Papers, wiki, Option Blackboard, encyclopedia, and cards.
MARK J. P. ANSON is affiliated with OppenheimerFunds, Inc., in New York. R ecent academic and practitioner Ž research Schneeweis 1996 ; . Schneeweis and Spurgin 1998 has emphasized the diversification benefits of a wide range of alternative investments including managed futures products as well as hedge funds. Many of these alternative investment products are based on active management strategies that often concentra…
Hundreds of papers and factors attempt to explain the cross-section of expected returns. Given this extensive data mining, it does not make sense to use the usual criteria for establishing significance. Which hurdle should be used for current research? Our paper introduces a new multiple testing framework and provides historical cutoffs from the first empirical tests in 1967 to today. A new factor needs to clear a mu…
This paper introduces an ARCH model (exponential ARCH) that (1) allows correlation between returns and volatility innovations (an important feature of stock market volatility changes), (2) eliminates the need for inequality constraints on parameters, and (3) allows for a straightforward interpretation of the "persistence" of shocks to volatility. In the above respects, it is an improvement over the widely-used GARCH …
Commodity futures risk premiums vary across commodities and over time depending on the level of physical inventories, as predicted by the Theory of Storage. Using a comprehensive dataset on 31 commodity futures and physical inventories between 1969 and 2006, we show that the convenience yield is a decreasing, non-linear relationship of inventories. Price measures, such as the futures basis, prior futures returns, and…
This paper examines how shocks to currency volatilities predict exchange rates. Using option-implied volatilities, we construct a dynamic, directed network of volatility connections. Currencies that transmit more volatility shocks, which control for common correlation, earn lower excess returns. Buying the weakest and selling the strongest transmitters delivers high risk-adjusted performance, driven by spot exchange …
The electronic platform has been increasingly popular for executing large corporate bond orders by asset managers, who in turn have to assess the quality of their executions via Transaction Cost Analysis (TCA). One of the challenges in TCA is to build a realistic benchmark for the expected transaction cost and to characterize the price impact of each individual trade with given bond characteristics and market conditi…
In the LIBOR era, banks routinely tied revolving credit facilities to credit-sensitive benchmarks. This study assesses the Across-the-Curve Credit Spread Index (AXI) -- a transparent, transaction-based measure of wholesale bank funding costs -- as a complement to SOFR, summarizing its behavior, construction, and loan-pricing implications. AXI aggregates observable unsecured funding transactions across short- and long…
This paper compares a series of contemporary portfolio construction approaches by employing ten U.S. stocks (TSLA, WMT, BAC, GS, LLY, MRK, GOOG, META, AAPL and XOM) in a time frame from September 2023 to December 2025. The paper explores both basic mean-variance optimization, constrained optimization, Fama French five factor regression modeling, Monte Carlo simulation, and the Black-Litterman model to determine how c…
Artificial transaction generation remains an important source of potential market manipulation on cryptocurrency exchanges, as it may distort reported liquidity and reduce market transparency. This study proposes a diagnostic framework for detecting unusual trading patterns based on complexity and statistical-structure measures derived from high-frequency trade-level data. The analysis considers log-returns, trading …
We audit whether candle-based machine-learning models can turn predictions of cryptocurrency extrema or short-horizon outcomes into positive Binance Spot paper policies after assumed costs. Numerical results come from scripted fixed-seed model runs and deterministic simulators; human-supervised AI agents supported the July 20 evidence-integrity revision through literature retrieval, separately tasked critique, artifa…
Agent skills, structured packages of procedural knowledge and executable resources that agents dynamically load at inference time, have become a reliable mechanism for augmenting LLM agents. Yet inference-time skill augmentation is fundamentally limited: retrieval noise introduces irrelevant guidance, injected skill content imposes substantial token overhead, and the model never truly acquires the knowledge it merely…
Equity Risk Premium measures the excess return investors expect from equities over risk-free assets and is a core framework for evaluating relative equity valuation.
Carry and Roll Down — Expected return from holding higher-yielding tenor as it rolls down a positively sloped curve.
MBS Prepayment Speed — Refinancing and turnover driven cash-flow uncertainty in agency mortgages.
Distressed Debt Ratio — Share of debt trading at deep discounts — early warning for credit cycle turns.
Realized Volatility — Historical return variation that determines PnL for delta-hedged option positions.
Size Premium — Historical return premium for smaller capitalisation stocks with liquidity caveats.
Liquidity Premium — Compensation for holding illiquid assets and providing immediacy.
Intraday Volatility — Within-day return variation informing execution timing and gamma scalping.
Commodity Carry — Return from rolling futures along the curve — core systematic commodity strategy.
Shareholder Yield — Combined dividends and buybacks as cash return to equity holders.
Historical Volatility — Realized return dispersion used as a benchmark versus implied.
Residual Momentum — Momentum on idiosyncratic returns after factor residualization.
Turnover Constraint (Quant).
Performance Dispersion Pods — Cross-pod return dispersion as platform health signal.
Quarter End Window Dressing Rates — Balance-sheet and window-dressing effects at turns.
Year End Funding Premium (Rates).
Abnormal Return (Quant).
Cumulative Abnormal Return (Quant).
Amihud Illiquidity — Average absolute return per unit volume as an illiquidity proxy.
Black Litterman Model — Bayesian blend of equilibrium returns and investor views.
Residual Return intraday (Quant).
Residual Return 1-day (Quant).
Residual Return 1-week (Quant).
Residual Return 1-month (Quant).
Residual Return 3-month (Quant).
Residual Return 6-month (Quant).
Residual Return 12-month (Quant).
Residual Return risk-on (Quant).
Residual Return risk-off (Quant).
Residual Return tightening (Quant).
Residual Return easing (Quant).
Residual Return stagflation (Quant).
Residual Return reflation (Quant).
Residual Return disinflation (Quant).
Residual Return liquidity-crisis (Quant).
Residual Return carry (Quant).
Abnormal Return (Quant).
Amihud Illiquidity — Average absolute return per unit volume as an illiquidity proxy.
Black Litterman Model — Bayesian blend of equilibrium returns and investor views.
Carry and Roll Down — Expected return from holding higher-yielding tenor as it rolls down a positively sloped curve.
Commodity Carry — Return from rolling futures along the curve — core systematic commodity strategy.
Cumulative Abnormal Return (Quant).
Distressed Debt Ratio — Share of debt trading at deep discounts — early warning for credit cycle turns.
Equity Risk Premium measures the excess return investors expect from equities over risk-free assets and is a core framework for evaluating relative equity valuation.
Historical Volatility — Realized return dispersion used as a benchmark versus implied.
Intraday Volatility — Within-day return variation informing execution timing and gamma scalping.
MBS Prepayment Speed — Refinancing and turnover driven cash-flow uncertainty in agency mortgages.
Performance Dispersion Pods — Cross-pod return dispersion as platform health signal.
Quarter End Window Dressing Rates — Balance-sheet and window-dressing effects at turns.
Realized Volatility — Historical return variation that determines PnL for delta-hedged option positions.
Residual Momentum — Momentum on idiosyncratic returns after factor residualization.
Residual Return 1-day (Quant).
Residual Return 1-month (Quant).
Residual Return 1-week (Quant).
Residual Return 12-month (Quant).
Residual Return 3-month (Quant).
Residual Return 6-month (Quant).
Residual Return carry (Quant).
Residual Return core (Quant).
Residual Return disinflation (Quant).