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Sifting the data – like a pro


We live in an age where information is at our fingertips. Our ‘fridge now talks to our microwave oven, and we have the most exhaustive encyclopaedia of knowledge in all the world’s languages in our back pocket. And we can binge-watch our favourite shows on TV at any time, whilst ordering dinner through a few clicks on an app.  

Artificial Intelligence through ChatGPT is suddenly taking a more central role in numerous industries. Who’s to say that this article you’re reading right now isn’t written by a chatbot in Nevada?

Well, it’s not – I’m sure you can see numerous contextual and grammatical errors in the copy.

Or is that just what Skynet wants you to think?


The same can be said of financial markets – gone are the days when all the information on traded companies was distributed on ‘flimsies’ by hand and later by telegraph. The tools that a trader can tap into today is tectonically-different to the old, open-outcry trading pits of the 1980s and 1990s.

Darren Sinden, writing for broker, ActivTrades looks into how to sift through the information avalanche that traders now deal with day-to-day.

Modern markets are rarely static, if ever. Instead, they are the very definition of dynamic, constantly moving and changing, as new information becomes available and new price action comes into play.

Financial Markets are the mechanism through which assets and instruments find their equilibrium price. The points at which buyers and sellers can be matched and businesses transacted it’s a process that goes on 24-hours-a-day, five-days-a-week, largely without interruption.

The amount of information that this level of trading produces is hard to comprehend and impossible for humans to digest. Against that background then traders should always be able to find a trade, shouldn’t they?

Well yes and no, because sometimes it can feel impossible to separate the signal from the background noise that the markets create. In effect, we have an information overload.

It’s possible to find something to trade in these in these circumstances. But we have to be careful that we are not trading for trading’s sake. Or that we aren’t looking for, and finding patterns that aren’t really there.  Effectively talking ourselves into a trade or trades, that don’t meet our usual trade profile or criteria.

Don’t break the rules

Having a trading process and set of rules or parameters that we stick to religiously, can help to prevent us from trading on emotions, or trading when we are bored and looking for something to do.

In my experience actioning trades that don’t fit into your trading plan is a sure-fire way to lose money and tie up precious resources. After all every time we put money into the market, we create an opportunity cost for ourselves.

Because that money can only be committed once, and while it is committed we can’t use it to act on other opportunities elsewhere. That’s one of the reasons why it’s never a good idea to use unrealised profits/account equity to open new positions – unrealised profits can become unrealised losses leaving your account facing a ‘double whammy’ as far as margins are concerned.

Systematic approach

Having trading rules and parameters that you follow can be thought of as taking a systematic approach to trading. And it’s not a bad idea to adopt a similar approach to your research and analysis. As we have already noted there are thousands of instruments traded around the world, each one of which can be viewed on various charts in multiple time frames.

If we imagine there are 10,000 tradeable instruments, each of which could be viewed on five different chart styles, over five different timescales, we find that we are faced with the prospect of having to review 250,000 charts daily – that’s the stuff of nightmares – especially when you consider that there far more tradeable instruments, chart styles and time scales, in the real world.

To avoid falling into that sort of trap we can apply a system or set of rules through which we can filter out the noise, to unearth the signals and information that’s useful to us.

Ideas generation

I recently wrote about the concept of trading ranges within a session, and how that data was information-rich. Which means it could inform our trade idea generation. Once we know the high, low, open and closing prices within a session or trading period, and have assessed their relationship to each other, we are in a far better position to decide what is likely to happen in the next trading period.

That might sound complicated but it really isn’t.

For example, an uptrend can be defined as a series of higher highs and higher lows, in the price of an instrument.  So if we find an instrument that finished the last trading period close to the high price in that period and well above the low point, and ideally above the high from the prior period, then we are looking at something that’s demonstrating upside momentum.

Conversely, if we find an instrument in which the price finishes near the lows, well below the highs, below the open, and the prior period low, then we are looking at downward price momentum in action.

One way to implement this kind of systematic approach is to utilise a spreadsheet in which we can sort and filter data. For example, the table above was created in Google Sheets and contains the Nasdaq 100 constituent stocks and simple price information thereof.

To the far right of the table, I have created a couple of qualitative screens by asking if the high price was greater than the opening price (=D7>F7) and whether the stock was up on the day i.e. is the last price higher than the previous close (=C7>H7) each of which produces a True or False flag.

By applying a data filter to the sheet, we can choose to select only those items that return a true value in each of those columns. That provides us with a much shorter list of stocks which we can examine in greater detail.

Applying simple screens to price, and other financial data can be a great way to find signals and market intelligence and screen out the incessant background noise.

The information provided does not constitute investment research. The material has not been prepared in accordance with the legal requirements designed to promote the independence of investment research and as such is to be considered to be a marketing communication.

All information has been prepared by ActivTrades (“AT”). The information does not contain a record of AT’s prices, or an offer of or solicitation for a transaction in any financial instrument. No representation or warranty is given as to the accuracy or completeness of this information.

Any material provided does not have regard to the specific investment objective and financial situation of any person who may receive it. Past performance is not a reliable indicator of future performance. AT provides an execution-only service. Consequently, any person acting on the information provided does so at their own risk.

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This article does not constitute investment advice. Do your own research or consult a professional advisor.

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