Questions tagged [time-series]
A temporal sequence of events measured at discrete points in time.
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Finding an invariant/stationary quantity in prediction markets?
I am looking at trade data for specific outcome of an event on a prediction market (Kalshi, but this could apply to others) and trying to model market microstructure effects such as inferring mid ...
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Process for Removing Error/Incorrect Cryptocurrency Trades
I have many time series of cryptocurrency pair trade data from Kraken (available for batch download here) with some that are very long and others that are very short.
I am attempting to build a basic ...
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Is GARCH assumption on constant drift wrong in log space?
GARCH assumes constant drift $\mu$ - this imply $E[e^r]$ won't be constant and jump wildly. And it contradicts the reality, for stock prices $E[S_{t}/S_{t-1}]=E[e^r]$ doesn't jump with each time step.
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Extracting seasonal factor of CPI from BLS
I want to extract the seasonal factor to get the seasonal adjustments of each CPI fixing in order to create a seasonally-adjusted CPI series.
The BLS publishes the seasonal-factor on their website at ...
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Kolmogorov Smirnov test on derivatives market data
If I want to test market data( say volatility or liquidity spreads) for swaptions in a particular currency (eg. USD) for 2 different periods of time and ascertain whether their distribution is more or ...
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Does Computing Log Returns as $\log(x_t / x_{t-1})$ Introduce Information Leakage in Time Series Forecasting?
I have tick-level data for a single trading day of a specific contract and aim to conduct time series analysis on it. The mid-price at each tick is computed as $MidPrice=×ばつ(Ask_1 +Bid_1)$. The data ...
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How does Ang et al. (2006) aggregate daily‐frequency FVIX returns into a monthly FVIX factor?
I’m trying to replicate Ang et al. (2006) "The Cross‐Section of Volatility and Expected Returns" where they construct a daily‐frequency volatility‐mimicking factor FVIX via
$\Delta VIX_t = c + b'X_t +...
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How can I robustly detect dynamic support and resistance levels programmatically in Python?
I am working on a Python project to programmatically detect dynamic support and resistance levels in historical price data, particularly for forex instruments such as EUR/USD. My primary goal is to ...
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Metric for volatility time series similarity - European swaptions
I'm trying to estimate the volatility surface of illiquid swaptions (say CHF) given hourly data (atm vol, skew, for different strikes) of other liquid swaptions (EUR, USD, etc.). Having the underlying ...
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Generating returns from another variable; is this approach sound?
Assume I have some financial return time series for every year, $y_{1y}, y_{2y}, y_{3y},...$.
I also have a financial return time series for every month, $x_{1m}, x_{2m}, ...$
We can of course ...
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Size of blocks in Block Bootstrapping of returns
I am working on long term portfolio allocations. With larger investment horizon like 5-10 years, 20 years of data that I have is not enough. So I decided to do some bootstrapping to generate some ...
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Python implementation of the BNS (Barndorff-Nielsen & Shephard) jump test
Is there a reliable implementation in python of the BNS jump test available?
Barndorff-Nielsen & Shephard (2006) "Econometrics of Testing for Jumps in Financial Economics Using Bipower ...
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What is the precise meaning of signal and noise in finance
A lot of people working in the finance industry are saying that what makes finance hard is that the signal to noise ratio (SNR) is extremely low.
I don't get what is precisely meant by that. How are ...
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How does clustering affect volatility and correlations differently?
In Betting Against Beta - Frazzini & Pedersen (2014, JFE), the authors state that correlations appear to move more slowly than volatilities, which implies that the clustering phenomenon affects ...
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Estimating asset correlation coefficient using CDS data and default probability
I have a CDS dataset with several instruments belonging to different sectors, par mid spread values and probability of default (recorded daily 2009-2023).
I want to take all the firms within one ...