Cultural Calendars and the Gold Drift: Are Holidays Moving GLD ETF?

Financial markets exhibit persistent calendar anomalies, which often defy the efficient‐market hypothesis by generating predictable return patterns tied to institutional or cultural events. In this paper, we document a novel, globally pervasive drift in gold prices surrounding major wealth-oriented festivals across the four principal cultural and religious domains: Christianity, Islam, Hinduism, and East Asian syncretic traditions. While each community endows its principal holidays with gift‐giving rituals and conspicuous displays of wealth, the sole differentiator among regions is the precise timing of these festivities on the Gregorian calendar.

Our central thesis is that gold, owing to its dual role as a universal wealth reservoir and socio-cultural status symbol, experiences concentrated, holiday-induced buying pressure that yields persistent and economically material drift in the GLD ETF. By quantifying this effect across four distinct cultural calendars, we introduce a previously undocumented demand-side factor into commodity-pricing models.

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Sunspots as a Natural Signal for Trading Wheat Futures?

When it comes to forecasting commodity prices, traders usually turn to weather patterns, supply-demand data, or economic indicators—but what if the sun itself could offer a clue? Our latest data analysis explores a surprising relationship: periods of high solar activity, measured by an increased number of sunspots, tend to precede lower long-term prices for agricultural staples like wheat and corn. The science behind it is simple—more sunspots often mean better growing conditions, which can boost crop yields and eventually put downward pressure on prices. It’s not a quick trade idea; the effects unfold over one to three years, as natural cycles gradually outweigh short-term noise from market speculation or temporary supply shocks. Unconventional? Yes. But in a market where every edge matters, even the sun might have something to say.

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How to Identify Ponzi Funds?

Can we spot a Ponzi scheme before it collapses? That question haunts regulators, investors, and journalists alike. But what if some modern investment funds operate on dynamics that, while not technically illegal, closely resemble Ponzi-like behavior? A new paper by Philippe van der Beck, Jean-Philippe Bouchaud, and Dario Villamaina examines whether certain actively managed funds inflate their own performance — and in doing so, unwittingly mislead investors chasing past returns.

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The Memorization Problem: Can We Trust LLMs’ Forecasts?

Everyone is excited about the potential of large language models (LLMs) to assist with forecasting, research, and countless day-to-day tasks. However, as their use expands into sensitive areas like financial prediction, serious concerns are emerging—particularly around memory leaks. In the recent paper “The Memorization Problem: Can We Trust LLMs’ Economic Forecasts?”, the authors highlight a key issue: when LLMs are tested on historical data within their training window, their high accuracy may not reflect real forecasting ability, but rather memorization of past outcomes. This undermines the reliability of backtests and creates a false sense of predictive power.

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How Fragile is Liquidity Across Asset Classes?

The paper “Through Stormy Seas: How Fragile is Liquidity Across Asset Classes?” is a very interesting examination of how liquidity properties have evolved over the past decade. Although the average bid–ask spread has declined, the kurtosis and skewness of the spread distribution have increased. What does this imply? On average, markets appear more liquid; however, liquidity evaporates more rapidly during stress events, amplifying tail risk and increasing execution slippage.

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