arXiv research

Hong Kong's housing prices predicted to slump for a decade.

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…

The paper interprets financial markets as crowds during booms and busts.

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

Study confirms financial bubbles' common patterns in isolated markets.

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…

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…

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

Accelerating Speculative Diffusions via Block Verification

Extended speculation game improves Hurst exponent of financial time series.

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

Proving the existence of speculative financial bubbles even a posteriori has proven exceedingly difficult so anticipating a speculative bubble ex ante would at first seem an impossible task. Still as illustrated by the recent turmoil in financial markets initiated by the so called subprime crisis there is clearly an ur…

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

Speculative bubbles have been occurring periodically in local or global real estate markets and are considered a potential cause of economic crises. In this context, the detection of explosive behaviors in the financial market and the implementation of early warning diagnosis tests are of critical importance. The recen…

We document and analyze the empirical facts concerning one of the clearest evidence of speculation in financial trading as observed in the postage collection stamp market. We unravel some of the mechanisms of speculative behavior which emphasize the role of fancy and collective behavior. In our conclusion, we propose a…

Adaptive speculative decoding framework for LLMs using bandit algorithms.

Improved diffusion model generation speed with speculative sampling.

Accelerates TPP sampling with speculative decoding for faster sequence generation.

Cactus improves auto-regressive decoding speed without sacrificing quality.

The object of this contribution is to present the ideas behind the thinking of the French economist Pierre-Joseph Proudhon (1809-1865) in relation to the causes and effects of Stock market speculation. It is based upon the works of this author but particularly on his "Manuel du spéculateur à la Bourse" (Stock Market Sp…

Recent increases in basic food prices are severely impacting vulnerable populations worldwide. Proposed causes such as shortages of grain due to adverse weather, increasing meat consumption in China and India, conversion of corn to ethanol in the US, and investor speculation on commodity markets lead to widely differin…

A novel CAB-XDE framework predicts speculative stock prices with high accuracy.

Kinetic models predict speculators' strategy can affect market prices.

GSI improves efficiency of large language model inference.

New RL algorithm for partially observable episodic POMDPs with polynomial sample complexity.

Detecting early signs of mood episodes in bipolar disorder patients.

EMDQN uses episodic memory to improve RL efficiency.

Study preference-based reinforcement learning in episodic kernel MDPs.

Algorithm tackles constrained reinforcement learning with concave-convex and knapsack constraints.

Algorithm improves multi-armed bandit performance by transferring reward samples.

BerlinUCB learns from episodic rewards in nonstationary contexts.

The Nasdaq Composite fell another $\approx 10$ on Friday the 14'th of April 2000 signaling the end of a remarkable speculative high-tech bubble starting in spring 1997. The closing of the Nasdaq Composite at 3321 corresponds to a total loss of over 35% since its all-time high of 5133 on the 10'th of March 2000. Simil…

Agent optimizes risky asset trading times based on Prospect Theory.

New game model improves financial stylized facts reproduction.

Speculation leads to power law price changes.

We introduce the speculate-correct method to derive error bounds for local classifiers. Using it, we show that k nearest neighbor classifiers, in spite of their famously fractured decision boundaries, have exponential error bounds with O(sqrt((k + ln n) / n)) error bound range for n in-sample examples.

Study tests if deep hedging differs from delta hedging in a GARCH market model.

EBU improves deep RL with episodic backward updates, achieving human-level performance with less data.

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

We present an interacting-agent model of speculative activity explaining bubbles and crashes in stock markets. We describe stock markets through an infinite-range Ising model to formulate the tendency of traders getting influenced by the investment attitude of other traders. Bubbles and crashes are understood and descr…

Study speculative trading using RL with exploratory framework.

Study good-deal hedging under uncertain market prices, reducing speculative components.

Improved regret bound for online learning in unknown MDPs.

Algorithm reduces episode count for CMDPs with constraints.

Algorithm improves online learning in adversarial bandits.

New reinforcement learning method for multi-armed bandits with special stop actions.

New algorithm learns reward signals from episodic returns for better reinforcement learning.

Recent droughts in the midwestern United States threaten to cause global catastrophe driven by a speculator amplified food price bubble. Here we show the effect of speculators on food prices using a validated quantitative model that accurately describes historical food prices. During the last six years, high and fluctu…