Ralph Sueppel

Managing Director of Macrosynergy.
Development of systematic macro trading strategies.

[Ralph Sueppel @macro_synergy]

Paper "Volatility Salience" constructs "a measure capturing the degree to which recent realized volatility deviations stand out from the market benchmark. High volatility salience leads to significantly lower delta-hedged option returns for both calls and puts." https://t.co/EfZRN5K2Uw

[Ralph Sueppel @macro_synergy]

Gold and macro factors
An empirical analysis of the past 30 years reveals that theory-based macro factors have significantly predicted gold futures returns at monthly and quarterly horizons. Related strategies would have generated respectable long-term P&L value with little correlation to major market benchmarks.
https://t.co/eEPWOmy1t8

[Ralph Sueppel @macro_synergy]

"The (Poly)market Price of Weather Risk" proposes "a method to estimate the market price of weather risk from the event probabilities implied by contracts sold on prediction markets... The market price of temperature risk is time-varying and also dependent on the strike: it is positive for high-temperature contracts and negative for low-temperature ones." https://t.co/jjI2PWwkE6

[Ralph Sueppel @macro_synergy]

"The MinervaScore as a Statistical Robustness Grade [for Backtesting]" combines "four established validation quantities: Deflated Sharpe Ratio, Probability of Backtest Overfitting, Superior Predictive Ability, and Minimum Track Record Length, with a regime-stability diagnostic." https://t.co/Umr1kJ582J

[Ralph Sueppel @macro_synergy]

"End-to-end deep learning for portfolio optimization A framework for direct portfolio weight prediction in daily trading": "The proposed framework integrates a convolutional neural network (CNN) for effective feature extraction and noise reduction, alongside a long short-term memory (LSTM) network to capture temporal dependencies." https://t.co/yiZIPq1JmC

[Ralph Sueppel @macro_synergy]

"Rethinking Time-Series Momentum in Equity Portfolios": "The common market momentum signal is systematically more effective than portfolio-specific momentum, suggesting that these portfolios are primarily exposed to a shared market state." https://t.co/NphYJgzAx5

[Ralph Sueppel @macro_synergy]

"Building a Piotroski F-Score Screener in Python": "Piotroski’s original research showed that high scoring value stocks meaningfully outperformed low scoring ones over time. The catch is that actually building a screener for it means pulling multiple years of balance sheet, income statement, and cash flow data for every ticker."
https://t.co/8cui0uTbRs

[Ralph Sueppel @macro_synergy]

"Forecasting Oil-Price Tail Risk with Newspaper Attention": "Oil-news attention... significantly improves out-of-sample forecasts of downside realized volatility for both WTI and Brent... The predictive content comes primarily from the volume of coverage rather than its tone."
https://t.co/EfDjTwvuHB

[Ralph Sueppel @macro_synergy]

Basic concept: "Betting against beta"
Investors who cannot leverage their exposure may overpay for 'high beta' assets. In this case, unconstrained traders can earn a non-standard premium by leveraging low-beta assets and shorting high-beta assets.
Sources:
https://t.co/a86nWIP0wa
https://t.co/55yrNq00eG
https://t.co/lnUYPzAsHC

[Ralph Sueppel @macro_synergy]

"Time-Varying Market Sensitivity to Macro News and Monetary Policy": "FOMC surprises have larger effects on the yield curve when macro-news sensitivity is high... Sensitivity is systematically related to inflation, labor-market deterioration, and the macroeconomic emphasis of Federal Reserve speeches." https://t.co/Y1j7akUMEl

[Ralph Sueppel @macro_synergy]

"Wealth management with macro factors":
"Out- and underperformance of asset classes depends on the macroeconomic environment. Consequently, the systematic, low-frequency adjustment of portfolio weights in response to macro factors can produce material excess returns. It is a practical and effective method to enhance long-term wealth generation."
https://t.co/ynlmroe9WC

[Ralph Sueppel @macro_synergy]

"International Yield Curves and Exchange Rates": "Using neural networks... international yield curves robustly forecast nominal and real exchange rates and excess currency returns out-of-sample for G10 currencies." https://t.co/1k3Gk86tAN

[Ralph Sueppel @macro_synergy]

"Researchers have only recently developed tools to estimate the term structure of equity risk premia and dividend growth expectations... We investigate the impact of monetary policy surprises... Negative surprises are associated with a 25-basis-point increase in the average risk premium [and] lower expected Dividend Growth Rates." https://t.co/abdj32KDyX

[Ralph Sueppel @macro_synergy]

"Generalized Mean Absolute Directional Loss for Machine Learning Trading Models": "Regardless of the selected asset class and the level of model complexity, the proposed [loss] function produces superior results." https://t.co/xrfSqdiF3S

[Ralph Sueppel @macro_synergy]

"Test Everything, Publish Both Results: A Protocol That Cuts Backtest False Positives": "We keep the graveyard [of trading strategy ideas] for the same reason a serious laboratory keeps its failed experiments: it is the record of contact with reality." https://t.co/lyvDo9IIRG

[Ralph Sueppel @macro_synergy]

"Conformal Kelly: Prediction Intervals as the Scale in Fractional Kelly Position Sizing":
"Conformal prediction turns any point forecaster into an interval forecaster... the Kelly criterion turns a belief about a return distribution into the bet size that maximizes expected log wealth." https://t.co/Zr3zUtSil0

[Ralph Sueppel @macro_synergy]

"Drawdown Risk Beyond Brownian Motion":
"The Sharpe ratio is necessary but badly insufficient for judging when a live strategy has crossed from normal pain into genuine trouble... Risk tables should be calibrated to the strategy’s style and, where the data allow, to its own history, reporting skew, tails, clustering and a persistence (Hurst) diagnostic alongside the Sharpe."
https://t.co/Upn9ja5X3K

[Ralph Sueppel @macro_synergy]

"FinSMART [is a] market-aligned reinforcement learning framework for financial sentiment analysis, which directly optimizes sentiment signals using realized market outcomes... [It] significantly outperforms existing state-of-the-art methods in profitability, risk-adjusted performance, and sentiment signal quality." https://t.co/bKCopkhuhO

[Ralph Sueppel @macro_synergy]

"Bond indices and systematic duration management"
presents "methods for adjusting the duration of major countries in global bond indices using point-in-time measures of local economic conditions... Historically, [these methods] would have added meaningful, uncorrelated value to bond index-tracking portfolios."

Research article and Jupyter notebook
https://t.co/g8W9ALogZe

[Ralph Sueppel @macro_synergy]

"Covered Interest Parity: The Long Run Evidence": "Employing a novel daily dataset for 19 advanced-economy currencies over the years 1963-2025, we find that, contrary to the prevailing view, deviations from the covered interest parity condition were both large and frequent."
https://t.co/wCt7Z5rVA2