A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
This paper uses SARIMA models to forecast Nifty 50 index.
The study forecasts ETF return direction using machine learning models.
It is well known that traded foreign exchange forwards and cross currency swaps (CCS) cannot be priced applying overnight cash and carry arguments as they imply absence of funding advantage of one currency to the other. This paper proposes a heuristic present value concept for multi-currency pricing and hedging which a…
A leveraged exchange traded fund (LETF) is an exchange traded fund that uses financial derivatives to amplify the price changes of a basket of goods. In this paper, we consider the robust hedging of European options on a LETF, finding model-free bounds on the price of these options. To obtain an upper bound, we establi…
The paper uses clustering and integer programming to optimize stock selection for investment funds.
Investors can enhance their portfolios by strategically using LETFs, especially with dynamic strategies.
Deep learning optimizes portfolio Sharpe ratio without forecasting returns.
Exchange Traded Funds (ETFs) have been gaining increasing popularity in the investment community as is evidenced by the high growth both in the number of ETFs and their net assets since 2000. As ETFs are in nature similar to index mutual funds, in this paper we examined if this growing demand for ETFs can be explained …
Using detailed statistical analyses of the size distribution of a universe of equity exchange-traded funds (ETFs), we discover a discrete hierarchy of sizes, which imprints a log-periodic structure on the probability distribution of ETF sizes that dominates the details of the asymptotic tail. This allows us to propose …
We use the 2014 market history of two high-returning biotechnology exchange-traded funds to illustrate how ex post mean-variance analysis should not be done. Unfortunately, the way it should not be done is the way it generally is done -- to our knowledge.
In mutual fund, an investment adviser gives advice to clients about investing in securities such as stocks, bonds, mutual funds, or exchange traded funds. Some investment advisers manage portfolios of securities. In this paper, we analyze advisor portfolio for each advisor so as to recognize the pattern in each adviser…
Study on CEF discount in Bangladesh, finds size and maturity impact, turnover negative.
Machine learning categorizes mutual funds for better investment strategies.
Study finds recurring patterns in cryptocurrency volatility and liquidity.
Investigate using LETFs to outperform benchmarks, finding them more likely to succeed.
Study finds discrepancies in open interest reporting for Bitcoin perpetual swaps.
Study analyzes risks and opportunities in blockchain currency markets.
This paper explores deep learning for financial trading, integrating sentiment analysis.
Study categorizes mutual funds using natural language processing from unstructured data.
In this article, we consider the small-time asymptotics of options on a \emph{Leveraged Exchange-Traded Fund} (LETF) when the underlying Exchange Traded Fund (ETF) exhibits both local volatility and jumps of either finite or infinite activity. Our main results are closed-form expressions for the leading order terms of …
We review the dynamics of the returns of Leveraged Exchange Traded Funds (LETFs) and propose a new measure of realized volatility: Shortfall from Maximum Convexity. We show that SMC has a more intuitive interpretation and provides more statistical information compared to the traditionally used sample standard deviation…
Study finds IBS useful for predicting ETF price movements.
Complex contagion model explains financial fire sales through continuous asset prices.
Uniswap analyzes liquidity provider risk and impermanent loss.
Machine learning models outperform traditional technical analysis in Bitcoin trading.
Currency carry trade is the investment strategy that involves selling low interest rate currencies in order to purchase higher interest rate currencies, thus profiting from the interest rate differentials. This is a well known financial puzzle to explain, since assuming foreign exchange risk is uninhibited and the mark…
The paper tackles financial market dynamics with new tech-driven data.
We investigate the relative information efficiency of financial markets by measuring the entropy of the time series of high frequency data. Our tool to measure efficiency is the Shannon entropy, applied to 2-symbol and 3-symbol discretisations of the data. Analysing 1-minute and 5-minute price time series of 55 Exchang…
Shorting IG ETFs can hedge bond portfolios during market drawdowns effectively.
Wavelet denoised-ResNet with LightGBM predicts Forex rate of change.
Paper finds funding rates on BitMEX predict Bitcoin inverse swap contracts.
The paper explores perpetual contracts in a financial market without arbitrage.
We study the portfolio problem of maximizing the outperformance probability over a random benchmark through dynamic trading with a fixed initial capital. Under a general incomplete market framework, this stochastic control problem can be formulated as a composite pure hypothesis testing problem. We analyze the connecti…
Quantum optimization for portfolios with risk and diversification constraints.
ETFs with 2x and 3x leverage underperformed the S&P 500 index due to compounding and volatility.
Two pension funds mutually insure against longevity risk.
The paper analyzes how open-end fund sales affect prices and returns.
This paper considers the problem of isolating a small number of exchange traded funds (ETFs) that suffice to capture the fundamental dimensions of variation in U.S. financial markets. First, the data is fit to a vector-valued Bayesian regression model, which is a matrix-variate generalization of the well known stochast…
This thesis applies entropy as a model independent measure to address three research questions concerning financial time series. In the first study we apply transfer entropy to drawdowns and drawups in foreign exchange rates, to study their correlation and cross correlation. When applied to daily and hourly EUR/USD and…
Study on pooled annuity funds and how initial savings affect income stability.
Commodity exchange-traded funds (ETFs) are a significant part of the rapidly growing ETF market. They have become popular in recent years as they provide investors access to a great variety of commodities, ranging from precious metals to building materials, and from oil and gas to agricultural products. In this article…
A classification of companies into sectors of the economy is important for macroeconomic analysis and for investments into the sector-specific financial indices and exchange traded funds (ETFs). Major industrial classification systems and financial indices have historically been based on expert opinion and developed ma…
Reinforcement learning crypto agent achieves high returns on Bitcoin derivatives.
New method clusters financial time series into volatility regimes.
A fractal approach to the long-short portfolio optimization is proposed. The algorithmic system based on the composition of market-neutral spreads into a single entity was considered. The core of the optimization scheme is a fractal walk model of returns, optimizing a risk aversion according to the investment horizon. …
By monitoring the time evolution of the most liquid Futures contracts traded globally as acquired using the Bloomberg API from 03 January 2000 until 15 December 2014 we were able to forecast the S&P 500 index beating the Buy and Hold trading strategy. Our approach is based on convolution computations of 42 of the most …
ETF on CRIX reduces crypto risk and diversifies growth.
Quantum computing tackles non-convex portfolio optimization with cardinality constraints.