arXiv · arXiv q-fin · 2025
High-frequency trading (HFT) is an investing strategy that continuously monitors market states and places bid and ask orders at millisecond speeds. Traditional HFT approaches fit models with historical data and assume that future market states follow similar patterns. This limits the effectiveness of any single model to the specific conditions it was trained for. Additionally, these models achieve optimal solutions o…
Yang Li, Zhi Chen, Steve Yang
OpenAlex · Journal of money credit and banking · 2004 · cites 380
This paper analyses the effects of US monetary policy on stock markets.We find that, on average, a tightening of 50 basis points reduces returns by about 3%.Moreover, returns react more strongly when no change had been expected, when there is a directional change in the monetary policy stance and during periods of high market uncertainty.We show that individual stocks react in a highly heterogeneous fashion and relat…
Michael Ehrmann, Marcel Fratzscher
OpenAlex · Cambridge University Press eBooks · 2003 · cites 329
Proper conduct of monetary policy requires understanding the monetary transmission mechanism, to monitor the economy, make decisions on the stance of policy, and explain the policy actions to the public. Hence, gathering evidence on the monetary transmission mechanism in the euro area has been a priority for the Eurosystem. This 2003 book presents the results of a multi-year collaborative project conducted by the Eur…
Unknown authors
OpenAlex · The Journal of Economic Perspectives · 1995 · cites 4183
The ‘credit channel’ theory of monetary policy transmission holds that informational frictions in credit markets worsen during tight-money periods. The resulting increase in the external finance premium--the difference in cost between internal and external funds--enhances the effects of monetary policy on the real economy. The authors document the responses of GDP and its components to monetary policy shocks and desc…
Ben Bernanke, Mark Gertler
arXiv · arXiv q-fin · 2021
This study evaluates the effect of collection policy on portfolio quality of microfinance banks in Adamawa State, Nigeria. Real data were collected from 51 credit officers, then a multi-stage sampling method was used to select a sample of 21 respondents from the population (i.e., 51 credit officers). In addition, we used regression analysis and descriptive statistics to analyze the data collected and to also test our…
Esther Yusuf Enoch, Abubakar Mahmud Digil, Usman Abubakar Arabo
arXiv · arXiv · 2025
This paper proposes a reinforcement learning--based framework for cryptocurrency portfolio management using the Soft Actor--Critic (SAC) and Deep Deterministic Policy Gradient (DDPG) algorithms. Traditional portfolio optimization methods often struggle to adapt to the highly volatile and nonlinear dynamics of cryptocurrency markets. To address this, we design an agent that learns continuous trading actions directly f…
Kamal Paykan
arXiv · arXiv · 2025
Transaction costs and regime shifts are major reasons why paper portfolios fail in live trading. We introduce FR-LUX (Friction-aware, Regime-conditioned Learning under eXecution costs), a reinforcement learning framework that learns after-cost trading policies and remains robust across volatility-liquidity regimes. FR-LUX integrates three ingredients: (i) a microstructure-consistent execution model combining proporti…
Jian'an Zhang
arXiv · arXiv · 2021
With the improvement of computer performance and the development of GPU-accelerated technology, trading with machine learning algorithms has attracted the attention of many researchers and practitioners. In this research, we propose a novel portfolio management strategy based on the framework of Deep Deterministic Policy Gradient, a policy-based reinforcement learning framework, and compare its performance to that of…
Huanming Zhang, Zhengyong Jiang, Jionglong Su
arXiv · arXiv · 2026
In this paper, we develop a continuous-time model-free reinforcement learning algorithm to learn deterministic equilibrium policies in general time-inconsistent control problems. Utilizing the extended Hamilton-Jacobi-Bellman system, we recast the original time-inconsistent problem into an equivalent two-stage problem. In the first stage, for given auxiliary functions, we employ the deterministic policy gradient appr…
Xin Guo, Yijie Huang, Xiang Yu
arXiv · arXiv · 2023
The energy transition has increased the reliance on intermittent energy sources, destabilizing energy markets and causing unprecedented volatility, culminating in the global energy crisis of 2021. In addition to harming producers and consumers, volatile energy markets may jeopardize vital decarbonization efforts. Traders play an important role in stabilizing markets by providing liquidity and reducing volatility. Sev…
Jonas Hanetho
arXiv · arXiv · 2013
In agreement with the recent research findings in the econophysics, we propose that the nonlinear dynamic chaos can be generated by the turbulent capital flows in both the quantitative easing transmission channels and the transaction networks channels, when there are the laminar turbulent capital flows transitions in the financial system. We demonstrate that the capital flows in both the quantitative easing transmiss…
Dimitri O. Ledenyov, Viktor O. Ledenyov
OpenAlex · American Economic Review · 2000 · cites 2589
We study the monetary-transmission mechanism with a data set that includes quarterly observations of every insured U.S. commercial bank from 1976 to 1993. We find that the impact of monetary policy on lending is stronger for banks with less liquid balance sheets—i.e., banks with lower ratios of securities to assets. Moreover, this pattern is largely attributable to the smaller banks, those in the bottom 95 percent of…
Anil Kashyap, Jeremy C. Stein
arXiv · arXiv · 2026
We develop simulation-based policy iteration for continuous-time portfolio choice with predictable returns and convex constraints. Each outer step re-evaluates a fixed-latent open-loop backpropagation-through-time (OL-BPTT) adjoint after deployment and solves the constrained update. Shifted-adjoint cancellation controls the adjoint--HJB Hamiltonian-gradient discrepancy by the policy-improvement residual. For CRRA por…
Jeonggyu Huh, Yeoneung Kim, Seungwon Jeong
arXiv · arXiv · 2026
Neural and numerical policy solvers can produce feasible controls even when the optimal rule and its binding constraints are unavailable. A primal-dual bracket certifies value loss, but it does not locate the optimal policy or explain which constraints genuinely bind. We show that, on the same declared simulation grid, one bracket can support both conclusions. For polyhedral controls, an exact conditional budget iden…
Jeonggyu Huh
arXiv · arXiv · 2026
This study addresses the optimal execution of large stock sell programs by introducing TT-DAC-PS (Twin-Target Deterministic Actor-Critic with Policy Smoothing), a deterministic actor-critic architecture that combines twin exponential-moving-average critic targets with pessimistic min backup, TD3-style target policy smoothing noise, delayed actor updates, and conservative Q regularisation to curb overestimation. Explo…
Ilia Zaznov, Atta Badii, Julian Kunkel, Alfonso Dufour
arXiv · arXiv · 2026
Traditional insurance pricing relies on risk-based principles that ensure actuarial fairness and solvency but do not explicitly account for policyholders' price sensitivity. We formulate insurance pricing as a decision-making problem and study it using tools from off-policy evaluation and stochastic control. We propose a kernelized inverse propensity score estimator that exploits local structure in the action space a…
Sascha Günther, Dimitri Semenovich, Mario V. Wüthrich
arXiv · arXiv · 2026
Many real-world problems require sequential decisions under uncertainty: when to inject or withdraw gas from storage, how to rebalance a pension portfolio each month, what temperature profile to run through a pharmaceutical reactor chain. Dynamic programming solves small instances exactly but scales exponentially in state dimensions. Black-box reinforcement learning handles high-dimensional states but trains slowly a…
Dmitri Goloubentsev, Natalija Karpichina
arXiv · arXiv · 2026
This paper examines how trade policy uncertainty influences the correlation between U.S. stock indices and short-term government bonds. The objective is to assess whether policy-related shocks, especially those linked to trade tensions, alter the traditional stock-T bill relationship and its implications for investors. We extend the Dynamic Conditional Correlation (DCC) framework by incorporating exogenous variables …
Demetrio Lacava