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The Secured Overnight Funding Rate (SOFR) is becoming the main Risk-Free Rate benchmark in US dollars, thus interest rate term structure models need to be updated to reflect the key features exhibited by the dynamics of SOFR and the forward rates implied by SOFR futures. Historically, interest rate term structure modelling has been based on rates of substantially longer time to maturity than overnight, but with SOFR …
Using a recently introduced method to quantify the time varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be anti-correlated; (ii) the change in central bank rates, as a proxy of the monetary policy of the central bank, should be a predictor of…
Our primary goal is to forecast and empirically examine the evolution of the implied volatility (IV) surface, with particular focus on the dates of scheduled meetings of the Federal Open Market Committee (FOMC). Firstly, we check if IV increases before the announcement and if thes effect is stronger for short-dated, out-the-money (OTM) options in high volatility regimes. In the second part, we turn the focus to verif…
Multimodal time-to-event prediction often requires integrating sensitive data distributed across multiple parties, making centralized model training impractical due to privacy constraints. At the same time, most existing multimodal survival models produce single deterministic predictions without indicating how confident the model is in its estimates, which can limit their reliability in real-world decision making. To…
Credit risk models are a critical decision-support tool for financial institutions, yet tightening data-protection rules (e.g., GDPR, CCPA) increasingly prohibit cross-border sharing of borrower data, even as these models benefit from cross-institution learning. Traditional default prediction suffers from two limitations: binary classification ignores default timing, treating early defaulters (high loss) equivalently…
The Federal Open Market Committee (FOMC) sets the federal funds rate, shaping monetary policy and the broader economy. We introduce \emph{FedSight AI}, a multi-agent framework that uses large language models (LLMs) to simulate FOMC deliberations and predict policy outcomes. Member agents analyze structured indicators and unstructured inputs such as the Beige Book, debate options, and vote, replicating committee reaso…
We present the first application of federated learning (FL) to the U.S. National Financial Capability Study, introducing an interpretable framework for predicting consumer financial distress across all 50 states and the District of Columbia without centralizing sensitive data. Our cross-silo FL setup treats each state as a distinct data silo, simulating real-world governance in nationwide financial systems. Unlike pr…
Forecasting central bank policy decisions remains a persistent challenge for investors, financial institutions, and policymakers due to the wide-reaching impact of monetary actions. In particular, anticipating shifts in the U.S. federal funds rate is vital for risk management and trading strategies. Traditional methods relying only on structured macroeconomic indicators often fall short in capturing the forward-looki…
This study introduces the Quantum Federated Neural Network for Financial Fraud Detection (QFNN-FFD), a cutting-edge framework merging Quantum Machine Learning (QML) and quantum computing with Federated Learning (FL) for financial fraud detection. Using quantum technologies' computational power and the robust data privacy protections offered by FL, QFNN-FFD emerges as a secure and efficient method for identifying frau…
We propose an optimal iterative scheme for federated transfer learning, where a central planner has access to datasets ${\cal D}_1,\dots,{\cal D}_N$ for the same learning model $f_θ$. Our objective is to minimize the cumulative deviation of the generated parameters $\{θ_i(t)\}_{t=0}^T$ across all $T$ iterations from the specialized parameters $θ^\star_{1},\ldots,θ^\star_N$ obtained for each dataset, while respecting …
The model of this paper gives a convenient strategy that a bank in the federal funds market can use in order to maximize its profit in a contemporaneous reserve requirement (CRR) regime. The reserve requirements are determined by the demand deposit process, modelled as a Brownian motion with drift. We propose a new model in which the cumulative funds purchases and sales are discounted at possible different rates. We …
In high frequency trading, accurate prediction of Order Flow Imbalance (OFI) is crucial for understanding market dynamics and maintaining liquidity. This paper introduces a hybrid predictive model that combines Vector Auto Regression (VAR) with a simple feedforward neural network (FNN) to forecast OFI and assess trading intensity. The VAR component captures linear dependencies, while residuals are fed into the FNN to…
We give a detailed account of correlations between credit sector/quality and treasury curve factors, using the robust framework of the Barclays POINT Global Risk Model. Consistent with earlier studies, we find a strong negative correlation between sector spreads and rate shifts. However, we also observe that the correlations between spreads and Treasury twists reversed recently, which is likely attributable to the Fe…
If the probability of default parameters (PDs) fed as input into a credit portfolio model are estimated as through-the-cycle (TTC) PDs stressed market conditions have little impact on the results of the capital calculations conducted with the model. At first glance, this is totally different if the PDs are estimated as point-in-time (PIT) PDs. However, it can be argued that the reflection of stressed market condition…
The variance measures the portfolio risks the investors are taking. The investor, who holds his portfolio and doesn't trade his shares, at the current time can use the time series of the market trades that were made during the averaging interval with the securities of his portfolio and assess the current return, variance, and hence the current risks of his portfolio. We show how the time series of trades with the sec…
We consider the investor who doesn't trade shares of his portfolio. The investor only observes the current trades made in the market with his securities to estimate the current return, variance, and risks of his unchanged portfolio. We show how the time series of consecutive trades made in the market with the securities of the portfolio can determine the time series that model the trades with the portfolio as with a …
The Non-Fungible-Token (NFT) market has experienced explosive growth in recent years. According to DappRadar, the total transaction volume on OpenSea, the largest NFT marketplace, reached 34.7 billion dollars in February 2023. However, the NFT market is mostly unregulated and there are significant concerns about money laundering, fraud and wash trading. The lack of industry-wide regulations, and the fact that amateur…
An increasing share of energy is produced from renewable sources by many small producers. The efficiency of those sources is volatile and, to some extent, random, exacerbating the problem of energy market balancing. In many countries, this balancing is done on the day-ahead (DA) energy markets. This paper considers automated trading on the DA energy market by a medium-sized prosumer. We model this activity as a Marko…
A reserve requirement is the fraction of deposits a bank must hold as reserves — a tool that is now often zero in the US, with liquidity rules doing the real work.
Behind the curve means policy (or a book) is too easy or too slow relative to incoming inflation, growth, or a Taylor-type benchmark — the market is already pricing a catch-up.
Don’t fight the Fed is the rule of thumb that a determined policy impulse (easing or tightening) will eventually dominate discretionary macro views.
Stuffed means a dealer or salesperson was left long (or short) inventory they did not want, usually after a client or a syndicate left paper on the desk.
Core PCE Inflation — The Fed's preferred inflation gauge, stripping volatile food and energy components.
Wage Growth — Nominal pay momentum that feeds services inflation persistence and Fed reaction functions.
The Great Depression was a multi-year collapse of output, prices, and banks after the 1929 crash, amplified by the gold standard, Fed errors, and a wave of bank failures — the defining 20th-century crisis.
The Panic of 1792 was the first US securities-market crash, after a leveraged attempt to corner federal debt, and the first Treasury-led lender-of-last-resort operation under Hamilton.
The Panic of 1907 was a New York trust-company run after a failed copper corner, stopped by a private J.P. Morgan syndicate — the crisis that created the Federal Reserve.
The Plaza Accord was a coordinated 1985 G5 intervention to weaken the dollar after a brutal early-1980s USD squeeze — not a crash, but a regime change in FX that re-priced US manufacturing and later fed Japan’s bubble politics.
Primary Dealer Survey — Desk-level policy expectations that front-run official communications.
Bank reserve balances reflect the quantity of reserves held by banks at the Federal Reserve and are central to understanding liquidity distribution and financial system stability.
BTFP usage tracks how much funding banks obtain through the Bank Term Funding Program, offering insight into balance-sheet stress and demand for official liquidity backstops.
Discount Window borrowing measures bank use of Federal Reserve emergency liquidity and serves as a signal of funding pressure and banking-sector strain.
The Fed balance sheet reflects the scale of Federal Reserve asset holdings and is a major driver of reserves, liquidity conditions, and policy transmission.
QT pace refers to the speed at which the Federal Reserve allows assets to roll off its balance sheet, affecting reserves, duration supply, and market liquidity.
Reverse Repo Facility usage shows how much cash is being parked at the Federal Reserve overnight and helps track reserve distribution, collateral demand, and system liquidity conditions.
Treasury General Account tracks the U.S. Treasury’s cash balance at the Federal Reserve and influences system liquidity by absorbing or releasing reserves.
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.
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.
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.
Bank reserve balances reflect the quantity of reserves held by banks at the Federal Reserve and are central to understanding liquidity distribution and financial system stability.
Core PCE Inflation — The Fed's preferred inflation gauge, stripping volatile food and energy components.
Discount Window borrowing measures bank use of Federal Reserve emergency liquidity and serves as a signal of funding pressure and banking-sector strain.
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.
The Fed balance sheet reflects the scale of Federal Reserve asset holdings and is a major driver of reserves, liquidity conditions, and policy transmission.
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.
The Great Depression was a multi-year collapse of output, prices, and banks after the 1929 crash, amplified by the gold standard, Fed errors, and a wave of bank failures — the defining 20th-century crisis.
The Panic of 1792 was the first US securities-market crash, after a leveraged attempt to corner federal debt, and the first Treasury-led lender-of-last-resort operation under Hamilton.
The Panic of 1907 was a New York trust-company run after a failed copper corner, stopped by a private J.P. Morgan syndicate — the crisis that created the Federal Reserve.
The Plaza Accord was a coordinated 1985 G5 intervention to weaken the dollar after a brutal early-1980s USD squeeze — not a crash, but a regime change in FX that re-priced US manufacturing and later fed Japan’s bubble politics.
QT pace refers to the speed at which the Federal Reserve allows assets to roll off its balance sheet, affecting reserves, duration supply, and market liquidity.
Reverse Repo Facility usage shows how much cash is being parked at the Federal Reserve overnight and helps track reserve distribution, collateral demand, and system liquidity conditions.
Standing Repo Facility — The Fed backstop for repo market dysfunction and dealer balance-sheet pressure.
Stuffed means a dealer or salesperson was left long (or short) inventory they did not want, usually after a client or a syndicate left paper on the desk.
Treasury General Account tracks the U.S. Treasury’s cash balance at the Federal Reserve and influences system liquidity by absorbing or releasing reserves.
Wage Growth — Nominal pay momentum that feeds services inflation persistence and Fed reaction functions.