Paper explores robust regression methods and their bias-variance trade-off.
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The theory of optimal trading under proportional transaction costs has been considered from a variety of perspectives. In this paper, we show that all the results can be interpreted using a universal law, illustrating the results in trading algorithm design.
The paper explains the concave shape of yield curves from trading perspectives.
Flexible algorithm of multicurrency trade on Forex market has been built on the grounds of non-linear stochastic wavelets (NSW) model. Probability of the loss-free trade has been evaluated. Results of the algorithm's real-time testing and issues of the algorithm's development are discussed.
We outline what we believe are the prerequisites and building-blocks for successfully devising trading models and other financial applications based on a complex systems perspective.
Optimal trading strategy between CEXs and DEXs with priority fees and stochastic delays.
The relationship between international trade and foreign direct investment (FDI) is one of the main features of globalization. In this paper we investigate the effects of FDI on trade from a network perspective, since FDI takes not only direct but also indirect channels from origin to destination countries because of f…
Study adversarial attacks on automated trading systems.
In this paper, we study the dynamics of absolute return, trading volume and bid-ask spread after the trading halts using high-frequency data from the Shanghai Stock Exchange. We deal with all three types of trading halts, namely intraday halts, one-day halts and inter-day halts, of 203 stocks in Shanghai Stock Exchange…
Model shows how price impact and transaction costs affect trading behavior and profits.
Study shows market quality improves with larger orders, not smaller tick sizes or higher trading frequencies.
This paper examines how the U.S.--China trade war affects stock markets, finding evidence of financial contagion and changes in risk channels.
The paper characterizes SLOPE's trade-off between FDP and TPP, showing its power limit and superiority over Lasso.
Addressing the ongoing examination of high-frequency trading practices in financial markets, we report the results of an extensive empirical study estimating the maximum possible profitability of the most aggressive such practices, and arrive at figures that are surprisingly modest. By "aggressive" we mean any trading …
Study trade-offs between statistical and computational efficiency in variational inference.
New formulas forecast fractional Brownian motion for financial trading.
We consider trading against a hedge fund or large trader that must liquidate a large position in a risky asset if the market price of the asset crosses a certain threshold. Liquidation occurs in a disorderly manner and negatively impacts the market price of the asset. We consider the perspective of small investors whos…
KFHE uses Kalman filters to improve ensemble classification accuracy.
We study trade-based manipulation of stock prices from the perspective of complex trading networks constructed by using detailed information of trades. A stock trading network consists of nodes and directed links, where every trader is a node and a link is formed from one trader to the other if the former sells shares …
Study compares deep learning stock trading strategies in adverse market conditions.
Paper unifies off-policy learning algorithms and introduces C-trace for better trade-offs.
We study dynamics of a simulated world with stock and money, driven by the externally given processes which we refer to as sentiments. The considered sentiments influence the buy/sell stock trading attitude, the perceived price uncertainty, and the trading intensity of all or a part of the market participants. We study…
LLMs improve stock price forecasting from financial news and reports.
We study the ever more integrated and ever more unbalanced trade relationships between European countries. To better capture the complexity of economic networks, we propose two global measures that assess the trade integration and the trade imbalances of the European countries. These measures are the network (or indire…
Novel OTT method for cryptocurrency trading offers high annualized profit.
Proposes FACT, a diagnostic for understanding group fairness trade-offs.
Develops a machine learning system to recommend swaption trades.
Achieving international food security requires improved understanding of how international trade networks connect countries around the world through the import-export flows of food commodities. The properties of food trade networks are still poorly documented, especially from a multi-network perspective. In particular,…
Algorithm learns optimal trading parameters from technical strategies.
Paper proposes using CNN for stock trading with data normalization.
Paper proposes a novel policy distillation method for better order execution in noisy markets.
We study the issue of PAC-Bayesian domain adaptation: We want to learn, from a source domain, a majority vote model dedicated to a target one. Our theoretical contribution brings a new perspective by deriving an upper-bound on the target risk where the distributions' divergence---expressed as a ratio---controls the tra…
Model explains periodic trading in financial markets through game theory.
Study evaluates LLMs for predicting Chinese stock movements using financial news sentiments.
Graph-based multi-view model predicts trading volume movement from various sources.
The Chain-of-Decision approach improves forecasting of financial professionals' trading decisions.
This paper detects fraudulent trading in the NFT market.
This paper develops a pricing model for data assets from the buyer's perspective.
We consider extensive data on Spanish international trades and population composition and, through statistical-mechanics and graph-theory driven analysis, we unveil that the social network made of native and foreign-born individuals plays a role in the evolution and in the diversification of trades. Indeed, migrants na…
Based on the approach of flow distances, the international trade flow system is studied from the perspective of multi-layer flow network. A model of multi-layer flow network is proposed for modelling and analyzing multiple types of flows in flow systems. Then, flow distances are introduced, and symmetric minimum flow d…
Study analyzes EU ETS carbon market dynamics, revealing inefficiencies and anomalies.
New research shows no trade-off between fairness and accuracy in machine learning.
Market manipulation is a strategy used by traders to alter the price of financial securities. One type of manipulation is based on the process of buying or selling assets by using several trading strategies, among them spoofing is a popular strategy and is considered illegal by market regulators. Some promising tools h…
We characterize the set of market models when there are a finite number of traded Vanilla and Barrier options with maturity written on the asset . From a probabilistic perspective, our result describes the set of joint distributions for when a finite number of marginal law constraint…
The European Union and Eurozone present an inquisitive case of strongly interconnected network with high degree of dependence among nodes. This research focused on investment network of European Union and its major trading partners for specific time period 2001 to 2014. The changing investment patterns within Eurozone …
Study on cryptocurrency trading patterns using multifractal analysis.
Optimal solar energy production and trading strategies in SREC markets identified.
Deep learning is a form of machine learning for nonlinear high dimensional pattern matching and prediction. By taking a Bayesian probabilistic perspective, we provide a number of insights into more efficient algorithms for optimisation and hyper-parameter tuning. Traditional high-dimensional data reduction techniques, …