The paper finds that bear markets cause recessions and bull markets cause expansions, with bull markets having a stronger causal effect.
problem Understanding the asymmetric causal relationships between market conditions and economic cycles.
method Asymmetric causality tests using partial sums of positive and negative market components, with bootstrap simulations and leverage adjustments.
result Bear markets cause recessions and bull markets cause expansions, with bull markets having a stronger causal effect.
Paper models market dynamics using bull and bear forces.
problem Complex market dynamics influenced by biases and narratives.
method Bias to Behavior from Bull-Bear Dynamics (B4) model.
result Model predicts market trends with superior performance and interpretable insights.
Pairs trading strategy fails to outperform market benchmarks, but performs well during bear markets.
problem The validity of pairs trading as a profitable strategy in modern markets.
method Used common distance and cointegration methods on US equities from 1990 to 2020, including the Covid-19 crisis.
result The pairs trading strategy does not consistently outperform market benchmarks, but performs well during bear markets.
Paper introduces Market-adaptive Ratio for better portfolio management.
problem Traditional risk-adjusted ratios fail to account for bull and bear markets.
method Integrates ρ parameter and uses reinforcement learning to adjust portfolio allocations dynamically. result Market-adaptive Ratio outperforms traditional ratios in bull and bear markets.
Paper predicts cryptocurrency bull and bear phases using Bitcoin's moving averages.
problem Determining cryptocurrency bull and bear phases based on Bitcoin performance.
method Employing predictive algorithms to forecast Bitcoin's 50 Day and 200 Day Moving Averages.
result Predicted data from Bitcoin's moving averages helps identify potential bull and bear phases.
Survival strategy for crypto firms in bear markets using BTC-to-sats payments rail.
problem Downside risk in crypto reserves during bear markets.
method Conservative treasury policy, operating line monetizing holdings, BTC-to-sats payments rail.
result Sustained mNAV premium through cycles with disclosed KPIs.
Trend following in cryptocurrencies yields high returns, similar to commodities.
problem Investing in cryptocurrencies using trend following strategies.
method A decade of data analysis on cryptocurrency markets and trend following strategies.
result Cryptocurrencies offer strong returns and diversification against traditional equities.
Method for factor analysis in short panels without assuming sphericity or Gaussianity.
problem Factor analysis in short panels without assuming sphericity or Gaussianity.
method Pseudo maximum likelihood method and asymptotically uniformly most powerful invariant test.
result Systematic risk explains a large part of cross-sectional total variance in bear markets but is not spanned by observed factors.
Study compares cryptocurrency and stock markets using statistical equilibrium models.
problem Comparing the stochastic structure of cryptocurrency and stock markets.
method Applied QRSE model to analyze daily returns of cryptocurrencies and S&P 500 companies.
result Revealed differences in informational efficiency between cryptocurrency and stock markets.
The dynamics of a stock market with heterogeneous agents is discussed in the framework of a recently proposed spin model for the emergence of bubbles and crashes. We relate the log returns of stock prices to magnetization in the model and find that it is closely related to trading volume as observed in real markets. Th…
We introduce and treat rigorously a new multi-agent model of the continuous double auction or in other words the order book (OB). It is designed to explain collective behaviour of the market when new information affecting the market arrives. The novel feature of the model is two additional slow changing parameters, the…
Macroscopic price evolution models are commonly used for investment strategies. There are first promising achievements in defining microscopic agent based models for the same purpose. Microscopic models allow a deeper understanding of mechanisms in the market than the purely phenomenological macroscopic models, and thu…
A phenomenon of the financial log-periodicity is discussed and the characteristics that amplify its predictive potential are elaborated. The principal one is self-similarity that obeys across all the time scales. Furthermore the same preferred scaling factor appears to provide the most consistent description of the mar…
Cryptocurrencies are increasingly correlated with traditional financial markets.
problem Determining the independence of cryptocurrencies from traditional financial markets.
method High-frequency detrended cross-correlation analysis over various time scales and market periods.
result Cryptocurrencies have become more aligned with traditional financial markets, especially during bear phases.
Paper predicts bearing degradation stages for pharmaceutical industry maintenance.
problem Predicting when to maintain specific parts of production machines.
method AutoEncoder-based k-means segmentation of high-frequency vibration data.
result Framework generates reliable predictions for bearing degradation stages.
We provide direct evidence of market manipulation at the beginning of the financial crisis in November 2007. The type of manipulation, a "bear raid," would have been prevented by a regulation that was repealed by the Securities and Exchange Commission in July 2007. The regulation, the uptick rule, was designed to preve…
Model predicts risk-adjusted returns across various financial markets.
problem Stationary models fail in predicting risk-adjusted returns due to market regime changes.
method Asset-independent regime-switching model using hidden Markov models.
result Accurately detects bull, bear, and high volatility periods for improved risk-adjusted returns.
Paper calculates greeks for DeFi LPs and introduces Impermanent Gain.
problem Liquidity Providers in DeFi are exposed to Impermanent Loss.
method Tailored Black & Scholes formulas for DeFi markets.
result Introduced Impermanent Gain for risk management.
In industrial applications, nearly half the failures of motors are caused by the degradation of rolling element bearings (REBs). Therefore, accurately estimating the remaining useful life (RUL) for REBs are of crucial importance to ensure the reliability and safety of mechanical systems. To tackle this challenge, model…
Study shows marketable order routing to wholesalers benefits all traders, leading to lower market depth and price volatility.
problem Determining the preference of retail traders for marketable order routing.
method Two models: one for market makers competing for retail order flow (Bertrand model) and another for price-taking competitive liquidity providers (open exchange model).
result Routing marketable orders to wholesalers is preferred by all traders, leading to mean reverting inventories and lower market depth.
We perform an analysis of fractal properties of the positive and the negative changes of the German DAX30 index separately using Multifractal Detrended Fluctuation Analysis (MFDFA). By calculating the singularity spectra f(α) we show that returns of both signs reveal multiscaling. Curiously, these spectra display a s…
Study shows investor sentiment boosts intraday trading in Chinese markets.
problem Impact of investor sentiment on intraday overtrading in Chinese A-share markets.
method High-frequency sentiment indices from social media analyzed for intraday overtrading in CSI 300 and CSI 500 constituents.
result Investor sentiment significantly increases intraday overtrading, especially among institutional investors.
During a stock market peak the price of a given stock (i) jumps from an initial level p1(i) to a peak level p2(i) before falling back to a bottom level p3(i). The ratios A(i)=p2(i)/p1(i) and B(i)=p3(i)/p1(i) are referred to as the peak- and bottom-amplitude respectively. The paper show…
Paper compares RL models for finance, finding Reward Clipping best.
problem Optimizing asset allocation in finance.
method Actor-only, actor-critic, and PPO models compared; Reward Clipping introduced.
result Reward Clipping model outperforms others in bull and bear markets.
Few-shot learning improves bearing fault diagnosis with limited data.
problem Challenges in collecting sufficient fault data for robust classifier training.
method Model-Agnostic Meta-Learning (MAML) for few-shot learning.
result Framework achieves up to 25% higher accuracy than Siamese network.
Develops portfolio theory without probabilistic analysis, focusing on pathwise decomposition.
problem Ensuring market viability without probabilistic assumptions.
method Uses pathwise decomposition and trend extractors to replace semimartingale decomposition.
result Growth-numéraire and viability equivalences are similar but not identical in pathwise setting.
Using a rolling windows analysis of filtered and aligned stock index returns from 40 countries during the period 2006-2014, we construct Granger causality networks and investigate the ensuing structure of the relationships by studying network properties and fitting spatial probit models. We provide evidence that stock …
Investors in stock market are usually greedy during bull markets and scared during bear markets. The greed or fear spreads across investors quickly. This is known as the herding effect, and often leads to a fast movement of stock prices. During such market regimes, stock prices change at a super-exponential rate and ar…
Most of the data-driven approaches applied to bearing fault diagnosis up to date are established in the supervised learning paradigm, which usually requires a large set of labeled data collected a priori. In practical applications, however, obtaining accurate labels based on real-time bearing conditions can be far more…
Paper argues the bear case for Bitcoin is bounded and terminal states are neutral to positive.
problem The identity of Bitcoin's creator and the associated overhang risk.
method Quantitative analysis of Satoshi's 1.148 million BTC position, considering various preference sets.
result The terminal states most consistent with observed behavior are neutral to slightly positive for Bitcoin's effective supply.
A new approach to obtaining market--directional information, based on a non-stationary solution to the dynamic equation "future price tends to the value that maximizes the number of shares traded per unit time" [1] is presented. In our previous work[2], we established that it is the share execution flow (I=dV/dt) and…
LLMs struggle to outperform markets over long periods and diverse stocks.
problem Overstated effectiveness of LLM-based investing strategies due to biases.
method FINSABER framework for systematic backtests over two decades and 100+ symbols.
result Previously reported LLM advantages deteriorate significantly under broader evaluation.
In this survey paper, we systematically summarize existing literature on bearing fault diagnostics with machine learning (ML) and data mining techniques. While conventional ML methods, including artificial neural network (ANN), principal component analysis (PCA), support vector machines (SVM), etc., have been successfu…
We propose a novel methodology to define, analyze and forecast market states. In our approach market states are identified by a reference sparse precision matrix and a vector of expectation values. In our procedure, each multivariate observation is associated with a given market state accordingly to a minimization of a…
In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we introduce investors with different investment horizons into the news-driven, analytic, agent-based market model developed in Gusev et al. (2015). This heterogeneous frame…
TPA-AD detects axle-box bearing anomalies using pseudo anomalies near normal boundaries.
problem Detecting axle-box bearing anomalies with only normal training data.
method Two-stage approach: pseudo anomalies, contrastive learning, KNN.
result Improves anomaly detection separability and sensitivity to degradation.
The paper develops a hybrid model for optimal order execution in markets with heterogeneous market makers.
problem Optimal liquidation in markets with limited inventory and risk capacity.
method Derives a reduced form model for aggregated inventory dynamics considering price impact.
result Optimal execution can be modeled as a linear-quadratic stochastic control problem.
In this paper, we solve portfolio rebalancing problem when security returns are represented by uncertain variables considering transaction costs. The performance of the proposed model is studied using constant-proportion portfolio insurance (CPPI) as rebalancing strategy. Numerical results showed that uncertain paramet…
This study examines asymmetric cross-correlations in cryptocurrency markets using fractal analysis.
problem Exploring asymmetric multifractal cross-correlations in cryptocurrency markets.
method Fractal analysis and MF-ADCCA method to investigate asymmetric volatility dynamics.
result Cross-correlations are stronger in downtrend markets than in uptrend markets for maturing BTC and ETH.
The study models mortgage prepayment risk using stochastic housing market activity.
problem Modeling prepayment risk in mortgages under varying housing market conditions.
method Developed a stochastic model for prepayment option value, using swaption pricing formulas and non-standard actuarial hedging.
result Housing market covariance significantly impacts prepayment option prices.
Agents prefer non-diversification in markets with extreme losses.
problem Optimal risk allocation and equilibria in markets with extremely heavy-tailed losses.
method Analysis of super-Pareto loss distributions and stochastic dominance.
result Non-diversification is preferred in markets with super-Pareto losses.
This paper explores BTC-denominated prediction markets to avoid stablecoin opportunity costs.
problem Opportunity costs and loss of BTC exposure when converting to stablecoins.
method Analyzes three methods of liquidity provision: cross-market making, automated market making, and DeFi redirection.
result Cross-market making provides the best user risk profile but requires active liquidity.
Market makers continuously set bid and ask quotes for the stocks they have under consideration. Hence they face a complex optimization problem in which their return, based on the bid-ask spread they quote and the frequency at which they indeed provide liquidity, is challenged by the price risk they bear due to their in…
Innovative ball bearing converts rotary to reciprocating motion.
problem Designing efficient motion conversion mechanisms.
method Closed curve envelopment theory and diameter-stroke ratio concept.
result Compact and vibration-reduced ball bearing design.
New tests for identifying the number of latent factors in short panels with small time dimensions.
problem Determining the number of latent factors in short panels with small time dimensions.
method Eigenvalue tests based on variance-covariance matrices of asset returns, with assumptions on spherical errors or instrumental variables for factor betas.
result Established asymptotic distributional results and proposed a novel statistical test for weak factors.
Constructing gene regulatory networks is a critical step in revealing disease mechanisms from transcriptomic data. In this work, we present NO-BEARS, a novel algorithm for estimating gene regulatory networks. The NO-BEARS algorithm is built on the basis of the NOTEARS algorithm with two improvements. First, we propose …
This work presents the results of an empirical research with the target of modeling the stylized facts of the daily expost System Marginal Price (SMP) of the Greek wholesale electricity market, using data from January 2004 to December of 2011. SMP is considered here as the footprint of an underline stochastic and nonli…
The paper analyzes insurance pricing and capital allocation in imperfect markets.
problem Analyzing insurance pricing and capital allocation in imperfect markets.
method Non-additive distortion pricing functional and principle of equal priority of payments in default.
result Derives the natural allocation of premium and margin with properties that merit the name.