Quantitative Finance

Olkhov, Victor

doi: 10.48550/arxiv.2508.08148pmid: N/A

Abstract:In his famous paper, Markowitz (1952) derived the dependence of portfolio random returns on the random returns of its securities. This result allowed Markowitz to obtain his famous expression for portfolio variance. We show that Markowitz's equation for portfolio random returns and the expression for portfolio variance, which results from it, describe a simplified approximation of the real markets when the volumes of all consecutive trades with the securities are assumed to be constant during the averaging interval. To show this, we consider the investor who doesn't trade shares of securities of his portfolio. The investor only observes the trades made in the market with his securities and derives the time series that model the trades with his portfolio as with a single security. These time series describe the portfolio return and variance in exactly the same way as the time series of trades with securities describe their returns and variances. The portfolio time series reveal the dependence of portfolio random returns on the random returns of securities and on the ratio of the random volumes of trades with the securities to the random volumes of trades with the portfolio. If we assume that all volumes of the consecutive trades with securities are constant, obtain Markowitz's equation for the portfolio's random returns. The market-based variance of the portfolio accounts for the effects of random fluctuations of the volumes of the consecutive trades. The use of Markowitz variance may give significantly higher or lower estimates than market-based portfolio variance.

Bosi, Stefano; Van, Cuong Le; Pham, Ngoc-Sang

doi: 10.48550/arxiv.2508.03230pmid: N/A

Abstract:We study an overlapping generations (OLG) exchange economy with an asset that yields dividends. First, we derive general conditions, based on exogenous parameters, that give rise to three distinct scenarios: (1) only bubbleless equilibria exist, (2) a bubbleless equilibrium coexists with a continuum of bubbly equilibria, and (3) all equilibria are bubbly. Under stationary endowments and standard assumptions, we provide a complete characterization of the equilibrium set and the associated asset price dynamics. In this setting, a bubbly equilibrium exists if and only if the interest rate in the economy without the asset is strictly lower than the population growth rate and the sum of per capita dividends is finite. Second, we establish necessary and sufficient conditions for Pareto optimality. Finally, we investigate the relationship between asset price behaviors and the optimality of equilibria.

Bradshaw, Corey J. A.; McDermott, Shana M.

doi: 10.48550/arxiv.2508.16872pmid: N/A

Abstract:Concerns about declining or ageing populations often centre on the fear that fewer people will translate to a weaker economy and lower living standards. But these fears are frequently based on oversimplified or misapplied interpretations of economic models, and appear to be driven more by political agendas rather than evidence. In reality, long-term prosperity depends more on how societies invest in education, skills, and technology, not just how many people they have. We examine national data at the global scale to test whether slower population growth or ageing populations are linked to worse economic or social outcomes. Using nine different indices of socio-economic performance (domestic comprehensive wealth, income equality, research and development expenditure, patent applications, human capital, corruption perception index, freedom, planetary pressure-adjusted Human Development Index, healthy life expectancy at birth), we find no evidence that they are. In fact, we find that countries with low or negative population growth perform better on average for all indicators, and that even within-country time series show that most older and slower-growing populations fare better on average. These findings challenge common assumptions and highlight the need to move beyond fear-based and politically motivated narratives toward a more informed understanding of what truly supports thriving societies.

Chalkley, Martin; Colbourn, Tim; Hallett, Timothy B.; Mangal, Tara D.; Molaro, Margherita; Mohan, Sakshi; She, Bingling; Revill, Paul; Tafesse, Wiktoria

doi: 10.48550/arxiv.2508.11730pmid: N/A

Abstract:As computational capacity increases, it becomes possible to model health systems in greater detail. Multi-disease health system models (HSMs) represent a new development, building on individual level epidemiological models of multiple diseases and capturing how healthcare delivery systems respond to population health needs. The Thanzi la Onse (TLO) model of Malawi is the first of its kind in these respects. In this article, we discuss how we have been bringing economic concepts into the TLO model, and how we are continuing to develop this line of research. This has involved incorporating more sophisticated approaches to account for the effects of the unavailability of healthcare workers, and we are working towards establishing the role of different forms of ownership of healthcare facilities and different management practices. Not only does this broad approach make the model more flexible as a tool for understanding the impact of resource constraints, it opens up the possibility of analysing considerably richer policy scenarios; for example establishing an estimate of the health gain that could be achieved through expanding the workforce or reducing healthcare worker absence.

Kennedy, Austin

doi: 10.1016/j.jimonfin.2025.103378pmid: N/A

Abstract:This paper examines fiscal policy spillovers through informal international financial channels, using the US stimulus checks as a positive, sudden, and direct fiscal shock. I utilize granular, transaction-level cryptocurrency data combined with an algorithm to probabilistically identify cross-border "crypto vehicle" transactions to construct bilateral cryptocurrency flows between countries. Using a difference-in-differences strategy, I compare cryptocurrency outflows between the US and other high-income countries and find a sharp but temporary increase in cryptocurrency outflows as a result of the direct stimulus. I quantify the fiscal spillover relative to expenditure and place an upper bound of 2.52% through this channel. This implies that fiscal spillovers through remittance channels are likely modest in size.

Bianchi, Sergio; Angelini, Daniele; Frezza, Massimiliano; Pianese, Augusto

doi: 10.48550/arxiv.2508.11649pmid: N/A

Abstract:Volatility, as a primary indicator of financial risk, forms the foundation of classical frameworks such as Markowitz's Portfolio Theory and the Efficient Market Hypothesis (EMH). However, its conventional use rests on assumptions-most notably, the Markovian nature of price dynamics-that often fail to reflect key empirical characteristics of financial markets. Fractional stochastic volatility models expose these limitations by demonstrating that volatility alone is insufficient to capture the full structure of return dispersion. In this context, we propose pointwise regularity, measured via the Hurst-Holder exponent, as a complementary metric of financial risk. This measure quantifies local deviations from martingale behavior, enabling a more nuanced assessment of market inefficiencies and the mechanisms by which equilibrium is restored. By accounting not only for the magnitude but also for the nature of randomness, this framework bridges the conceptual divide between efficient market theory and behavioral finance.

Mondal, Koushik; Menon, Balagopal G; Sahadev, Sunil

doi: 10.48550/arxiv.2508.17992pmid: N/A

Abstract:The survival of unorganized pharmacies is increasingly challenging in the face of growing competition from organized and e-pharmaceutical retail channels in emerging economies. A theoretical model is developed to capture the triple-channel interactions among unorganized, organized and e-retailing in emerging markets, taking into account the essential features of the pharmaceutical retail landscape, consumers, retailers and pharmaceutical products. Given the retailer and customer-specific factors, the price-setting game between the triple-channel retailers yielded the optimal prices for these retailers. The analysis found that the product category level demand has no influence on optimal pricing strategies of the retailers. The analysis also reveals counterintuitive results, for instance, (i) an increase in customer acceptance of unorganized retailers will result in a decrease in profits of both unorganized and organized retailers; (ii) as the distance and transportation cost to unorganized retailers increases for the consumers, the profit of the unorganized retailer increases; and (iii) consumers marginal utility of money has no influence on the optimal price, but have an influence on the profit of the three retail channels. Our research findings offer valuable insights for policymakers facing challenges in achieving a balanced growth among the organized, unorganized, and e-pharmaceutical retail sectors in emerging economies. Keywords: Unorganized, Organized, and Online E-Retail; Nanostores; Emerging Markets; Game Theory.

Zhang, Duo; Li, Jiayu; Mo, Junyi; Chen, Elynn

doi: 10.1145/3768292.3770407pmid: N/A

Abstract:Accurate volatility forecasts are vital in modern finance for risk management, portfolio allocation, and strategic decision-making. However, existing methods face key limitations. Fully multivariate models, while comprehensive, are computationally infeasible for realistic portfolios. Factor models, though efficient, primarily use static factor loadings, failing to capture evolving volatility co-movements when they are most critical. To address these limitations, we propose a novel, model-agnostic Factor-Augmented Volatility Forecast framework. Our approach employs a time-varying factor model to extract a compact set of dynamic, cross-sectional factors from realized volatilities with minimal computational cost. These factors are then integrated into both statistical and AI-based forecasting models, enabling a unified system that jointly models asset-specific dynamics and evolving market-wide co-movements. Our framework demonstrates strong performance across two prominent asset classes-large-cap U.S. technology equities and major cryptocurrencies-over both short-term (1-day) and medium-term (7-day) horizons. Using a suite of linear and non-linear AI-driven models, we consistently observe substantial improvements in predictive accuracy and economic value. Notably, a practical pairs-trading strategy built on our forecasts delivers superior risk-adjusted returns and profitability, particularly under adverse market conditions.

Bernard, Carole; Chen, Jinghui; Vanduffel, Steven

doi: 10.48550/arxiv.2508.16600pmid: N/A

Abstract:Recent studies have highlighted the significance of higher-order moments - such as coskewness - in portfolio optimization within the financial domain. This paper extends that focus to the field of actuarial science by examining the impact of these moments on key actuarial applications. In the first part, we derive analytical lower and upper bounds for mixed moments of the form $\mathbb{E}(X_1X_2^d)$, where $X_i \sim F_i$ for $i=1,2$, assuming known marginal distributions but unspecified dependence structure. The results are general and applicable to arbitrary marginals and positive integer orders $d$, and we also identify the dependence structures that attain these bounds. These findings are then applied to bound centered mixed moments and explore their mathematical properties. The second part of the paper investigates the influence of higher-order centered mixed moments on key actuarial quantities, including expected shortfall (ES), marginal expected shortfall (MES), and life annuity valuation. Under a copula-based mixture model, we show that coskewness and other odd-order mixed moments exhibit a monotonic relationship with both ES and annuity premiums. However, the effect on MES is more nuanced and may remain invariant depending on the underlying dependence structure.

Mancini, Cecilia

doi: 10.48550/arxiv.2508.18876pmid: N/A

Abstract:We describe a Matlab routine that allows us to estimate the jumps in financial asset prices using the Threshold (or Truncation) method of Mancini (2009). The routine is designed for application to five-minute log-returns. The underlying assumption is that asset prices evolve in time following an Ito semimartingale with, possibly stochastic, volatility and jumps. A log-return is likely to contain a jump if its absolute value is larger than a threshold determined by the maximum increment of the Brownian semimartingale part. The latter is particularly sensitive to the magnitude of the volatility coefficient, and from an empirical point of view, volatility levels typically depend on the time of day (TOD), with volatility being highest at the beginning and end of the day, while it is low in the middle. The first routine presented allows for an estimation of the TOD effect, and is an implementation of the method described in Bollerslev and Todorov (2011). Subsequently, the TOD effect for the stock Apple Inc. (AAPL) is visualized. The second routine presented is an implementation of the threshold method for estimating jumps in AAPL prices. The procedure recursively estimates daily volatility and jumps. In each round, the threshold depends on the time of the day and is constructed using the estimate of the daily volatility multiplied by the daytime TOD factor and by the continuity modulus of the Brownian motion paths. Once the jumps are detected, the daily volatility estimate is updated using only the log-returns not containing jumps. Before application to empirical data, the reliability of the procedure was separately tested on simulated asset prices. The results obtained on a record of AAPL stock prices are visualized.