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This study introduces an interpretable machine learning (ML) framework to extract macroeconomic alpha from global news sentiment. We process the Global Database of Events, Language, and Tone (GDELT) Project's worldwide news feed using FinBERT -- a Bidirectional Encoder Representations from Transformers (BERT) based model pretrained on finance-specific language -- to construct daily sentiment indices incorporating mea…
We consider the randomness of market trade as the origin of price and return stochasticity. We look at time series of trade values and volumes as random variables during the averaging interval Δ and describe the dependences of market-based volatilities of price and return on the volatilities and correlations of market trade values and volumes. We describe the market-based origin of the lower boundaries of the accurac…
Understanding how market participants react to shocks like scheduled macroeconomic news is crucial for both traders and policymakers. We develop a calibrated data generation process DGP that embeds four stylized trader archetypes retail, pension, institutional, and hedge funds into an extended CAPM augmented by CPI surprises. Each agents order size choice is driven by a softmax discrete choice rule over small, medium…
We propose DeePM (Deep Portfolio Manager), a structured deep-learning macro portfolio manager trained end-to-end to maximize a robust, risk-adjusted utility. DeePM addresses three fundamental challenges in financial learning: (1) it resolves the asynchronous "ragged filtration" problem via a Directed Delay (Causal Sieve) mechanism that prioritizes causal impulse-response learning over information freshness; (2) it co…
This study examines the effects of macroeconomic policies on financial markets using a novel approach that combines Machine Learning (ML) techniques and causal inference. It focuses on the effect of interest rate changes made by the US Federal Reserve System (FRS) on the returns of fixed income and equity funds between January 1986 and December 2021. The analysis makes a distinction between actively and passively man…
In the peer to peer (P2P) lending platform, investors hope to maximize their return while minimizing the risk through a comprehensive understanding of the P2P market. A low and stable average default rate across all the borrowers denotes a healthy P2P market and provides investors more confidence in a promising investment. Therefore, having a powerful model to describe the trend of the default rate in the P2P market …
We develop a model to price inflation and interest rates derivatives using continuous-time dynamics that have some links with macroeconomic monetary DSGE models equipped with a Taylor rule: in particular, the reaction function of the central bank, the bond market liquidity, inflation and growth expectations play an important role. The model can explain the effects of non-standard monetary policies (like quantitative …
Large language models can extract richer signals from financial news than fixed sentiment lexicons, and recent work has explored feeding such signals into portfolio construction. We study an uncertainty-aware construction that feeds model-predicted risk -- decomposed into aleatoric and epistemic components -- directly into the covariance matrix of portfolio allocators, rather than treating portfolio risk as fixed or …
Forecasting benchmarks for retrieval-augmented LLMs routinely confound model capability with information leakage: features labeled with a target's timestamp are often not observable at the system's decision time. We study leakage-controlled equity factor ranking with a retrieval-augmented 7B open-source LLM forecaster. At each month-end from 2023-04 to 2026-03, the forecaster observes only decision-time information: …
We test whether large language models (LLMs) add value in commodity portfolio construction when the information set and implementation rules are held fixed across strategies. A Hawkish Agent (inflation-tightening prior), a Dovish Agent (growth-easing prior), a Debate Agent, and a deterministic z-score Rule Agent each receive identical FRED macro z-scores and route their tilt signals through the same portfolio engine.…
Agent-based models (ABMs) are increasingly used in macroeconomics, but their analysis still often relies on ad hoc Monte Carlo campaigns with heterogeneous statistical effort across parameter settings. We show how statistical model checking (SMC), implemented through MultiVeStA, can provide a principled analysis layer for a realistic macroeconomic ABM without rewriting the simulator in a dedicated formalism. Our case…
Daily probability changes in Kalshi macro prediction markets forecast cryptocurrency realized volatility through two distinct channels. The monetary policy channel, measured by Fed rate repricing on KXFED contracts, predicts Bitcoin volatility in sample with t = 3.63 and p < 0.001 but exhibits regime dependence tied to the 2024-2025 rate-cutting cycle. The recession risk signal from KXRECSSNBER proves more stable out…
We study how a central bank should dynamically set short-term nominal interest rates to stabilize inflation and unemployment when macroeconomic relationships are uncertain and time-varying. We model monetary policy as a sequential decision-making problem where the central bank observes macroeconomic conditions quarterly and chooses interest rate adjustments. Using publicly accessible historical Federal Reserve Econom…
Crypto enthusiasts claim that buying and holding crypto assets yields high returns, often citing Bitcoin's past performance to promote other tokens and fuel fear of missing out. However, understanding the real risk-return trade-off and what factors affect future crypto returns is crucial as crypto becomes increasingly accessible to retail investors through major brokerages. We examine the HODL strategy through two in…
The global financial crisis (GFC) triggered the use of macroprudential policies imposed on the banking sector. Using bank-level panel data for Israel for the period 2004-2019, we find that domestic macroprudential measures changed the composition of bank credit growth but did not affect the total credit growth rate. Specifically, we show that macroprudential measures targeted at the housing sector moderated housing c…
This paper extends the tactical asset allocation literature by incorporating regime modeling using techniques from machine learning. We propose a novel model that classifies current regimes, forecasts the distribution of future regimes, and integrates these forecasts with the historical performance of individual assets to optimize portfolio allocations. Utilizing a macroeconomic data set from the FRED-MD database, ou…
This paper examines the influence of low-frequency macroeconomic variables on the high-frequency returns of copper futures and the long-term correlation with the S&P 500 index, employing GARCH-MIDAS and DCC-MIDAS modeling frameworks. The estimated results of GARCH-MIDAS show that realized volatility (RV), level of interest rates (IR), industrial production (IP) and producer price index (PPI), volatility of Slope, PPI…
High-frequency trading (HFT) that executes algorithmic trading in short time scales, has recently occupied the majority of cryptocurrency market. Besides traditional quantitative trading methods, reinforcement learning (RL) has become another appealing approach for HFT due to its terrific ability of handling high-dimensional financial data and solving sophisticated sequential decision-making problems, \emph{e.g.,} hi…
Systemic Risk Indicator — Aggregate capital shortfall under stress — connects banking to macro hedges.
Gold price reflects demand for a non-yielding reserve asset and is often used as a signal for real yields, macro uncertainty, and confidence in fiat systems.
A discretionary CTA uses judgment on timing, size, and markets — often a global-macro book that happens to be futures-registered.
Managed futures is the strategy category: client capital traded in a diversified futures universe, usually systematic trend, sometimes with carry, reversion, or macro overlays.
A CTA that trades futures on economic data, not only price — growth, inflation, positioning, and nowcasts as the signal set.
The MOVE Index tracks implied volatility in the U.S. Treasury market and serves as a benchmark for rates uncertainty and macro stress.
Don’t fight the Fed is the rule of thumb that a determined policy impulse (easing or tightening) will eventually dominate discretionary macro views.
China credit impulse measures the change in new credit growth relative to GDP and is widely used as a leading indicator for Chinese demand and global cyclical momentum.
Sudden Stop Capital Flows — Abrupt cessation of foreign financing forcing sharp macro adjustment.
Barings Bank was wiped out in 1995 by Nick Leeson’s hidden Nikkei futures losses in Singapore — a rogue-trader plus failed control story, not a macro crisis.
Countercyclical Capital Buffer — Bank capital requirements that tighten or ease through the credit cycle.
Funding stress signal derived from FX swap pricing distortions and balance sheet constraints.
The Fed’s dual mandate is maximum employment and stable prices — two goals that agree in a demand shock and fight in a supply shock.
Emergency Liquidity Facility — Standing and ad-hoc facilities that reveal where stress is concentrated in the financial system.
Federal Funds Rate — The effective overnight policy rate anchor that transmits through the entire USD funding stack and global risk appetite.
The FOMC is the Fed body that sets the funds-rate target and the balance-sheet stance — the US rates committee.
A Financial Conditions Index aggregates variables such as rates, credit spreads, equities, and the dollar to measure how supportive or restrictive the market environment is for growth and risk assets.
Fiscal policy is government spending and taxes — the demand impulse that is not the policy rate.
Foreign Exchange Intervention — Official buying or selling of currency to manage disorderly moves and imported inflation.
Forward Guidance — How central bank language shapes term premium and front-end rate expectations before actual policy moves.
A hard landing is a policy-induced recession — inflation (or a bubble) comes down because demand was broken.
Macroprudential Policy — Countercyclical tools that alter credit creation before traditional monetary policy reacts.
Monetary policy is the central bank’s control of short rates, liquidity, and sometimes the balance sheet — the price of reserves and the path of the front end.
Neutral Rate Estimate — Estimates of the equilibrium real policy rate that separates restrictive from accommodative stance.
Quantitative easing is large-scale central-bank asset purchases that expand reserves — a duration and liquidity operation when the policy rate is pinned.
Quantitative Tightening Pace — The speed of balance-sheet runoff and its impact on reserves, collateral markets, and term funding.
A soft landing is disinflation (or a slowdown) without a recession — the hoped-for path off a hike cycle.
Standing Repo Facility — The Fed backstop for repo market dysfunction and dealer balance-sheet pressure.
The term structure of interest rates across maturities, used to read growth, liquidity, and stress expectations.
Yield Curve Control — Official caps on benchmark yields and the distortions they create in RV and cross-market hedging.
The 3M10Y Treasury curve compares 10-year Treasury yields with 3-month Treasury bill yields and is closely watched as a recession and policy-cycle indicator.
US 10-Year Real Yield measures the inflation-adjusted yield on 10-year Treasuries and is a key benchmark for discount rates, financial conditions, and macro asset pricing.
Time equity beta with oil’s recent move or level — a macro overlay that treats crude as a growth/inflation signal.
Barings Bank was wiped out in 1995 by Nick Leeson’s hidden Nikkei futures losses in Singapore — a rogue-trader plus failed control story, not a macro crisis.
Countercyclical Capital Buffer — Bank capital requirements that tighten or ease through the credit cycle.
Funding stress signal derived from FX swap pricing distortions and balance sheet constraints.
Time equity beta with oil’s recent move or level — a macro overlay that treats crude as a growth/inflation signal.
A discretionary CTA uses judgment on timing, size, and markets — often a global-macro book that happens to be futures-registered.
Don’t fight the Fed is the rule of thumb that a determined policy impulse (easing or tightening) will eventually dominate discretionary macro views.
The Fed’s dual mandate is maximum employment and stable prices — two goals that agree in a demand shock and fight in a supply shock.
Emergency Liquidity Facility — Standing and ad-hoc facilities that reveal where stress is concentrated in the financial system.
Federal Funds Rate — The effective overnight policy rate anchor that transmits through the entire USD funding stack and global risk appetite.
The FOMC is the Fed body that sets the funds-rate target and the balance-sheet stance — the US rates committee.
A Financial Conditions Index aggregates variables such as rates, credit spreads, equities, and the dollar to measure how supportive or restrictive the market environment is for growth and risk assets.
Fiscal policy is government spending and taxes — the demand impulse that is not the policy rate.
Foreign Exchange Intervention — Official buying or selling of currency to manage disorderly moves and imported inflation.
Forward Guidance — How central bank language shapes term premium and front-end rate expectations before actual policy moves.
Gold price reflects demand for a non-yielding reserve asset and is often used as a signal for real yields, macro uncertainty, and confidence in fiat systems.
A hard landing is a policy-induced recession — inflation (or a bubble) comes down because demand was broken.
Macroprudential Policy — Countercyclical tools that alter credit creation before traditional monetary policy reacts.
Managed futures is the strategy category: client capital traded in a diversified futures universe, usually systematic trend, sometimes with carry, reversion, or macro overlays.
Monetary policy is the central bank’s control of short rates, liquidity, and sometimes the balance sheet — the price of reserves and the path of the front end.
The MOVE Index tracks implied volatility in the U.S. Treasury market and serves as a benchmark for rates uncertainty and macro stress.
Neutral Rate Estimate — Estimates of the equilibrium real policy rate that separates restrictive from accommodative stance.
Quantitative easing is large-scale central-bank asset purchases that expand reserves — a duration and liquidity operation when the policy rate is pinned.
Quantitative Tightening Pace — The speed of balance-sheet runoff and its impact on reserves, collateral markets, and term funding.
A soft landing is disinflation (or a slowdown) without a recession — the hoped-for path off a hike cycle.