[:cs]Optimalizace obchodního systému[:en]Investment strategy optimization[:]

[:en]An investment strategy is basically a list of exact rules (algorithm), which defines investment decisions (buy and sell orders), can analyze and manage real-time risks based on current market situations. Investment decisions can be divided into two groups – entry rules for opening investment positions and exit rules for closing investment positions. Our research department uses a method which takes these two rule categories and applies different development attitude on each of them.

Standard old-fashioned approach

Standard old-fashioned development approach is based on using financial experts‘ rules what depends on experience, knowledge and personal attitude. These entry and exit rules are usually very subjective and may lack a deeper analysis of various datasets (news, fundamentals, technical, psychological). However, it doesn’t mean that an investment algorithm containing these rules is wrong and can’t generate profit in a long-term period. It can be very robust and stable.

New era approach

Our research department loves new technologies which can help to deliver higher and more stable performance, lower drawdowns with a shorter recovery period, better Sharpe ratio and other key performance metrics. Current research is focused on implementing machine learning and genetic programming to investment strategies – specifically to improve the effectiveness of the exit rules. We use a few simple entry rules defined by a financial market expert (old-fashioned approach), but exit rules are generated by modern technologies for deep analysis of different datasets. Exit rules contain simple or sophisticated patterns founded by genetic programming and machine learning, but this whole approach is still under expert control and each rule is validated with strict conditions to avoid over-fitting.

Customers will be able to benefit from these algorithms by using them directly on their own accounts through specialized trading platforms or by investing in the big funds which will use these algorithms.

Vision

Our vision is based on improving human skills with data analysis technologies and deliver higher and more stable performance. We are not trying to take-over human decisions, but we are trying to make them better.

If you are interested in more information stay tuned to our website or get in touch! It would be a pleasure to invite you for an meeting at our office.

Michal Dufek[:]

Stock Screener

[:cs]Jak jsme Vás informovali v našich předchozích příspěvcích, náš tým se nezabývá pouze state-of-art technologiemi a researchem obchodních strategií, které využívají hedgové fondy. Do našeho portfolia patří i běžné a relativně jednoduché reportovací a analytické nástroje. Jedním z těchto nástrojů je intuitivní stock screener, který můžete využít k jednoduchému seřazení “nejlepších” titulů dle Vámi navolených preferencí.

Další stock screener?

Většina stock screenerů je založena na tom, že máte k dispozici určitý universe (množinu) aktiv, který prostřednictvím filtrů (které máte k dispozici) prosíváte, dokud Vám nezbydou taková aktiva, která vyhovují předvoleným kritériím. Uživatelskou nevýhodou takového workflow je ten fakt, že potřebujete přesně vědět, co hledáte. Valná většina “hledajících” uživatelů ovšem v počátečním okamžiku neví přesně, dle jaké metodiky svoje výstupy hledá.

Náš stock screener tento fakt respektuje a řeší jej pomocí dvoustupňové klasifikace výstupu.

Jak to funguje?

V našem screeneru nejprve intuitivně volíte priority (technicky vyjádřeno se jedná o filtry), díky kterým vyjadřujete svoje preference (měna investice, riziková averze, investiční horizont apod.). Díky těmto preferencím nadefinujete metodu hodnocení skenované množiny aktiv, a tedy v důsledku Vašeho výběru dojde k nastavení hodnoticího modelu, který škáluje jednotlivé assety do žebříčku.

Black box, o kterém nevím, co uvnitř dělá?

Na výstupu dostanete seznam akcií, které i) vyhovují Vašim prioritám a ii) jsou seřazeny “od nejlepšího” dle hodnocení modelu, který reflektuje Vaše preference. Jednotlivá kritéria obsažená v hodnoticím modelu uvidíte ve výstupní tabulce spolu s ohodnocenými assety.

Nemůže se tedy stát, že byste nevěděli proč a jak model k výsledku došel. Hodnoticí model není pouze transparentní, ale je také libovolně upravitelný prostřednictvím nastavení indikátorů, které komplexní hodnoticí model utváří. Tuto funkci mohou ocenit zejména odborně zdatní analytici, kteří si dle vlastního úsudku přejí určité technické indikátory preferovat, nebo naopak diskriminovat.

Pokud Vás zajímá více o této aplikace, sledujte náš web nebo se na nás přímo obraťte.

Michal Dufek[:en]As we informed you in our previous posts, our team is not dealing only with state-of-art technologies and research of business strategies using hedge funds. Our portfolio is also complemented by common and relatively easy reporting and analytical tools. One of these tools is an intuitive stock screener that can be used for easy sorting of “the best” titles according to your selected preferences.

Another Stock Screener?

Most of the stock screeners are based on the fact that you have a certain universe (group) of assets that is refined through available filters until assets which match the selected criteria are found. User disadvantage of such workflow is the fact that you exactly need to know what you are looking for. However, in the beginning, the vast majority of “searching” users does not know precisely which methodology to use to search for their outcomes.

Our stock screener respects this and solves it by using the two-stage output classification.

How Does It Work?

In our screener, first of all, you intuitively choose priorities (technically speaking – filters), thanks to which the preferences are expressed (investment currency, risk aversion, investment horizon etc.). With these preferences, you define the method of the evaluation of the scanned asset set and, as a result of your choice, the evaluation model is set up, scaling individual assets to a chart.

Black Box I Have No Idea What Is Doing Inside?

On the output, you will be given a list of shares which a) meet your priorities and b) are sorted “from the best” according to the evaluation model which reflects your preferences. Individual criteria included in the evaluation model can be seen in the output table together with rated assets. Therefore, there is no chance of not knowing why and how the model reached the outcome. The evaluation model is not only transparent but also freely adjustable via indicator settings which form this complex evaluation model. This function can be appreciated especially by professionally competent analysts who want to use their own judgement to prefer or, on the contrary, to discriminate certain technical indicators.

If you are interested in more information about this application, stay tuned to our website or reach us directly straight away.

Michal Dufek[:]