A Whole New World: Trading Signals within Online Trading Platforms
by Patrick Oberhaensli, on Apr 18, 2019 3:58:14 PM
In this article, we will not only discuss what trading signals are and how they can be categorised but also address on what basis they are built. Beyond current applications, we will also show the potential for the future of trading signals.
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The "Machine" Making Decisions
Trading signals are alerts on which a trader can effectively trade either according to a strategy or by having a “machine” making the decisions instead. In both situations, its possible to apply a robo-advisor – an investment robo-advisor, to be precise – but when the implementation is done “automatically” on the basis of a mandate, the robo-advisor is in fact more integrated. If the investor were to use the signals simply as a second opinion, then the service can hardly be considered as a trading signals service but it nonetheless has a value-adding function: and it could well be a first step in the case of an institutional type-of-investor.
Such a strategy is often called a system (a specific type of system) as it will rely on quantitative asset management. In regards to more advanced strategies not only long or out-of-the-market positions will be considered but short positions as well. At the origin of the system, there is a model or a set of models that could also be combined. A model is by definition a representative simplification of the real world. Models are developed either internally or externally – eventually in a cooperation as well.
Trading Signals Expectations
In the context of an online trading platform, the trader may find a robo-advisor-labeled offering that, via an asset management mandate, will establish an asset allocation. It will then typically be implemented with (passive) Exchange Traded Funds and be rebalanced according to specified rules. The expectations investors have regarding a trading signals service are in fact much higher, also in terms of risk-adjusted return – a likely reason why advanced or (quite) unique trading signals are still uncommon.
Now, in terms of models commonly used to generate trading signals, we can state the following: within quantitative approaches, one can find applications of technical analysis but also more general “Quant”-techniques or even Quantamental. The Quantamental practice implies the use of fundamental data in a purely quantitative way. Technical analysis takes into consideration that the price history (in particular but it may include trading volume as well) tells the “whole story” and allows to extrapolate future movements, which is in contradiction with even the weak form of the Efficient Market Hypothesis (EMH).
For trading signals purposes, trend following is the most common. A big advantage of that, is the possibility to realise positive returns by going in a short position when a market is actually… falling - an example of that are the equity markets during the 2008-2009 crash. The main difficulty is being able to correctly identify a real trend – and loosing as little money as possible when the trend wasn’t one in fact (referred to “false signals”). But “Quant” allows investors to develop a large set of different strategies that can also diversify trend following: innovation is the key, and that requires a combination of expert techniques associated with the corresponding experience and creativity.
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The Future of Trading Signals Service
The great news: in the future we are likely to see the trading signals services expand rapidly, even if beyond the strategy development matters there are also important Information Technology investments that are necessary. And regarding Quantamental, the hype about big data or better said… smart data becomes clear, even though this is a much more general question about “Quant”. That’s because a huge volume of fundamental data is available today at the micro-level, the company or sector related information but also an increasing quantity at the macro – whole economy – level.
It is also important to understand that the strategies related to trading signals shall be self-risk-managing (and risk-controlling): that’s within its DNA – related to the automated process. At the same time, the provider could “logically” offer different levels of (reasonable) leverage, increasing that way the attractiveness of the service. Finally, the platform provider could also explore different ways to bring the signals in the right light from a graphical perspective: advanced graphics are a set of tools the provider is anyway used to develop further.
Another key advantage of the trading signals offering is possibly still underestimated: given its quantitative nature, the platform provider can “easily” make available the necessary “due diligence” figures. Why? Because there are no discretionary decisions made by a portfolio manager as there is simply… no portfolio manager. The “human intelligence” is integrated in the development of the models themselves. The potential user can then analyse the strategy with much more depth –and certainly beyond a detailed description of the process.
Trading signals are a service that allow the online trading provider to differentiate its offerings in a very effective way. This can already be seen today if the pricing model is adapted, but will become even more noticeable in the future (talking about highly “intelligent” robo-advisors). At the same time, it must be clear that an over-simplistic offering adding little to no value could rather disengage platform users. Trading signals open the possibilities to a whole new world of investing, an opportunity which should not to be missed.