Articles related to algorithmic trading and software tools aiding automated investment operations.

Algorithmic crypto trading: market specifics and strategy development

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

Among trading professionals, interest in cryptocurrency 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 exciting 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 how we execute market making strategies for crypto exchanges

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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 and 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, restrict the possibility of algorithmic use, especially in the HFT field. This is crucial for market-making activities, which now require separate deals with trading venues.

DERIVATIVES

As for market-making, we should notice an almost non-existent derivatives market in the crypto world. 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 the index derivatives (contracts that reflect 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 popular cryptocurrencies. Combining it with highly limited margin trading possibilities and none of the index derivatives (contracts that reflect 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, cryptocurrency 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, the 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 probably will remain, one of the biggest challenges for cryptocurrency trading. Trading on bitcoin and Ethereum, and all other altcoins with smaller market capitalization, is split among over 200 different exchanges. Executing a larger volume of assets often requires seeking liquidity in 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 aggregate them internally. When an investment decision is made, the strategy splits the order among exchanges that offer the 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 cross-exchange 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 on 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 looks for differences among three currency pairs that 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 the 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 for using triangular arbitrage in the 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 the exchange’s 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 price 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 in volatile crypto markets. This situation may happen in markets with a strong bias or when market maker is quoting wrong or delayed prices, which arbitrageurs will immediately exploit. 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 exciting subjects for future articles.

Read more about how we execute market making strategies for crypto exchanges

Crypto market making

SUMMARY

Fast-developing crypto markets are attracting many 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. To embrace the fast-changing crypto environment, one needs algorithmic trading systems with an open architecture that evolves alongside the market.

VWAP Trading Strategy

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Bitcoin and Arbitrage: hand in hand

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Our platform implemented by large brokerage house!

Empirica has successfully finished the implementation of its Algorithmic Trading Platform in one of the largest brokerage houses in Poland.

Brokerage house will use our software to:

  • aid its internal trading operations, like market making of derivatives on Warsaw Stock Exchange
  • offer functionalities of our platform to its institutional clients, which will be able to build, test and execute their own algorithmic trading strategies

Implementation included connecting of our software system directly to the system of the Warsaw Stock Exchange (Universal Trading Platform delivered by NYSE Technologies), as well as the integration with transaction systems of a brokerage house. Additionally, we have fulfilled and successfully passed tests regarding the highest security, stability, and performance requirements.

This implementation is an important milestone for our system. The usage by a team of market makers is proof that our system is capable of performing high-throughput and low latency operations on the level required by most sophisticated traders on the capital markets.

 

 

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Next release of our algorithmic platform. Version 1.3.4 – has code name “The Firebolt”.

Next implementations of our Algorithmic Trading Platform by customers don’t stop us from developing the platform itself. Working agile requires us to keep the pace in short and frequent iterations, which in case of product means frequent releases, keeping the whole product line stable.

A few iterations that we planned in our 1.3.4 release, code named by our developers ‘The Firebolt’, will include among others:

– even faster real-time replication of all server-side components in master-slave mode (for deployment in larger institutions)

– extended client side backtesting capabilities

– sophisticated charting of backtesting results and statistics

– multiscreen mode of client side application

– additional web-based server-side module for administration & management

 

For those curious about the release name and unfamiliar with Harry Potter, Firebolt is:

“The state-of-the-art racing broom. The Firebolt has unsurpassable balance and pinpoint precision. Aerodynamic perfection.”
—Harry Potter: Quidditch World Cup

“The Firebolt has an acceleration of 150 miles an hour in ten seconds and incorporates an unbreakable Braking Charm. Price upon request.”
—Harry reads about the features of the Firebolt.

Speed, precision, balance, perfection. These are the words that describe our software, therefore choosing the code name was kind of obvious :).

 

The Firebolt broom

 

 

HFT – the good, the bad and the ugly

High Frequency Trading, known also as HFT, is a technology of market strategies execution. HFT is defined by technically simple and time costless algorithms that run on appropriate software optimized for data structures, level of memory usage and processor use, as well as suitable hardware, co-location and ultra low-latency data feeds.

 

Although HFT exists on the market for over 20 years, it has became one of the hottest topic during past few years. It is caused by several factors, such as May 6, 2010, “Flash crash”, latest poor situation on the market and Michael Lewis book – “Flash Boys”. Let’s look where all that fuss comes from.

 

The Bad

 

Among other things, the advantage over other market participants and ability to detect market inefficiencies is the reason why so many people critics HFT so much. Most common charges put on the table are:

 

  • Front Running – HFT companies use early access to incoming quotes to buy shares before other investors and then turn around and sell him just bought shares with slightly bigger price.
  • Quote Stuffing – Way of market manipulation by quick sending and withdrawing large number of orders. Because of speed of operations, it creates a false impression of the situation on the market that leads other participants to executing against phantom orders. Then there is nothing else to do, but to exploit favorable prices by HFT investors.
  • Spoofing – Another method for market manipulation by placing orders and then cancelling them for price increase/decrease. It is based on placing big order on the market to bait other investors, and when the market starts to react, quickly cancel it. Then new price allows to gain some profit by HFT investor.

 

But that’s just a tip of the iceberg. It can be often heard that there is lack of proper HFT regulations, exist false belief that there are Dark Pools without any regulations where HFT companies can hide their activity, and there is still active argument if HFT brings liquidity to the market or just useless volume.

 

The Ugly?

 

Bill Laswell once said “People are afraid of things they don’t understand. They don’t know how to relate. It threatens their security, their existence, their career, image.” That phrase perfectly fits to what is happening now on High Frequency Trading topic. When people would like to take a closer look on how exchanges work, probably, they would be less sceptic to High Frequency Trading.

 

Thus, on most, maybe even on all, exchanges exist two mechanism which can efficiently handle problem of quote stuffing and spoofing. First of them is limitation of number of messages per second that can be send from one client. For example on New York Stock Exchange there is a limit of 1000 messages/sec, so it means that if HFT company burst whole 1000 of messages in first half of the period, in second half it cannot send any message, so it’s cut out of the market. Other limitation used by exchanges is a limit of messages per trade. It hits even harder in quote stuffing and spoofing. In most of the cases limit is around 500 messages per trade and if someone exceed it then he should be prepared for fines. On top of it company that frequently break limits could be banned from exchange for some time.

 

If we talk about front running, first thing we have to know is a fact that front running, in the dictionary meaning, is illegal action, and there are big fines for caught market participants who use it. Front running is using informations about new orders before they will go to the order book. Let’s say Broker gets new order with price limit to process, but before putting it to exchange, he will buy all available shares at better price than limit and then he execute client’s new order at limit getting extra profit. That’s highly not allowed and that’s not what HFT companies do.

 

All they do is tracking data feed, analyzing quotes, trades, statistics and basing on that information they try to predict what is going to happen in next seconds. Of course, they have advantage due to latency on data feed and so on, because of co-location, better connection and algorithms, but it’s still fair.

Hft-scalping-for-large-orders.svg

(source: Wikipedia)

 

HFT companies have to play on the same rules as other market participants, so they don’t have any special permits letting them do things not allowed for others. Same with Dark Pools, specially that they are regularly controlled by Finance Regulators.

 

The Good

 

First, we have to know that suppliers of liquidity, i.e. Market Makers and some investors use HFT. They place orders on both sides of the book, and all the time are exposed to sudden market movement against them. The sooner such investors will be able to respond to changes in the market, the more he will be willing to place orders and will accept the narrower spreads. For market makers the greatest threat is the inability to quickly respond to the changing market situation and the fact that someone else could realize their late orders.

 

System performance in this case is a risk management tool. Investments in the infrastructure, both a software and hardware (including co-location), are able to improve their situation in terms of risk profile. The increase in speed is then long-term positive qualitative impact on the entire market, because it leads to narrowing of the spread between bids and offers – that is, reduce the transaction costs for other market participants, and increase of the liquidity of the instruments.

 

HFT AND MARKET QUALITY

 

In April of 2012. IIROC (Investment Industry Regulatory Organization of Canada), the Canadian regulatory body, has changed fee structure based so far only on the volume of transactions, adding the tariffs and fees that also take into account the number of sent messages (new orders, modifications and cancellations). In result, introducing new fees made trading in the high frequencies more difficult. It was very clearly illustrated by data from the Canadian market.

 

Directly in the following months these fees caused a decrease in the number of messages sent by market participants by 30% and hit, as you might guess, precisely the institutions that use high-frequency trading, including market makers. The consequence for the whole market was increase in the average bid-ask spread by 9%.

NO PLACE FOR MISTAKES

 

When people talk about HFT, both enthusiast and critics, it is not rare to hear that HFT is risk free. Well, on the face of it, after analyzing how HFT works you would possibly agree with it, but there is a dangerous side of HFT that can be not so obvious and people often forgot about it. HFT algorithms works great if the code is well written, but what would happen if someone would run wrong, badly tested or incompatible code on a real market?

 

We don’t have to guess it, because it happened once and it failed spectacularly, it was a “Knightmare”. Week before unfortunate 1st of August Knight Capital started to upload new version of its proprietary software to eight of their servers. However Knight’s technicians didn’t copy the new code to one of eight servers. When the market started at 9:30 AM and all 8 server was run, the horror has begun. Old incompatible code messed up with the new one and Knight Capital initiated to lose over $170,000 every second.

(source: nanex.net)

It was going for 45 minutes before someone managed to turn off the system. For this period Knight Capital lost around $460 million and became bankrupt. That was valuable lesson for all market participants that there is no place for mistakes in HFT ecosystem, because even you can gain a lot of money fast, you can lose more even faster.

 

SUMMARY

 

HFT is a natural result of the evolution of financial markets and the development of technology. Companies that invest their own money in technology in order to take advantage of market inefficiencies deserve to profit like any other market participant.

 

HFT is not as black as is painted.

 

Aldridge, Irene (2013), High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems, 2nd edition, Wiley,

 

 

Warsaw Stock Exchange certifies our Trading Platform

 

Empirica’s Algorithmic Trading Platform has successfully passed the XDP protocol communication certification, issued by the Warsaw Stock Exchange.

From now on Empirica is officially listed as the ISV (Independent Software Vendor) for the Warsaw Stock Exchange.

WSE uses the Universal Trading Platform delivered by NYSE Technologies. The same system is used by many other European and world stock exchanges. Fulfillment of technical criteria of the Warsaw Stock Exchange makes certification for those markets only a formality for our platform.

 

 

Empirica in the press – ‘The age of robots … ‘

On the first of July 2014 large polish economic magazine Puls Biznesu published an article “The age of robots comes to Warsaw Stock Exchange’. Article is quoting, among others, Empirica’s representatives speaking on the topic of the growth of algorithmic trading in Poland. Excerpts below.

‘Popularization of algorithmic trading on conferences like this one is step in good direction, says Michal Rozanski CEO of Empirica, a company which delivers Algorithmic Trading Platform. Expert says that computers will never replace a human in all the tasks. First and the foremost machines are taking over the processes that human traders had to perform manually. ‘I am sure that the development of algorithmic trading will not change the soul of the markets. It will not change to the race of engineers. It is and always has been the race on new, better ideas.’ says Michal Rozanski. 

 In his opinion both small and big investors will benefit. ‘Appliance of algorithmic trading tools increases liquidity and descreases bid/ask spreads which in turn decreases transaction cost born by all investors’ adds expert.

Michal Rozanski stresses that appliance of algorithmic trading does not limit to transactions with shortt time horizon, e.g. counted in miliseconds. Each trader can designs algorithms adjusted for it’s own requirements. ‘Let’s imagine an investor who would like to open a large position on KGHM shares or futures on WIG20. To make it happen it’s best to divde the order to tens or hundreds of smaller orders, which allows to hide her intentions from other market participants. Investor remains anonymous and minimizes market impact of her large order.’ explains Michal Rozanski. 

‘I am convinced that development of algorithmic trading can be a breakthrough moment in the history of our market, as long as we will treat the matter seriously and deliberately. On Wall Street share of algorithms in total turnover is estimated at 50%, in Europe at 40%, and in Poland still at below 20%. ‘ says Adam Maciejewski, CEO of Warsaw Stock Exchange.

Link to article…

artykul_pb_era_robotow

 

 

Empirica holds workshop on Warsaw Stock Exchange

Algorithmic trading workshop took place on 27th of July 2013 as a part of the second conference held by economic magazine ‘Puls Biznesu’ and Warsaw Stock  Exchange.

Michał Różański, representing Empirica, held workshop on the practical aspects of selecting tools for algorithmic trading by financial institutions. He stressed and covered in detail, especially one aspect of algorithmic trading which is from our practical experience constantly undervalued – namely proper testing of algorithms.

Very interesting was also a lecture of Emil Lewandowski who showed an algorithm which was able to detect a flash crash an hour before it actually happened. Algorithm was implemented, backtested, executed and presented to all the participants our Algorithmic Trading Platform. It was indeed very interesting example of application of algorithmic trading!

Among other guest were representatives from IBM, Sungard, List and M10.

Link to event:

http://konferencje.pb.pl/konferencja/705,handel-algorytmiczny-cz-ii

 

 

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Empirica with lecture at ‘Algorithmic Trading Conference’

Conference on the subject of ‘Algorithmic Trading’ was held at Warsaw Stock Exchange headquarters on the 28th of February 2013. The event was open by the WSE president, Adam Maciejewski. Among the invited guests were:

  • Peter Van Kleef, Lakeview Capital president
  • Michal Rozanski, CEO of Empirica
  • Andrzej Endler, CEO of M10
  • Michal Kobza, Warsaw Stock Exchange.

Michal Rozanski from Empirica made lecture on topic ‘Tools supporting financial institutions in algorithmic trading’. He showed not only common functionalities and architectures of available solutions, but also talked about practical aspects of hard decision every financial institution faces – to build software tools by own IT department or to buy from external vendors.

Very interesting was lecture held by Peter Van Kleef. Among other topics he shared his experiences from high frequency trading and how it has changed during last years.

We have informations that organizators intend to prepare soon another event relating to topic of algorithmic trading.

Link: GPW conference