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275380106 · May 202619922001200920172026
48 results for speculative trading

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

problem Understanding speculative behavior and price bubbles in electronic markets.
method Agent-based model with two types of traders: mean reverting and speculative.
result Speculative traders lead to increased volatility and price deviations from fundamental value.

Study speculative trading using RL with exploratory framework.

problem Sequential optimal stopping problem over entry and exit times with general utility function and price process.
method Formulated as a sequential optimal stopping problem, solved using Cox processes driven by bounded, non-randomized intensity controls. Characterized randomized control via probability measure over jump intensities and regularized objective function by Shannon's entropy. Established error estimates and convergence of RL objective to value function.
result Closed-form solutions for optimal policy and value function are derived.

A speculative agent with Prospect Theory preference chooses the optimal time to purchase and then to sell an indivisible risky asset to maximize the expected utility of the round-trip profit net of transaction costs. The optimization problem is formulated as a sequential optimal stopping problem and we provide a comple…

2019-11-22abs ↗pdf ↗

We present and study a Minority Game based model of a financial market where adaptive agents -- the speculators -- interact with deterministic agents -- called producers. Speculators trade only if they detect predictable patterns which grant them a positive gain. Indeed the average number of active speculators grows wi…

2001-01-22abs ↗pdf ↗

Modeling price impacts and trading signals for optimal execution and speculation.

problem Optimal execution and speculation in markets with trade signals.
method Price impact model driven by order flow, stochastic price impact, Meyer-σσ-fields signal process, Marcus-type SDEs.
result Derivation and numerical solution of HJB equation for optimal execution, enhanced speculative strategies.

What return should you expect when you take on a given amount of risk? How should that return depend upon other people's behavior? What principles can you use to answer these questions? In this paper, we approach these topics by exploring the consequences of two simple hypotheses about risk. The first is a common-sense…

2002-01-18abs ↗pdf ↗

Study replicates reference-dependent preferences impact on risk-return trade-off in Chinese stock market.

problem Impact of reference-dependent preferences on risk-return trade-off in Chinese stock market.
method Utilized CGO proxy, econometric techniques (Dependent Double Sorting, Fama-MacBeth regressions), and data from 1995-2024.
result Reference-dependent preferences have a weaker or absent positive risk-return relationship in the Chinese market.

The paper revisits classical competition theory to explain speculative asset price dynamics.

problem Understanding the dynamics of speculative asset prices and their volatility.
method Specialized classical model of competition with reservation prices, incorporating speculation.
result The model explains excess, fat-tailed, and clustered volatility in speculative asset prices.

We introduce a system of kinetic equations describing an exchange market consisting of two populations of agents (dealers and speculators) expressing the same preferences for two goods, but applying different strategies in their exchanges. We describe the trading of the goods by means of some fundamental rules in price…

2017-09-01abs ↗pdf ↗

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

problem NFTs' royalties are criticized for being neutralized by speculators.
method Analyzes NFTs' royalties in various market conditions and their effects on creators.
result Royalties enable creators to capitalize on speculators' presence through risk sharing, info reduction, and price discrimination.

During a speculative episode the price of an item jumps from an initial level p_1 to a peak level p_2 before more or less returning to level p_1. The ratio p_2/p_1 is referred to as the amplitude A of the peak. This paper shows that for a given market the peak amplitude is a linear function of the logarithm of the pric…

1999-10-23abs ↗pdf ↗

We show that the introduction of Tobin taxes in agent-based models of currency markets can lead to a reduction of speculative trading and reduce the magnitude of exchange rate fluctuations at intermediate tax rates. In this regime revenues for the market maker obtained from speculators are maximal. We here focus on Min…

2006-03-06abs ↗pdf ↗

Research identifies four motivational groups for crypto-metaverse landowners.

problem Understanding motivations of retail investors in the crypto-metaverse.
method Detailed financial behavior survey and principal components analysis.
result Four distinct motivational groups identified: Aesthetics, Social, Speculation, Innovation.

A prototype model of stock market is introduced and studied numerically. In this self-organized system, we consider only the interaction among traders without external influences. Agents trade according to their own strategy, to accumulate his assets by speculating on the price's fluctuations which are produced by them…

1997-09-10abs ↗pdf ↗

Defines speculative bubbles in discrete-time models based on discounted stock price losing mass.

problem Characterizing speculative bubbles in discrete-time models.
method Introduces a new definition based on discounted stock price behavior and provides probabilistic characterizations.
result Speculative bubbles in discrete time are linked to solutions of a linear Volterra integral equation.

PreBit predicts Bitcoin price movements using social media and financial data.

problem Predicting extreme price movements of Bitcoin due to its volatility and speculative trading.
method Hybrid model combining FinBERT embeddings of Twitter content with candlestick data and technical indicators.
result The hybrid model can predict significant market movements with a profitable trading strategy.

A model of open economics composed of producers and speculators is investigated by numerical simulations. The capital flows from the environment to the producers and from them to the speculators. The price fluctuations are suppressed by the speculators. When the aggressivity of the speculators grows, there is a transit…

1999-06-16abs ↗pdf ↗

We study analytically and numerically Minority Games in which agents may invest in different assets (or markets), considering both the canonical and the grand-canonical versions. We find that the likelihood of agents trading in a given asset depends on the relative amount of information available in that market. More s…

2006-03-19abs ↗pdf ↗

This study attempts to analyze patterns in cryptocurrency markets using a special type of deep neural networks, namely a convolutional autoencoder. The method extracts the dominant features of market behavior and classifies the 40 studied cryptocurrencies into several classes for twelve 6-month periods starting from 15…

2019-10-27abs ↗pdf ↗

This study optimizes trading and arbitrage in decentralized finance's CPMs, revealing convexity costs and developing efficient strategies.

problem Optimizing trading and arbitrage in decentralized finance's constant product markets (CPMs).
method Developed models for CPMs in competing centralised exchanges, CPMs, and both venues. Derived computationally efficient strategies.
result Accurately estimated convexity costs in CPMs, which are linear in trade size and nonlinear in liquidity depth and exchange rate.

New model explains price dynamics of Bitcoin with psychological factors.

problem Understanding price variations in cryptocurrency markets with psychological factors.
method Extended agent-based model with heterogeneous psychological parameters.
result Model shows diverse dynamics based on psychological correlation.

Strategic brokers exploit private information in broker-mediated markets, affecting informed traders' performance.

problem Strategic interactions and information leakage in broker-mediated markets.
method Study of strategic trading behavior and information leakage in a broker-mediated market.
result Brokers hold a strategic advantage over informed traders due to information leakage in trading flows.

A general framework is suggested to describe human decision making in a certain class of experiments performed in a trading laboratory. We are in particular interested in discerning between two different moods, or states of the investors, corresponding to investors using fundamental investment strategies, technical ana…

2013-06-09abs ↗pdf ↗

This paper analyzes speculative decoding, a method to speed up large language model inferences.

problem Theoretical understanding of speculative decoding is lacking.
method Conceptualizes speculative decoding as a markov chain problem and studies its key properties.
result Reveals fundamental connections between LLM components and their impact on decoding efficiency.

Brokers and an informed trader compete for liquidity, affecting trading costs and inventory risk.

problem How brokers and an informed trader manage liquidity and trading costs.
method Sequential Stackelberg game, solving for trading strategies, numerical solutions.
result Equilibrium strategies and liquidity prices determined, not Pareto efficient.

In this paper, we consider a simple kinetic model of economy involving both exchanges between agents and speculative trading. We show that the kinetic model admits non trivial quasi-stationary states with power law tails of Pareto type. In order to do this we consider a suitable asymptotic limit of the model yielding a…

2004-12-21abs ↗pdf ↗

This paper studies the problem of trading futures with transaction costs when the underlying spot price is mean-reverting. Specifically, we model the spot dynamics by the Ornstein-Uhlenbeck (OU), Cox-Ingersoll-Ross (CIR), or exponential Ornstein-Uhlenbeck (XOU) model. The futures term structure is derived and its conne…

2016-01-16abs ↗pdf ↗

Adaptive speculative decoding framework for LLMs using bandit algorithms.

problem Adaptive speculative decoding for LLMs to balance speed and quality.
method Formulated as a Multi-Armed Bandit problem, proposed UCBSpec and EXP3Spec algorithms.
result UCBSpec algorithm achieves optimal regret performance up to universal constants.

Study optimizes Bitcoin futures hedging to reduce liquidation risk.

problem Optimizing hedging strategies to minimize liquidation risk in Bitcoin futures.
method Derived a semi-closed form optimal hedging strategy considering spot and futures extreme returns, loss aversion, leverage, and collateral management.
result Optimal strategy reduces both hedged portfolio variance and liquidation probability.

We propose a continuous-time model of trading with heterogeneous beliefs. Risk-neutral agents face quadratic costs-of-carry on positions and thus their marginal valuations decrease with the size of their position, as it would be the case for risk-averse agents. In the equilibrium models of heterogeneous beliefs that fo…

2017-05-16abs ↗pdf ↗

The continuous-time version of Kyle's (1985) model is studied, in which market makers are not fiduciaries. They have some market power which they utilize to set the price to their advantage, resulting in positive expected profits. This has several implications for the equilibrium, the most important being that by setti…

2019-08-23abs ↗pdf ↗