready for production. By putting all responsibilities in the hands of the project team you can achieve similar reliability and availability, with a faster time to the market. The team also communicates better and can focus its energy on the core business, rather than administration and firefighting.

There is a lot of savings in time and cost in automation. And there are a lot of things that can be automated. Our DevOps processes have matured with our product, and now they are our most precious assets.

 

  1. The technology.

The range of technologies applied for crypto software projects can be as wide as for any other industry. What technology makes best fit for the project depends, well, on the project. Some projects are really simple such as mobile or web application without complicated backend logic behind the system. So here technology will not be a challenge. Generally speaking, crypto projects can be some of the most challenging projects in the world. Here technologies applied can be the difference between success and failure. Need to process 10K transaction per second with a mean latency under 1/10th ms. You will need a proven technology, probably need to resign from standard application servers, and write a lot of stuff from scratch, to control the latency on every level of critical path.

Mobile, web, desktop? This is more of a business decision than technical. Some say the desktop is dead. Not in trading. If you sit whole day in front of the computer and you need to refer to more than one monitor, forget the mobile or web. As for your iPhone? This can be used as an additional channel, when you go to a lunch, to briefly check if the situation is under control.

 

  1. The Culture.

After all these points up till now, you have a talented team, working as a well-oiled mechanism with agile processes, who know what to do and how to do it. Now you need to keep the spirits high through the next months or years of the project.

And it takes more than a cool office, table tennis, Xbox consoles or Friday parties to build the right culture. Culture is about shared values. Culture is about a common story. With our fintech products or services we are often going against big institutions. We are often trying to disrupt the way their business used to work. We are small and want to change the world, going to war with the big and the powerful. Doesn’t it look to you like another variation of David and Goliath story? Don’t smile, this is one of the most effective stories. It unifies people and makes them go in the same direction with the strong feeling of purpose, a mission. This is something many startups in other non fintech branches can’t offer. If you are building the 10th online grocery store in your city, what can you tell your people about the mission?

Read more on how Empirica delivers its crypto software development services

 

Final words

Crypto software projects are usually technologically challenging. But that is just a risk that needs to be properly addressed with the right people and processes or with the right outsourcing partner. You shouldn’t outsource the responsibility of taking care of your customers or finding the right market fit for your product. But technology is something you can usually outsource and even expect significant added value after finding the right technology partner.

At Empirica we have taken part in many challenging crypto projects, so learn our lessons, learn from others, learn your own and share it. This cycle of learning, doing and sharing will help the crypto community build great systems that change the rules of the game in the financial world!

 

 

Algorithmic crypto trading: market specifics and strategy development

By Marek Koza, Product Owner of Empirica’s Algo Trading Platform

Among trading professionals, interest in crypto-currency trading is steadily growing. At Empirica we see it by an increasing number of requests from trading companies, commonly associated with traditional markets, seeking algorithmic solutions for cryptocurrency trading or developing trading software with us from scratch. However, new crypto markets suffer from old and well-known problems. In this article, I try to indicate the main differences between traditional and crypto markets and take a closer look at a few algorithmic strategies (known as trading bots on crypto markets) that are currently effective in the crypto space. Differences between crypto and traditional markets constitute an interesting and deep subject in itself which is evolving quickly as
the pace of change in crypto is also quite fast. But here I only want to focus on algorithmic trading perspectives.

 

Read more about our tool for market making strategies for crypto exchanges  – Liquidity Engine

 

LEGISLATION

First, there is a lack of regulations in terms of algorithmic usage. Creating DMA algorithms on traditional markets requires a great deal of additional work to meet reporting, measure standards as well as limitations rules provided by regulators (e.g., EU MiFIDII or US RegAT). In most countries crypto exchanges have yet to be covered by legal restrictions. Nevertheless, exchanges provide their own internal rules and technical limitations which, in a significant way, restricts the possibility of algorithmic use, especially in HFT field. This is crucial for market-making activities which now requires separated deals with trading venues.

 

DERIVATIVES

As for market-making, we should notice an almost non-existent derivatives market in the cryptoworld. Even if a few exchanges offer futures and options, they only apply to a few of the most popular cryptocurrencies. Combining it with highly limited margin trading possibilities and none of index derivatives (contracts which reflect wide market pricing), we see that many hedging strategies are almost impossible to execute and may only exist as a form of spot arbitrage.

 

 

 

 

 

 

 

 

 

 

 

 

As for market-making, we should notice an almost non-existent derivatives market in the cryptoworld. Even if a few exchanges offer futures and options, they only apply to a few of the most popular cryptocurrencies. Combining it with highly limited margin trading possibilities and none of index derivatives (contracts which reflect wide market pricing), we see that many hedging strategies are almost impossible to execute and may only exist as a form of spot arbitrage.

 

DECENTRALIZATION

The above-mentioned facts are slightly compensated for by the biggest advantage of blockchain currencies – fast and direct transfers around the world without banks intermediation. With cryptoexchange APIs mostly allowing automation of withdrawal requests, it opens up new possibilities for algorithmic asset allocation by much smaller firms than the biggest investment banks. This is important due to two things. Firstly, there is still no one-stop market brokerage solution we know from traditional markets. Secondly, cryptocurrencies trading is distributed among many exchanges around the world. It could therefore be tricky for liquidity seekers and heavy volume execution. It implies there is still much to do for execution algorithms such as smart order routing.

 

CONNECTIVITY

A smart order routing strategy GUI

Another difference is direct market access for algorithmic trading. While on traditional markets DMA is costly, cryptocurrency exchange systems provide open APIs for all their customers that may be used without upfront prerequisites. Although adopted protocols are usually easy to implement, they are often too simplistic. They do not usually offer advanced order types. Besides, order life-cycle status following is cumbersome and trading protocols differ among exchanges since each one requires its own implementation logic. That makes a costly technical difference compared to traditional markets with common standards, including FIX protocol.

 

MARKET DATA

Fast, precise and up-to-date data are crucial from an algorithmic trading perspective. When a trader develops algorithms for cryptocurrencies, she should be aware of a few differences. APIs provided by crypto-exchanges give easy access to time & sales or level II market data for everyone for free. Unfortunately, data protocols used in the crypto space are unreliable and trading venue systems often introduce glitches and disconnections. Moreover, not every exchange supports automatic updates and an algorithm has to issue a request every time it needs to check on the state of a market, which is difficult to reconcile with algorithmic strategies.

The APIs of most exchanges allow downloading of historical time & sale data, which is important in the algorithmic developing process. However, historical level II data are not offered by exchanges. We should also notice that despite being immature, the systems of crypto trading venues are evolving and becoming more and more professional. This forces trading systems to follow and adapt to these changes, which adds big costs to systems’ maintenance. In the following sections I overview a few trading algorithms that are currently popular among crypto algo traders because of the differences between traditional and crypto markets listed above.

 

SMART ORDER ROUTING

Liquidity is and most probably will remain, one of the biggest challenges for cryptocurrency trading. Trading on bitcoin and etherium and all other altcoins with smaller market capitalisation, is split among over 200 different exchanges. Executing a larger volume on any type of assets often requires seeking liquidity on more than one trading venue. To achieve that, cryptocurrency traders may apply smart order routing strategies. These follow limit order books for the same instrument from different exchanges and aggregates them internally. When an investment decision is made, the strategy splits the order among exchanges that offer best prices for the instrument. A well-designed strategy will also manage partially filled orders left in the order book in case some volume disappears before the order has arrived at the market. This strategy could be combined with other execution strategies such as TWAP or VWAP.

Empirica algorithmic trading platform front-end app (TradePad) for crypto-markets.

 

ARBITRAGE

The days when simple crossexchange arbitrage was profitable with manual execution are over. Nowadays price differences among exchanges for the most actively trading crypto-assets, are much smaller than a year ago and transactional and transfer costs (especially for fiat) still remain at a high level. Trading professionals are now focused towards using more sophisticated arbitrage algorithms such as maker-taker or triangular arbitrage. The former works by quoting a buy order on one exchange, based on VWAP for a particular amount of volume from another exchange (the same instrument) decreased by expected fees and return. A strategy is actively moving quoted order and if the passive gets executed, it sends a closing order to the other exchange. As the arbitrage is looking for bid-bid and ask-ask difference and maker fees are often lower, this type of arbitrage strategy is more cost-effective.

Triangular arbitrage may be executed on a single exchange because it is looking for differences among three currency pairs which are connected to each other. To illustrate, let us use this strategy with BTCUSD, ETHUSD and ETHBTC pairs. This strategy keeps following order books of these three instruments. The goal is to find the inefficient quoting and execute trades on three instruments simultaneously. To understand this process, we should notice that ratio between BTCUSD and ETHBTC should reflect the ETHUSD market rate. Contrary to some FX crosses, all cryptocurrency pairs are priced independently. This creates numerous possibilities of using triangular arbitrage in crypto space.

 

MARKET MAKING

Market making should be considered more as a type of business than as just a strategy. The main task of a market maker is to provide liquidity to markets by maintaining bid and ask orders to allow other market participants to trade any time they need. Since narrow spreads and adequate prices are among the biggest
factors of exchange’ attractiveness, market making services are in high demand. On the one hand, crypto exchanges have special offers for liquidity providers, but on the other hand, they require from new coins issuers a market maker before they start listing an altcoin.

These agreements are usually one source of market maker income. Another one is a spread – a difference between a buy and a sell prices provided to the other traders. The activity of a market maker is related to some risks. One of them is inventory imbalance – if a market maker buys much more than sells or sells much more than buys, she stays with an open long or short position and takes portfolio risk, especially on volatile crypto markets. This situation may happen in markets with a strong bias, or when market maker is quoting wrong or delayed prices, which will immediately be exploited by arbitrageurs. To avoid such situations, market makers apply algorithmic solutions such as different types of fair price calculations, trade-outs, hedging, trend and order-flow predictions, etc. Technology and math used in market making algorithms are an interesting subject for future articles.

 

Read more about our tool for market making strategies for crypto exchanges  – Liquidity Engine

 

SUMMARY

Fast developing crypto markets are attracting a growing number of participants, including more and more trading professionals from traditional markets. However, the crypto space has its own specificity such as high decentralization, maturing technology and market structure. Compared to other markets, these differences make some strategies more useful and profitable than others. Arbitrage – even simple cross-exchange is still very popular. Market making services are in high demand. Midsized and large orders involve execution algorithms like smart order routing. At the end of the day to embrace the fast changing crypto environment, one needs algorithmic trading systems with an open architecture that evolves alongside the market.

 

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Cryptohopper – Technical Review 2019

There is quite a hot market for cryptocurrency trading platforms and algorithmic trading bots. New crypto traders and active traders from capital markets are pouring in funds into algorithmic strategies and bots to make the most out of the constant opportunistic cryptocurrency fluctuation. On the other hand trading platform, providers and investment bots are tailoring their strategies to be tuned well to different scenarios depending on the type of events occurring within the market.
Due to the expansion of development from these trading bots and their adaptability to different events, the process of choosing one has become quite challenging, even for those with technical and trading background, hence at Empirica, we decided to bring knowledge about professional crypto trading bots to interested readers and traders and our selected bot for this article is Cryptohopper.

In this review, we will cover relative features included in Cryptohopper trading platform. We analyze ways that traders can utilize Cryptohopper for their trades. We also take a look at their tool from a technical point of view (our team at Empirica has been focused on the institutional algorithmic trading platform and market making algorithms for almost 10 years). Later in the review, we will also take a look at options we believe Cryptohopper lacks. But first and foremost:

What is Cryptohopper?

Cryptohopper is an retail algorithmic trading platform with a series of configurable trading features (more on professional algorithmic trading platform). Cryptohopper’s platform is shaped around 5 key elements, which each have been developed further to meet the needs of traders. The 5 key elements are:

  • Mirror trading
    This feature allows investors to copy the trades of experienced and successful forex investors. Strategies are available through a marketplace, some free and some paid.
  • Paper trading
    A simulated trading practice to assess trading algorithms with real and live data.
  • Strategy designer
    A technical indicator assembler which lets traders design their strategies using the listed indicators. There are currently somewhere around 130 technical indicators provided by Cryptohopper.
  • Algorithmic trading
    An automated way of executing trading algorithms with a specified set of configuration.
  • Trailing stop
    It’s a feature designed to stop strategies to operate if a defined trigger has been pulled.

 

Which exchanges are supported by Cryptohopper?

There are in total of 10 exchanges that are supported by Cryptohopper. Exchanges are KuCoin, Bitvavo, Binance, Coinbase pro, Bitterex, Poloniex, Kraken, Huobi, Bitfinex and Binance.US. 

 

How can I trade with Cryptohopper?

Depending on your sophistication level and trading knowledge, Traders can utilize Cryptohopper platform to their use. There are two bots, the market-making and Arbitrage bots and there are also strategies that can be used to select a set of indicators to form a strategy.

 

Market Making Bot

The market making bot is designed for retail investors (check market making bot for professional users). It is designed to perform liquidity provision to the market of traders’ choice. The market making bot is a configurable algorithm that executes buy and/or sell (take and/or make) by placing a layered limit of buy and sell orders. 

To initiate using the market making bot, traders must go through the preliminary configurations. Starts with choosing an exchange and setting up the API keys. Even using the API the fund still will be located in the exchange and in order to trade on the exchange, traders need to generate an API key and then connect that to their Cryptohopper account. 

After the initial configuration, there is also a set of more advanced Market Making configuration. Market and Pricing is the second stage of Market Making setup at Cryptohopper. This stage includes configuration of the market and which pair trader is interested in. Then moving on to the strategy setup with market trends. Market trends are either uptrend, downtrend or it could stay as neutral. Additionally, the order sequence of buying and selling with a given sequence, the order layer which represents the tiered buy and sell orders that are going to be placed and the moving on to the amount constraints within layers (e.g. buy amount, higher ask and percentage lower bid).

Cryptohopper Trading Bot Review

 

The Cryptohopper Market Making bot is also equipped with an “Auto-cancel” functionality which based on the configuration determines when to open and close positions. There is also a time limit to trigger the cancel on the bot. Seemingly the most important feature of the Auto Cancel is the Cancel on the trend, which enables auto cancelling on the bot when the marker changes to a direction e.g. from neutral to a downtrend or from neutral to uptrend and etc. Cancellation on the bot could also be triggered with percentage change, this only happens if the market has a certain specified percentage change or within a given period. The auto-cancel feature also works with the depth limit, which Traders can set from a minimum of 1 to a maximum of 500. Additionally, Traders that are interested in Cryptohopper Market Making bot can set their “Stop-loss” settings. Stop-loss can be triggered in the event of a turn in the market. 

Cryptohopper market making bot also provides a revert and backlog feature, where it can move all the failed orders to the Traders’ backlog. Traders can also revert all their cancelled orders from the backlog if Traders decide to revert back a failed market maker orders and re-execute the orders. There are many more settings on reverting back orders that can be automated with configuration, to name of the settings, only revert if it will lead to a profit, or revert/not revert with market trends such as neutral trend, downtrend or uptrend.

In order to slow down the market making bot, Cryptohopper introduced the cool down feature, which the bots cooldowns by removing the order after a certain time has passed.

Cryptohopper has designed a dashboard with some widgets for Traders to monitor the market making bot in action. There is a trading view widget which is a visual representation of the current prices.

Cryptohopper Trading Bot Review

Among other widgets available on the Cryptohopper dashboard, there is the order book visualizations with the possibility of manual Market Making which enables buying and selling to be connected to each other and will input that order into the Market Making bot logs.

Cryptohoppe also has created an inventory for all failed trades to be stored in a place called backlog. In order for Traders to be able to use the Cryptohopper Market Making bot they need to be subscribed to the “hero hopper Pro” package, which costs a monthly subscription fee of 99$.

 

The Arbitrage bot:

The Arbitrage bot of Cryptohopper is designed to capitalize from changes across different markets. The bot allows to trade discrepancies in the market, taking advantage in market price between the same pairs on different exchanges.

Just like the market making bot, the Arbitrage bot also requires a pre-setup procedure to get going with the bot. The procedure starts with setting up the maximum open time of all buy orders, which determined the number of minutes a buy order remains open before the order is cancelled. Following that, there is the maximum open time of all sell orders which does the same thing but for all sell orders.

The setting up procedure then takes traders to exchange setting, where traders should specify two exchanges that would like to perform their arbitrage. Afterwards, they will set the percentage sell amount, which it should use to create the amounts which are being traded and then the Arbitrage amount per market which how much of trade at a time should take place.

In case interested trader would like to utilize exchange specific configuration, they can set minimum profit that they would like arbitrage with. Additionally, there are options to have the maximum open time of the Arbitrage. Traders are also given the possibility to simultaneous arbitrages which determine the maximum number of simultaneous or concurrent arbitrages. Furthermore, they set rate on buy and sells which specify the amount the Arbitrage should check. 

The Arbitrage dashboard also includes a backlog where all failed trades will be stored. The dashboard also has the latest Arbitrage trades that were both successful and failed. There are also other widgets inside the Arbitrage dashboard, e.g. exchange arbitrage dashboard results, the last five trades and market Arbitrage results.

Strategies:

Traders using Cryptohopper platform could create a trading strategy with a collection of indicators they have selected. These are the indicators to buy and sell trades. Cryptohopper has created a strategy designer feature where traders create and custom their strategies. There are three ways trades can utilize a strategy. First is to use Market Strategies, these are strategies bought on the Marketplace (we cover features of Marketplace later in this article). Strategies bought from Marketplace which could also be automatically be updated every time the seller of the strategy makes changes on the strategy. Second is built-in strategies, Cyrptohopper offers a set of built-in strategies that are offered free of charge. These are rather basic strategies such as uptrend strategies, buy the dip strategies, Bollinger strategies and etc. Third and last is My strategies, these are custom made strategies that traders built.

Strategy designer:

Strategy designer is a place where traders can personalize their technical analysis setting. There are given a set of indicators where traders can find and configure a wide selection of trading indicators. Traders on cryptohopper can decide on the chart period, buy and sell signals and candle period when selecting an indicator. With candle patterns, traders can directly respond to price movements from the chart data of an exchange. 

Furthermore, traders can design their strategies by adding a JSON code, this section is designed for more technical and programmer traders. These traders could also modify existing strategies. Once strategies are configured and up and running, Cryptohopper strategy dashboard allows traders to monitor their strategies. 

Cryptohopper Marketplace:

The marketplace is a section within the strategy creation process. This unit is designed solely for social and mirror trading. This is where traders with a usually lower level of experience and knowledge in trading can browse already created strategies and use it for their funds to invest with.

There is a set of strategies and templates available in the marketplace. Each template and strategy has a corresponding base-currency and exchange. Therefore templates can be chosen based on traders preferences. Additionally, all templates have information about their ratings, total downloads, modifications and recentness. 

The marketplace also consists of Signalers. All signals in the marketplace correspond to an exchange. A trader can configure their trading using only signals. The Signal configuration could limit orders. The setting also allows traders to take profit with a given percentage set.

 

Strategy statistics:

Cryptohopper provides traders with a set of statistics in order for traders to be able to monitor the performance of their strategies and trades. There is a variety of ways provided in the statistics dashboard to see how trades and strategies are performing. 

The time period for all buy and sell order, allocation of funds based on currency, open positions and base currency reserved. Traders can view their profit stats basing on currency invested on, base currency returns, the base currency gained/lost in current positions and trading fees paid. 

Profit based on sell triggers is another statistic available for traders to monitor profit related to percentage profit, trailing stop loss and auto close within time. Traders can also view profits based on buy triggers that we generated by strategies, signalers, trailing stop buy.

Cryptohopper Academy

For traders who would like to be familiar with Cryptohopper as a trading platform, there is a tutorial-like instruction supported by Cryptohopper itself and other instructors can also use this academy portal to provide education knowledge to interested traders.

 

Our take:

Cryptohopper has done a decent job working out a tool that traders would feel comfortable doing their trades. We really liked the interface and how they have designed a user journey that would fit a different type of traders with different level of expertise. The wording in the platform is well explanatory and hints around important features. Though, as a solution provider for professional crypto market makers, we believe the assessment of market trends are done manually by users and very sensitive to human error. The market making bot has a low ability to manage more market at once and needs of content human supervision.

Check our take on how trading bots for professional crypocurrency traders are build and designed.

Bitcoin and Arbitrage: hand in hand

Liquidity, the greatest challenge for crypto exchanges

There is a general consensus that liquidity is the most important factor for all tradable markets. The ability or lack thereof, of a market to allow assets to be bought and sold at stable prices, is a major issue associated with cryptocurrencies. 

According to a recent Encrybit report, one in every three investors is worried about the problem of liquidity on crypto exchanges.

 

The importance of the liquidity problem requires tools and methods to manage markets liquidity. This document proposes an approach to monitor and manage liquidity. Monitoring is intended for the exchange management to understand their platform’s current liquidity level and how to improve it. Liquidity management starts with the exchange engaging professional market makers or using proper tools to take care of  liquidity. Last but not least exchanges should track the market impact of trades of different sizes, and oblige their market makers to fulfil certain conditions.

 

Empirica brings experience, tools, know-how and best practices in the area of technology for liquidity analytics and liquidity provision from capital markets to digital assets. We have been active in the market since 2011, working with stock exchanges and market makers with a track record on automated liquidity provision and measurement. 

 

How can an exchange manage its liquidity

 

Both for those who are just launching a new exchange or who have been operating an exchange for some time already, it is crucial to monitor liquidity metrics of all markets.

 

Read more about our tool for monitoring crypto exchange quality – Liquidity Analytics Dashboard

 

As in any tradable market, liquidity is provided by market makers, who mostly use automated market making algorithms. However, crypto exchanges have an alternative to the external market makers, as they are able to take this crucial aspect of exchange – the provision of liquidity – into their own hands.

 

Regardless of whether they use external market makers or an internal market making desk, crypto exchanges should outline to the liquidity providing party certain conditions pertaining to how the liquidity is provided and then constantly monitor the execution of these obligations. 

 

With proper tools, exchanges are able to track liquidity metrics and are able to react accordingly if agreed conditions are not met. Analytic tools also allow exchanges to compare liquidity in their markets to other crypto exchanges.

 

Monitoring liquidity

 

When executing a transaction, most investors only consider explicit transaction costs (taxes, commissions, fees). But that is only a part of the total cost. The larger the trade, the more dominant the part of the cost taken over by implicit costs.

 

Total transaction costs = Explicit transaction costs + Implicit transaction costs

 

One of the most important implicit costs to consider is market impact, also referred to as slippage. Market impact is a result of the price slipping down or edging up when you trade an asset. As the investor can not execute the entire order at the best offer, the trade is moved down the order book.

 

Exchanges, which want to attract not only small but also bigger investors, should monitor market impact and other important liquidity metrics in all of their markets.

 

Liquidity provision

 

To increase liquidity, crypto exchanges use market making services from external parties. This is a standard practice in any financial market.

 

Market makers

 

A market maker is a company or individual that regularly buys and sells financial assets at a publicly quoted price to provide liquidity to the markets. Their role is to satisfy market demand.

 

Crypto exchanges need market makers. If liquidity is low on a venue, exchanges usually try to attract market makers by the following methods:

  • Decreasing maker trading fees
  • Sharing profit from taker fees
  • Paying market makers for their activity

 

It’s  a “chicken or egg” problem. New exchanges and exchanges with low liquidity need market makers to attract other investors. The market makers, however, do not want to enter illiquid markets as there is not much volume to be made from takers and there is also additional business risk involved. Hence many illiquid exchanges need to pay market makers for their services. 

 

While working with crypto exchanges we often hear multiple reasons as to why crypto exchanges are not happy with their market makers. The main problems include:

  • Market makers choosing to support trading pairs that are most liquid; they are not interested in making markets on less liquid pairs
  • Spreads maintained by market makers are too wide
  • Market makers come and go in the markets that they promise to take care of, so exchanges would like to have tools tracking the activity of their liquidity providers
  • Market makers do not keep the order sizes as promised

Liquidity provision tools for crypto exchanges

 

Crypto exchanges have an alternative to market makers, or a complementary approach. They are able to run an automated market making desk themselves. In order to do that, though, they need funds, proper liquidity provision algos and a trader to monitor them.

 

Market making requires a good combination of technology and some trading skills. The algos must be low-latency and capable of scaling to thousands of orders per second, on numerous trading pairs. It needs a disciplined approach to trading and risk management. 

 

There are many market making tools on the market. They range from simple black-box bots to sophisticated algorithmic engines with market making capabilities.

 

When searching for self liquidity provision tools one should be considering the following criteria:

 

  • Reliability

 

Market making algorithms should work 24/7, and be able to recover from unexpected situations like connection problems with an exchange.

 

  • Security

 

Market making systems have  access to the funds of the exchange, so it is important to choose from proven solutions.

 

  • Transparency

 

In the case of black-box algorithms, the bot developers should be widely known in the community. Exchanges should consider skipping bots and going for proven institutional-grade market making solutions available on the market.

 

  • Parametrization

 

In the case of algorithmic market making it is good practice to choose solutions that enable parametrization and tuning up of execution according to the current market situation.

  • Access to source code and custom changes

Ideally crypto exchanges should have an option to take over the market making algorithms source code and let their team develop and tune it further. Very often exchanges might want to add secret sauce to the algorithms that will create their competitive advantage in the market. 

 

Read more about our tool for market making strategies for crypto exchanges  – Liquidity Engine

 

Competing with other exchanges is a challenge today. In July 2019 services like CoinMarketCap or coinpaprika listed about 260 exchanges. However, Empirica’s internal research shows that there are currently more than 600 crypto exchanges in various stages of maturity, and further new exchanges being launched every month. Every exchange is trying to attract new investors, but it is clear that at some point only those exchanges with the best liquidity will survive. That is why crypto venues should not only manage their own liquidity but also observe the liquidity level of their competition, and identify inefficiencies that can be addressed.

 

About us

Empirica is a trading software company that specializes in liquidity measurement and liquidity provision software that can help exchanges manage their liquidity. Empirica is offering solutions such as Algorithmic Trading Platform used by professional cryptocurrency investors, crypto market makersrobo advisory systemcrypto trading bots and cryptocurrency exchange software development services.

 

The biggest market maker in Poland uses Empirica Platform

It’s been two years since Empirica has successfully deployed the full version of Algorithmic Trading Platform for Dom Maklerski Banku Ochrony Środowiska (DM BOS Brokerage House). Since then DM BOS has become the most active market maker on Polish capital market, running its market making and algorithmic trading operations through Empirica’s platform.

With a great pleasure Empirica would like to inform that DM BOS was lately awarded as Polish Capital Market Leader 2016 by Warsaw Stock Exchange (WSE).

The Gala was attended by representatives of the most important capital market institutions: issuers, brokerage houses, banks, investment firms, industry organisations and associations. DM BOS was awarded in following categories:

 

  • for the biggest share of a local market maker in trading in equities on the Main Market in 2016,
  • for the biggest share of a market maker in the volume of trade in index options in 2016 on the derivatives market,
  • for high quality of the reporting of trades to KDPW_TR in 2016.

– We are very pleased to see, that using our software DM BOS was awarded by WSE in main categories. I would like to sincerely congratulate managers of DM BOS such amazing results for the 2016. Since 2012, when we started our cooperation we are committed to continuously develop and enhance our algorithmic trading platform in order to achieve the highest technical requirements and to satisfy different and changing needs of our customer. I would like to thank DM BOS once again for the opportunity to be a part of their winning market making strategy. – Michal Rozanski, CEO of Empirica

WSE is the biggest securities exchange in Central and Eastern Europe and organises trading on one of the most dynamically growing capital markets in Europe. WSE operates a regulated market of shares and derivative instruments and the alternative stock market NewConnect for growing companies. WSE is developing Catalyst, a market for issuers of corporate and municipal bonds, as well as commodity markets. Since 9 November 2010, GPW is a public company listed on Warsaw Stock Exchange.

About us

Empirica is a trading software company focused on developing the potential that cryptocurrencies bring to financial markets. Empirica is offering solutions such as Algo Trading Platform used by professional cryptocurrency investors, market maker software, robo advisory softwarecrypto trading bots and trading software development services for companies from capital and cryptocurrency markets.

Introduction to Liquidity Metrics

This paper offers a summary of indicators which may be used to demonstrate and examine liquidity developments in financial markets. These measures are employed in foreign markets, currency, and capital markets to exemplify their usefulness. Lots of measures have to be considered since there isn’t any single theoretically appropriate and approved measure to ascertain a market’s level of liquidity and since market-specific variables and peculiarities have to be considered.

 

Read more about our tool for monitoring crypto exchange liquidity with Liquidity Analytics Dashboard

 

Liquid markets are perceived as desired due to the advantages they supply, such as allocation and data efficiency. The advantage might not be accurate for investors jointly. As Keynes noted (1936, p. 160):”For the simple fact that every individual investor selects himself that his devotion is”liquid” (although this cannot be accurate for many investors jointly ) calms his nerves and leaves him much more prepared to conduct a threat.” Consequently, recent crises in financial markets, particularly, have sparked research about the way to gauge the condition of market liquidity and to better forecast and protect against liquidity crises.

 

This paper has two functions. It offers a summary of numerous distinct theories associated with liquid financial markets.

 

Analysts motivated this job. Like Borio (2000), who reports that at the run-up to financial disasters, markets frequently seem unnaturally liquid, but through times of anxiety, liquidity will vanish.

 

Market participants comprehend a financial advantage liquid, should they can sell considerable quantities of the advantage without impacting its price. Liquid financial assets are characterized by having trade costs; simple timely and trading payoff; and trades with limited effect on the market price. The significance of a few of the qualities of liquid markets can alter over time. During times of equilibrium, for example, the perception of the asset’s liquidity could reflect trade costs. During times of anxiety and principles that are changing, instantaneous price detection and adjustment to a new balance becomes more significant.

 

Liquid markets often display five attributes:

  • tightness
  • immediacy
  • depth
  • breadth
  • resiliency

 

Tightness refers to trade costs, like the gap between buy and sell prices, such as the bid-ask spreads in markets, as well as costs. Immediacy signifies the rate with which orders could be implemented and, within this context too, settled, and consequently reflects, among other items, the efficacy of their trading, clearing, and settlement systems. Breadth implies that orders are big and numerous in bulk with minimal effect on prices. Resiliency is a feature of markets in which orders flow to fix order imbalances, which are inclined to move prices away from what fundamentals warrant. Depth refers to the existence of abundant orders, either actual or easily uncovered of potential buyers and sellers, both above and below the price at which a security now trades. 

 

These conditions reflect various measurements of the degree to which an asset immediately and with no costs can be changed into legal tender.

 

In these conditions are to some degree overlapping. The majority of the available data do not correspond with those measurements, which disrupts their measurement. A variety of aspects have to be considered, because they influence the measurements of liquidity. They vary in the microstructure of this market, the bank’s implementation of its policy.

 

Knowing the microstructure of this market is crucial, when proxies, such as bid-ask spreads and turnover ratios, are utilized as liquidity signs. A market may be a platform which enables sellers and buyers to interact, a physical place. Professors have a world in your mind using a Walrasian auctioneer performing a price tätonnement procedure ensuring trading in market clearing prices. In summary, prices are a statistic. In the professional’s world, however, trading can occur in a variety of platforms (as an example, trader or auction markets) in non market clearing prices due to factors like market illiquidity.

 

It is contended that traders offer liquidity, because they offer a market. But because traders usually attempt to square their positions maintain a predetermined structural position prior to the close of the day they just “supply” liquidity by taking stock positions provided that they presume sellers and buyers will continue to emerge. In an auction market, sellers and prospective buyers distribute orders, and a digital system or agents will suit them. Auction markets are order or price could be continuous if there are trades and driven. Market intermediaries in auction systems can additionally take stock rankings in order to ease liquidity (e.g., so-called experts in broadly traded securities). Trading systems make it possible for participants to submit limit-orders, which enhance the liquidity. The intermediaries having access to the trading strategies can cover their costs by charging a commission or else they quote ask and bid prices to be paid by the sellers and buyers.

 

A distinction is made between the market, in which problems are offered, and also the market, where individuals who’ve Purchased the problems at the market can resell them. The market consequently provides liquidity.

 

It’s very important to comprehend the reporting demands of trades in markets prior to trading volumes may be utilized as a liquidity index.

 

An advantage is liquid if it can be converted to legal tender, which each definition is liquid. Some financial statements, such as require deposits, are almost perfectly liquid–provided that the credit institution is liquid as they may be converted without cost or delay to cash during regular conditions, while the conversion of different claims to legal tender can involve agents’ commissions, settlement delays, etc.. The emphasis is on trade costs and immediacy. It’s regarding the ease by which, in the lack of info changing an asset’s fundamental price quantities of this asset could be disposed of quickly at a sensible price.

 

A financial market’s liquidity is dependent upon the substitutability among the assets traded in a market, and the way liquid every one of those assets are. Whether there are issuers in the bond markets and equities markets, credit risk could protect against substitutability and result in segmentation of this market. Regardless of having the exact same issuer, human assets might nevertheless have distinct attributes, for example different maturities on the market for government securities, distinct voting rights for preference stocks, etc.. This aggregation problem leaves difficult an effort to employ measures with the goal of measuring a market’s liquidity.

 

This paper explains measures to judge an asset’s market liquidity with a view to evaluate whether a financial market, or in minimum a few of its sections, can be distinguished as liquid.

 

Our next article will classify liquidity measures in line with this size they greatest measure. Additionally, it discusses factors that might impact capability and their interpretation to catch a specified facet of liquidity. Issues related to assemble the measures will be also discussed. Section Ill uses the liquidity measures to the market, currency, and capital markets of a group of nations. Section IV lists a few of the qualitative aspects that are important to look at when assessing the liquidity measures across markets and states. Section V notes liquidity measures during times of stress may vary.

About empirica

We are trading software company focused on developing the potential that cryptocurrencies bring to financial markets. Empirica is offering algorithmic trading tools used by professional investors and solutions for cryptocurrency liquidityRobo Advisory softwarecrypto trading bots and trading software development services for companies from capital and cryptocurrency markets.