by Vladimir Zlacky | Mar 8, 2025 | News
For a long time, financial economists have been arguing about market efficiency—the extent to which the prices of financial assets contain all relevant information. If one believes in the strong form of the efficiency hypothesis, i.e., that market prices contain all relevant information, then all assets would be fairly priced and there would be no way to generate risk-adjusted excess returns on the market. Only passive investment strategies would make sense in that case.
Yet, we know that some market participants earn excess returns for a protracted period of time, which casts doubt on the strong form of market efficiency hypothesis. Active investment strategies clearly pay off. However, they require good data.
Traditionally, investors have been using both individual financial and economy-wide data to value stocks and predict their returns. Metrics such as price-earnings, price-cash flow, EV/EBITDA, dividend yield, or price-to-book value have been envisaged to forecast prices using individual company accounting data. Furthermore, a wealth of macroeconomic and relevant sector-level data have been brought to bear on forecasting the stock prices. Sophisticated models – whether based on fundamental or technical analysis – were developed to make use of this data, helping some investors gain abnormal returns. However, it seems that even though new models and techniques are being developed every day, it is increasingly difficult to beat the market while using only the traditional sources of data. These data come with a time lag, sometimes misrepresent the true state of the company, often are subject to problematic revisions and do not necessarily capture the reality in a complex way. Hence, investors are increasingly turning to alternatives.
With the advent of machine learning and artificial intelligence (AI), the investment community has begun exploiting alternative data, which the new technology allows to process very efficiently and at a recognition level increasingly on par with humans.
Which alternative data have been gaining traction with investors recently?
Since about the mid-2000s, various social media has become widespread and transformed many aspects of our lives. With a penetration rate of some of the social media reaching sky-high levels, its influence and the information value of its content might be enormous. Prevailing sentiments not only about the individual companies but also about the general economic and political environment are revealed daily by the contributions found on the social media. It seems that there is a value (with regard to asset pricing) to be exploited in scrutinizing how connection networks are formed as well as in analyzing individual contribution posted on social media. Further attesting to this, several academic studies suggest that using data from social media can help predict stock returns or market events. (1,2)
On a separate front, many hedge funds and other investors have started using satellite-based information on shipping containers, mines, ports, parking lots, plantations, or farmlands, which can capture economic activity in real time. From this, they can derive insight into the overall economic activity and/or even expected sales of public companies involved. One particular study indicates that the number of containers in ports can significantly predict stock index returns in 27 out of 33 countries at a daily frequency for the 2019–2021 period. An investor making use of satellite data on marine ports can, on average, receive an annualized return of 16.4%. (3)
Increasingly, investors, especially those exposed to stocks in the consumer goods sector, have been trying to gain additional insight into consumer behavior. Transaction data from debit and credit cards clearly contain valuable information that can be exploited to forecast stock returns. One recent study shows that debit/credit transaction data positively predict various measures of a company’s future earnings surprises up to three quarters in the future (4). The study found that a portfolio constructed using insights from card transactions generates returns of 16% per annum net of transaction costs. Clearly, consumer transaction data garnered from various sources can be enormously valuable to investors.
The market for mobile phone applications has been booming in recent years. With the increasing number of application users, the mobile application market provides a new fresh source of data that could help predict a firm’s future financial performance. One particular study investigates the relationship between mobile app usage and future stock returns utilizing a panel data set of 326 public firms that have released mobile applications on the Apple iOS App Store or Google Play Store (5). The results of the study show that monthly abnormal app downloads and abnormal daily users are positively associated with the next-month abnormal stock returns. This suggests that mobile app usage can help predict firm-level future stock returns.
Above were just some of the examples of alternative data frequently used by the investor community nowadays. Other examples include data on bank loans announcements, product review data, electricity consumption data, or data on shipping trackers. Increasingly, investors are also using geolocation and climate data to predict economic activity or a specific company’s performance. Sophisticated investors also increasingly use AI technology to deeply analyze transcripts of the earnings calls by employing tools like ChatGPT for detection of tone, hidden clues, and nuances in corporate statements. They also scrutinize video earnings calls for both tone of the CEOs’ voices as well as their body language. Interestingly, some investigators go as far as using biometric data of CEOs or data on their spending patterns to predict their personality types and accordingly stock returns or a likelihood of potential misconduct.
In a similar vein, according to Deloitte’s report, one of the largest Japanese investment managers used data from job portals and recruitment websites to infer the strength of organizational culture in individual firms to help generate investment picks (6). Clearly, there are no bounds to one’s imagination and inquiry, and we will probably see a significant expansion of using alternative data going forward.
Deloitte’s report predicts astounding growth in the size of the market for alternative data (6). While revenues for alternative data providers reached an estimated USD 11 bn in 2024, the market is likely to grow by more than 50% annually (CAGR) until the end of the decade. By then, the total revenues for alternative data providers are predicted to surpass those of traditional financial data providers.
What are the implications for investment managers?
Given the current market dynamic, it seems that investment firms that shy away from using alternative data and fail to incorporate them into their business model might not only forgo alpha but also be exposed to additional risks due to suboptimal decisions.
This is because alternative data can create an information advantage for the investment managers via (6):
- Unique insight – alternative data can provide insight that is not available from traditional financial or economic data
- Timeliness – these can be real-time or nearly real-time data, allowing investors to make much quicker decisions than relying on traditional financial data
- Predictive power – alternative data can improve the predictive power of forecasting models, helping anticipate the market movements or the company performance
Rush or perish?
Unique and timely insights into asset pricing, together with forecasting models’ higher predictive power, can contribute to the higher alpha of investment firms that use alternative data. In this very competitive investment landscape, it seems that in the longer run, investment managers that intensively use these data will earn abnormal returns and clearly outcompete those that do not. Furthermore, alternative data can improve risk assessments and lead to more effective detection of early warning signals about potential risks. All of this means that the firms on the frontier of adopting alternative data will gain a competitive edge over firms that have been relying only on traditional data. This will also likely lead to a higher customer satisfaction and retention in the technologically most advanced firms, the ultimate objective of any business undertaking.
In a nutshell, rushing to adopt the most recent technology and embrace alternative sources of data might be the only way to remain competitive in this market.
Vladimír Zlacký, LookingEast.eu
References:
- Cookson, J. Anthony; Lu, Runjing; Mullins, William; and Niessner, Marina. The Social Signal. Journal of Financial Economics, volume 158, 2024
- Cookson, J. Anthony; Niessner, Marina; Schiller,Christoph. Can Social Media Inform Corporate Decisions? Evidence from Merger Withdrawal, working paper, 2025
- Honghai Yu; Xianfeng Hao; Liangyu Wu; Yuqi Zhao; Yudong Wang. Eye in outer space: satellite imageries of container ports can predict world stock returns. Humanities and Social Science Communications, 2023
- Tarun Gupta; Edward Leung; Viorel Roscavan: Consumer Spending and the Cross-Section of the Stock Returns. The Journal of Portfolio Management July 2022
- Ziqing Yuan; Hailiang Chen; Can Mobile App Usage Help Predict Firm Level Stock Returns? Fortieth International Conference on Information Systems, Munich 2019
- Deloitte Insights. Alternative data at investment management firms: From discovery to integration, 2024
by Vladimir Zlacky | Jan 24, 2021 | News
When taking a ride on the London underground some time ago, I noticed a remarkable thing. Nearly all passengers were reading something, many of them educating themselves. The train was also all covered by small display ads on all kinds of part-time or evening educational programs; from the lower-level ones to prestigious business school programs. Londoners clearly have understood for some time that something is going on
We live in the age of the unfolding structural change. Even if the covid-19 crisis somewhat diverts our attention from some of these changes, advances in science and technology and the Artificial Intelligence (AI) revolution are bringing massive innovations to the workplace. The most visible ones are those resulting in robotization and automation. These innovations combined are causing disruption in nearly all sectors of the economy worldwide.
Clearly, as a result of this disruption, some workers will have to be released from their work positions others will find it in their interest to dive deeper into their respective fields. As one of the world’s most preeminent thinkers of our age, Thomas Friedman tells us, this will mean that lifelong learning programs will gain more salience in the future and will be a key to addressing the skill gaps stemming from changes in labor market demands due to the disruption on the marketplace.
Here are some words about many roles such lifelong learning programs could play in the adjustment of the economies to the unfolding technological revolution.
First, some workers – be that for example assembly-line, lower services, or even higher-skill workers – will be released from their previous work positions. Many of them will be seeking retraining programs to resume an economic activity on a new occupation or in a new sector. Various re-training programs – at all levels to help workers of various skillsets- under the rubric of lifelong learning could conduce to such reskilling.
Second, other workers during their careers will need to specialize further and deepen their skills to keep abreast with the knowledge progress – lifelong learning provides an opportunity for such additional expert-skilling (so-called upskilling). Ensuingly, we might see substantial changes in the educational landscape worldwide; executive masters or even executive part-time doctoral programs will probably pop up in the soon future on a more massive scale than before.
Third, yet some other workers might have “missed the right career train” when they were young or at some other point in their career. Nevertheless, a well-functioning society aspiring to be creating prosperity for all should not overly penalize weakness or failure and give individuals multiple chances to succeed in the marketplace during their lifetime.
Which are the examples of policies that could help trigger massive lifelong learning in the economy?
Tax incentives such as no or reduced VAT/sales tax on textbooks and learning instruments could be one way of supporting learning in general. Individual tax credits for undertaken high-quality but oftentimes expensive executive training is another way of incentivizing more training activity taken by individuals.
Additionally, a lot of relevant education is happening within the corporate sector. Super-tax deductibility of training costs with a higher than 1.0x coefficient – thus increasing tax shield, reducing the effective cost of the trainings – would incentivize more training activity within the corporate world.
Instigating the culture of massive life-long learning in society will probably take some time. Policymakers via moral suasion or through generous budget allocations could help in this undertaking. Given that continuous re-trainings on the labor market are necessary for modern economies to be resilient, the benefits of lifelong learning programs clearly justify these efforts.
Vladimir Zlacky
LookingEast.eu
January 24, 2021
by Vladimir Zlacky | Oct 29, 2020 | News
Some memories last long. Such as do the ones, which relate to my graduate studies of economics at Harvard. Amongst the most interesting lectures, which I ever attended, were those given by Prof. Jeffrey Sachs, one of the world’s most influential economists and a very incisive mind. He liked to say that there were geographic explanations for many economic phenomena in the world. Why do I recall this now?
The United States lags behind many a similarly developed country in the quality of its public infrastructure. Is this partly due to the differences in government efficiency or relative public’s preferences for public investments? Probably so, but perhaps factors such as the size of the country, population density, and geographical distribution of settlements and economic activity play a role too.
The other day, I noticed a graph with OECD data, which compared the government’s size (measured by relative government expenditures) among the member countries of this rich countries’ economic club. The data from 2018 reveal that the government’s size varied from the low of 25,4% of Gross Domestic Product (GDP) in Ireland to the highest of 55,9% GDP in France. Not a big surprise, one would think. However, what is perhaps surprising is that the data show that Switzerland has a relatively small government (33,7%GDP) while the US had government expenditures at the level of 37,8% of GDP in 2018.
Even if simplifying a bit, one would typically expect that countries with a bigger government would also better provide for public goods. Seen in this context, the comparison between these two rich countries is in a way mind-boggling. While their estimated GDP per capita in 2020 in PPP is broadly comparable (the US has GDP pc 63 ths dollars Switzerland GDP is 67,6 ths dollars), any visitor to both countries will notice a remarkable difference in the quality of provided public goods. Local infrastructures such as roads, bridges, train stations, or public premises in general look in much better shape in Switzerland than in the US, at least visually. This visual difference is much more significant than would be implied by slightly higher income per capita in Switzerland. Such visual difference is also supported by the data – according to one source (statista.com) Switzerland’s quality of infrastructure was the fourth-best in the world while that of the US was ranked 13th in 2019.
Why such a difference? What makes the US – probably the most advanced country in the world – lag behind Switzerland in the quality of public goods provision even though it has a bigger government? Yes, one explanation might be relative government efficiency – perhaps the Swiss get it right here too. Also, different preferences for a structure of government expenditures (investment vs. other) probably play a role.
However, it appears that the fact that the US is a geographically large country might be an explaining factor too. A vast country with a relatively low density of population (34 people per sq km vs 207 in the case of Switzerland) means that the geographical intensity of economic activity is much lower in the US than in Switzerland. Many dispersed cities, small towns, and villages across a vast country need to be connected by road, train, electricity, and perhaps other infrastructures – all of this takes substantial resources, whether for construction or repair. Yet economic intensity per sq km to support this infrastructure is low in the US.
In order to illustrate the point, let us make the following thought experiment. Imagine collapsing the map of the US into, say, a quarter of the territory – as if one dragged left-down the upper right corner of the map by the mouse on the computer screen. The GDP would remain more-less the same, yet connectivity costs and related infrastructure spending would be lower on the now reduced territory.
Obviously, this is just simplification – what really seems to matter is not only the size of the country but also the geographical distribution/dispersion of economic activity and settlements within the country. How this precisely works, I leave to economists more proficient in spatial analysis.
Nevertheless, it should be safe to say that the geographical distribution of economic activity/settlements which is partly shaped by the size of the country helps explain the level of infrastructure spending in the country -i.e. should have a bearing on the overall size of the government.
Relatedly, some homework for readers to crack: Do frequent earthquakes on the West coast of the US implying a preference for not living in tall buildings and an ensuing low geographical economic intensity go a certain way towards explaining the fiscal problems of southern California?
Vladimir Zlacky
by Vladimir Zlacky | Jul 30, 2020 | News
Elsewhere recently, I argued that advanced, sophisticated services with an international focus might significantly help the future growth of the Slovak economy. (1) With the manufacturing sector’s dynamism petering out, a more multi-prong policy focus would likely bring strong growth benefits.
Activity in fields like IT services, advanced consulting services, and higher-end tourism are examples of such advanced services. Other examples would include international trade companies, commercial fairs organizers, high-end medical services, top marketing or interior design studios, or even as specialized services as tennis academies or local showbiz (also popular in Czechia). All these services can have a significant international orientation ( perhaps also focusing on China and other eastern markets) and thus tap vast global markets bringing massive export or quasi-export earnings for the Slovak economy in the future.
Which are the policies that would conduce to the development of such an advanced sophisticated services base? These services derive their value mostly from the human talent augmented by education – hence an urgent need to bolster the human-capital capacity of the country. Utilizing the announced massive EU sponsored aid within the Recovery Fund framework would be one way of supporting the proliferation and growth of such services in a foreseeable time horizon.
In a nutshell, aiding the formal education and lifelong learning sectors, engineering reverse brain drain to Slovakia, and helping diffusion of knowledge in the economy would all combined go a long way towards boosting human capital in Slovakia.
Which specific policies would likely be helpful in human capital formation? Helping a formal education sector at all levels would be one way of supporting the growth and prosperity of such firms in the medium to long-term horizon. First, some resources should be channeled to increasing wages in the whole education sector so that the sector attracts better talent than previously. Other specific policies – such as free laptop computers for all children in elementary and high schools or technological upgrades of labs in many fields would go some way towards aiding the formation of technical capabilities of pupils and students. Gratis vouchers of a specific value per year issued for book purchases would prompt children in elementary schools to read more. Importantly, the availability of scientific articles at low or no direct cost to the researcher would help readier adaptation of frontier knowledge in basic and applied research. Hence, some resources from the Recovery Fund could go towards a country-wide subscription to the primary databases of scientific journals. So could the resources be earmarked for more R&D activity via grants subsidized from the Recovery Fund. Efforts to continually redesign and update school curricula at all levels to keep abreast of the best practices internationally should be sine-qua-non.
There are many reasons why lifelong learning can have positive spillover effects on the economy. First, the AI revolution will bring a tremendous amount of innovations and ensuing disruption to the marketplace. The Slovak economy- like most others – will have to undergo a structural change. Some workers will be released from their previous occupations, and many of them will be seeking retraining programs to start economic activity in a new sector. Second, other workers during their careers will need to specialize further and deepen their skills to keep abreast of the knowledge progress – lifelong learning provides an opportunity for such additional expert-skilling. Third, yet some others might have “missed the right career train” when young or at some point. Nevertheless, a well-functioning society aspiring to be creating prosperity for all should not overly penalize weakness or failure and give individuals multiple chances to succeed in the workplace during their lifetime.
Which are the examples of policies that could help trigger massive lifelong learning in the economy? Tax incentives such as no VAT on textbooks and learning instruments could be one way of supporting learning in general. Individual tax credits for undertaken high-quality but oftentimes expensive executive training is another way of incentivizing more training by individuals. Additionally, a lot of education is happening within the corporate sector. Super-tax deductibility of training costs with a higher than 1.0x coefficient – thus increasing tax shield, reducing the effective cost of the corporate-level trainings – would incentivize more training activity in the corporate world.
Importantly, Slovakia has suffered for decades from a massive brain drain. Some of the most talented people of the nation have left the country for better career opportunities outside of Slovakia. The Slovak economy would tremendously benefit from the return of at least some of these workers – they could be the future entrepreneurs, high-level managers, or experts in sophisticated services firms or elsewhere. Given that the pool of the local talent is limited and probably represents a bottleneck to further development, even pecuniary ways of incentivizing the return of Slovak professionals from abroad (such as via tax breaks) could be considered for implementation.
The diffusion of international frontier knowledge in many fields of the economy – so that the knowledge pool can be tapped into by private firms in Slovakia – is quintessential for having internationally competitive domestic firms. Expert scientific and other advanced conferences with foreign experts participating organized in Slovakia could help such diffusion. Subsidizing the costs of hosting such expert conferences could be one direct way of promoting the spread of frontier knowledge in the Slovak economy. The exchange of academics at all levels internationally, perhaps subsidized also from the funds made available by the EU, could be another way of bringing academics closer to the knowledge frontier. Slovak firms could thus tap into such a further augmented talent pool and strengthen their competitiveness.
Aiding the formal education as well as the lifelong learning sectors, engineering reverse brain drain to Slovakia, and helping diffusion of knowledge in the economy would all combined go a long way towards boosting human capital in Slovakia. While valuable in its own right, this could also help the country develop an internationally competitive services sector and return the Slovak economy onto the path of fast growth and convergence in the medium term from which it was derailed.
Vladimir Zlacky
LookingEast.eu
(1) Vladimir Zlacky, Slovak Economy: What next, Slovak Spectator, July 2020
by Vladimir Zlacky | Jul 21, 2020 | News
The result of the three decades of the transformation of Slovakia’s economy has been substantial catching-up with the developed West. In 2019, the income per capita in Slovakia in comparable prices reached 72% of EU-28 even surpassing Greece and nearing the level of Portugal. One particular calculation suggests that Slovakia’s nominal GDP in EUR terms increased about tenfold since the birth of the country in 1993.(1) Sectorally, the structure of the economic activity has reached the Western model and technologically we saw enormous progress (2). While the first decade post 1989 Revolution was characterized by basic economic reforms and thorny path to democracy, the second one was by the admission to the EU and, structurally, the enormous expansion of the automotive and electronics sectors. Unfortunately, the last decade saw a decline of FDI inflow, policy dormancy on certain fronts, and stagnation of the overall economic convergence.
At the start of another decade, the natural question arises: Which is the next big thing for the Slovak economy in the 2020s? Since a future vibrancy of the automotive and electronics sectors is at the question, what will be a future source of Slovak economy dynamism? In this blog, it is argued that domestically owned advanced exportable and quasi exportable services merit substantial policy focus as they could significantly help the growth of the Slovak economy. Things like IT services, advanced professional and consulting services, and high-end tourism are examples of such services. Other examples could include international trade companies, commercial fairs organizers, top-end marketing or interior design studios, or even as specializes services as tennis academies or local showbiz (popular in Czechia) – all with significant international activities. Since start-ups are an important source of the economy’s vibrancy, let us ponder – what are the advantages of advanced services start-ups vis-a-vis the ones in manufacturing?
First, the advanced services firms are easier to establish logistically – compare what it takes to construct and start running a production factory vis-a-vis to, say, establishing a consulting firm. No doubt, for most manufacturing projects the startup process is a very complex and demanding undertaking with substantial operational risks relative to advanced service sector startups.
Second, advanced sophisticated services usually feature very high added value produced per capita – higher than the value added created in most sectors of manufacturing. Hence, from the point of view of the nation-wide allocation of resources and the resulting recording of created value added in national accounting, it should be advantageous if resources flow to the sector of advanced services. This is also an environmentally friendly allocation of human resources.
Third, it can be argued that, in most cases, it is easier to reach the knowledge/technology frontier in case of advanced services than it is in the case of advanced manufacturing production. R&D in manufacturing is a complex, difficult, and costly undertaking and it is a question of how advanced Slovakia’s R&D base compares to the developed West. For illustration, just compare what is easier – to be on the knowledge frontier for creating, for instance, a corporate identity package by a Slovak marketing studio for a foreign client or to be on the technology frontier for producing a branded Swiss-like watch to export?
Fourth, clearly, most manufacturing start-ups require a lot more capital than start-ups in services do. Furthermore, a start-upper/entrepreneur in some manufacturing sector has much more to lose financially if his project fails. Hence many relatively risky projects might never be implemented in manufacturing while comparable start-up projects in the advanced services sector may still be undertaken. Ceteris paribus, this can lead to more entrepreneurial activity in a country where policy focus pushes resources to flow to a less capital intensive advanced services sector.
Last but not least, advanced services firms typically feature a much higher labor share on a produced value than does a typical manufacturing firm. With the AI revolution expected to dramatically drive the labor share down in the economy and thus magnifying distributional issues, the proliferation of advanced services firms can counter such trends.
Manufacturing and the automotive/engineering cluster within it have an enormous tradition in Slovakia. The sector has been a driver of economic growth to date in Slovakia and, no doubt, efforts should be made to develop the cluster further. However, the AI revolution and ensuing robotization will reduce the importance of labor costs advantage across sectors including in the automotive. For at least that reason, attempts to attract additional FDI in the sector might be an uphill battle in the future. Given that the manufacturing start-ups are not an easy undertaking in their own right, we should not forget that the development of a vibrant sector of advanced services represents probably an easier route to higher income per capita levels. A policy focus should not overlook that.
Vladimir Zlacky
LookingEast.eu
(1) Vladimir Zlacky, Slovak Economy: What next, Slovak Spectator, July 2020
(2) Vladimir Zlacky, Lubos Korsnak: A brief note on sector productivity in CEE 1995-2009,2012, UniCredit research note, published on LookingEast.eu
