---
title: Term Premia and Bond Convexity: Sliding Curves, Trading Strategies, and Model Impact
url: https://www.ml-quant.com/papers/ssrn/7687582/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-11-14
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 7687582
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7687582
featured: 2026-11-13
citations: unknown
topic: Derivatives & Volatility
---


# Term Premia and Bond Convexity: Sliding Curves, Trading Strategies, and Model Impact

The paper derives term premia and convexity from rebalancing strategies rather than theory, showing that volatility smile materially affects convexity value and linking the result to empirical swap estimates.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7687582
- Identifier: SSRN 7687582
- Released: 2026-11-13
- First featured: Quant Letter No. 139 (2026-11-13): https://www.ml-quant.com/issues/2026-11-13/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility
- Authors: Vladimir Piterbarg, Wouter Van der Helm

## Related

- [Risk Revisited](https://www.ml-quant.com/papers/ssrn/4825844/): The study identifies recency, cluster, and sign as three factors shaping investors' risk perceptions of a stock, influencing trading volume and future volatility.
- [Rough Volatility: Fact or Artefact?](https://www.ml-quant.com/papers/arxiv/2203.13820/): Fact or Artifact: The study proposes a new method to estimate the roughness of financial asset volatility, attributing observed roughness to microstructure noise.
- [Universal Diffusion Models for Implied Volatility Surfaces: Learning Shared Dynamics Across Stocks](https://www.ml-quant.com/papers/arxiv/2609.22893/): A universal diffusion model trained on pooled data from 50 stocks learns to jointly generate implied volatility surface changes and stock returns, extrapolating well to unseen stocks.
- [Realised Volatility Forecasting: Machine Learning via Financial Word Embedding](https://www.ml-quant.com/papers/arxiv/2108.00480/): A new NLP framework shows that adding news text can improve stock volatility forecasting, particularly during volatile times, when combined with standard models.
- [Analysis of Fundamental and Technical Financial Ford Motor Company with The Arrangements of Implication Black Volatility](https://www.ml-quant.com/papers/ssrn/4482880/): The study shows that Ford Motor Company had its smallest earnings per share payout gap in 2020 compared to previous years.
- [Asymptotic Expansions for High-Frequency Option Data](https://www.ml-quant.com/papers/ssrn/4440168/): A new method for analyzing financial data helps test for sudden volatility changes, with evidence from SP500 options indicating significant variation.
