Discretionary goes quant, and quant goes fundamental

Why both a desk trader with two decades of experience and the founder of a multi-million quant fund look at the same educational programme for self-development?

I am frequently asked about the reasons I run educational programmes in systematic trading; well, there are a number of reasons, and meeting interesting people from the industry is one of them. Mentoring is a bi-directional process, and of course I also learn a lot from my students — and sometimes it allows to come to very interesting conclusions not only about an individual student’s personality, but about general trends in the trading industry in whole.

Some time ago I started to note that professionals from seemingly diametrically opposite poles of the industry demonstrate equally strong interest in our educational programme. For example, one of them is a veteran desk trader with quite a solid background and experience of work in very large family offices, and another — a founder of a 100% algo fund with several millions in assets under management and a strong track record.

At first glance it’s hard to understand why both of them could be interested in the same education because it’s equally hard to imagine two other professionals which would be more unlike each other. The former has always made trading decisions based only on his discretion, the latter has never placed a single discretionary trade. The former relied solely on market research and analysis of various economical factors, while the latter ran only complex algorithms to analyse price time series. Generally speaking, the first student has always trusted only in qualitative market analysis, and the second — in quantitative.

So, what was the reason which brought both of them to the same place?

In my opinion the main reason is the global changes in markets themselves, and not only in their structure, but also in the mentality of the key decision makers, in the way trading decisions are made. At this point it would be very tempting to say that these changes result from the wider acceptance of algo trading — and this is today commonplace in many publications. However upon a more thorough examination we can see two processes here.

First, indeed, the popularity of algo trading is currently at its peak and still growing, and of course it couldn’t have left the markets untouched. The public opinion formed by thought leaders and numerous publications tend to consider algo trading as a definite means of improving the consistency of returns — even though there is no uniform, clear understanding of what algo trading actually is. Thus there’s no wonder that discretionary traders start to look for modern solutions to be in line with the most recent developments in the industry.

At the same time experienced algo traders tend to note the need to constantly re-adapt their algorithms to ever changing markets along with other issues pertaining to this kind of trading business. Besides that, the fact that almost all historically record trades were made by discretionary traders also adds to the feeling that throwing away traditional market research in favour of algorithms we might have thrown the baby out with the bath water.

Therefore there’s no wonder that these two worlds find a point of mutual interest today. Our educational course in systematic and algorithmic trading has been developed to bridge the gap between these two seemingly different approaches to trading, and to use the best of the two worlds: fundamental analysis to be adequate to the market processes and their perpetual changes, and quant solutions to be more precise with actual entries and exits, to better assess risks and eliminate emotional component from trading decision making process. This way traditional discretionary traders are able to efficiently use their extremely valuable experience, and established algo traders have an opportunity to reconsider the very development paradigm to make their algos more relevant to actual market processes and to incorporate elements of traditional market research in order to improve the consistency of returns and make risks more understandable and more manageable.

Finally I’d like to note that all the aforesaid does not mean that the Edgesense educational programme is open only to established market professionals. Perhaps making the first steps in the market learning the best of these two worlds is the shortest way to consistency in trading.

— Alex Krishtop, founder of Edgesense

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