Top-notch investment strategies require top-notch research. The Robeco ‘Super Quant’ internship research projects, in areas such as language analysis or survey-based macroeconomic data, are part of this ongoing effort.
In its effort to keep offering top-notch investment strategies, each year Robeco’s quantitative research department runs several research projects with our ‘Super Quant’ interns, under the supervision of our experienced researchers. Internships typically last for six months and are combined with writing a master’s thesis on the same research topic. For Robeco, these internships represent a unique opportunity to hire students from some of the best universities in finance and econometrics, and to either drill deeper in our existing intellectual property or explore new areas of research. This article describes the key findings of three of these internships in 2018.
This project looked into the links between companies or industries that are not fully incorporated in the prices of financial assets. The idea was to uncover and exploit a potential indirect momentum effect that spills over to the companies we can invest in. Such an indirect momentum effect could enhance our existing stock and corporate bond selection models.
To check whether an indirect momentum effect could provide valuable information, we used monthly data and regressed individual equity or industry returns on one-month lagged industry returns, using a Lasso (least absolute shrinkage and selection operator) regression method.
We made predictions both at industry level, leading to an industry rotation strategy we called ‘industry to industry’, and at individual equity level, leading to a strategy we called ‘industry to company’. The analysis showed that the ‘industry to company’ signal is stronger than the “industry to industry’ signal.
We analyzed 353,173 filings, which amounted to 20 million pages and 5 billion words
This project investigated whether variables derived from the text in annual and quarterly reports may provide useful information for equity and credit investors. To this end, we downloaded all the 10-K and 10-Q files available from the EDGAR database of the US Securities and Exchange Commission.
After some adjustments – to remove numbers, symbols and punctuation marks, for example – we looked at several variables, such as text length, readability and sentiment. In total, we analyzed 353,173 filings, which amounted to 20 million pages and 5 billion words. The processing time was approximately 8 hours. To put this all into perspective, the average financial analyst reads 200 words per minute and would therefore need 50 years to digest all this information.
Our study showed that text analysis can be used to automate and speed up the reading process and that text variables are informative for a firm’s future equity and credit performance, mostly concerning volatility. In conclusion, automated text processing adds value compared with manual methods used in the past.
This project analyzed the use of macroeconomic data to predict equity, bond and currency returns. Most statistics are published with a lag and many academic studies argue that equity returns can predict GDP growth, but that the opposite is not true.
Recent academic work came to different conclusions: macroeconomic data may provide useful investment signals after all. Our study confirmed this, finding for instance that currencies from countries with the best economic momentum outperform those of countries with the worst economic momentum.
This project also looked at so-called ‘surprise’ indices produced by brokers. For many macroeconomic statistics, economists are polled ahead of publication. The ‘surprise’ is the difference between the predicted and the actual outcome. One feature of these indices is that they are not flat, but rise and fall over time. This implies that surveys go through overly pessimistic and overly optimistic periods, which, in turn, can be used to predict equity and bond returns.
Read more about our Super Quant internship program.
1See for example: M. Dahlquist and H. Hasseltoft, 2017, ‘Economic Momentum and Currency Returns’.
Confermo di essere un cliente professionale
Le informazioni e le opinioni contenute in questa sezione del Sito cui sta accedendo sono destinate esclusivamente a Clienti Professionali come definiti dal Regolamento Consob n. 16190 del 29 ottobre 2007 (articolo 26 e Allegato 3) e dalla Direttiva CE n. 2004/39 (Allegato II), e sono concepite ad uso esclusivo di tali categorie di soggetti. Ne è vietata la divulgazione, anche solo parziale.
Al fine di accedere a tale sezione riservata, si prega di confermare di essere un Cliente Professionale, declinando Robeco qualsivoglia responsabilità in caso di accesso effettuato da una persona che non sia un cliente professionale.
In ogni caso, le informazioni e le opinioni ivi contenute non costituiscono un'offerta o una sollecitazione all'investimento e non costituiscono una raccomandazione o consiglio, anche di carattere fiscale, o un'offerta, finalizzate all'investimento, e non devono in alcun caso essere interpretate come tali.
Prima di ogni investimento, per una descrizione dettagliata delle caratteristiche, dei rischi e degli oneri connessi, si raccomanda di esaminare il Prospetto, i KIIDs delle classi autorizzate per la commercializzazione in Italia, la relazione annuale o semestrale e lo Statuto, disponibili sul presente Sito o presso i collocatori.
L’investimento in prodotti finanziari è soggetto a fluttuazioni, con conseguente variazione al rialzo o al ribasso dei prezzi, ed è possibile che non si riesca a recuperare l'importo originariamente investito.