arXiv · arXiv q-fin · 2013
The currency carry trade is the investment strategy that involves selling low interest rate currencies in order to purchase higher interest rate currencies, thus profiting from the interest rate differentials. This is a well known financial puzzle to explain, since assuming foreign exchange risk is uninhibited and the markets have rational risk-neutral investors, then one would not expect profits from such strategies…
Matthew Ames, Guillaume Bagnarosa, Gareth W. Peters
OpenAlex · The Journal of Finance · 1996 · cites 2072
ABSTRACT This article examines the optimal capital structure of a firm that can choose both the amount and maturity of its debt. Bankruptcy is determined endogenously rather than by the imposition of a positive net worth condition or by a cash flow constraint. The results extend Leland's (1994a) closed‐form results to a much richer class of possible debt structures and permit study of the optimal maturity of debt as …
Hayne E. Leland, Klaus Bjerre Toft
arXiv · arXiv · 2024
The Capital Asset Pricing Model (CAPM) relates a well-diversified stock portfolio to a benchmark portfolio. We insert size effect in the CAPM, capturing the observation that small stocks have higher risk and return than large stocks, on average. Our goal is to make the resulting linear regressions have independent identically distributed Gaussian residuals. In some cases, we find that including the Volatility Index a…
Abraham Atsiwo, Andrey Sarantsev
arXiv · arXiv · 2024
The Proof of Efficient Liquidity (PoEL) protocol, designed for specialised Proof of Stake (PoS) consensus-based blockchains that incorporate intrinsic DeFi applications, aims to support sustainable liquidity bootstrapping and network security. This concept seeks to efficiently utilise budgeted staking rewards to attract and sustain liquidity through a risk-structuring engine and incentive allocation strategy, both of…
Arman Abgaryan, Utkarsh Sharma, Joshua Tobkin
arXiv · arXiv · 2023
This paper presents an empirical analysis of the capital asset pricing model using trading data for the Chinese A-share market from 2000 to 2019. Firstly, the standard CAPM is tested using a Fama-MacBetch regression and although the results successfully test the three core hypotheses, the resulting beta risk does not have a significant impact on returns. Secondly, the Fama-French three-factor model, which uses a comb…
Kai Ren
arXiv · arXiv · 2013
The principal portfolios of the standard Capital Asset Pricing Model (CAPM) are analyzed and found to have remarkable hedging and leveraging properties. Principal portfolios implement a recasting of any correlated asset set of N risky securities into an equivalent but uncorrelated set when short sales are allowed. While a determination of principal portfolios in general requires a detailed knowledge of the covariance…
M. Hossein Partovi
arXiv · arXiv · 2010
This paper examines the validity of the Capital Asset Pricing Model (CAPM) on the Ugandan stock market using monthly stock returns from 10 of the 11 companies listed on the Uganda Stock Exchange (USE), for the period 1st March 2007 to 10th November 2009. Due to the absence of readily available Uganda Stock Exchange(USE) data, and the placement of daily price lists in pdf only, on the USE website: http://www.use.or.ug…
David Wakyiku
arXiv · arXiv · 2026
We present SAiFE_gym, a Python module that provides a collection of simulation environments for studying trading problems in Constant Product Markets (CPMs) with Concentrated Liquidity (CL). These markets give Liquidity Providers (LPs) granular control over how their capital is allocated and enable them to adjust their range of liquidity provision dynamically based on market conditions, which in turn, dictates how th…
Georgios Chionas, Charalampos Kleitsikas, Stefanos Leonardos, Leandro Sánchez-Betancourt, Carmine Ventre
arXiv · arXiv · 2026
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…
Daniele Maria Di Nosse, Fabrizio Lillo
arXiv · arXiv · 2026
Automated market makers (AMMs) are a cornerstone of decentralised finance (DeFi). Constant product markets with concentrated liquidity, such as UniswapV3, are now a well-established design. In these markets, liquidity providers (LPs) face a sequential decision problem: they must decide when to rebalance their positions and which price ranges to allocate capital to as market conditions evolve. We formulate dynamic liq…
Georgios Chionas, Charalampos Kleitsikas, Stefanos Leonardos, Leandro Sánchez-Betancourt, Carmine Ventre
arXiv · arXiv · 2026
We introduce $\textbf{Slippage-at-Risk (SaR)}$, a quantitative framework for measuring liquidity risk in perpetual futures exchanges. Unlike backward-looking metrics such as Value-at-Risk computed on historical returns or realized deficit distributions, SaR provides a \emph{forward-looking} assessment of liquidation execution risk derived from current order book microstructure. The framework comprises three complemen…
Otar Sepper
arXiv · arXiv · 2025
We establish a general matched filter principle for order flow normalization: optimal normalization must match the scaling behaviour of the signal-generating process. For capacity-constrained institutional investors, market capitalization normalization ($S^{MC}$) is the matched filter; for volume-targeting traders (e.g., VWAP/TWAP algorithms), trading value normalization ($S^{TV}$) is optimal. Monte Carlo simulations…
Sungwoo Kang
arXiv · arXiv · 2025
Prediction markets have gained adoption as on-chain mechanisms for aggregating information, with platforms such as Polymarket demonstrating demand for stablecoin-denominated markets. However, denominating in non-interest-bearing stablecoins introduces inefficiencies: participants face opportunity costs relative to the fiat risk-free rate, and Bitcoin holders in particular lose exposure to BTC appreciation when conver…
Fedor Shabashev
arXiv · arXiv · 2025
This study investigates the pre-trained RNN attention models with the mainstream attention mechanisms, such as additive attention, Luong's three attentions, global self-attention and sliding window sparse attention, for the empirical asset pricing research on the top 420 large-cap US stocks. This is the first paper on the large-scale state-of-the-art (SOTA) attention mechanisms applied in the asset pricing context. T…
Shanyan Lai
arXiv · arXiv · 2025
Concentrated Liquidity Market Makers (CLMMs) represent a fundamental innovation in market microstructure, transforming liquidity provision from passive portfolio allocation to active risk management. This evolution creates significant challenges for performance evaluation and strategy optimization, particularly due to the absence of comprehensive historical liquidity data. We address these challenges through a novel …
Andrey Urusov, Rostislav Berezovskiy, Anatoly Krestenko, Andrei Kornilov, Yury Yanovich
arXiv · arXiv · 2025
This paper proposes an innovative Transformer model, Single-directional representative from Transformer (SERT), for US large capital stock pricing. It also innovatively applies the pre-trained Transformer models under the stock pricing and factor investment context. They are compared with standard Transformer models and encoder-only Transformer models in three periods covering the entire COVID-19 pandemic to examine …
Shanyan Lai
arXiv · arXiv · 2025
Decentralized exchanges (DEXs) face persistent challenges in liquidity retention and user engagement due to inefficiencies in conventional automated market maker (AMM) designs. This work proposes a dual-mechanism framework to address these limitations: a ``Better Market Maker (BMM)'', which is a liquidity-optimized AMM based on a power-law invariant ($X^nY = K$, $n = 4$), and a dynamic rebate system (DRS) for redistr…
CY Yan, Steve Keol, Xo Co, Nate Leung
arXiv · arXiv · 2025
Cryptocurrency portfolio management requires the fusion of heterogeneous multi-modal signals, including structured price and on-chain time series, unstructured news text, and technical indicators, under high-volatility and real-time constraints. While deep learning approaches show predictive capability, their opacity limits practical adoption, and single large language model (LLM) agents struggle to process the bread…
Yichen Luo, Yebo Feng, Jiahua Xu, Paolo Tasca, Yang Liu