This paper studies the empirical tracking performance of leveraged ETFs on gold, and their price relationships with gold spot and futures. For tracking the gold spot, we find that our optimized portfolios with short-term gold futures are highly effective in replicating prices. The market-traded gold ETF (GLD) also exhi…
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48 results for “Gold”
This paper provides an innovative perspective on the role of gold as a hedge and safe haven. We use a quantile-on-quantile regression approach to capture the dependence structure between gold returns and changes in uncertainty under different gold market conditions, while considering the nuances of uncertainty levels. …
Gold prices show seasonal behavior, with January and July having opposite returns.
problem Seasonal behavior in gold prices during the turn of the year.
method Statistical analysis and decomposition techniques.
result Gold prices exhibit strong cyclical behavior during the turn-of-the-year period, with January showing the highest return and July showing significant negative returns.
This paper aims to investigate the role of gold as a hedge and/or safe haven against oil price and currency market movements for medium (calm period) and large (extreme movement) fluctuations. In revisiting the role of gold, our study proposes new insights into the literature. First, our empirical design relaxes the as…
Crypto-assets perform better than gold as safe-havens during market crashes.
problem Evaluating safe-haven properties of crypto-assets and gold during the 2020 market crash.
method Comparative analysis of Crypto-assets (Tether, Cardano, Dogecoin, Bitcoin, Ethereum, Litecoin, Ripple) and gold for European indices.
result Tether, Cardano, and Dogecoin exhibited hedging properties similar to gold, while gold was not more efficient as a safe-haven.
The paper analyzes gold, oil, and bitcoin futures volatility and basis.
problem Understanding the volatility and basis of gold, oil, and bitcoin futures.
method Contract-by-contract analysis of spot and futures prices, trading volume, and open interest data.
result Trading volume positively affects volatility in all three assets, while open interest has a possible negative effect.
Gold and currency markets form a unique pair with specific interactions and dynamics. We focus on the efficiency ranking of gold markets with respect to the currency of purchase. By utilizing the Efficiency Index (EI) based on fractal dimension, approximate entropy and long-term memory on a wide portfolio of 142 gold p…
This paper analyzes the direction of the causality between crude oil, gold and stock markets for the largest economy in the world with respect to such markets, the US. To do so, we apply non-linear Granger causality tests. We find a nonlinear causal relationship among the three markets considered, with the causality go…
We give emphasis on the use of chaos-based rigorous nonlinear technique called Visibility Graph Analysis, to study one economic time series - gold price of USA. This method can offer reliable results with fiinite data. This paper reports the result of such an analysis on the times series depicting the fluctuation of go…
Log-Periodic Oscillation Analysis and Possible Burst of the "Gold Bubble" in April - June 2011q-fin.ST
This working paper analyzes the gold price dynamics on the basis of methodology developed by Didier Sornette. Our calculations indicate that this dynamics is close to the one of the "bubbles" studied by Sornette and that the most probable timing of the "burst of the gold bubble" is April - June 2011. The obtained resul…
Achilles predicts Gold vs USD with a profitable trading bot.
problem Accurate and consistent prediction of commodity prices.
method LSTM neural network for minute-by-minute predictions.
result $1623.52 profit in 23 days of testing.
We devise a USDCHF trading strategy using the dynamics of gold as a filter. Our strategy involves modelling both USDCHF and gold using a coupled hidden Markov model (CHMM). The observations will be indicators, RSI and CCI, which will be used as triggers for our trading signals. Upon decoding the model in each iteration…
There are several researches that deal with the behavior of SEs and their relationships with different economical factors. These range from papers dealing with this subject through econometrical procedures to statistical methods known as copula. This article considers the impact of oil and gold price on Tehran Stock Ex…
Efficient implementation of portfolio strategies involving cryptocurrencies and VIX INDEX and Goldq-fin.PM
Investment strategies involving cryptocurrencies and VIX INDEX show positive impact in market performance.
problem Investment strategies involving cryptocurrencies and VIX INDEX.
method Parameter estimation on raw data, comparison of two different portfolios, and analysis of different market conditions.
result VIX INDEX positively impacts the investment portfolio of cryptocurrencies in both standard and downward markets.
This non-linear relationship in the joint time-frequency domain has been studied for the Indian National Stock Exchange (NSE) with the international Gold price and WTI Crude Price being converted from Dollar to Indian National Rupee based on that week's closing exchange rate. Though a good correlation was obtained duri…
Study reduces financial dynamics complexity using PCA for NASDAQ, oil, gold, and USD.
problem Understanding complex financial interactions among multiple assets.
method Time-delay embedding and PCA for dimensionality reduction, followed by linear regression.
result Limited number of principal components capture dominant dynamics of each asset.
Forecast-to-Fill: Benchmark-Neutral Alpha and Billion-Dollar Capacity in Gold Futures (2015-2025)q-fin.TR
Forecast-to-fill strategy generates durable alpha in gold futures.
problem Generating alpha in gold futures using simple state variables.
method Rolling 10-year training, 6-month testing; fractional Kelly sizing; ATR-based exits.
result 43% annualized return, 37% alpha, Sharpe ratio of 2.88.
Conditional generative adversarial networks (cGANs) have gained a considerable attention in recent years due to its class-wise controllability and superior quality for complex generation tasks. We introduce a simple yet effective approach to improving cGANs by measuring the discrepancy between the data distribution and…
Introduces a new stationary GE-process for gold price analysis.
problem Analyzing gold price data with a flexible stationary process.
method Developed a new stationary GE-process with three parameters. Analyzed synthetic and real gold price data.
result Maximum likelihood estimators can be obtained for the unknown parameters.
PPI++ outperforms gold-standard labels only if pseudo-labels are highly correlated.
problem Optimizing statistical estimation using noisy pseudo-labels.
method Exact finite-sample analysis of PPI++ on mean estimation problem.
result PPI++ has provably worse estimation error than gold-standard labels alone in some settings.
Meta-Router: Bridging Gold-standard and Preference-based Evaluations in Large Language Model Routingcs.LG
Meta-Router optimizes LLM selection using gold-standard and preference-based data.
problem Training a high-quality LLM router with combined data sources is challenging due to bias and scarcity.
method Developed an integrative causal router training framework to correct bias and improve routing accuracy.
result Our approach delivers more accurate routing and improves the trade-off between cost and quality.
Bi-LSTM with attention predicts gold and bitcoin prices accurately.
problem Predicting prices of gold and bitcoin in financial derivatives markets.
method Bidirectional LSTM neural network with attention mechanism, feature engineering, two-layer deep learning.
result Achieved 71.94% and 73.03% accuracy for bitcoin and gold respectively.
We demonstrate that the tail dependence should always be taken into account as a proxy for systematic risk of loss for investments. We provide the clear statistical evidence of that the structure of investment portfolios on a regulated market should be adjusted to the price of gold. Our finding suggests that the active…
Our study proposes a new currency system to protect wealth from over-issued fiat and stablecoins.
problem The over-issuance of fiat and stablecoins undermines the stability of currency purchasing power.
method We introduce a parallel monetary system based on redeemable self-decaying money (RSDM) to provide a stable currency alternative.
result A parallel monetary system including RSDM, domestic fiat, and major reserve currencies can safeguard wealth and prevent the reverse Gresham law.
Gold, Oil, and Stocksq-fin.ST
We employ a wavelet approach and conduct a time-frequency analysis of dynamic correlations between pairs of key traded assets (gold, oil, and stocks) covering the period from 1987 to 2012. The analysis is performed on both intra-day and daily data. We show that heterogeneity in correlations across a number of investmen…
Long-range correlation and fluctuation in the gold market time series of world's two leading gold consuming countries, namely China and India, are studied. For both the market series during the period 1985-2013 we observe a long-range persistence of memory in the sequences of maxima (minima) of returns in successive ti…
Unified framework for learning with indirect supervision signals.
problem Learning from indirect supervision signals when gold labels are missing or costly.
method Developed a unified theoretical framework for multi-class classification with variable supervision.
result Introduced the concept of separation to characterize learnability and generalization bounds.
Improved MF-DFA model analyzes precious metals market efficiency and multifractality.
problem Analyze price fluctuations in precious metals market.
method Proposed Bi-OSW-MF-DFA method compared to MF-DFA.
result Bi-OSW-MF-DFA method shows better efficiency in precious metals market analysis.
The Impact of Bitcoin ETF Approval on Bitcoin's Hedging Properties Against Traditional Assetsq-fin.GN
ETF approval boosts Bitcoin's correlation with equities, stabilizes with gold, and maintains negative correlation with fiat currencies.
problem Impact of Bitcoin ETF approval on Bitcoin's relationships with traditional assets.
method Rolling correlation analysis, Chow tests, and DCC-GARCH models.
result Bitcoin's correlation with equities increased significantly post-ETF approval, while its relationship with gold stabilized and remained negatively correlated with fiat currencies.
Bitcoin Gold, Litecoin Silver:An Introduction to Cryptocurrency's Valuation and Trading Strategycs.CE
This study compares Bitcoin and Litecoin using cryptocurrency metrics and trading strategies.
problem Valuation and trading strategies for cryptocurrencies.
method Metrics like UTXO, STXO, WAL, CDD, and trading strategies based on PU ratio.
result Bitcoin's superior store-of-value proposition compared to Litecoin validated.
The multifractal detrended fluctuation analysis technique is employed to analyze the time series of gold consumer price index (CPI) and the market trend of three world's highest gold consuming countries, namely China, India and Turkey for the period: 1993-July 2013. Various multifractal variables, such as the generaliz…
ChatGPT improves financial reasoning, overcoming biases in gold investment.
problem Improving financial reasoning and overcoming biases in investment decisions.
method Applied advanced prompt engineering and semantic news information to enhance LLMs' performance.
result ChatGPT with CoT prompt provides more explainable predictions and higher investment returns.
The receiver operating characteristic (ROC) curve is a very useful tool for analyzing the diagnostic/classification power of instruments/classification schemes as long as a binary-scale gold standard is available. When the gold standard is continuous and there is no confirmative threshold, ROC curve becomes less useful…
Study of the forecasting models using large scale microblog discussions and the search behavior data can provide a good insight for better understanding the market movements. In this work we collected a dataset of 2 million tweets and search volume index (SVI from Google) for a period of June 2010 to September 2011. We…
This paper clarifies Bitcoin's volatility and predictability across daily, weekly, and monthly scales.
problem Clarify Bitcoin's volatility and predictability across different time scales.
method Using daily, weekly, and monthly closing prices and log-returns data, analyze volatility and predictability.
result Bitcoin exhibits high volatility and high predictability, with different behaviors at different time scales.
Efficiently evaluate generative models at the prompt level using tensor factorization.
problem Fine-grained evaluations of generative models are costly and often misaligned with human judgment.
method Tensor factorization model that merges cheap autorater data with a small set of human gold-standard labels.
result The method provides accurate and tight confidence intervals for model performance.
New method improves statistical inference using machine learning-imputed data.
problem Improving statistical inference with imputed data from machine learning.
method Two-phase sampling approach for Z-estimation with ML-imputed outcomes.
result Guaranteed efficiency matching or exceeding classical inference, regardless of prediction quality.
Financial ``Anti-Bubbles'': Log-Periodicity in Gold and Nikkei collapsescond-mat.stat-mech
We propose that imitation between traders and their herding behaviour not only lead to speculative bubbles with accelerating over-valuations of financial markets possibly followed by crashes, but also to ``anti-bubbles'' with decelerating market devaluations following all-time highs. For this, we propose a simple marke…
We propose a mathematical procedure for finding informed traders in ultra-high frequency trading. We wrote it as Vector ARMA and found condition of its stationarity. For the price exposure complied with ARMA(1,2) we proved that underlying asset price difference can be derived as ARMA(1,1) process. For validation of the…
Study characterizes and mitigates imbalances in neurosymbolic learning.
problem Characterizing and mitigating class-specific risks in neural classifiers.
method Theoretical analysis and practical techniques including estimating marginal gold labels and mitigating imbalances at training and testing time.
result Learning imbalances can be greatly impacted by the symbolic component σ, unlike in supervised and weakly supervised learning.
Study compares Bitcoin, gold, and gas price complexity using multifractal and multiscale entropy methods.
problem Quantifying complexity of financial time series for market analysis.
method Employed MF-DFA and RCMSE to analyze Bitcoin, GBP/USD, gold, and natural gas price log-return time series.
result Bitcoin shows higher complexity compared to other markets, linked to higher nonlinear correlations.
This study examines whether tokenized assets improve liquidity and finds significant differences across categories.
problem Improving liquidity for real-world assets through tokenization.
method Examined tokenized real-world assets using Ethereum-based data, measuring liquidity through turnover, active addresses, and active-month indicator.
result Gold-backed tokens show more persistent on-chain activity than Treasury and private-credit-related products, but asset value alone does not reliably predict liquidity.
Bitcoin fails to prove safe haven status during pandemic.
problem Determining if Bitcoin is a reliable safe haven asset during crises.
method Quantile correlations of Bitcoin with S&P500, VIX, and gold.
result Gold is a better safe haven during crises, not Bitcoin.
The Second Wave of the Global Crisis? A Log-Periodic Oscillation Analysis of Commodity Price Seriesq-fin.ST
This article continues our analysis of the gold price dynamics that was published in December 2010 (abs/1012.4118) and forecasted the possibility of the "burst of the gold bubble" in April - June 2011. Our recent analysis suggests the possibility of one more substantial fluctuation before the final collapse in July 201…
In semantic parsing for question-answering, it is often too expensive to collect gold parses or even gold answers as supervision signals. We propose to convert model outputs into a set of human-understandable statements which allow non-expert users to act as proofreaders, providing error markings as learning signals to…
New Lie algebras from knot homology.
problem Defining Lie algebras from knot homology.
method Using group homology, analogous to Goldman Lie algebra.
result Relations among new Lie algebras discussed.
Objective: To evaluate unsupervised clustering methods for identifying individual-level behavioral-clinical phenotypes that relate personal biomarkers and behavioral traits in type 2 diabetes (T2DM) self-monitoring data. Materials and Methods: We used hierarchical clustering (HC) to identify groups of meals with simila…
In many machine learning scenarios, supervision by gold labels is not available and consequently neural models cannot be trained directly by maximum likelihood estimation (MLE). In a weak supervision scenario, metric-augmented objectives can be employed to assign feedback to model outputs, which can be used to extract …