A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
This paper optimizes portfolio rebalancing under uncertain security returns using meta-heuristic algorithms.
Study shows SEC crypto classification led to significant market reactions.
Markowitz simplified portfolio returns assuming constant trade volumes.
New model values equity-linked securities with guaranteed return.
Unified market-based description of returns and variances of trades.
This paper deals with an optimal position management problem for a market maker who has to face uncertain customer order flows in an illiquid market, where the market maker's continuous trading incurs a stochastic linear price impact. Although the execution timing is uncertain, the market maker can also ask its OTC cou…
It is customary that when security prices fully reflect all available information, the markets for those securities are said to be efficient. And if markets are inefficient, investors can use available information ignored by the market to earn abnormally high returns on their investments. In this context this paper tri…
We consider the problem of belief aggregation: given a group of individual agents with probabilistic beliefs over a set of uncertain events, formulate a sensible consensus or aggregate probability distribution over these events. Researchers have proposed many aggregation methods, although on the question of which is be…
A new method uses preference relations to reconcile contradictory trading signals from multiple securities.
The paper examines Indian market bubbles using financial ratios.
Market-based portfolio variance measures risks using trade data.
This paper studies directed exploration for reinforcement learning agents by tracking uncertainty about the value of each available action. We identify two sources of uncertainty that are relevant for exploration. The first originates from limited data (parametric uncertainty), while the second originates from the dist…
The paper addresses portfolio allocation with uncertain covariance matrices, finding a logarithmic risk dependence.
We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative meas…
The vector of periodic, compound returns of a typical investment portfolio is almost never a convex combination of the return vectors of the securities in the portfolio. As a result the ex post version of Harry Markowitz's "standard mean-variance portfolio selection model" does not apply to compound return data. We pro…
The future value of a security is described as a random variable. Distribution of this random variable is the formal image of risk uncertainty. On the other side, any present value is defined as a value equivalent to the given future value. This equivalence relationship is a subjective. Thus follows, that present value…
Optimizes a portfolio for an investor preferring accepted securities over a reference security.
SPAC data shows premium investors get better terms, non-premium get quid pro quo deals.
In this paper we consider an interval portfolio selection problem with uncertain returns and introduce an inclusive concept of satisfaction index for interval inequality relation. Based on the satisfaction index, we propose an approach to reduce the interval programming problem with uncertain objective and constraints …
How an investor invests in the market is largely influenced by the market efficiency because if a market is efficient, it is extremely difficult to make excessive returns because in an efficient market there will be no undervalued securities i.e. securities whose value is less than its assumed intrinsic value, which of…
This study investigates how Decision-Focused Learning improves stock return predictions for better portfolio optimization.
The correlation matrix is the key element in optimal portfolio allocation and risk management. In particular, the eigenvectors of the correlation matrix corresponding to large eigenvalues can be used to identify the market mode, sectors and style factors. We investigate how these eigenvalues depend on the time scale of…
Historical returns depend on historical closing prices and distributions. We describe how to compute adjusted closing prices from closing price/distribution data with an emphasis on spreadsheet implementation. Then the growth of a security from one date to another (1 + total return) is just the ratio of the correspondi…
We analyze four structured products that have caused severe losses to investors in recent years. These products are: return optimization securities, yield magnet notes, reverse exchangeable securities, and principal-protected notes. We describe the basic structure of these products, analyze them probabilistically using…
Investors' models of future returns are uncertain and interrelated.
We develop a theory of securities price formation and dynamics based on quantum approach and without presuming any similarities with quantum mechanics. Disorder introduced by trading environment leads to probability distribution of returns that is not a smooth curve, but a speckle-pattern fluctuating in both price coor…
Classical mean-variance portfolio theory tells us how to construct a portfolio of assets which has the greatest expected return for a given level of return volatility. Utility theory then allows an investor to choose the point along this efficient frontier which optimally balances her desire for excess expected return …
Framework for responsible LLM deployment with human involvement and decentralized technologies.
This paper explores portfolio management strategies to maximize alpha and minimize beta.
We present a phenomenological study of stock price fluctuations of individual companies. We systematically analyze two different databases covering securities from the three major US stock markets: (a) the New York Stock Exchange, (b) the American Stock Exchange, and (c) the National Association of Securities Dealers A…
Geometrically convex return risk measures on AM-algebras
New method corrects Markowitz variance for trading volume fluctuations.
Bayesian method improves portfolio selection by updating expected returns.
Risk is an inherent feature of agricultural production and marketing and accurate measurement of it helps inform more efficient use of resources. This paper examines three tail quantile-based risk measures applied to the estimation of extreme agricultural financial risk for corn and soybean production in the US: Value …
There is bountiful evidence that political uncertainty stemming from presidential elections or doubt about the direction of future policy make financial markets significantly volatile, especially in proximity to close elections or elections that may prompt radical policy changes. Although several studies have examined …
Paper optimizes financial trading strategies under uncertain market conditions.
The SIP's accuracy is questioned, leading to skewed returns for high-volume stocks.
This paper examines SVB's failure and its impact on bank stocks.
There are some statistical anomalies in the Chinese stock market, i.e., positive return skewness, anti-leverage effect (positive returns induce higher volatility than negative returns); and reverse volatility asymmetry (contemporaneous return-volatility correlation is positive). In this paper, we first confirm the exis…
A strategy to beat benchmarks by investing in heavily shorted but fundamentally sound securities.
This paper analyzes the robust growth rate of leveraged ETFs under uncertain parameters.
Develops a model for optimal trading with uncertain volume targets.
We study the price dynamics of stocks traded in the NASDAQ market by considering the statistical properties of an ensemble of stocks traded simultaneously. For each trading day of our database, we study the ensemble return distribution by extracting its first two central moments. According to previous results obtained …
We introduce a new general framework for constructing the best trading strategy for a given historical indicator. We construct the unique trading strategy with the highest expected return. This optimal strategy may be implemented directly, or its expected return may be used as a benchmark to evaluate how far away from …
Robust optimization improves portfolio selection by accounting for deep uncertainties.
Funds inflate their returns due to price pressure, leading to wealth reallocation and market crashes.
Price and return predictions are limited by economic complexity, not just volatility.
Research improves fraud detection in e-commerce by predicting delayed transaction data.