The rise of finfluencers and social implications
As retail investors increasingly turn to social media, a new study reveals how online “finfluencers” change behaviours, and why their growing reach requires policymakers to rethink the rules of financial advice in this nascent landscape.
Wong Wei Chen
25 August 2025
Since the days when Anthony Robbins (now known as Tony Robbins) was touring the lecture circuit and dishing out financial insights through bestselling self-help books, the landscape where money experts ply their trade has evolved tremendously.
Now, “finfluencers” offering financial advice through social media platforms are a phenomenon. They are fast becoming a compelling alternative to traditional financial advisors, and high-profile personalities enjoy follower bases that number in the millions. Likewise, Tony Robbins has thoroughly reinvented himself, and today enjoys a massive digital presence across Instagram, Facebook, TikTok, YouTube and other platforms.
Yet, finfluencers are relatively new to the game and operate in nebulous territory that is substantially less regulated than traditional financial advisory. Are there qualifying examinations that they need to pass first before they share their wisdom with the crowds? Should this new breed of gurus be embraced as the way forward, or is some caution warranted, at least until the industry becomes more mature?
In their working paper “The Impact of Finfluencers on Retail Investment” Hull and Qi analyse data from a social trading platform in four Nordic countries to study investors’ behavioural patterns and their implications for policymakers.
Background
The platform studied by the researchers is affiliated with a leading Northern European brokerage firm that has 300,000 users, and manages approximately €11 billion in assets. After an investor has opened an account with the brokerage firm, registration on the platform is free and the investor’s trading activity is shown to other users on the network.
An important platform feature is that trading history remains viewable on the platform, even after a user deactivates his account and leaves. This critically ensures that there is no survivorship bias in the data.
Survivorship bias occurs when only data from successful accounts that remain are available for study, while data from unsuccessful users who have left are deleted or somehow made inaccessible. Naturally, any study skewed by survivorship bias would yield unrealistically optimistic findings.
Hull and Qi’s dataset, which contains time-stamped daily transaction records for both influencers and their followers, spans nearly a decade from the platform’s inception in 2014 to early 2023.
Findings
A baseline observation was that finfluencers ranked higher by the platform enjoyed bigger follower bases. Finfluencers are assigned performance ratings based on the Sharpe ratio, which is a measure of returns calibrated against the risk taken.
As a simple illustration, a person who earned $1,000 on a low-risk investment would be ranked better than another who earned the same amount, but on a high-risk investment. Technically, the Sharpe ratio's denominator is the standard deviation of returns over time, where a larger standard deviation means more dispersion of returns (or, more simply, more volatility or risk). A large denominator, in turn, lowers the value of the Sharpe ratio, and hence the finfluencer’s rating.
“Long-term rational” finfluencers – that is, those who focus on asset value and growth potential – were the most favoured, while "short-term rational” finfluencers were the least popular. The latter category includes those who focus on frequent trading strategies, such as seeking to exploit arbitrage between markets or other short-term price misalignments.
This finding suggests that followers on this platform were economically rational – as opposed to other types of followers who gravitate towards a charismatic figure (e.g. a popular singer) and may at times exhibit highly irrational behaviour. Their preference for long-term rational finfluencers shows that they sought gains based on real growth rather than speculative activity aimed at exploiting market distortions.
This rationality, however, appears to be compromised when the researchers found that investors tended to follow finfluencers of the same nationality and language, suggesting the influence of homophily. While mixing with people who are highly similar is a comforting thought, it may not represent the best economic outcome. Additionally, investors were also more inclined to follow male finfluencers, which alludes to a stereotype of men being better at money and numbers than women.
Establishing causality – the instrumental variable
Any measure of a finfluencer's impact on followers must account for unobservable influences – known as endogeneity – that can confound the findings. For example, if a finfluencer and a follower both hold the same stock, it does not necessarily mean the former influenced the latter. They might simply have similar preferences, or they both reacted to positive news. Reverse causality is also possible: a finfluencer might choose popular stocks to match their followers’ interests.
To address endogeneity challenges, Hull and Qi used an instrumental variable (IV) approach in their regression analysis. An IV is a factor that affects the independent variable (exposure to a finfluencer in this study), but is not directly related to unobserved factors that affect the outcome. This allows researchers to isolate the true causal effect of finfluencer exposure on a follower’s investment behaviour.
For illustration, consider the classic example of the connection between attending college (independent variable) and income later in life (dependent variable). Although college attendance and income are correlated, people who go to college may already be smarter, more motivated, or wealthier – traits that also affect income. These unobserved traits, not the college degree itself, could explain higher earnings.
An IV – such as distance from home to the nearest college – can be used here, as people who live closer are more likely to attend, but distance is not closely related to their intelligence, motivation, or family wealth. This helps researchers estimate the true effect of college on income, excluding confounding factors.
In Hull and Qi’s study, the IV was the automatic assignment of new users to follow platform-made influencers (employees of the platform) when they created their accounts. This assignment was random and unrelated to the users’ own preferences or investment behaviour, ensuring that exposure to these influencers was exogenous. By using this IV, the researchers could estimate the causal impact of finfluencers on retail investor behaviour, ruling out the possibility that the results were driven by pre-existing similarities or reverse causality.
Their IV estimates showed that following an influencer was associated with substantial changes in a follower’s portfolio and trading decisions. On average, a follower’s overlap with an influencer increased by 3.8 percentage points for holdings, 0.3 percentage points for purchases, and 4.6 percentage points for sales.
Policy Implications
Hull and Qi’s study uncovers a key tension at the core of the finfluencer phenomenon: potential conflicts of interest. Finfluencers face a choice – should they offer sound, independent financial advice (which could be unpopular), or should they focus on actions conducive to growing their follower base, even if these actions might be detrimental to their followers?
The study found evidence that some finfluencers, especially those affiliated with the platform, tended to trade more in products issued by the platform and adopt strategies that generate higher trading volumes.
This benefits the platform through increased commissions, but does not translate into better investment performance for followers. In other words, finfluencer incentives do not always align with follower interests.
From a policy perspective, these findings suggest several concerns that need to be addressed.
- Transparency and Disclosure: There is a need for clear disclosure of finfluencers’ affiliations and incentives, so followers can judge their advice with better information.
- Investor Protection: Regulators may need to consider safeguards to protect retail investors from being unduly influenced by finfluencers whose main preoccupation is to increase popularity or platform profits, rather than promote sound investing.
- Market Efficiency: While finfluencers can help democratise financial information and increase participation, they can also contribute to market noise and herding if followers blindly mimic trades without understanding the risks.
In summary, as finfluencers continue to shape retail investing, policymakers should balance the benefits of social trading against the risks of conflicts of interest and the potential for misleading influence.
Hull, Isaiah is an associate professor of finance at the BI Norwegian Business School.
Qi, Yingjie is an assistant professor of finance at the Copenhagen Business School.