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.
Classifies financial markets up to financial indistinguishability.
We maximize the expected utility from terminal wealth for an HARA investor when the market price of risk is an unobservable random variable. We compute the optimal portfolio explicitly and explore the effects of learning by comparing it with the corresponding myopic policy. In particular, we show that, for a market pri…
We study utility indifference prices and optimal purchasing quantities for a contingent claim, in an incomplete semi-martingale market, in the presence of vanishing hedging errors and/or risk aversion. Assuming that the average indifference price converges to a well defined limit, we prove that optimally taken position…
Study solves DREs for trading strategies using signals and past prices.
We introduce a class of utility-based market makers that always accept orders at their risk-neutral prices. We derive necessary and sufficient conditions for such market makers to have bounded loss. We prove that hyperbolic absolute risk aversion utility market makers are equivalent to weighted pseudospherical scoring …
This paper formulates an utility indifference pricing model for investors trading in a discrete time financial market under non-dominated model uncertainty. The investors preferences are described by strictly increasing concave random functions defined on the positive axis. We prove that under suitable conditions the m…
This paper considers the optimal portfolio selection problem in a dynamic multi-period stochastic framework with regime switching. The risk preferences are of exponential (CARA) type with an absolute coefficient of risk aversion which changes with the regime. The market model is incomplete and there are two risky asset…
The comparative statics of the optimal portfolios across individuals is carried out for a continuous-time complete market model, where the risky assets price process follows a joint geometric Brownian motion with time-dependent and deterministic coefficients. It turns out that the indirect utility functions inherit the…
Study examines how COVID-19 affected stock and crypto market efficiency.
A new LSV model uses relative quantities for better trading and risk management.
The use of absolute return volatility has many modelling benefits says John Cotter. An illustration is given for the market risk measure, minimum capital requirements.
This paper is intended as an investigation of the statistical properties of {\it absolute log-returns}, defined as the absolute value of the logarithmic price change, for the Nikkei 225 index in the 28-year period from January 4, 1975 to December 30, 2002. We divided the time series of the Nikkei 225 index into two per…
This paper develops a new methodology for studying continuous-time Nash equilibrium in a financial market with asymmetrically informed agents. This approach allows us to lift the restriction of risk neutrality imposed on market makers by the current literature. It turns out that, when the market makers are risk averse,…
This letter uses the Block Maxima Extreme Value approach to quantify catastrophic risk in international equity markets. Risk measures are generated from a set threshold of the distribution of returns that avoids the pitfall of using absolute returns for markets exhibiting diverging levels of risk. From an application t…
Study optimal portfolios for many players in a market model with random coefficients.
Study optimizes market making in Chinese stock market with stochastic control and scenario analysis.
We give a complete solution to the problem of minimizing the expected liquidity costs in presence of a general drift when the underlying market impact model has linear transient price impact with exponential resilience. It turns out that this problem is well-posed only if the drift is absolutely continuous. Optimal str…
The paper analyzes how knowing the market price of risk impacts optimal investment strategies.
Optimal liquidation strategy for a risk-averse investor in a one-sided limit order book driven by a Levy process.
Solves ambiguity in incomplete markets by minimizing price measure entropy.
Investors optimize equity and CDS trading to mitigate default risk.
Predict stock prices using financial news sentiment analysis.
The paper extends the market price of risk for electricity swap contracts, incorporating jump risk.
Introduces an asymmetric model for measuring market risk.
This essay quantifies convexities in incomplete markets using entropy, adjusting prices for risk and incompleteness.
Model quantifies market price of trading liquidity risk and market depth.
When investors have heterogeneous attitudes towards risk, it is reasonable to assume that each investor has a pricing kernel, and that these individual pricing kernels are aggregated to form a market pricing kernel. The various investors are then buyers or sellers depending on how their individual pricing kernels compa…
Predicting absolute magnitude of fluctuations of price, even if their sign remains unknown, is important for risk analysis and for option prices. In the present work, we display our predictions about absolute magnitude of daily fluctuations of the Dow Jones Industrials Average (DJIA), utilizing the original theory of c…
Study analyzes prediction market convergence and pricing mechanisms.
We consider the optimal investment problem when the traded asset may default, causing a jump in its price. For an investor with constant absolute risk aversion, we compute indifference prices for defaultable bonds, as well as a price for dynamic protection against default. For the latter problem, our work complements S…
Neural networks for stock price prediction often misrepresent model performance due to flawed error metrics.
Study financial contracts pricing in markets with nonproportional costs and constraints.
The NYSE and NASDAQ stock markets have very different structures and there is continuing controversy over whether differences in stock price behaviour are due to market structure or company characteristics. As the influence of market structure on stock prices may be obscured by exogenous factors such as demand and supp…
Model for hedging price and quantity risks in electricity markets.
This paper proposes a new framework for financial risk that considers predictability rather than volatility.
DFMM automates market making with adaptive pricing and risk management.
Machine learning predicts Bitcoin price with high accuracy.
Assuming that agents' preferences satisfy first-order stochastic dominance, we show how the Expected Utility paradigm can rationalize all optimal investment choices: the optimal investment strategy in any behavioral law-invariant (state-independent) setting corresponds to the optimum for an expected utility maximizer w…
This paper offers a framework for FX dealers to decide between internalizing and externalizing their market making to balance risk control and costs.
This review classifies electricity price models for risk management.
Recurring international financial crises have adverse socioeconomic effects and demand novel regulatory instruments or strategies for risk management and market stabilization. However, the complex web of market interactions often impedes rational decisions that would absolutely minimize the risk. Here we show that, for…
We perform a large-scale simulation of an Ising-based financial market model that includes 300 asset time series. The financial system simulated by the model shows a fat-tailed return distribution and volatility clustering and exhibits unstable periods indicated by the volatility index measured as the average of absolu…
The paper studies risk-based prices in financial markets under volatility uncertainty.
Derives a new formula for measuring risk aversion in markets.
The paper assesses how equity tail risk impacts US Treasury bond returns.
Deep hedging strategies for Green PPAs in electricity markets reduce risk.
This paper highlights the role of risk neutral investors in generating endogenous bubbles in derivatives markets. We find that a market for derivatives, which has all the features of a perfect market except completeness and has some risk neutral investors, can exhibit extreme price movements which represent a violation…
The study reveals traders' risk aversion and a new risk premium from market volumes.