The paper defines successful active management and introduces a framework.
problem The elusive criteria for successful active management in the literature.
method Introducing definitions of key concepts and a logically coherent evaluation framework.
result A strong defense of active management emerges through the defined concepts.
De Finetti's 1931 work laid the groundwork for modern arbitrage theory.
problem The lack of recognition of de Finetti's contributions to arbitrage theory.
method Examining de Finetti's 1931 work and its relation to recent developments in Robust Finance.
result De Finetti's work is considered the precursor of Asset Pricing Theory.
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…
The paper reviews historical and modern approaches to asset pricing probability measures.
problem Constructing or selecting probability measures for asset pricing.
method Historical review of various approaches including state price theory, martingale measures, and modern data-driven methods.
result Modern asset pricing involves constructing, transforming, or selecting probability measures to represent market prices.
Combines option pricing and portfolio theory for optimal hedging.
problem Optimal hedging of European options in various price dynamics.
method Derives optimal holdings and unhedged risk for different price dynamics.
result Derives solutions for various price dynamics including binomial, diffusion, volatility, volatility-of-volatility, and jump diffusion.
Combines multiple asset views with machine learning for better portfolio allocation.
problem Portfolio allocation with multiple uncertain asset views.
method Consistency-based data fusion techniques for combining Black-Litterman model with machine learning predictions.
result Improved portfolio allocation through fusion of multiple view estimates.
Generalizes insider trading model to multiple assets.
problem Modeling informed trading in a multi-asset context.
method Formulated an infinite-dimensional Bayesian trading game.
result Obtained a parsimonious equilibrium with closed-form solutions.
Investors use various asset allocation strategies to meet financial goals.
problem Finding the optimal asset allocation for individual investors is challenging.
method Conducted a benchmark study comparing traditional and machine learning approaches.
result Deep reinforcement learning models outperformed traditional methods in both bullish and bearish markets.
Introduces new financial models using subordinated processes.
problem Modeling asset returns with behavioral finance considerations.
method Introduces multiple internally embedded financial time-clocks, subordinated to Brownian motion, with a behavioral subordinator.
result New log-price process with multiple embedded subordinations, requiring estimation of new parameters.
Along with the advance of opinion mining techniques, public mood has been found to be a key element for stock market prediction. However, how market participants' behavior is affected by public mood has been rarely discussed. Consequently, there has been little progress in leveraging public mood for the asset allocatio…
Hopfield networks outperform deep-learning methods in portfolio optimization.
problem Optimizing portfolios and managing asset allocation efficiently.
method Application of Hopfield networks to portfolio optimization, using combinatorial purged cross-validation.
result Modern Hopfield Networks perform on par or better than deep-learning methods, with faster training times and better stability.
Quantum algorithm for dynamic asset allocation using expected shortfall.
problem Dynamic risk management in finance, especially tail risks.
method Quantum annealing algorithm in QUBO form for expected shortfall constraint.
result Quantum algorithm provides a faster solution for dynamic asset allocation.
Price and return predictions are limited by economic complexity, not just volatility.
problem Limited accuracy of price and return probability forecasts by Gaussian distributions.
method Analyzes economic reasons behind limitations in predicting price and return statistical moments.
result Predictions of price and return probabilities by Gaussian distributions are inaccurate due to economic complexity.
This paper is devoted to study the optimal portfolio problem. Harry Markowitz's Ph.D. thesis prepared the ground for the mathematical theory of finance. In modern portfolio theory, we typically find asset returns that are modeled by a random variable with an elliptical distribution and the notion of portfolio risk is d…
Project predicts stock prices for robust portfolio design in Indian sectors.
problem Precise stock price prediction for robust portfolio design.
method Minimum variance and optimal risk portfolio optimization using past stock prices.
result Backtesting shows improved performance of optimized portfolios over equal weight portfolio.
Integrates ESG factors into Bachelier's model for asset pricing.
problem Incorporating ESG factors into classical finance models.
method Defines ESG price process and integrates into Bachelier's model.
result Enables option pricing valuation with ESG factors.
Statistical arbitrageurs have inelastic demand, contrary to classical models.
problem Understanding the demand elasticity of statistical arbitrageurs.
method Thirteen models from the literature and a quantitative equilibrium model.
result Aggregate demand remains inelastic even with statistical arbitrageurs.
Study tests 11 stylized facts for modern stock markets, finding support for 8.
problem Whether stylized facts from 2001 still hold for modern markets.
method Replicated 11 stylized facts for intraday returns of Dow 30 stocks using authoritative data.
result 8 of 11 stylized facts supported, 3 not supported.
Modern portfolio theory(MPT) addresses the problem of determining the optimum allocation of investment resources among a set of candidate assets. In the original mean-variance approach of Markowitz, volatility is taken as a proxy for risk, conflating uncertainty with risk. There have been many subsequent attempts to al…
Transformer model improves asset allocation by unifying forecasting and optimization.
problem Separation of forecasting and optimization leads to suboptimal portfolios.
method Signature Informed Transformer using path signatures and specialized attention.
result Direct minimization of Conditional Value at Risk improves performance.
TPLVM models portfolio construction for non-Gaussian financial data.
problem Optimal asset allocation in finance with non-Gaussian fluctuations.
method Student's t-process latent variable model (TPLVM) for portfolio optimization.
result TPLVM outperforms Gaussian process latent variable model in minimum-variance portfolio construction.
Machine learning models outperform traditional CAPM in forecasting financial asset prices.
problem Predicting and forecasting financial asset prices and returns.
method Comparison of modern Machine Learning algorithms with the Capital Asset Pricing Model (CAPM) on U.S. equities data.
result Implemented Machine Learning models significantly outperform the CAPM on out-of-sample test data.
Utility and risk are two often competing measurements on the investment success. We show that efficient trade-off between these two measurements for investment portfolios happens, in general, on a convex curve in the two dimensional space of utility and risk. This is a rather general pattern. The modern portfolio theor…
The paper develops a test for EU portfolio efficiency in high dimensions.
problem Testing the efficiency of the EU portfolio in high-dimensional settings.
method Shrinkage-based approach for portfolio weights and random matrix theory.
result Asymptotic behavior of the test statistic under high-dimensional conditions.
Paper uses AI to optimize crypto portfolios, showing better risk-adjusted returns.
problem Managing volatile crypto markets with high volatility.
method Multi-agent system designed to autonomously construct and evaluate crypto-asset allocations.
result Dynamic optimization strategy outperforms static equal weighting strategy in terms of risk-adjusted returns.
We explain the main concepts of Prospect Theory and Cumulative Prospect Theory within the framework of rational dynamic asset pricing theory. We derive option pricing formulas when asset returns are altered with a generalized Prospect Theory value function or a modified Prelec weighting probability function and introdu…
For the past two decades investors have observed long memory and highly correlated behavior of asset classes that does not fit into the framework of Modern Portfolio Theory. Custom correlation and standard deviation estimators consider normal distribution of returns and market efficiency hypothesis. It forced investors…
The study identifies core and satellite segments in the cryptocurrency market.
problem Identifying similar cryptocurrencies for strategic asset allocation.
method Segmentation of the cryptocurrency market using image / pattern recognition methods.
result Core and satellite segments identified in the cryptocurrency market.
Paper uses inverse optimization to measure risk preference from investment portfolios.
problem Measuring subjective risk preference in investment portfolios.
method Inverse optimization on mean-variance framework.
result Quantified risk preference parameters validated with existing measures.
The paper refutes standard asset pricing models and introduces new theories.
problem Inaccuracies in standard asset pricing models.
method Introduces new theories and empirical tests to explain asset pricing anomalies.
result New theories explain why standard models are inaccurate and provide insights.
A new risk budgeting scheme derived from universal portfolio theory.
problem Risk allocation in portfolio management.
method Integrates Cover's universal portfolio selection with modern risk allocation models.
result Proves mathematical equivalence to a novel universal portfolio scheme.
Game theory model shows optimal investment strategy for wealth growth.
problem Minimizing time to reach large wealth in a stochastic asset market.
method Proved strategy of proportional asset investment minimizes expected time.
result Proportional investment strategy asymptotically minimizes time to large wealth.
The study examines higher-order modern portfolio theory with complex critical points and feasible portfolio variety.
problem Understanding the complex critical points and feasible portfolio variety in higher-order modern portfolio theory.
method Established genericity conditions for utility functions with higher-order cumulants, analyzed discriminant loci, and determined the dimension and degree of the feasible portfolio variety.
result The utility function has a constant number of complex critical points under genericity conditions, and the feasible portfolio variety has a determined dimension and degree.
In the world of modern financial theory, portfolio construction has traditionally operated under at least one of two central assumptions: the constraints are derived from a utility function and/or the multivariate probability distribution of the underlying asset returns is fully known. In practice, both the performance…
Asset liquidity in modern financial markets is a key but elusive concept. A market is often said to be liquid when the prevailing structure of transactions provides a prompt and secure link between the demand and supply of assets, thus delivering low costs of transaction. Providing a rigorous and empirically relevant d…
Private credit markets have expanded significantly, offering unique lending technology to private equity firms.
problem Understanding the growth and characteristics of private credit markets.
method Systematic survey of academic literature, development of integrated theoretical framework, empirical evidence.
result Private credit markets offer a distinct lending technology with higher spreads over syndicated loans.
Complexity helps identify sparse risk factors in asset pricing.
problem Tension between feature richness and economic parsimony in high-dimensional asset pricing.
method Expanding feature space and using basis pursuit to discover sparse risk factors.
result Nonlinear feature expansions combined with basis pursuit yield superior out-of-sample performance.
Study improves portfolio optimization by reducing estimation errors and turnover.
problem Inefficient out-of-sample performance of modern portfolio theory.
method Combines sparse model approaches with covariance estimation techniques and includes a turnover constraint.
result Shows it's possible to maintain low-risk profile while selecting a subset of assets and reducing turnover.
Market efficiency at least requires the absence of weak arbitrage opportunities, but this is not sufficient to establish a situation where the market is sensitive, i.e., where it "fully reflects" or "rapidly adjusts to" some information flow including the evolution of asset prices. By contrast, No Weak Arbitrage togeth…
Modernizes classical theory linking isothermic surfaces to Bonnet pairs.
problem Classical theory of isothermic surfaces and Bonnet pairs.
method Identifies derivatives of Bonnet pairs with retraction form of isothermic surfaces.
result Modern account and identification of retraction form.
New algorithm improves asset ranking for better cross-sectional portfolios.
problem Sub-optimal ranking of assets in cross-sectional systematic strategies.
method Learning-to-rank algorithms to enhance portfolio construction.
result Modern machine learning ranking algorithms boost Sharpe Ratios by approximately threefold.
Option pricing is an integral part of modern financial risk management. The well-known Black and Scholes (1973) formula is commonly used for this purpose. This paper is an attempt to extend their work to a situation in which the unconditional volatility of the original asset is increasing during a certain period of tim…
New method uses impact IRR to assess impact investments.
problem Determining financial returns of impact investments remains challenging.
method Adapts modern portfolio theory and financial tools to evaluate impact investments.
result Demonstrates the feasibility and utility of impact IRR for optimizing impact investments.
The paper proposes using network science to improve portfolio optimization by reducing noise in covariance estimation.
problem Noise in covariance estimation leads to suboptimal portfolio performance.
method The paper introduces SR-IFN, a network-based method to filter out noise from empirical covariance, enhancing portfolio optimization.
result The SR-IFN network improves portfolio performance by selecting peripheral, diversified assets and inversely weighting them based on centrality.
Modern differential cohomology explained with applications.
problem Understanding differential cohomology from a modern perspective.
method Sheaves on manifolds, Chern-Weil theory, differential characters, differential characteristic classes.
result Differential lift of the first Pontryagin class.
Develops a theory linking managers' disclosures to market pricing.
problem Linking managers' earnings guidance to market pricing.
method Mathematical theory of managerial disclosure in asset pricing.
result Foundational approach for understanding disclosure impacts.
Predict water pipe failures using machine learning and survival analysis.
problem Difficulty in accessing water pipes for maintenance.
method Classical and modern classifiers for short-term prediction, survival analysis for long-term forecast, and oversampling technique for imbalanced data.
result Identifies important risk factors for water pipe failures.
New theory shows perishable goods markets are more stable and efficient.
problem Lower stability and efficiency of markets for re-tradable assets compared to perishable goods.
method Reformulation of no-trade and no-arbitrage theorems in neoclassical finance.
result Perishable goods markets exhibit higher stability and efficiency.