Skip to content

2021 Q3 Quarterly Research Archive

Records scoring at least 40 within the primary scope pass rule review and are published without additional manual review. This page does not validate author claims or provide investment advice.

  • Coverage: 2021-07-01 to 2021-09-30
  • Passed rule review: 7
  • Sources: 5

Topic distribution

Domains

  • volatility: 4
  • microstructure: 2
  • hedging exposure risk: 1
  • execution costs: 1
  • lifecycle infrastructure: 1

Methods

  • research methods: 3
  • financial ml: 1

Facets

  • instrument index options: 1

Passed rule review

Deep Learning for Exotic Option Valuation

  • Published: 2021-09-07
  • Source: arXiv Quantitative Finance History
  • Publication status: preprint
  • Original source: Open original source

Why it matters

The study compares classical model calibration with a neural-network volatility-feature approach to address consistency and speed trade-offs in exotic option valuation. (abstract:S1, abstract:S3, abstract:S4, abstract:S6, abstract:S7)

Main author claims

  • They argue that model calibration can lose information in the volatility surface and may produce inconsistency between exotic and plain-vanilla pricing. (abstract:S3)
  • They propose a volatility-feature approach that keeps the model structure while using volatility-surface points as neural-network inputs. (abstract:S4, abstract:S5)
  • The authors report: Experiments are reported to show expected VFA outperformance relative to MCA, with faster valuations once network training is complete. (abstract:S6, abstract:S7)

Data, method, or discussion scope

Comparison of MCA versus VFA in practical volatility-surface settings for exotic option valuation as presented in the abstract experiments. (abstract:S1, abstract:S4, abstract:S6, abstract:S7)

Main limitations

The abstract omits training data details, test instruments, error metrics, and generalization checks across other asset classes. (abstract:S4, abstract:S6, abstract:S7)

One hundred years of rare disaster concerns and commodity prices

  • Published: 2021-08-11
  • Source: Journal of Futures Markets
  • Publication status: peer_reviewed
  • Original source: Open original source

Why it matters

Treating rare disaster concern as news-implied volatility and testing long-horizon return predictability offers an alternative macro-risk channel for commodity futures pricing. (abstract:S1, abstract:S2, abstract:S3, abstract:S4)

Main author claims

  • The authors report: Rare disaster concern is reported to predict index commodity futures returns over the full 1926–2016 sample. (abstract:S1)
  • The authors report: The result reportedly holds after controlling for business-cycle conditions, macro variables, and the VIX. (abstract:S2)
  • They also claim out-of-sample performance and robustness across recession/expansion, contango/backwardation, and inflation-up/down regimes. (abstract:S3, abstract:S4)

Data, method, or discussion scope

Index-commodity-futures returns over 1926–2016, with tests of predictive ability versus rare-disaster concern and controls for cycle/macro/VIX conditions. (abstract:S1, abstract:S2, abstract:S3, abstract:S4)

Main limitations

No details are provided on construction of the rare-disaster variable, estimation windows, or exact in-sample/out-of-sample split design. (abstract:S1, abstract:S2, abstract:S3, abstract:S4)

How Japan’s settlement price methodology impacts option expiry

  • Published: 2021-08-11
  • Source: Optiver Market Insights
  • Publication status: institutional_report
  • Original source: Open original source

Why it matters

The description highlights that settlement methodology can materially affect valuation and proceeds, making it operationally relevant for option expiry outcomes. (description:S1, description:S2, description:S3)

Main author claims

  • The authors report: The material states settlement methodologies are crucial because they affect final valuation and option proceeds. (description:S1)
  • The authors report: Settlement timing and calculation differ materially across products and markets. (description:S2)
  • The authors report: The description says the paper highlights issues with OSE Large Nikkei 225 settlement methodology and proposes improvements. (description:S3)

Data, method, or discussion scope

Scope is confined to the described settlement-price methodology discussion for Large Nikkei 225 options on OSE. (description:S2, description:S3)

Main limitations

No verifiable formulas, error diagnostics, or cross-market comparisons are provided in the supplied text. (description:S1, description:S3)

Directed market makers: another path to internalization?

  • Published: 2021-08-10
  • Source: Optiver Market Insights
  • Publication status: institutional_report
  • Original source: Open original source

Why it matters

The piece raises market-structure concerns by contrasting directed market maker privileges with potential internalization and reduced price-improvement incentives. (description:S1, description:S2)

Main author claims

  • The authors report: Directed market makers receive special privileges such as larger allocations in exchange for heavier quoting obligations. (description:S1)
  • The authors report: The report asks whether the DMM model still makes sense given its role in enabling internalization and discouraging price improvement. (description:S2)

Data, method, or discussion scope

Scope is a market-structure discussion framed by the description; no empirical sample or statistical decomposition is provided in the supplied material. (description:S1, description:S2)

Main limitations

As a description, it does not include verifiable methodology, covered markets, or quantified results. (description:S1, description:S2)

Do economic variables forecast commodity futures volatility?

  • Published: 2021-07-29
  • Source: Journal of Futures Markets
  • Publication status: peer_reviewed
  • Original source: Open original source

Why it matters

The study tests whether supply/demand uncertainty, time-to-maturity, and term-structure slope explain nearby commodity-futures 5-minute realized volatility, linking market-economy signals to short-horizon volatility forecasting and risk use. (abstract:S1, abstract:S2, abstract:S4, abstract:S5)

Main author claims

  • The authors support the uncertainty-resolution and theory-of-storage hypotheses and reject the time-to-maturity hypothesis. (abstract:S2)
  • The authors report: The findings are reported as robust to including autoregressive terms in the baseline model. (abstract:S3)
  • The paper reports mixed in- and out-of-sample forecasting performance for models with these economic variables and tests them in expected shortfall modeling. (abstract:S4, abstract:S5)

Data, method, or discussion scope

The evidence scope is the modeled realized volatility of nearby commodity futures at 5-minute frequency using those economic variables, plus in/out-of-sample forecasting and expected shortfall testing. (abstract:S1, abstract:S2, abstract:S4, abstract:S5)

Main limitations

The abstract provides limited scope details: no sample coverage, commodity segment breakdown, transaction-cost treatment, or parameter settings for the expected shortfall specification. (abstract:S1, abstract:S4, abstract:S5)

Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces

  • Published: 2021-07-22
  • Source: arXiv Quantitative Finance History
  • Publication status: preprint
  • Original source: Open original source

Why it matters

The study applies dynamic functional time-series methods to multi-currency IV-surface forecasting and reports out-of-sample accuracy gains; its stylized strategy does not establish economic gains in live trading. (abstract:S2, abstract:S4, abstract:S5)

Main author claims

  • The authors report: Dynamic functional principal component analysis generally improves out-of-sample forecast accuracy for FX implied volatility surfaces. (abstract:S2)
  • The authors report: The dynamic univariate functional time-series method shows the greatest forecast improvement. (abstract:S3)
  • The authors report: Multiple instances of statistically significant forecast accuracy improvements are found for various currency pairs and maturities, and a stylized trading strategy demonstrates potential economic benefits. (abstract:S4, abstract:S5)

Data, method, or discussion scope

Daily implied volatility surface data for EUR-USD, EUR-GBP, and EUR-JPY across various maturities are used. Out-of-sample forecasting is compared against established benchmarks. A trading strategy assesses economic value, though it is unclear if transaction costs are included. (abstract:S4, abstract:S5)

Main limitations

The abstract does not report the sample period, the names of benchmark models, or details of the trading strategy (including cost assumptions). Economic benefits come from a 'stylized' strategy, which may not reflect real-world execution conditions. The analysis is limited to three major currency pairs, with unknown performance for other pairs or emerging markets. (abstract:S4, abstract:S5)

The Kid who Kaptures Kurtosis with Kris Sidial of Ambrus Group

  • Published: 2021-07-01
  • Source: The Derivative by RCM Alternatives
  • Publication status: unknown
  • Original source: Open original source

Why it matters

The podcast description provides a practitioner entry point into volatility arbitrage, microstructure, and gamma hedging; it is background material, not verifiable strategy or performance evidence. (description:S2, description:S4)

Main author claims

  • The description identifies Kris Sidial as an Ambrus Group co-CIO and frames the firm around unusual outcomes in U.S. equity derivatives. (description:S2)
  • The authors report: The podcast covers topics such as market microstructure, gamma hedging, liquidity cascades, and options books (positions and reading). (description:S4)
  • The authors report: The guest has worked on exotic options desks, at prop firms, and now runs his own hedge fund. (description:S3)

Data, method, or discussion scope

The podcast is a qualitative interview based on the guest's personal experience and opinions, with no systematic data or empirical analysis. The scope covers U.S. equity derivatives markets, but information is presented as anecdotes and viewpoints. (description:S2, description:S4)

Main limitations

Not a research publication; lacks peer review and verifiable evidence. Content may contain promotional material and personal bias. The description provides limited information, and any specific declarations made in the podcast cannot be verified. The disclaimer notes it is for informational purposes only. (description:S9, description:S10, description:S13)