One Year On; Text Sentiment Analytics Still A Niche Play
- It’s been a year since I opined that text-based sentiment analysis was yet to take off in retail fx trading and that’s still the case.
It’s almost a year since I penned an opinion that text-based sentiment analysis was yet to take off in retail forex trading and, I am sorry to say, that’s still the case. Yes, there are a few brokers that have taken steps to launching something but they are few.
On the one hand I am still surprised the uptake has been so slow given the potential to activate clients in a rather slow period for the asset class. I am particularly surprised no-one (as far as I am aware) is using this kind of data in copy or mirror-trading solutions, which probably wouldn’t be as expensive for the broker as building infographics or apps.
But then I guess there are other factors at play as to why the uptake has been slow.
First, when volumes (revenues) are down, as they are, companies tend to turn on themselves. That is, they cut costs – staff, development & marketing budgets (as Bart points out here) and sadly, as a result, innovation.
Second, the use of so-called ‘big data’ – of which text sentiment Analytics Analytics Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analyt Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analyt Read this Term is a small part – has not even seen a massive uptake across the entire financial services industry. If you haven’t seen it yet, check out the recent report from Aite Group on Thomson Reuters’ behalf for their survey of institutional use of big data. It’s called “Big Data in Capital Markets: At the Start of the Journey”.
A particularly poignant quote from the survey below shows that big data is still niche in financial services.
“The majority of firms active in the capital markets do not have a big data strategy in place at an enterprise level—only 5% of the 423 firms contacted felt they had enough knowledge of the subject to participate… The most popular use cases for big data within respondent firms are analytics for trading and quantitative research.”
The ‘good’ part about that quote is that the popular use case is analytics for trading and quantitative research – which is exactly where retail brokers should be using it and passing on the benefits to their clients.
So, all things considered, perhaps I shouldn’t be surprised the retail forex industry hasn’t embraced text sentiment analytics yet. After all, retail brokers are the financial market leaders in another slice of big data – online marketing. And they’re pretty good at analyzing customer trading behavior for Risk Management Risk Management One of the most common terms utilized by brokers, risk management refers to the practice of identifying potential risks in advance. Most commonly, this also involves the analysis of risk and the undertaking of precautionary steps to both mitigate and prevent for such risk.Such efforts are essential for brokers and venues in the finance industry, given the potential for fallout in the face of unforeseen events or crises. Given a more tightly regulated environment across nearly every asset class, One of the most common terms utilized by brokers, risk management refers to the practice of identifying potential risks in advance. Most commonly, this also involves the analysis of risk and the undertaking of precautionary steps to both mitigate and prevent for such risk.Such efforts are essential for brokers and venues in the finance industry, given the potential for fallout in the face of unforeseen events or crises. Given a more tightly regulated environment across nearly every asset class, Read this Term purposes. Maybe it’s just a case of ‘all in good time’. Oh, and when (if) volumes pick up again.
It’s almost a year since I penned an opinion that text-based sentiment analysis was yet to take off in retail forex trading and, I am sorry to say, that’s still the case. Yes, there are a few brokers that have taken steps to launching something but they are few.
On the one hand I am still surprised the uptake has been so slow given the potential to activate clients in a rather slow period for the asset class. I am particularly surprised no-one (as far as I am aware) is using this kind of data in copy or mirror-trading solutions, which probably wouldn’t be as expensive for the broker as building infographics or apps.
But then I guess there are other factors at play as to why the uptake has been slow.
First, when volumes (revenues) are down, as they are, companies tend to turn on themselves. That is, they cut costs – staff, development & marketing budgets (as Bart points out here) and sadly, as a result, innovation.
Second, the use of so-called ‘big data’ – of which text sentiment Analytics Analytics Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analyt Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analyt Read this Term is a small part – has not even seen a massive uptake across the entire financial services industry. If you haven’t seen it yet, check out the recent report from Aite Group on Thomson Reuters’ behalf for their survey of institutional use of big data. It’s called “Big Data in Capital Markets: At the Start of the Journey”.
A particularly poignant quote from the survey below shows that big data is still niche in financial services.
“The majority of firms active in the capital markets do not have a big data strategy in place at an enterprise level—only 5% of the 423 firms contacted felt they had enough knowledge of the subject to participate… The most popular use cases for big data within respondent firms are analytics for trading and quantitative research.”
The ‘good’ part about that quote is that the popular use case is analytics for trading and quantitative research – which is exactly where retail brokers should be using it and passing on the benefits to their clients.
So, all things considered, perhaps I shouldn’t be surprised the retail forex industry hasn’t embraced text sentiment analytics yet. After all, retail brokers are the financial market leaders in another slice of big data – online marketing. And they’re pretty good at analyzing customer trading behavior for Risk Management Risk Management One of the most common terms utilized by brokers, risk management refers to the practice of identifying potential risks in advance. Most commonly, this also involves the analysis of risk and the undertaking of precautionary steps to both mitigate and prevent for such risk.Such efforts are essential for brokers and venues in the finance industry, given the potential for fallout in the face of unforeseen events or crises. Given a more tightly regulated environment across nearly every asset class, One of the most common terms utilized by brokers, risk management refers to the practice of identifying potential risks in advance. Most commonly, this also involves the analysis of risk and the undertaking of precautionary steps to both mitigate and prevent for such risk.Such efforts are essential for brokers and venues in the finance industry, given the potential for fallout in the face of unforeseen events or crises. Given a more tightly regulated environment across nearly every asset class, Read this Term purposes. Maybe it’s just a case of ‘all in good time’. Oh, and when (if) volumes pick up again.