arXiv research

Paper improves fractional trading for risk-averse investors by considering current drawdowns.

Proves existence and uniqueness of optimal trading strategy for multivariate returns.

New framework for pricing derivatives in Hermite markets with reduced arbitrage opportunities.

Study simulates liquidity in fractional ownership markets using ABM.

We consider fractional Black-Scholes market with proportional transaction costs. When transaction costs are present, one trades periodically i.e. we have the discrete trading with equidistance $n^{-1}$ between trading times. We derive a non trivial hedging error for a class of European options with convex payoff in the…

Lazy, perfectly informed investors trade infrequently due to costs.

New formulas forecast fractional Brownian motion for financial trading.

Large trades in a financial market are usually split into smaller parts and traded incrementally over extended periods of time. We address these large trades as hidden orders. In order to identify and characterize hidden orders we fit hidden Markov models to the time series of the sign of the tick by tick inventory var…

The study compares differencing methods for financial data and finds fractional differencing improves model performance.

A new model uses time-changed fractional Brownian motion to price financial options.

In this note we study the bilateral merchandise trade flows between 186 countries over the 1948-2005 period using data from the International Monetary Fund. We use Pajek to identify network structure and behavior across thresholds and over time. In particular, we focus on the evolution of trade "islands" in the a world…

Study evaluates discretized arbitrage strategies in fractional financial markets.

We study the arbitrage opportunities in the presence of transaction costs in a sequence of binary markets approximating the fractional Black-Scholes model. This approximating sequence was constructed by Sottinen and named fractional binary markets. Since, in the frictionless case, these markets admit arbitrage, we aim …

Investment strategy using fractional Kelly portfolios for better growth expectations.

Modeling fees impacts on arbitrage profits and LP losses in AMMs.

We solve exactly a simple model of trend following strategy, and obtain the analytical shape of the profit per trade distribution. This distribution is non trivial and has an option like, asymmetric structure. The degree of asymmetry depends continuously on the parameters of the strategy and on the volatility of the tr…

While absence of arbitrage in frictionless financial markets requires price processes to be semimartingales, non-semimartingales can be used to model prices in an arbitrage-free way, if proportional transaction costs are taken into account. In this paper, we show, for a class of price processes which are not necessaril…

Extended Kyle model with long memory trading volume, finds excessive price volatility.

We revisit the optimal investment and consumption problem with proportional transaction costs. We prove that both the value function and the slopes of the lines demarcating the no-trading region are analytic functions of cube root of the transaction cost parameter. Also, we can explicitly calculate the coefficients of …

We construct a general stochastic process and prove weak convergence results. It is scaled in space and through the parameters of its distribution. We show that our simplified scaling is equivalent to time scaling used frequently. The process is constructed as an integral with respect to a Poisson random measure which …

Paper proposes optimal portfolio strategy under rough stochastic volatility models.

The paper analyzes how automated market makers can retain trading fees.

We provide an exact solution to the ideal-gas-like models studied in econophysics to understand the microscopic origin of Pareto-law. In these class of models the key ingredient necessary for having a self-organized scale-free steady-state distribution is the trading or collision rule where agents or particles save a d…

Composite likelihood inference of fractional Gaussian processes with sequentially optimal subset selection

The paper analyzes optimal portfolio allocation under a fast mean-reverting fractional stochastic environment.

We consider the ideal-gas models of trading markets, where each agent is identified with a gas molecule and each trading as an elastic or money-conserving (two-body) collision. Unlike in the ideal gas, we introduce saving propensity $λ$ of agents, such that each agent saves a fraction $λ$ of its money and trades with t…

We consider the ideal-gas models of trading markets, where each agent is identified with a gas molecule and each trading as an elastic or money-conserving (two-body) collision. Unlike in the ideal gas, we introduce saving propensity $λ$ of agents, such that each agent saves a fraction $λ$ of its money and trades with t…

We complement the theory of tick-by-tick dynamics of financial markets based on a Continuous-Time Random Walk (CTRW) model recently proposed by Scalas et al., and we point out its consistency with the behaviour observed in the waiting-time distribution for BUND future prices traded at LIFFE, London.

TradeMech nets trades without changing counterparty relationships.

Trading invariance hypothesis is revised with high correlation to trading costs.

Model shows worldwide trade crises can be localized or global, depending on trade balance.

I explain the root of persistent failure of efforts to remove tax-induced distortions of economic incentives. It lies in FUNDAMENTAL IMPOSSIBILITY of objectively evaluating tax base. Distortions can be entirely avoided in the sector of publicly traded corporations. Evaluation can be bypassed by taxing it in shares (to …

NeuroMemFPP uses LSTM to estimate FPP parameters with high accuracy.

Agent-based model simulates speculative electronic market with price bubbles.

Using Trades and Quotes data from the Paris stock market, we show that the random walk nature of traded prices results from a very delicate interplay between two opposite tendencies: long-range correlated market orders that lead to super-diffusion (or persistence), and mean reverting limit orders that lead to sub-diffu…

Privacy subsidy found in market trading with noisy direction signals.

We mathematically analyze a simple market model where trading at each point in time involves only two agents with the sum of their money being conserved and with neither parties resulting with negative money after the interaction process. The exchange involves random re-distribution among the two players of a fixed fra…

We investigate the problem of wealth distribution from the viewpoint of asset exchange. Robust nature of Pareto's law across economies, ideologies and nations suggests that this could be an outcome of trading strategies. However, the simple asset exchange models fail to reproduce this feature. A yardsale(YS) model in w…

Develops a new framework for drawdown risk beyond Gaussian assumptions.

Market impact is reduced when orders are filled with concentrated counterparts.

This paper detects fraudulent trading in the NFT market.

We present two statistical causes for the distortion of correlations on high-frequency financial data. We demonstrate that the asynchrony of trades as well as the decimalization of stock prices has a large impact on the decline of the correlation coefficients towards smaller return intervals (Epps effect). These distor…

Covid lockdown increased interest in Italian stock market, leading to new investors.

We consider the problem of estimating the support of a vector $β^* \in \mathbb{R}^{p}$ based on observations contaminated by noise. A significant body of work has studied behavior of $\ell_1$-relaxations when applied to measurement matrices drawn from standard dense ensembles (e.g., Gaussian, Bernoulli). In this paper,…

We have numerically simulated the ideal-gas models of trading markets, where each agent is identified with a gas molecule and each trading as an elastic or money-conserving two-body collision. Unlike in the ideal gas, we introduce (quenched) saving propensity of the agents, distributed widely between the agents ($0 \le…

In standard clustering problems, data points are represented by vectors, and by stacking them together, one forms a data matrix with row or column cluster structure. In this paper, we consider a class of binary matrices, arising in many applications, which exhibit both row and column cluster structure, and our goal is …

We propose a discrete time algorithm for the valuation of employee stock options based on exponential indifference prices and taking into account both the possibility of partial exercise of a fraction of the options and the use of a correlated traded asset to hedge part of their risk. We determine the optimal exercise …

Sampling a fraction of pairs can match full evaluation in machine learning losses.