Study finds key investing characteristics for success in equity markets.
problem Understanding what traits lead to financial success in equity markets.
method Exploratory factor analysis and multiple linear regression on 403 respondents' data.
result Investing characteristics significantly impact individual investors' excess return.
The paper diagnoses factor models using characteristic axes and zero-curve restrictions.
problem Tackles systematic sign reversals and overcorrections in factor model pricing errors.
method Extends cap-axis integral diagnostic to general characteristic axes, measuring pricing errors as bridge-alpha curves.
result Axis-level pricing errors are nearly orthogonal to maximum-Sharpe gains, showing systematic sign reversals and overcorrections.
The paper diagnoses factor-model pricing errors using characteristic axes and bridge-alpha curves.
problem Tackles systematic sign reversals and overcorrections in factor-model pricing errors.
method Extends cap-axis integral diagnostic to characteristic axes, measures pricing errors as bridge-alpha curves, and uses a predetermined characteristic order to generate zero-curve restrictions.
result Axis-level pricing errors are nearly orthogonal to maximum-Sharpe gains, showing significant sign reversals and overcorrections.
RL learns to ignore factors in factor investing portfolios.
problem Combining factor investing and reinforcement learning for optimal portfolio allocation.
method RL agent learns through sequential allocations based on firms' characteristics using Dirichlet distributions.
result RL-based portfolios are very close to equally-weighted allocations, indicating agnostic factor learning.
Investment strategies involving cryptocurrencies and VIX INDEX show positive impact in market performance.
problem Investment strategies involving cryptocurrencies and VIX INDEX.
method Parameter estimation on raw data, comparison of two different portfolios, and analysis of different market conditions.
result VIX INDEX positively impacts the investment portfolio of cryptocurrencies in both standard and downward markets.
Real Estate Investment Trusts (REITs) are the only truly liquid assets related to real estate investments. We study the behavior of U.S. REITs over the past three decades and document their return characteristics. REITs have somewhat less market risk than equity; their betas against a broad market index average about .…
In this paper, we study the ruin problem with investment in a general framework where the business part X is a L{é}vy process and the return on investment R is a semimartingale. We obtain upper bounds on the finite and infinite time ruin probabilities that decrease as a power function when the initial capital increases…
The paper models cryptocurrency market bubbles using agent-based models.
problem Understanding speculative bubbles in cryptocurrency markets.
method Agent-based models and ODE models to estimate return rates and market values.
result Formulated formula for total system risk.
Enhances investment performance by leveraging cross-market information.
problem Maximizing portfolio performance in asset markets with shared characteristics.
method Transfer learning applied to portfolio optimization.
result Achieves maximum Sharpe ratio asymptotically.
Generative model learns investment strategies without explicit utility specification.
problem Challenges in modeling complex, multi-objective fund optimization.
method Generative adversarial network (GAN) framework that learns latent strategy representations.
result Framework captures diverse investment styles and realizations of optimization parameters.
Analyst reports contain valuable information for investment decisions.
problem Investment value in analyst reports is not fully understood or utilized.
method Embedded analyst reports with LLMs and ML forecasts of future returns.
result Portfolios formed on analyst report narratives outperform numerical forecasts and established factors.
The investment economy is a main characteristic of prosperous society. The investment portfolio management is a main financial problem, which has to be solved by the investment, commercial and central banks with the application of modern portfolio theory in the investment economy. We use the learning analytics together…
In this paper we propose a novel application of Gaussian processes (GPs) to financial asset allocation. Our approach is deeply rooted in Stochastic Portfolio Theory (SPT), a stochastic analysis framework introduced by Robert Fernholz that aims at flexibly analysing the performance of certain investment strategies in st…
Enhances thematic investing with stock embeddings from textual data.
problem Challenges in constructing thematic portfolios due to overlapping sector boundaries and evolving market dynamics.
method Introduces THEME, a framework that fine-tunes embeddings using hierarchical contrastive learning, aligning themes and stocks using their hierarchical relationship and incorporating stock returns.
result Theme-aligned portfolios demonstrate compelling performance, significantly outperforming large language models in thematic asset retrieval.
Strategic valuation of efficient and well-timed network investments under uncertain electricity market environment has become increasingly challenging, because there generally exist multiple interacting options in these investments, and failing to systematically consider these options can lead to decisions that underva…
Game theory models storage investment to balance market competition and profits.
problem Strategic storage investment impacts electricity market prices and revenues.
method Formulated a non-cooperative game between investors to model strategic storage decisions.
result Increasing storage capacity reduces individual profits but increases total investment.
We pursue an inverse approach to utility theory and consumption & investment problems. Instead of specifying an agent's utility function and deriving her actions, we assume we observe her actions (i.e. her consumption and investment strategies) and ask if it is possible to derive a utility function for which the observ…
TDA improves cryptocurrency portfolio management.
problem Traditional methods fail to manage cryptocurrencies effectively.
method Topological Data Analysis (TDA) for identifying investment opportunities.
result TDA-based portfolio management outperforms traditional methods.
The portfolio optimization problem in which the variances of the return rates of assets are not identical is analyzed in this paper using the methodology of statistical mechanical informatics, specifically, replica analysis. We define two characteristic quantities of an optimal portfolio, namely, minimal investment ris…
The study assesses music as an investment asset class using discounted cashflow models.
problem Quantifying the risk and return characteristics of music royalty assets.
method Fitting three discounted cashflow models to Royalty Exchange platform transactions and backtesting performance.
result Life of Rights music assets had risk and return characteristics comparable to stocks in the S\&P500 over 5 years.
Behavioral theories posit that investor sentiment exhibits predictive power for stock returns, whereas there is little study have investigated the relationship between the time horizon of the predictive effect of investor sentiment and the firm characteristics. To this end, by using a Granger causality analysis in the …
TDA improves stock portfolio selection by analyzing data structure.
problem Traditional portfolio selection methods fail to handle stock market data complexities.
method Two-stage method involving time series generation and clustering with TDA features.
result TDA-based portfolio outperforms other methods consistently over different time frames.
Artificial intelligence, or AI, enhancements are increasingly shaping our daily lives. Financial decision-making is no exception to this. We introduce the notion of AI Alter Egos, which are shadow robo-investors, and use a unique data set covering brokerage accounts for a large cross-section of investors over a sample …
Trend following in cryptocurrencies yields high returns, similar to commodities.
problem Investing in cryptocurrencies using trend following strategies.
method A decade of data analysis on cryptocurrency markets and trend following strategies.
result Cryptocurrencies offer strong returns and diversification against traditional equities.
This paper diagnoses factor-model pricing errors using a new method.
problem Measuring pricing errors in factor models with general characteristic axes.
method Developed a method to measure factor-model pricing errors as bridge-alpha curves, using a predetermined characteristic order and prefix portfolios.
result Adding a counterpart factor flips the curve's sign on every axis, but only HML and CMA overcorrect enough to be rejected.
We study Atlas-type models of equity markets with local characteristics that depend on both name and rank, and in ways that induce a stable capital distribution. Ergodic properties and rankings of processes are examined with reference to the theory of reflected Brownian motions in polyhedral domains. In the context of …
Study uses MLP models to predict large-cap US stocks, finding 2-3 hidden layers more flexible.
problem Predicting asset prices for large-cap US stocks.
method Applied MLP models with dynamic structure to factor models, focusing on firm characteristics.
result MLP models with 2-3 hidden layers more flexible in modeling factors, better for downside risk control.
This study examines representation bias in open-source Qwen models for investment decisions.
problem Representation bias in financial applications of large language models.
method Balanced round-robin prompting over 150 U.S. equities, constrained decoding, token-logit aggregation.
result Firm size and valuation increase model confidence, while risk factors decrease it.
A strategy to beat benchmarks by investing in heavily shorted but fundamentally sound securities.
problem Overcoming behavioral biases in investing, particularly the 'rebound effect'.
method Quantitative metrics, historical data, and securities lending modeling.
result The Bounce Basket strategy can outperform market returns during market downturns.
Cryptocurrencies show similarities to traditional markets but also have unique characteristics.
problem Understanding the investment potential and characteristics of cryptocurrencies.
method Organized stylized facts and analyzed through empirical asset pricing.
result Cryptocurrencies exhibit similarities to traditional markets but also have distinct characteristics.
We study a robust portfolio optimization problem under model uncertainty for an investor with logarithmic or power utility. The uncertainty is specified by a set of possible Lévy triplets; that is, possible instantaneous drift, volatility and jump characteristics of the price process. We show that an optimal investment…
The numeraire portfolio in a financial market is the unique positive wealth process that makes all other nonnegative wealth processes, when deflated by it, supermartingales. The numeraire portfolio depends on market characteristics, which include: (a) the information flow available to acting agents, given by a filtrati…
Automated investment managers, or robo-advisors, have emerged as an alternative to traditional financial advisors. The viability of robo-advisors crucially depends on their ability to offer personalized financial advice. We introduce a novel framework, in which a robo-advisor interacts with a client to solve an adaptiv…
We present analytical investigations of a multiplicative stochastic process that models a simple investor dynamics in a random environment. The dynamics of the investor's budget, x(t), depends on the stochasticity of the return on investment, r(t), for which different model assumptions are discussed. The fat-tail d…
The study finds significant financial sector volatility and tail risk spillovers to real economy sectors.
problem Volatility and tail risk spillovers from financial to real economy sectors.
method New measure of tail risk spillover, empirical analysis of U.S. economy 2001-2011.
result Significant volatility and tail risk spillovers from financial to real economy sectors, especially during crises.
WSB's investment advice significantly outperformed the S&P500 over 3 years, but not consistently.
problem Reliability of investment advice from WSB community.
method Data analysis of WSB posts and stock performance from 2019-2021.
result A WSB portfolio grew 200% over 3 years and 480% over 1 year, outperforming S&P500.
Investors benefit from long horizons in a market with mean-reverting equity returns.
problem Optimal portfolio choice in a market with mean-reverting risk-free rate and equity risk-premium.
method Mean-variance optimization, Euler-Lagrange equation, Calculus of Variations, spectral problem.
result Optimal policies are characterized by eigenvalues of the lambda-matrix, leading to better risk-return trade-offs for long-term investors.
The paper defines the time function of stock prices using a mathematical model.
problem Understanding the movement and predictability of stock prices over time.
method Empirical evidence and mathematical modeling of white noise.
result Derives auto-correlation function, displacement formula, and power spectral density of stock price movement.
Research identifies four motivational groups for crypto-metaverse landowners.
problem Understanding motivations of retail investors in the crypto-metaverse.
method Detailed financial behavior survey and principal components analysis.
result Four distinct motivational groups identified: Aesthetics, Social, Speculation, Innovation.
In this paper, we develop an expected utility model for the retirement behavior in the decumulation phase of Australian retirees with sequential family status subject to consumption, housing, investment, bequest and government provided means-tested Age Pension. We account for mortality risk and risky investment assets,…
DSPO optimizes portfolio construction from raw stock data efficiently.
problem Manual design and misalignment in traditional portfolio construction methods.
method End-to-end neural network framework with Monotonical Logistic Regression loss.
result DSPO constructs optimal sorted portfolios with high performance metrics.
Model predicts alternating market dominance for two competing firms.
problem Alternating market dominance of two competing firms in a competitive market.
method Deterministic model with investment strategy, stability analysis of fixed points, bifurcation diagrams, time-series analysis.
result Leapfrogging regime is stabilized by specific parameter values and high elasticity coefficient.
Model shows how heterogeneity in strategies and risk tolerance affects financial market stability.
problem Understanding how heterogeneity impacts financial market dynamics.
method Agent-based model incorporating heterogeneous investment strategies and risk tolerance.
result Heterogeneity in strategies and risk tolerance suppresses price fluctuations.
A framework tackles model uncertainty in ALM, providing robust investment strategies.
problem Model uncertainty in asset liability management (ALM).
method Wasserstein barycenter approach to handle various information sources and uncertainties.
result The proposed framework selects robust investment portfolios that remain optimal under various uncertainties.
The article first describes characteristics of major infrastructure projects. Second, it documents a much neglected topic in economics: that ex ante estimates of costs and benefits are often very different from actual ex post costs and benefits. For large infrastructure projects the consequence is cost overruns, benefi…
FinMem enhances LLM trading agents with layered memory and character design.
problem Developing purpose-driven LLM agents for financial decision-making.
method Integrates layered memory and character design modules into an LLM framework.
result Significantly enhanced trading performance in financial markets.
In the seminal work [9], several macroscopic market observables have been introduced, in an attempt to find characteristics capturing the diversity of a financial market. Despite the crucial importance of such observables for investment decisions, a concise mathematical description of their dynamics has been missing. W…
Study benchmarks mutual funds in India using DEA, finding efficiency metrics.
problem Benchmark mutual funds in India based on efficiency metrics.
method Data Envelopment Analysis (DEA) model incorporating risk, cost, return, and information ratio.
result DEA model identifies efficiency frontier and compares results with traditional metrics.