|We have just released beta of Empirica – Algorithmic Trading Paltform for retail investors! It’s lifetime free for development, testing and optimizing of trading algorithms.
Our development team (exactly this team who implemented the entire system) also provides full support in algorithms development as well as connectivity to brokers. If you need help just contact us.
Among many features what is unique is our exchange simulation where you can influence market conditions under which you test your algorithms. No others software offers such a realistic level of simulation.
In paid versions we offer the execution of algorithms in robust server side architecture.
We strive for your feedback!
Empirica Trading Platform – http://empirica.io
Articles related to quantitative trading and software tools aiding automated investment operations.
Empirica has successfuly 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 Warsaw Stock Exchange (Universal Trading Platform delivered by NYSE Technologies), as well as the integration with transaction systems of brokerage house. Additionally we have fulfilled and successfuly passed tests regarding the highest security, stability and performance requirements.
This implementation is an important milestone for our system. The usage by team of market makers is a proof that our system is capable of performing high-throughput and low latency operations on level required by most sophisticated traders on the capital marketets.
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
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 Universal Trading Platform delivered by NYSE Technologies. The same system is used by many other European and world stock exchanges. Fulfilment of technical criteria of Warsaw Stock Exchange makes certification for those markets only a formality for our platform.
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…
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:
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
Time-Weighted Average Price (TWAP) is another trading algorithm based on weighted average price and in compare to Volume-Weighted Average Price its calculations are even simplier. Also it’s one of the first execution algorithms and unlike most algorithms nowadays it’s passive execution algorithm that waits for proper market price to come, doesn’t chase it.
As TWAP doesn’t bother about volume it’s extremely simple to obtain it. All it takes is to get Typical Price for every period bar using equation below and then calculate average of Typical Prices.
Typical Price = (Close+High+Low+Open)/4
Let’s just take a look at example results calculated on 1-minute interval intraday Morgan Stanley’s stock.
The most common use of TWAP is for distributing big orders throughout the trading day. For example let’s say you want to buy 100,000 shares of Morgan Stanley. Putting one such a big order would vastly impact the market and the price most likely would start to raise. To prevent that, investor can define time period in TWAP Strategy over which they want to buy shares. It will slice evenly big order into smaller ones and execute them over defined period.
TWAP could be used as alternative to VWAP, but because of itssimplicity we have to remember about some pitfalls. Even if we slice big orders, we do it evenly, thus there is a possibility to hit on low liquidity period when our splitted order will impact the market hard. That’s why it’s recommended to use TWAP over short periods or on stocks that are believed to not have any volume profile to follow.
There is also another threat coming directly from dividing big order evenly, namely, other traders or predatory algorithms. Obviously trading in such a predictable way can lead to situation where other traders or algorithms would look through our strategy and start to “game” us.
Barry Johnson in his book suggests adding some randomness to the strategy as a solution to the issue. He says that “We can use the linear nature of the target completion profile to adopt a more flexible trading approach. At any given time, we can determine the target quantity the order should have achieve just by looking up the corresponding value on the completion rate chart.”
In practice it means that when we have run 4-hour TWAP we don’t slice the order into evenly parts, but otherwise we focus on percentage completion. So for instance we would want to have 25% of the strategy completed by first hour, 50% by second and 75% by third. That gives a more freedom into size of orders, so we can be more random with it and hence less predictable for other traders on the market.
TWAP vs VWAP
As both indicators use same mechanism, i.e. weighted average price, it’s common to compare them. Despite that VWAP’s nature is more complex and includes volume in its calculations, on instruments with low turnover TWAP and VWAP values can be close. On the other hand when a session starts to be more volatile both indicators will diverge.
On a table below there are TWAP and VWAP calculated for whole trading day. As we can see at the beginning of the trading day the difference is less than a cent, but on close the difference raised up to 2 cents. It happened because during the day there were some small volume trades for lower price that didn’t affected VWAP, but did TWAP.
TWAP Strategy is another great tool for executing big orders without impacting the market too hard. Like everything it has its own pros and cons and it’s up to us to select if TWAP will be the best strategy to use for our case or maybe we should consider using VWAP or other strategy.
- H. Kent Baker, Greg Filbeck. “Portfolio Theory of Management” (2013) , pp.421
- Barry Johnson “Algorithmic & Trading DMA – An introduction to direct access trading strategies” (2010), pp. 123-126
Nanex released a video showing the results of half a second of worldwide high frequency trading with Johnson and Johnson stock. I simply sped up the footage to get a better feel of what it looked like. Blow Your Mind.
CNN’s Maggie Lake gets a rare look inside the super-fast trading industry.
Dr. Sean Gourley is the founder and CTO of Quid. He is a Physicist by training and has studied the mathematical patterns of war and terrorism. He is building tools to augment human intelligence.
Citadel Group, a high-frequency trading firm located in Chicago, trades more stocks each day than the floor of the NYSE.
One of the scariest high frequency trading algos ran in the electronic S&P 500 futures (eMini) contract on January 14, 2008 starting at 2:01:11Eastern. During its 7 second reign, there were over 7,000 trades (52,000 contracts), and the price eventually oscillated within milliseconds, the equivalent of about 400 points in the Dow Jones Industrial Average!
HFT is controlled by proprietary trading firms and spans across multiple securities, including equities, derivatives, index funds and ETFs, currencies and fixed income instruments.For HFT, participants want the following infrastructure in place:
– High speed computers, which need costly and regular hardware upgrades;
– Real time data feeds, which must avert even the delay which could affect profits; and of a microsecond
– Computer algorithms, which are the heart of HFT and AT.
Benefits of HFT
– HFT is beneficial to traders, but does it help the total marketplace? Some market that is overall gains that HFT assistants cite contain:
– Bid-ask spreads have reduced due to HFT trading, making markets more efficient. Empiric evidence contains that after Canadian authorities in April 2012 imposed fees that deterred HFT, studies indicated that “the bid-ask spread rose by 9%,” possibly due to diminishing HFT trades. And thus facilitates the effects of market fragmentation.
– HFT assists in the price discovery and price formation process, as it is centered on a high number of orders (see related: How The Retail Investor Profits From High Frequency Trading.)
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