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.
The paper explains the fair basis in bond-CDS trading during financial crises.
We study the problem of dynamically trading a futures contract and its underlying asset under a stochastic basis model. The basis evolution is modeled by a stopped scaled Brownian bridge to account for non-convergence of the basis at maturity. The optimal trading strategies are determined from a utility maximization pr…
In the third part of this series we introduce consistent relative value measures for CDS-Bond basis trades using the bond-implied CDS term structure derived from fitted survival rate curves. We explain why this measure is better than the traditionally used Z-spread or Libor OAS and offer simplified hedging and trading …
Triangle fees adjust fees based on trade size and price movement, improving price accuracy and revenue.
The paper tackles dynamic collateral control for spot-perpetual basis trading in decentralized finance.
The paper analyzes gold, oil, and bitcoin futures volatility and basis.
Algorithm of multicurrency trading at the market of Forex is realized on the basis of nonlinear stochastic wavelets. The distinctive feature of the algorithm is the possibility of weakly- and strongly connected horizontal self-assemblies, as well as use of nested structures. On-line trading with eight currency couples …
In this paper, we propose stock trading based on the average tax basis. Recall that when selling stocks, capital gain should be taxed while capital loss can earn certain tax rebate. We learn the optimal trading strategies with and without considering taxes by reinforcement learning. The result shows that tax ignorance …
Study on hedging and valuation of basis risk in incomplete markets with partial information.
Study automates feature selection and clustering for HFT stock price forecasting.
Pairs trading strategy improved using Ornstein-Uhlenbeck process.
The VIX is used to enhance quantitative trading strategies.
Using the United Nations COMTRADE database we apply the reduced Google matrix (REGOMAX) algorithm to analyze the multiproduct world trade in years 2004-2016. Our approach allows to determine the trade balance sensitivity of a group of countries to a specific product price increase from a specific exporting country taki…
Corrects gaps in a method for optimizing high-frequency trading strategies.
Calibrating a trading rule using a historical simulation (also called backtest) contributes to backtest overfitting, which in turn leads to underperformance. In this paper we propose a procedure for determining the optimal trading rule (OTR) without running alternative model configurations through a backtest engine. We…
Ecological systems have a high level of complexity combined with stability and rich biodiversity. Recently, the analysis of their properties and evolution has been pushed forward on a basis of concept of mutualistic networks that provides a detailed understanding of their features being linked to a high nestedness of t…
Reinforcement learning is explored as a candidate machine learning technique to enhance existing analytical solutions for optimal trade execution with elements from the market microstructure. Given a volume-to-trade, fixed time horizon and discrete trading periods, the aim is to adapt a given volume trajectory such tha…
Decision trees improve intraday trading strategies for NIFTY50 stocks.
Study uses Google matrix analysis to show how COVID-19 changed international trade flows.
The study analyzes trading imbalances from SEC Form 13F-HR filings to identify profitable trading opportunities.
This study evaluates price improvements in order flow auctions on Ethereum.
Agent learns to trade currency pairs with improved risk management.
Banks must manage their trading books, not just value them. Pricing includes valuation adjustments collectively known as XVA (at least credit, funding, capital and tax), so management must also include XVA. In trading book management we focus on pricing, hedging, and allocation of prices or hedging costs to desks on an…
Derivative traders are usually required to scan through hundreds, even thousands of possible trades on a daily basis. Up to now, not a single solution is available to aid in their job. Hence, this work aims to develop a trading recommendation system, and apply this system to the so-called Mid-Curve Calendar Spread (MCC…
Reinforcement learning crypto agent achieves high returns on Bitcoin derivatives.
Model simulates Perpetual Futures market with agent behavior.
The paper analyzes algorithmic trading in cryptocurrency exchanges, finding a profitable strategy involving indirect conversions.
This paper considers method of creation of an advisor and indicator based on the spectral stochastic analysis model, both with linear and non-linear approximation. The problem of entrance to one or another trade position is solved on the basis of combined analysis of dynamics of quotations of all currency pairs, what a…
Two new algorithms reduce online kernel regression's computational cost while maintaining optimal regret bounds.
Machine learning predicts Bitcoin returns but trading performance drops with costs.
We carry out a large-scale empirical data analysis to examine the efficiency of the so-called pairs trading. On the basis of relevant three thresholds, namely, starting, profit-taking, and stop-loss for the `first-passage process' of the spread (gap) between two highly-correlated stocks, we construct an effective strat…
Develops a new trading strategy for statistical arbitrage with path-dependent signals.
TGARCH model shows CSI-300 futures reduce spot price volatility.
Quantum theory is used to model secondary financial markets. Contrary to stochastic descriptions, the formalism emphasizes the importance of trading in determining the value of a security. All possible realizations of investors holding securities and cash is taken as the basis of the Hilbert space of market states. The…
Brazil proposes a new BRICS trade currency to dominate international trade.
This review examines various LOB simulation models in algorithmic trading.
MFIN networks improve crypto trading with multiple features.
The study examines how market trade randomness influences price and return volatility.
Global optimization problems whose objective function is expensive to evaluate can be solved effectively by recursively fitting a surrogate function to function samples and minimizing an acquisition function to generate new samples. The acquisition step trades off between seeking for a new optimization vector where the…
Margin trading and short selling boost green tech innovation in China.
American put options are among the most frequently traded single stock options, and their calibration is computationally challenging since no closed-form expression is available. Due to the higher flexibility in comparison to European options, the mathematical model involves additional constraints, and a variational in…
Globalization processes interweave economic structures at a worldwide scale, trade playing a central role as one of the elemental channels of interaction among countries. Despite the significance of such phenomena, measuring economic globalization still remains an open problem. More quantitative treatments could improv…
By monitoring the time evolution of the most liquid Futures contracts traded globally as acquired using the Bloomberg API from 03 January 2000 until 15 December 2014 we were able to forecast the S&P 500 index beating the Buy and Hold trading strategy. Our approach is based on convolution computations of 42 of the most …
The marvel of markets lies in the fact that dispersed information is instantaneously processed and used to adjust the price of goods, services and assets. Financial markets are particularly efficient when it comes to processing information; such information is typically embedded in textual news that is then interpreted…
New ARIMA framework improves forecast accuracy for economic and financial time series.
We propose a method for extending a given asset pricing formula to account for two additional sources of risk: the risk associated with future changes in market--calibrated parameters and the remaining risk associated with idiosyncratic variations in the individual assets described by the formula. The paper makes simpl…
CNN predicts stock fluctuations using company news headlines.
Paper classifies short straddles on S&P500 daily.