Restarting the economic growth will need considerable private sector injections of funds over a 3–5 year recovery cycle.
Thursday, April 29, 2020, the U.S. Department of Commerce reported that consumer spending dropped by 7.5% in March. The day before, the advance estimate for gross domestic product (GDP) for the first quarter of 2020, indicated a contraction of 4.8%.
The consumer spending contraction is particularly problematic as consumer spending accounts for 70% of total economic output in the U.S.
It will be difficult to restart the economy without consumer spending. It will be difficult to restart small business without money that can be spent. …
A few general points to help everyone when assessing dynamic strategies synthesizing Porter 5 and Blue Ocean.
Frame the situation in the marketplace from a perspective of context and competitive environment.
Applying an external lens to the situation helps in understanding the context within which the strategic decision making is or was taking place, which then crafts strategic options that are relevant to the consumers in that marketplace. Answering the following questions will uncover both the context the decisions were made and the competitive environment:
Adapting increasingly sophisticated analytical tools helps enterprises to explore FinTech opportunities: it is not story of technology anymore, but a story built on data.
FinTech combines financial services with modern technology. The first start came before 2008, but the acceleration kicked off post 2010, more specifically in the past 3–4 years.
LendingClub (2007), Social finance (SoFi) — many of these have been exposed to some internal problems, either manipulated loans or excessive default rates. Problem is in the skin in the game and the difference in having a stake in the loan or in the intermediation of the loan. …
Alternative data conferences connect actors in the buy-side ecosystem to explore novel use cases as the demand for alternative data is increasingly intense. Only the largest and most sophisticated players with distinctly unique roles can leverage their critical edge. Increasing demands on data remains a challenge that only few can solve.
With annual purchases of alternative data by U.S.-based buy-side firms projected to reach $900 million by 2021, the competition to find, extract, refine, package, and ultimately sell alternative data is immense. …
Machine learning models are complex chains of processes where a number of different steps interlink to create a cohesive production flow. With the digital transformation of financial services, the role of digitally savvy, sophisticated fintechs that embrace proactive deployment machine learning is pivotal.
Most, if not all, firms in financial services and fintechs are now pushing the existent boundaries of machine learning actively as new digital transformation pressures became the competitive paradigm.
Firms that fail to prioritize strategic, machine learning driven digital transformation will likely fail to reshape their traditional business models. …
Quantamental strategies combine statistical thinking with big data to “think fast and slow” and to enhance the ability to generate alpha.
Investing is about the size and direction of alpha — and the consistency thereof. Alpha captures the excess return on a portfolio or strategy where the market factor exposures and/or risk factor sensitivities are predetermined. Alpha builds on academic work that initially analyzed the world from the relatively simple perspective of the joint explanatory power of linear regression and mean variance optimization. …
Alternative data is a buzzword, yet it wields enormous potential not only for investors and businesses, but also for governments and regulators. It is the result of our unprecedented data revolution, yet it is obscure and hard to find, although it is hiding in plain sight.
Some believe that by 2020 (in little less than one year’s time) each individual will generate around 2 MB of data each day, with a significant proportion of this data created in readily analyzable and easily accessible digital format. …
To improve on the performance of traditional, fundamentally driven investment management approaches, asset managers are incorporating various quantitative approaches in their search for new sources of alpha – the quantamental approach.
Quantamental is a portmanteau of quantitative and fundamental and describes portfolio management approaches that combine fundamental analysis with quantitative approaches.
The fundamental approach to portfolio analysis focuses on a limited number of stocks, typically within a sector or some common fundamental characteristics such as:
Because alternative data is transforming the investment management processes for asset managers – hedge funds, mutual funds, foundations, and pension funds – understanding the complex forces driving this digital transformation provide strategic opportunities. Investment managers that do not follow this seismic shift and update their investment processes are increasingly facing strategic risks and disintermediation: they may very well outmaneuvered by existing and new competitors who build their process around alternative data.
Sophisticated investment managers are increasingly augmenting their decision making processes using alternative data sources from news and social media feeds, metadata from email, voice, and video communications, information from satellites and other geospatial information. Most asset managers see direct benefit from using this information to improve their alpha generating capacity to bolster the performance from structured time series and accounting information. …