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We propose a hybrid model of portfolio credit risk where the dynamics of the underlying latent variables is governed by a one factor GARCH process. The distinctive feature of such processes is that the long-term aggregate return distributions can substantially deviate from the asymptotic Gaussian limit for very long horizons. We introduce the notion of correlation surface as a convenient tool for comparing portfolio …
In practice daily volatility of portfolio returns is transformed to longer holding periods by multiplying by the square-root of time which assumes that returns are not serially correlated. Under this assumption this procedure of scaling can also be applied to contributions to volatility of the assets in the portfolio. Close prices are often used to calculate the profit and loss of a portfolio. Trading at exchanges lo…
Empirical correlation matrices estimated from financial return time series are contaminated by statistical noise arising from finite sample size, obscuring genuine interactions among assets. We apply spectral decomposition to separate the empirical correlation matrix into a structured component associated with eigenvalues exceeding the Marchenko-Pastur bounds and a random component representing statistical noise. Usi…
Many empirical studies have discussed market liquidity, which is regarded as a measure of a booming financial market. Further, various indicators for objectively evaluating market liquidity have also been proposed and their merits have been discussed. In recent years, the impact of high-frequency traders (HFTs) on financial markets has been a focal concern, but no studies have systematically discussed their relations…
Price impact of a trade is an important element in pre-trade and post-trade analyses. We introduce a framework to analyze the market price of liquidity risk, which allows us to derive an inhomogeneous Bernoulli ordinary differential equation. We obtain two closed form solutions, one of which reproduces the linear function of the order flow in Kyle (1985) for informed traders. However, when traders are not as asymmetr…
The composition of natural liquidity has been changing over time. An analysis of intraday volumes for the S&P500 constituent stocks illustrates that (i) volume surprises, i.e., deviations from their respective forecasts, are correlated across stocks, and (ii) this correlation increases during the last few hours of the trading session. These observations could be attributed, in part, to the prevalence of portfolio tra…
We give a detailed account of correlations between credit sector/quality and treasury curve factors, using the robust framework of the Barclays POINT Global Risk Model. Consistent with earlier studies, we find a strong negative correlation between sector spreads and rate shifts. However, we also observe that the correlations between spreads and Treasury twists reversed recently, which is likely attributable to the Fe…
Stock prices are observed to be random walks in time despite a strong, long term memory in the signs of trades (buys or sells). Lillo and Farmer have recently suggested that these correlations are compensated by opposite long ranged fluctuations in liquidity, with an otherwise permanent market impact, challenging the scenario proposed in Quantitative Finance 4, 176 (2004), where the impact is *transient*, with a powe…
We study Anderson localization in a one-dimensional disordered system with long-range correlated hopping decaying as $1/r^{a}$ with complex hopping amplitudes that break time-reversal symmetry in a tunable fashion by varying their argument. We find analytically a corelation-induced algebraic localization that is robust to a finite strength of the time-reversal-symmetry-breaking parameter, beyond which all states delo…
We introduce the Historical and Dynamic Volatility Ratios (HVR/DVR) and show that equity and index volatilities are cointegrated at intraday and daily horizons. This allows us to construct a VECM to forecast portfolio volatility by exploiting volatility cointegration. On S&P 500 data, HVR is generally stationary and cointegration with the index is frequent; the VECM implementation yields substantially lower mean abso…
Unlike developed market, some emerging markets are dominated by retail and unprofessional trading. China A share market is a good and fitting example in last 20 years. Meanwhile, lots of research show professional investor in China A share market continuously generate excess return compare with total market index. Specifically, this excess return mostly come from stock selectivity ability instead of market timing. Ho…
Volatility-based trading strategies have attracted a lot of attention in financial markets due to their ability to capture opportunities for profit from market dynamics. In this article, we propose a new volatility-based trading strategy that combines statistical analysis with machine learning techniques to forecast stock markets trend. The method consists of several steps including, data exploration, correlation and…
Understanding stock market instability is a key question in financial management as practitioners seek to forecast breakdowns in asset co-movements which expose portfolios to rapid and devastating collapses in value. The structure of these co-movements can be described as a graph where companies are represented by nodes and edges capture correlations between their price movements. Learning a timely indicator of co-mo…
We develop a theoretical trading conditioning model subject to price volatility and return information in terms of market psychological behavior, based on analytical transaction volume-price probability wave distributions in which we use transaction volume probability to describe price volatility uncertainty and intensity. Applying the model to high frequent data test in China stock market, we have main findings as f…
In the LIBOR era, banks routinely tied revolving credit facilities to credit-sensitive benchmarks. This study assesses the Across-the-Curve Credit Spread Index (AXI) -- a transparent, transaction-based measure of wholesale bank funding costs -- as a complement to SOFR, summarizing its behavior, construction, and loan-pricing implications. AXI aggregates observable unsecured funding transactions across short- and long…
Artificial transaction generation remains an important source of potential market manipulation on cryptocurrency exchanges, as it may distort reported liquidity and reduce market transparency. This study proposes a diagnostic framework for detecting unusual trading patterns based on complexity and statistical-structure measures derived from high-frequency trade-level data. The analysis considers log-returns, trading …
Generating synthetic financial time series that preserve the statistical properties of real market data is essential for stress testing, risk model validation, and scenario design. Existing approaches struggle to simultaneously reproduce heavy-tailed distributions, negligible linear autocorrelation, and persistent volatility clustering. We developed a hybrid hidden Markov framework that discretized excess growth rate…
Using a proprietary dataset of meta-orders and prediction signals, and assuming a quasi-linear impact model, we deconvolve market impact from past correlated trades and a predictable return component to elicit the temporal dependence of the market impact of a single daily meta-order, over a ten day horizon in various equity markets. We find that the impact of single meta-orders is to a first approximation universal a…
Dispersion Trading — Index vol versus single-name vol — a pure play on implied correlation.
Copula Models — Dependence modeling linking marginal distributions — infamous from 2008 structured credit.
Gold Real Yields Correlation — Gold as non-yielding asset inversely sensitive to real rates and USD.
Heston Model — Mean-reverting variance with spot-vol correlation generating smile.
Correlation Trading — Trading implied versus realized correlation in index members.
Implied Correlation Index — Market-implied average correlation among index constituents.
Correlation Breakdown — Diversification failing as correlations spike in crises.
Correlation Hub US (Systems).
Correlation Hub Euro Area (Systems).
Correlation Hub UK (Systems).
Correlation Hub Japan (Systems).
Correlation Hub China (Systems).
Correlation Hub EM Asia (Systems).
Correlation Hub LatAm (Systems).
Correlation Hub CEEMEA (Systems).
Correlation Hub Canada (Systems).
Correlation Hub Australia (Systems).
Correlation Hub Nordics (Systems).
Correlation Hub ASEAN (Systems).
Correlation Hub risk-on (Systems).
Correlation Hub risk-off (Systems).
Correlation Hub tightening (Systems).
Correlation Hub easing (Systems).
Correlation Hub stagflation (Systems).
Correlation Hub reflation (Systems).
Correlation Hub disinflation (Systems).
Correlation Hub liquidity-crisis (Systems).
Correlation Hub carry (Systems).
Correlation Hub recession (Systems).
Correlation Hub desk (Systems).
Correlation Hub portfolio (Systems).
Correlation Hub ops (Systems).
Correlation Hub nightly (Systems).
Correlation Hub realtime (Systems).
Correlation Swap 1M (Derivatives).
Correlation Swap 3M (Derivatives).
Correlation Breakdown — Diversification failing as correlations spike in crises.
Correlation Hub ASEAN (Systems).
Correlation Hub Australia (Systems).
Correlation Hub Canada (Systems).
Correlation Hub carry (Systems).
Correlation Hub CEEMEA (Systems).
Correlation Hub China (Systems).
Correlation Hub desk (Systems).
Correlation Hub disinflation (Systems).
Correlation Hub easing (Systems).
Correlation Hub EM Asia (Systems).
Correlation Hub Euro Area (Systems).
Correlation Hub Japan (Systems).
Correlation Hub LatAm (Systems).
Correlation Hub liquidity-crisis (Systems).
Correlation Hub nightly (Systems).
Correlation Hub Nordics (Systems).
Correlation Hub ops (Systems).
Correlation Hub portfolio (Systems).
Correlation Hub realtime (Systems).
Correlation Hub recession (Systems).
Correlation Hub reflation (Systems).
Correlation Hub risk-off (Systems).
Correlation Hub risk-on (Systems).