arXiv research

Symbolic dynamics applied to share prices reveals complex, non-Markovian patterns.

New method uses execution flow to predict market direction.

Financial economic models often assume that investors know (or agree on) the fundamental value of the shares of the firm, easing the passage from the individual to the collective dimension of the financial system generated by the Share Exchange over time. Our model relaxes that heroic assumption of one unique "true val…

Algorithm learns shared demand structure across dynamic pricing experiments.

The study extracts market direction from transaction data.

We study the problem of determination of asset prices in an incomplete market proposing three different but related scenarios. One scenario uses a market game approach whereas the other two are based on risk sharing or regret minimizing considerations. Dynamical schemes modeling the convergence of the buyer's and of th…

Study examines pricing strategies in competitive supply chains with discrete prices.

Study asset pricing with transaction costs, showing unique equilibrium exists.

Study risk-sharing equilibria with general transaction costs, proving mean-reversion of returns.

Broker uses multi-task dynamic pricing to learn competitive prices in credit markets.

Share price returns on different time scales can be well modelled by a superstatistical dynamics. Here we provide an investigation which type of superstatistics is most suitable to properly describe share price dynamics on various time scales. It is shown that while chi-square superstatistics works well on a time scale…

SHHK Stock Connect increases A-H share price premium, more for less efficient markets.

A new framework forecasts stock trends by mining shared information from concepts.

This paper studies the equilibrium pricing of asset shares in the presence of dynamic private information. The market consists of a risk-neutral informed agent who observes the firm value, noise traders, and competitive market makers who set share prices using the total order flow as a noisy signal of the insider's inf…

This paper investigates the effects of the "uptick rule" (a short selling regulation formally known as rule 10a-1) by means of a simple stock market model, based on the ARED (adaptive rational equilibrium dynamics) modeling framework, where heterogeneous and adaptive beliefs on the future prices of a risky asset were f…

Dynamic pricing aims to match power supply and demand in an energy transition.

The distribution of share prices follows Zipf's law, similar to financial indicators.

Study shows changes in information sharing between Bitcoin markets during 2017 crash.

Share prices of financial companies from the S&P 500 list have been modeled by a linear function of consumer price indices in the USA. The Johansen and Engle-Granger tests for cointegration both demonstrated the presence of an equilibrium long-term relation between observed and predicted time series. Econometrically, t…

We consider the problem of dynamic buying and selling of shares from a collection of $N$ stocks with random price fluctuations. To limit investment risk, we place an upper bound on the total number of shares kept at any time. Assuming that prices evolve according to an ergodic process with a mild decaying memory proper…

Study proposes a new approach to market dynamics using flow and liquidity data.

Study complexity in financial market using Shannon entropy.

Short sales allow tax deferral by offsetting gains from ordinary sales.

Model liquidity premia using a risk-sharing economy with quadratic costs.

Study examines reasons for Nutek India's share price drop.

The aim of this study is to investigate quantitatively whether share prices deviated from company fundamentals in the stock market crash of 2008. For this purpose, we use a large database containing the balance sheets and share prices of 7,796 worldwide companies for the period 2004 through 2013. We develop a panel reg…

Utility based methods provide a very general theoretically consistent approach to pricing and hedging of securities in incomplete financial markets. Solving problems in the utility based framework typically involves dynamic programming, which in practise can be difficult to implement. This article presents a Monte Carl…

This paper analyzes stock market data to predict share prices using regression models.

A framework for fair derivative contract pricing and risk-sharing between parties with funding differences.

A new method is proposed to obtain the risk neutral probability of share prices without stochastic calculus and price modeling, via an embedding of the price return modeling problem in Le Cam's statistical experiments framework. Strategies-probabilities $P_{t_0,n}$ and $P_{T,n}$ are thus determined and used, respective…

Study compares market microstructure between two South African exchanges.

Model examines how margin trading affects stock market stability.

Investigates trading with integer constraints in discrete time.

Model resolves asset pricing puzzles with price-impact.

Solves superhedging for European options in a model with transient price impact and settlement requirements.

Price gap, defined as the logarithmic price difference between the first two occupied price levels on the same side of a limit order book (LOB), is a key determinant of market depth, which is one of the dimensions of liquidity. However, the properties of price gaps have not been thoroughly studied due to the less avail…

Study compares LSTM models with sentiment analysis for stock price prediction.

Hybrid model combines PCA and RNN for better aerospace stock price prediction.

Ride sharing has important implications in terms of environmental, social and individual goals by reducing carbon footprints, fostering social interactions and economizing commuter costs. The ride sharing systems that are commonly available lack adaptive and scalable techniques that can simultaneously learn from the la…

New method optimizes share buyback contracts without optimal control's limitations.

In this article, we consider the optimal execution problem associated to accelerated share repurchase contracts. When firms want to repurchase their own shares, they often enter such a contract with a bank. The bank buys the shares for the firm and is paid the average market price over the execution period, the length …

Develops a machine-learning framework for optimal share repurchase hedging.

Biondi et al. (2012) develop an analytical model to examine the emergent dynamic properties of share market price formation over time, capable to capture important stylized facts. These latter properties prove to be sensitive to regulatory regimes for fundamental information provision, as well as to market confidence c…

Paper analyzes dynamic deviation measures and risk-sharing solutions.

This paper develops a theoretical model for SPPC prices and improves accounting standards.

NFT royalties boost creator earnings by sharing risk, reducing info asymmetry, and enabling price discrimination.

A portfolio of different stocks and a risk-less security whose composition is dynamically maintained stable by trading shares at any time step leads to a growth of the capital with a nonrandom rate. This is the key for the theory of optimal-growth investment formulated by Kelly. In presence of transaction costs, the op…

The paper studies an oligopolistic equilibrium model of financial agents who aim to share their random endowments. The risk-sharing securities and their prices are endogenously determined as the outcome of a strategic game played among all the participating agents. In the complete-market setting, each agent's set of st…