Papers, wiki, Option Blackboard, encyclopedia, and cards.
Traditional risk-adjusted returns, such as the Treynor, Sharpe, Sortino, and Information ratios, have been pivotal in portfolio asset allocation, focusing on minimizing risk while maximizing profit. Nevertheless, these metrics often fail to account for the distinct characteristics of bull and bear markets, leading to sub-optimal investment decisions. This paper introduces a novel approach called the Market-adaptive R…
This paper studies a type of periodic utility maximization problem for portfolio management in incomplete stochastic factor models with convex trading constraints. The portfolio performance is periodically evaluated on the relative ratio of two adjacent wealth levels over an infinite horizon, featuring the dynamic adjustments in portfolio decision according to past achievements. Under power utility, we transform the …
On a daily investment decision in a security market, the price earnings (PE) ratio is one of the most widely applied methods being used as a firm valuation tool by investment experts. Unfortunately, recent academic developments in financial econometrics and machine learning rarely look at this tool. In practice, fundamental PE ratios are often estimated only by subjective expert opinions. The purpose of this research…
ABSTRACT Most structural models of default preclude the firm from altering its capital structure. In practice, firms adjust outstanding debt levels in response to changes in firm value, thus generating mean‐reverting leverage ratios. We propose a structural model of default with stochastic interest rates that captures this mean reversion. Our model generates credit spreads that are larger for low‐leverage firms, and …
This paper compares different methods for forecasting the term structure of U.S. and European zero-coupon government bonds using both traditional econometric and Machine Learning (ML) approaches. We compare classical models (e.g., Dynamic Nelson-Siegel (DNS) and Principal Component Analysis (PCA)) with different Neural Network (NN) architectures, including those inspired by the classical models, on the U.S. Treasury …
We perform an extensive and robust study of the performance of three different pairs trading strategies—the distance, cointegration and copula methods—on the entire US equity market from 1962 to 2014 with time-varying trading costs. For the cointegration and copula methods, we design a computationally efficient two-step pairs trading strategy. In terms of economic outcomes, the distance, cointegration and copula meth…
Recent multimodal large language models have achieved strong performance in unified text and image understanding and generation, yet extending such native capability to 3D remains challenging due to limited data. Compared to abundant 2D imagery, high-quality 3D assets are scarce, making 3D synthesis under-constrained. Existing methods often rely on indirect pipelines that edit in 2D and lift results into 3D via optim…
We demonstrate that wave amplification enables even weak nonlinearities to reshape linear wave-packet transport in nonreciprocal systems. We study the dynamics of bulk Gaussian wave packets in the Hatano--Nelson model with onsite cubic nonlinearity. We show that the interplay between nonlinearity and amplification generates growing frequency shifts that drive the wave packet through three successive dynamical regimes…
Deep generative models are increasingly used as simulators for downstream decision-making under data scarcity, but in risk-sensitive applications their usefulness depends on rare adverse scenarios rather than typical samples. Standard generative objectives prioritize bulk distributional fidelity, leaving low-probability tails vulnerable to localized optimization noise and making tail-dependent functionals unstable un…
This paper presents a method for forecasting limit order book durations using a self-exciting flexible residual point process. High-frequency events in modern exchanges exhibit heavy-tailed interarrival times, posing a significant challenge for accurate prediction. The proposed approach incorporates the empirical distributional features of interarrival times while preserving the self-exciting and decay structure. Thi…
We study the economic viability of liquidity provision in decentralised exchanges (DEXs) within a structural framework in which market outcomes are endogenous. We formulate strategic interactions as a sequential game: a risk-averse liquidity provider (LP) sets the supply of liquidity in the DEX and a costly dynamic replication strategy in a centralised exchange (CEX), price-sensitive traders determine trading volumes…
This research presents a comprehensive framework for analyzing liquidity in financial markets, particularly in the context of high-frequency trading. By leveraging advanced machine learning classification techniques, including Logistic Regression, Support Vector Machine, and Random Forest, the study aims to predict minute-level price movements using an extensive set of liquidity metrics derived from the Trade and Quo…
This paper compares a series of contemporary portfolio construction approaches by employing ten U.S. stocks (TSLA, WMT, BAC, GS, LLY, MRK, GOOG, META, AAPL and XOM) in a time frame from September 2023 to December 2025. The paper explores both basic mean-variance optimization, constrained optimization, Fama French five factor regression modeling, Monte Carlo simulation, and the Black-Litterman model to determine how c…
We propose Process-Aware Policy Optimization (PAPO), a method that integrates process-level evaluation into Group Relative Policy Optimization (GRPO) through decoupled advantage normalization, to address two limitations of existing reward designs. Outcome reward models (ORM) evaluate only final-answer correctness, treating all correct responses identically regardless of reasoning quality, and gradually lose the advan…
We introduce the Historical and Dynamic Volatility Ratios (HVR/DVR) and show that equity and index volatilities are cointegrated at intraday and daily horizons. This allows us to construct a VECM to forecast portfolio volatility by exploiting volatility cointegration. On S&P 500 data, HVR is generally stationary and cointegration with the index is frequent; the VECM implementation yields substantially lower mean abso…
The time proximity of trades across stocks reveals interesting topological structures of the equity market in the United States. In this article, we investigate how such concurrent cross-stock trading behaviors, which we denote as co-trading, shape the market structures and affect stock price co-movements. By leveraging a co-trading-based pairwise similarity measure, we propose a novel method to construct dynamic net…
In this article, the long-term behavior of the stock market index of the New York Stock Exchange is studied, for the period 1950 to 2013. Specifically, the CRSP Value-Weighted and CRSP Equal-Weighted index are analyzed in terms of market efficiency, using the standard ratio variance test, considering over 1600 one week rolling windows. For the equally weighted index, the null hypothesis of random walk is rejected in …
Automated Market Makers based on concentrated liquidity, such as Uniswap v3, significantly improve capital efficiency but expose Liquidity Providers (LPs) to adverse selection costs, formalized as Loss-Versus-Rebalancing (LVR). While theoretical literature quantifies these costs, the interplay between realistic blockchain microstructure and endogenous pricing mechanisms remains under-explored. This paper develops a g…
The ECB balance sheet reflects the scale of European Central Bank asset holdings and helps track euro-area liquidity, policy transmission, and duration absorption.
Treasury auction bid-to-cover ratio measures the amount of demand relative to supply at an auction and is used to assess investor appetite for government debt.
QT pace refers to the speed at which the Federal Reserve allows assets to roll off its balance sheet, affecting reserves, duration supply, and market liquidity.
Term premium is the extra compensation investors demand for holding longer-term bonds instead of rolling short-term debt, reflecting duration risk, uncertainty, and market structure.
AI pattern combining vector retrieval with model reasoning to reduce hallucination and add memory.
Structured orchestration of tools, models, and memory into repeatable decision pipelines.
Duration Risk — Interest-rate sensitivity of bond portfolios, amplified in low-yield high-duration regimes.
Key Rate Duration — Bucketed rate sensitivity across curve points for relative-value and hedge construction.
Distressed Debt Ratio — Share of debt trading at deep discounts — early warning for credit cycle turns.
Put Call Ratio — Relative demand for downside protection versus upside participation.
Cointegration Pairs Trading — Mean-reversion on stationary spreads between related instruments.
Short Interest Ratio — Crowded short positioning that can fuel squeezes or confirm bearish consensus.
Copper Gold Ratio (Commodities).
Bank Capital Ratio — Loss-absorbing equity buffer determining lending capacity and dividend policy.
Liquidity Coverage Ratio — Regulatory high-quality liquid asset requirement for 30-day stress.
Net Stable Funding Ratio — Stable funding versus long-term assets — constrains maturity transformation.
NPL Ratio Banks — Non-performing loan share signaling late-cycle credit deterioration.
Ratio Spread (Derivatives).
Term Premium Estimate — Compensation for duration risk beyond expected short rates.
Liability Driven Investing — Pension hedging of liabilities with long duration bonds/swaps.
Cointegration Test (Quant).
Information Ratio (Quant).
Sharpe Ratio (Quant).
Sortino Ratio (Quant).
Calmar Ratio (Quant).
ETH BTC Ratio (Crypto).
Distressed Ratio (Fixed Income).
Options Expiration Pinning (Equity).
Leverage Ratio Book (Systems).
Concentration Risk (Systems).
Supplementary Leverage Ratio (Banking).
Duration Gap Banking (Banking).
Loan to Deposit Ratio (Banking).
Diversification Ratio (Quant).
Operation Twist (Macro Policy).
ESG Integration Factor (Quant).
Structured orchestration of tools, models, and memory into repeatable decision pipelines.
Bank Capital Ratio — Loss-absorbing equity buffer determining lending capacity and dividend policy.
Calmar Ratio (Quant).
CET1 Ratio (Banking).
Cointegration Pairs Trading — Mean-reversion on stationary spreads between related instruments.
Cointegration Test (Quant).
Concentration Risk (Systems).
Copper Gold Ratio (Commodities).
Credit Migration Risk (Credit).
Cyber Operational Risk ASEAN (Banking).
Cyber Operational Risk Australia (Banking).
Cyber Operational Risk broker-dealer (Banking).
Cyber Operational Risk Canada (Banking).
Cyber Operational Risk CEEMEA (Banking).
Cyber Operational Risk China (Banking).
Cyber Operational Risk EM Asia (Banking).
Cyber Operational Risk Euro Area (Banking).
Cyber Operational Risk GSIB (Banking).
Cyber Operational Risk India (Banking).
Cyber Operational Risk Japan (Banking).
Cyber Operational Risk Korea (Banking).
Cyber Operational Risk LatAm (Banking).
Cyber Operational Risk Nordics (Banking).
Cyber Operational Risk regional (Banking).