Investment choices are heavily dependent on investor preferences and investment decision methodology. When it comes to the latter, there has been one particular phenomenon in empirical market dynamics that has traditionally flummoxed market analysts and quants: the “January Effect”. In this phenomenon, observed market volumes (and volatility) seen across the calendar month of January over the last couple of decades are generally higher than in the rest of the year. Furthermore, institutional quants generally consider them to be more optimistic than in the rest of the year.
This is something of a problem towards rationalizing market trajectory: there is a plethora of data and analytics from nearly hundreds of sources that institutional quants pore over to get a sense how markets should shape up over the near future. Barring major upsets, this “sense of shape” is supposed to hold true. The “January Effect” is deemed to be an outlier in that it nearly always dents this idea of “shape”.
Over the years, institutional quants have made numerous studies and attributed probable causes without any strong consensus being developed. For instance, some quants argue that this “bump” in January is likely due to increased inflows in January from asset managers who have received additional capital from their clients by the end of the previous year; when they make investments to fulfil their clients’ mandates, instrument prices are influenced, which other investors piggyback on to exacerbate. Others argue that the effect is for “psychological” reasons: clients, advisors and investment managers have stronger convictions following year-end vacations and make investment decisions accordingly – which get corrected or strengthened as the months roll past.
“Cultural” reasons on account of increased participation of investors in the Eastern Hemisphere also finds some mention: since the Chinese/Lunar New Year generally rolls in around the beginning of the Gregorian year’s calendar, some quants attribute increased trading activity as a form of “gambling for good luck” contributing to the “January Effect” as well.
Incidentally, “gambling for luck” is by no means solely a “Chinese” phenomenon; for instance, despite it being a public holiday, the National Stock Exchange and the Bombay Stock Exchange in India operate “muhurat” sessions every year (typically in the evening and lasting an hour) during Diwali where many traders make bets to propitiate and honour Goddess Lakshmi, the matron deity of wealth and prosperity. Outside of markets, games of chance in bazaars and social gatherings are also quite common in this period. Diwali falls somewhere between October and November in any Gregorian year.
While there is no strong consensus, the fact remains that the “January Effect” is an observable phenomenon. However, whether this tends to be dominantly positive or negative is open for interpretation. Lets consider two massive markets: the broad-based S&P 500 and the tech-heavy Nasdaq-100.
From 2000 onwards, trends in the S&P 500 can be tabulated thus:
In the 23 years of full-year observations, trends in January were similar to that of the entire year only 12 times. In the years where the year’s trajectory was directional to that in January, the latter were typically more pronounced.
For the Nasdaq-100, the tabulated trends are somewhat similar:
In the 23 years of full-year observations, trends in January were similar to that of the entire year only 11 times. However, in the years where the year’s trajectory was directional to that in January, the latter were also typically more pronounced.
The key takeaways of this empirical study for both these markets are two-fold:
While much ado tends to be made in financial media publications about January’s trends to be indicative of a general trend for the rest of the year, the fact remains – at least as gleaned from empirical observations – that this month’s volumes/directionality are as likely to be indicative as not.
In the article published last week, it was indicated that the outlook for the current year remains somewhat bearish (or even mildly bullish) with a diminished hope for the market (be it broad or tech) returning inflation-adjusted returns. The previous article also mentioned that the conditions are optimal for realizing short-term profits from tactical trading, which Exchange-Traded Products (ETPs) are perfectly poised to deliver at very economical and scalable costs. Exchange-Traded Products (ETPs) provide magnified exposure while potential losses limited to only the invested amount and no further.
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Violeta è entrata a far parte di Leverage Shares nel settembre 2022. È responsabile dello svolgimento di analisi tecniche e ricerche macroeconomiche ed azionarie, fornendo pregiate informazioni per aiutare a definire le strategie di investimento per i clienti.
Prima di cominciare con LS, Violeta ha lavorato presso diverse società di investimento di alto profilo in Australia, come Tollhurst e Morgans Financial, dove ha trascorso gli ultimi 12 anni della sua carriera.
Violeta è un tecnico di mercato certificato dall’Australian Technical Analysts Association e ha conseguito un diploma post-laurea in finanza applicata e investimenti presso Kaplan Professional (FINSIA), Australia, dove è stata docente per diversi anni.
Oktay è entrato a far parte di Leverage Shares alla fine del 2019. È responsabile della crescita aziendale, mantenendo relazioni chiave e sviluppando attività di vendita nei mercati di lingua inglese.
È entrato in LS da UniCredit, dove è stato responsabile delle relazioni aziendali per le multinazionali. La sua precedente esperienza è in finanza aziendale e amministrazione di fondi in società come IBM Bulgaria e DeGiro / FundShare.
Oktay ha conseguito una laurea in Finanza e contabilità ed un certificato post-laurea in Imprenditoria presso il Babson College. Ha ottenuto anche la certificazione CFA.
