Research
Every research paper we have written up, newest paper first. New arrivals are screened automatically for topical fit with systematic trading; the ones that clear it are read, written up, and — where the idea is testable on our data — backtested. Particular focus on alpha hypotheses that can be formalised and tested. The Radar also covers portfolio construction, market risk and execution where the research is directly relevant to systematic investment processes. Follow new entries by RSS.
16,915 papers screened · 588 on the radar · 121 shown
We study strategic liquidity provision in decentralized exchanges with concentrated liquidity as a mean-field game.
PAPER REPORTS · Margin-gated provision backtest on four Base pools, 7497 hours, September 2024 to July 2025: in the market 2.5–12% of…
This paper extends the damped-sinc (DSINC) method for American options beyond the affine Heston class to general one-factor stochastic-volatility models.
We develop an arithmetic multi-factor stochastic volatility model for commodity futures and options.
PAPER REPORTS · V3 vanilla option portfolio one-day hedge, 2013-2024 (2,809 dates), in-sample, no transaction costs stated: hedging… · VC3 calendar spread option portfolio one-day hedge with 2 hedge options, 2013-2024 (2,806 dates), in-sample:…
PAPER REPORTS · DCC-ePOET-1, out-of-sample global MVP on 331 S&P 500 stocks: Var 0.445, Annual-SD 10.840, mean Sharpe ratio 2.281,… · DCC-ePOET-2 (latent factors only, no observable factors), same setup: Var 0.464, Annual-SD 11.049, mean Sharpe ratio…
The short-term blow up behaviour of the ATM-IV skew is commonly modelled by either a rough volatility process with small Hurst index or an infinite variation Lévy process in the log-price dynamics.
Abstract This study examines the association between derivatives trading and the spot return volatility of cryptocurrencies, focusing specifically on Bitcoin (BTC) and Ethereum (ETH).
Although advances in artificial intelligence (AI) and machine learning (ML) have transformed financial risk assessment, many early-warning frameworks for systematic risk still rely on isolated macro-financial indicators with limited integration of established…
Pergerakan harga emas yang dipengaruhi oleh volatilitas pasar dan ketidakpastian ekonomi memerlukan metode peramalan serta analisis risiko yang akurat.
PAPER REPORTS · ARIMA(1,1,1) price forecast: MAPE 9.15%, MAE USD 396.14, RMSE USD 454.31, directional accuracy 100%. · MC GBM Geopolitik scenario: MAPE 10.37%, MAE USD 426.43, RMSE USD 465.29, directional accuracy 100%.
OUR BACKTEST · Sharpe 0.01 · Return +0.6% · Max DD -35.1%
Background: Foreign investors can improve liquidity in emerging markets, but concentrated withdrawals may coincide with sharp price adjustment.
Abstract Climate change increasingly affects real estate markets because property assets are location-specific and directly exposed to environmental conditions.
Regime-switching multi-factor models are widely used in quantitative finance, but filtering does not by itself determine when an agent should act on inferred regime changes.
OUR BACKTEST · Sharpe 0.63 · Return +57.2% · Max DD -14.2%
We propose a structured continuous-time stochastic volatility model for one-day-ahead integrated-variance forecasting.
PAPER REPORTS · SPX out-of-sample (second half of 2004–2022, raw RV proxy): QLIKE 0.0709, MSE_var 2.6538, MAE_var 0.4285 · Best-loss counts across 17 indices: QLIKE 15/17, MSE_var 12/17, MAE_var 17/17; retained in 90% MCS on 15/17 (QLIKE),…
We study a local stochastic volatility (LSV) model in which the variance factor follows a generalized Langevin equation (GLE) with colored noise, and past returns act on variance through a memory kernel with state-dependent amplitudes.
We present a statically and dynamically arbitrage-free European option market model with smooth interpolation between option prices, based on the SANOS framework, and prove that its dynamics admit a unique strong solution.
Conditional volatility-based option pricing research generally emphasizes improving volatility inputs, but has not yet fully explained the relative contribution of each parameter to variation in simulated option-pricing responses for Indonesian index stocks.
This study examined the volatility effects of climate policy uncertainty on renewable energy stock returns in Nigeria using the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model.
Global financial markets are increasingly exposed to shocks that propagate rapidly across countries, sectors, and asset classes, generating synchronized volatility that reflects the systemic dimension of financial risk.
FLEX options are customized exchange-traded contracts allowing participants to choose nonstandard strikes, expirations, exercise styles, and settlement terms while retaining central clearing.
PAPER REPORTS · Rich-IV short straddle, research proxy (0.85 haircut, event close): N 40, mean P&L 1.5350% per trade, win rate 80.0%,… · Rich-IV short straddle, execution-stressed (1.25× median chain relative spread + $0.65/contract × 4 legs): N 40, mean…
Abstract The energy and digital transitions are increasing demand for metals used in renewable energy, electrification, storage, and digital infrastructure.
Abstract We formulate a dimensionally consistent time-fractional Black–Scholes model through inverse-stable subordination. A product pricing measure fixes the clock law and operational numeraire, while clock risk remains unspanned.
Market-regime models typically assume a finite set of discrete latent states. We examine whether high frequency limit-order-book dynamics exhibit distinct regime separation or apparent regimes result from discretising an underlying continuum, analysing deep…
PAPER REPORTS · Intraday volatility forecast (not a trading strategy): pooled expanding-year walk-forward OOS R2 0.6821 / 0.7273 /… · Next-window RV direction hit rate: 61.2% (30s), 60.5% (45s), 59.5% (60s) from the continuous predictive block;…
Taiwan’s central role in global semiconductor manufacturing exposes Taiwan-related ETFs to technology concentration, geopolitical uncertainty, and supply-chain disruptions, resulting in return distributions characterized by heavy tails, volatility clustering,…
OUR BACKTEST · Sharpe 0.37 · Return +28.9% · Max DD -34.3%
We determine the leading logarithmic asymptotics of the fixed-maturity right tail of the SABR model with $β\in(0,1)$ and absorption at zero, for every correlation $ρ\in(-1,1)$.
networks and Transformer models for financial volatility forecasting, with specific applications to the CBOE Volatility Index (VIX) and cryptocurrency markets (Bitcoin, Ethereum).
Abstract We investigate statistical tests for multivariate realized volatility models which are estimated using realized covariance matrices computed from intraperiod (high-frequency) financial data.
OUR BACKTEST · Sharpe 0.54 · Return +24.3% · Max DD -22.3%
Neural network-based approaches have emerged as efficient alternatives to traditional optimization-based procedures for the calibration of stochastic volatility models.
We study the anatomy of commodity risk by distinguishing micro, market-level, and economy-wide sources.
European option smiles determine the risk-neutral marginal laws of an asset, but not their intertemporal coupling, which is decisive for many applications.
We study the short-maturity implied volatility and the skew stickiness ratio for baskets of assets with continuous, possibly rough, stochastic volatility.
We develop a non-perturbative framework for stochastic-volatility option pricing organised by the two-particle-irreducible (2PI) effective action and the Dyson-Schwinger gap equations of quantum field theory.
Building on the forest expansion of Alòs, Gatheral and Radoičić and on the explicit Bergomi-Guyon smile expansion derived by Bourgey and Gatheral (2026), we derive fixed-point approximations, in terms of the implied total variance at a small number of magic…
Option-implied factors are largely, but not entirely, spanned by the equity factor zoo. We construct 137 option-implied characteristics for optionable U.S.
PAPER REPORTS · bakshiKurt long-short factor (value-weighted decile, S&P 500 constituents, 30-day maturity): -11.23% annualized mean,… · ivs_convexity long-short factor: -14.78% annualized mean, vol 17.94%, Sharpe -0.82, MDD -96.94%, skew -3.59, t = -2.57;…
OUR BACKTEST · Sharpe -0.19 · Return -21.5% · Max DD -44.4%
Commodity option surfaces contain information beyond the at-the-money volatility level.
Volatility forecasts play a central role in financial risk management because their overall level and day-to-day movements affect downstream decisions. Most studies compare forecasting models while keeping the training loss fixed.
We study the infinite-horizon optimal investment and consumption problem in a general class of continuous financial markets, where uncertainty is driven by a continuous non-decreasing stochastic clock representing accumulated variance.
We examine the conditional volatility dynamics of the USD 1Yx10Y forward swap rate using GARCH(1,1), GJR-GARCH(1,1), and a two-regime Markov-switching GARCH (MSGARCH) model.
PAPER REPORTS · 95% one-day-ahead interval coverage, 1500 test days (34.36% of sample): GJR 94.00%, GARCH 93.80%, MSGARCH 93.8% · 1300 test days: GJR 93.62%, GARCH 93.23%, MSGARCH 93.154%
We study affine stochastic Volterra equations on the cone of symmetric positive semidefinite matrices.
Modeling the dynamics of option implied volatility surface (IVS) is crucial for pricing, hedging, and risk-managing option portfolios.
Intraday electricity markets enable participants to adjust energy positions close to delivery, with price forecasts necessary to support trading and the scheduling of flexible electricity resources as well as increasingly responsive consumers.
PAPER REPORTS · Test AQL 10.62 €/MWh, MAE 28.04, RMSE 101.76, R² 0.39, AQCE 2.29%, AQCR 0.00% — averaged over forecast origins…
We examine log-optimal portfolio allocation when the long-run price of an asset follows a power-law trajectory, $P(t)=At^α$, and its instantaneous return variance decays as $σ^2(t)=σ_0^2 t^{-2γ}$.
This paper proposes discrete-time approximations to rough continuous-time models of realized variance (RV). The leading rough models can be viewed as autoregressive processes driven by fractional Gaussian noise.
PAPER REPORTS · 1-day-ahead MSE relative to HAR benchmark, average over 10 ETFs, 2010-01-04 to 2024-12-31 rolling 500-day window, no… · 1-day-ahead QLIKE relative to HAR, same sample: log-RAR 0.7942, log-RHAR 0.7925
The standard Euler discretization schemes for numerical option pricing under stochastic volatility models are known to exhibit high biases and potential unreliability.
This paper develops inference for a Gaussian-nested hypergeometric family of distribution functions.
Variance swaps are a convenient instrument for trading vega and convexity, and a listed contract now trades on Cboe.
Modern economic and financial data are increasingly organized as multiway arrays, with observations indexed simultaneously by geographic regions, industrial sectors, asset categories, and other economic characteristics.
PAPER REPORTS · TF-BEKK constrained global minimum-variance portfolio, 250-day out-of-sample period 2024-04-09 to 2025-04-18, Chinese… · TF-BEKK has the highest cumulative return at the end of the 250-day out-of-sample window (Figure 4) and the highest AV…
Early warning of market turbulence is usually treated as a classification problem, yet a usable system must also produce trustworthy probabilities, stay parsimonious and convert forecasts into defensible positions.
PAPER REPORTS · Optimized policies, mean of the eleven metaheuristics on the untouched holdout (25 Apr 2019-21 Feb 2020, 5 bp per unit… · Best optimized method by mean return (CS), 30 runs: balanced accuracy 0.693 +/- 0.026, AUC 0.763 +/- 0.019, return…
OUR BACKTEST · Sharpe 0.89 · Return +22.5% · Max DD -8.6%
Return models for risk-neutral financial valuation based on skew Brownian motions (SBMs) have been introduced about twenty years ago, and have recently enjoying growing popularity.
This paper proposes an investment strategy through resource allocation into Kalshi Crypto Event Contracts in order to effectively hedge exposure to spot asset volatility.
PAPER REPORTS · Bullish 2024 (Mar-Dec 2024 contract), Strategy C with Kalshi fees: +38.69% return vs BTC +36.23%; Sharpe 1.27 (1.30… · Flat Dec 2025 (Nov-Dec 2025 contract), Strategy C: -3.04% (Table 1) vs BTC -3.58%; Sharpe -0.10 with fees (+0.05…
Normalized implied-volatility coordinates reveal no-arbitrage structure that is less transparent in strike space. This paper centers on a single quantity that gives those coordinates a direct probabilistic interpretation.