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.
16,925 papers screened · 589 on the radar
The factor HJM stochastic volatility model introduced by Sepp and Rakhmonov (2025) obtains tractable swaption pricing by freezing the nonlinear swap-rate loading along a deterministic expected-state path.
This paper studies European option pricing in a regime-switching Heston-Hull-White framework.
PAPER REPORTS · In-sample (train, 2 Jan-6 Aug 2024, 8,286 obs) DL-RS-HHW pricing error: RMSE 0.0072, MAE 0.0050 (option prices in yuan;… · Out-of-sample (test, 7 Aug-30 Sep 2024, 1,234 obs) DL-RS-HHW pricing error: RMSE 0.0179, MAE 0.0097
In this paper, we study causal non-causal state space models to model time series characterised by a local explosive increase followed by a sharp decrease such as stock prices.
In financial markets, a sequential policy that reacts systematically to price movements may become predictable to other market participants.
PAPER REPORTS · Exposure-matched within-stock timing alpha, principal 10-minute Qwen3.5 price text: -45.7 bps per stock-day, 95% CI… · Chart-only 10m: -29.9 bps, CI [-33.7,-26.2], 14,937 stock-days; multimodal 10m: -48.9 bps, CI [-52.7,-45.0], 14,438…
Abstract Conventional financial market forecasting models are challenged by the non-stationarity, the existence of regime changes, the presence of structural breaks, and the phenomena of volatility clustering in financial markets.
PAPER REPORTS · Directional accuracy 87.5% ± 2.1, NIFTY-50 daily, 2010-2025, walk-forward validation, no transaction cost assumption… · MSE 0.012 ± 0.003 (normalized), RMSE 0.110 ± 0.014 (121.8 index points), MAE 0.084 ± 0.011 (93.1 index points), MAPE…
Haug and Haug extend the Margrabe exchange option by adding knock-in and knock-out provisions written on the ratio of two asset prices. This paper applies and develops their framework for stock-for-stock takeover bids with collars.
Large language models (LLMs) are increasingly used to discover trading strategies, and much of the resulting literature shares a methodological weakness: many candidate strategies are generated, the best is reported, and neither look-ahead bias nor the…
PAPER REPORTS · Best gpt-4.1 discovery (E3, RSI x volume, 453-stock universe): design Sharpe 1.69 (2017-2021), evaluation Sharpe 0.18… · Best claude-sonnet-5 discovery: design Sharpe 0.44 (2017-2021), evaluation Sharpe -0.33 / -29% (2022-2025), DSR 0.18,…
OUR BACKTEST · Sharpe -0.10 · Return -10.8% · Max DD -47.8%
Bitcoin inverse options, traded on the Deribit exchange and settled in the underlying cryptocurrency rather than in fiat currency, combine extreme and genuinely rough volatility dynamics with a non-linear, currency-dependent payoff structure.
We study exponential-utility maximization for high-frequency trading in a discretized fractional Brownian motion model. Using spectral methods for stationary Gaussian sequences, we derive the asymptotic growth rate of the optimal certainty equivalent.
Abstract House flipping has been increasingly popular in Poland since the mid-2010s yet it’s economic nature remains unexplored. This study investigates the problem of the primary source of profits of flippers – value creation generated by improvements (e.g.
PAPER REPORTS · Mean profit of all identified flips: 36.45% (profit relative to purchase price), 14 Polish cities, 2005-2023; no… · Method I sample overall average profitability 39.82% (text also states 39.92%); unimproved flips 32.82%; improved flips…
This paper develops a unified framework for assessing systemic risk and identifying contagion channels in the global banking system using a Temporal Heterogeneous Multiplex Graph Neural Network.
PAPER REPORTS · MSE 0.0309 on one-quarter-ahead change in log(1+CDS), out-of-sample, N=336 bank-quarter forecasts (sample 1998-2025,… · MAE 0.1342, out-of-sample
Algorithmic trading now represents a market exceeding $20 billion, where even marginal gains in signal robustness can translate into economically significant returns.
PAPER REPORTS · Hybrid ensemble, OOS 2025 (252 trading days), 2.2bp per trade per leg: total return 51.26%, Sharpe 2.44, Sortino 5.35,… · Hybrid ensemble, OOS 2025: annualised CAPM alpha 0.423 (p = 0.011), beta 0.048, Probabilistic Sharpe Ratio 0.960
OUR BACKTEST · Sharpe 0.75 · Return +696.5% · Max DD -365.1%
We model equity markets using geometric Brownian particles entering and exiting at rank-dependent intensities.
PAPER REPORTS · p=0 (equally weighted) diversity-weighted portfolio capitalization growth: +3.4% per year above the front speed,… · p=1 (market) portfolio: -0.5% per year relative to the front, 1975-2024, frictionless
OUR BACKTEST · Sharpe 0.63 · Return +66.6% · Max DD -37.1%
We report a market in which a positive return is visible in prices yet cannot be realized by a fixed trading policy, and we measure why.
Abstract The emergence of cryptocurrencies has presented investors with novel portfolio diversification opportunities.
PAPER REPORTS · Unconstrained mean-CVaR with crypto: mean monthly return 2.63%, mean monthly CVaR 1.15%, mean monthly risk-return ratio… · Unconstrained without crypto: mean monthly return 0.46%, CVaR 0.42%, risk-return ratio 1.09%
Abstract Precious metals historically have been adopted as an effective hedging instrument by investors due to their price dynamics shaped in line with economic and financial risks.
Abstract High-dimensional multivariate normal (MVN) integration is a computational bottleneck in many statistical applications, particularly in finance and econometrics.
Coupled feedback networks are often monitored channel by channel even though cross-channel paths alter both stability margins and transmitted disturbances.
PAPER REPORTS · Detection power 1.00 with false-alarm rate 0.12 on zero-coupling entries under independent regime-switching gains (n =… · Detection power 1.00, false-alarm rate 0.22, off-diagonal RMSE 0.28 under correlated staircase gains (same design)
We develop a PDE-based methodology for pricing and hedging European contingent claims in general one-dimensional diffusion markets characterized solely by their scale function and speed measure, possibly without a classical SDE representation, and with…
PAPER REPORTS · Bachelier (premium 2.0), N_MC=2000, N^space_FD=4000, T=10, no transaction costs: MTE* −0.002 ± 0.008 and StDTE* 0.192 ±… · Skew-Sticky 1 (premium 0.271, κ₋₁=0.3, κ₁=0.7, ρ=1, r=0.2, ELMM exists): MTE* 0.058 ± 0.022 and StDTE* 0.506 ± 0.024 at…
Lead-lag relationships are widely used in financial time series, and many clustering algorithms based on them have been developed. The traditional DTW-KMedoids algorithm performs well both on the synthetic dataset and the real financial dataset.
PAPER REPORTS · Sharpe 0.866, annual return 6.21%, annual volatility 7.17%, max drawdown -63.908, hit rate 0.520, profit-loss ratio… · Sharpe 0.808 / 0.790 (KShape mod / med), lead strategy, 679 assets, same period; drawdowns -67.604 / -69.418
OUR BACKTEST · Sharpe 0.39 · Return +27.5% · Max DD -39.3%
This paper develops the first end-to-end application of cross-sectional learning-to-rank to the S&P 500 weekly options (SPXW) zero-day-to-expiration surface, integrated with margin-aware position sizing, an abstention rule driven by model uncertainty, and a…
PAPER REPORTS · Out-of-time 2025 annualized Sharpe 4.308 to 5.761 across seven sizing methods, net of Reg-T margin, tiered IBKR fees,… · Headline Edge Allocation OOT 2025: Sharpe 5.7612, Sortino 7.0291, annualized return 10.48% (excess of risk-free),…
Backtests of trading strategies are often selected after many parameter trials. A strong historical result can therefore reflect search luck rather than a persistent signal.
PAPER REPORTS · Genuine-edge discrimination AUROC 0.9890 in synthetic ground truth at headline difficulty (n = 2000, T = 1260 daily… · OOS-survival (Sharpe_OOS > 0) AUROC 0.863 and Spearman 0.611 vs realized OOS Sharpe, same synthetic headline cell
We show that the key optimization results of the classical Markowitz portfolio selection theory, originally formulated for variance as the risk measure, remain available in explicit closed form under a broader class of strictly convex quadratic risk measures.
OUR BACKTEST · Sharpe 0.50 · Return +143.8% · Max DD -75.0%
This work complements our previous paper, which studies borrower-side strategies in decentralized lending markets, by focusing on lender-side capital allocation.
PAPER REPORTS · core-inspired strategy: 5.5% APY, $100k budget, Morpho USDC markets on Ethereum, Jan 1 2026 - Apr 1 2026, daily… · prime-inspired strategy: 3.3% APY, $100k budget, same period and cost assumption
We study equilibria in a closed, fee-free constant-function market maker (CFMM) economy with two assets and two traders.
In this paper we propose a new formulation of the Bayesian Filter as used in the discrete-time Markov-Switching-Multifractal (MSM) model of volatility based on existing permutation symmetry within the likelihood structure.
OUR BACKTEST · Sharpe 0.90 · Return +54.5% · Max DD -20.2%
KellyBoost is a single multi-output XGBoost model whose softmax output is the portfolio: with y the vector of per-asset holding-period returns, the training loss is - log(1 + w y), the negative log growth rate, so the fitted model is the growth-optimal…
PAPER REPORTS · KellyBoost (searched, gross of costs), 2013-01 to 2026-07, 163 monthly decisions: mean log growth 0.47 (x100 per 20-day… · KellyBoost hand-built feature pipeline, same period: logG 0.39, annualized return 5.7%, vol 22.9%, Sharpe 0.28, max DD…
Option prices are prices of insurance, so the risk-neutral probabilities they imply overstate physical crash risk. A power utility pricing kernel undoes the premium.
Tick-level trade-and-quote data for the Tokyo Stock Exchange is distributed through the Nikkei NEEDS service as thousands of zipped CSV archives spanning four data types with era-dependent schemas and Japanese-language layouts.
Understanding the propagation of extreme events is important in many economic and environmental applications, yet most econometric methods for causal inference focus on average effects rather than tail behavior.
Large language models (LLMs) are increasingly used in investment decision-making, yet prior work shows that they exhibit systematic, model-specific investment preferences.
PAPER REPORTS · Weekly rebalanced equal-weight long-only top-100 portfolio from Qwen3-8B scores, 427 S&P 500 stocks, 29 signal weeks /… · Realized Sharpe of the top-100 portfolios is shown only graphically (Figure 5c, axis range roughly 2–4); no point…
OUR BACKTEST · Sharpe 0.52 · Return +57.3% · Max DD -40.6%
Implied volatility surfaces summarise the option market and are central to many financial applications.
PAPER REPORTS · Surface point-forecast RMSE aggregated over 30 horizons: 0.01262 vs persistence 0.01343, +6.09% gain; MAE gain +3.45%;… · h=1: RMSE 0.00619 vs persistence 0.00535 (-15.72%); MAE -34.49%
OUR BACKTEST · Sharpe -0.00 · Return -1.0% · Max DD -329.1%
The stability of markets hosting leveraged exchange-traded products is governed not by any single product's loop gain but by the spectral radius of a loop-gain matrix, and scalar per-product monitoring underestimates system feedback by construction.
A companion paper \cite{ItkinDF2026} introduced the Diagonal Frog (DF) positivity-preserving schemes for anisotropic Fokker--Planck equations, advancing each directional substep by a Krylov-computed matrix exponential, which dominates the cost.
W-shaped smiles appear in near-expiry options around binary events such as earnings, and have been associated with bimodal risk-neutral densities. The three-parameter eSSVI slice cannot produce them.
At 15-minute horizons, directional mean reversion is far stronger and more pervasive in cryptocurrency markets than in US equities: scored under one matched, strictly out-of-sample protocol, 90% of 183 Binance pairs carry significant directional reversal…
PAPER REPORTS · Gross edge per trade peaks near 1.3 bp of notional (BTC/ETH, 15m, 2025-01 to 2026-02) against a 5 bp cheapest maker… · Directional accuracy rises monotonically with confidence threshold, clearing 56% on the most confident bars (BTC/ETH);…
We study discrete-time asset pricing with bid-ask spreads and model uncertainty. The family of probability measures enters the no-arbitrage condition through the union of its supports.
Basket options are difficult to value under correlated lognormal dynamics because weighted sums and differences of lognormal variables have no tractable distribution.
Deep hedging is a data-driven approach to learn hedging strategies. It relies on synthetic price paths generator, as real market data is often limited for training.
OUR BACKTEST · Sharpe 1.78 · Return +5.9% · Max DD -0.6%
Abstract A key puzzle in finance is why algorithmic traders with advanced neural models sometimes fail to beat simple traditional strategies, while in other cases they clearly outperform them.
PAPER REPORTS · Cluster 0 (most efficient), test 2025-2026, net of 0.1% one-way costs: DDPG annualised return 34.72%, cumulative… · Cluster 0 best classical: HRP Sharpe 1.591, Calmar 2.3562, max drawdown -13.07%, annualised return 30.80%
OUR BACKTEST · Sharpe 0.78 · Return +25.3% · Max DD -11.7%
The Marketron model of \cite{HalperinItkin2025Mark} and its option pricing extension in \cite{HalperinItkinMarketron2} suffer from structural non-identifiability: an eighteen-parameter space traps solvers in suboptimal local minima and renders economic…
Abstract Market timing models aim to anticipate short-term market movements according to a given source of information. Such information could be extracted from an analysis of history or a forecast of the future.
PAPER REPORTS · S&P500 timing, 2018: index -6.7% annualized; Strat1-L 3.8%, Strat1-LS 14.3%, Strat2-L 0.8%, Strat2-LS 8.2% (no… · S&P500 timing, 2023: index 21.6%; Strat1-L 21.9%, Strat1-LS 22.1%, Strat2-L 25.5%, Strat2-LS 29.4% (no transaction…
OUR BACKTEST · Sharpe 0.61 · Return +49.0% · Max DD -31.2%
This study evaluates the return performance and risk characteristics of selected companies suitable for mutual-fund and equity investment analysis over the period 2021–22 to 2025–26.
Abstract We study the distributional and tail-risk properties of Bitcoin and the major cryptocurrencies using daily returns from June 2014 to May 2026.
Costly LLM features matter only if calibration lets them affect the forecast. We document a failure of this link in a next-day risk study of two broad-market funds. Full-history scoring preceded the 2022 calibration.
PAPER REPORTS · Prespecified LLM importance feature: zero improvement, 95% interval [0,0], on all four endpoints (SPY/VIX binary and… · Signed LLM repair, SPY/VIX continuous variance: improvement -0.007452, 95% interval [-0.015888, -0.001066], Bonferroni…
We study continuous-time dynamic portfolio optimization under a Conditional Value-at-Risk (CVaR) constraint on the investor's terminal loss.
PAPER REPORTS · Complete market, binding c = -0.94, T = 1 simulated: E[W_T] = 1.0242, CVaR_0.95(-W_T) = -0.9406, average exposure… · Complete market, nonbinding c = -0.86, T = 1 simulated: E[W_T] = 1.0322, CVaR_0.95(-W_T) = -0.8671, average exposure…
OUR BACKTEST · Sharpe 0.75 · Return +55.2% · Max DD -26.8%
Hedge ratios, factor models and diversified portfolios all rest on an estimate of which firms move together.
PAPER REPORTS · Variance-harvest attribution (selling variance at VIX-squared against the paper's 12m equal-weighted realized leg, July… · Risk by REC quartile over the same 329 months: probability of loss 0.29, 0.21, 0.26, 0.15; mean loss given loss…
OUR BACKTEST · Sharpe 0.73 · Return +68.2% · Max DD -36.5%
We introduce Deep-MKV-TS, a path-dependent McKean-Vlasov framework for financial scenario generation. The stochastic dynamics are chosen by matching selected path and volatility features of generated scenarios to those observed in the data.
PAPER REPORTS · Frozen ES drawdown-risk decision, 123 held-out sessions (January-June 2026): Deep-MKV-TS average exposure 1.99 +/- 0.06… · Conditional-forecast CRPS (x1000, lower better) on the 123-session chronological held-out test, four-seed mean +/- sd:…
Automated market makers (AMMs) are a cornerstone of decentralised finance (DeFi). Constant product markets with concentrated liquidity, such as UniswapV3, are now a well-established design.
PAPER REPORTS · PPO_narrow, risk-neutral, sigma=0.01, g=2: mean PnL 49.91 +/- 0.38 USDC, 5% CVaR 9.15 +/- 0.65, over 1000 evaluation… · PPO, risk-neutral, sigma=0.01, g=2: mean PnL 42.31 +/- 0.97 USDC, 5% CVaR 6.08 +/- 0.97
PAPER REPORTS · Minimum Variance Portfolio (MVP), 2019-2025 daily, no transaction costs stated: mean daily return 0.0005519, daily… · Minimum Correlation Portfolio (MCP): mean daily return 0.0007516, std dev 0.0014739, Sharpe (std dev) 0.5099, Sharpe…
OUR BACKTEST · Sharpe 0.21 · Return +11.2% · Max DD -24.8%