Questions tagged [prediction]
The prediction tag has no usage guidance.
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Predict future Implied Volatility Surface with LSV models
From my understanding, Local Stochastic Volatility (LSV) models (such as the Heston-LSV for instance) are ones of the most used diffusion models used for exotic pricing. One of their advantages (by ...
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Predictive Forecast (Close, 14)
I've been following an asset wherein a "R-squared predictive forecast (close, 14)" is posted online each day. On some days, this figure is extremely high, like .92.
Exactly what is the ...
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Boosting models for algo trading
I’m currently working on a xgboost model to predict the price change above or below a given percentage between a candle’s open price and the next candle’s close price. I use a wide range of features, ...
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Neural network time series prediction tool [closed]
What are some of the state of the art time series prediction tool with neural network?
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Predict a company business classification
I am trying to predict whether companies belong to a universe considered by an index provider for a particular thematic index using natural language processing techniques.
In this particular example, ...
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Closed cycle of pairs in pairs trading
Suppose I am trading cointegrated pairs $A_1A_2, A_2A_3, \ldots A_{k-1}A_k, A_kA_1$ and I got a signal to
long $A_1$, short $A_2$;
long $A_2$, short $A_3$;
$\cdots$
long $A_k$, short $A_1$.
How ...
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246
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Principal Portfolios Prediction Matrix estimation (Bryan Kelly)
I have recently discovered Bryan Kelly's paper on Principal Portfolios (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3623983) and had some doubts about the prediction matrix $\Pi$. He defines $\...
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Is there a general approach to predicting future (vanilla) option prices in practice?
I realize that this question may be verging on asking for the proprietary/"secret", so if suggestion of a general approach that doesn't divulge details isn't really possible, I understand.
...
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Testing predictability of a proposed predictor in case of multiple returns
Say I have a T daily observations for the last ten years on a new predictor $x_t$ which I think is a predictor of the expected weekly return on the stock market, $r_{t,t+5} = r_{t+1}+...+r_{t+5}$, ...
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One-day-ahead prediction of S&P500 with Temporal Convolutional Networks
I'm trying to predict the one-day ahead movement of the S&P 500 with Temporal Convolutional Networks 1 to capture some "memory".
I use daily close data with the loss function $\mathrm{...
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Understanding how markets predict BoC's policy interest rate decisions
I read in the newspaper things like,
Interest rate swaps, which are based on market expectations about future rate decisions, are pricing in at least one Bank of Canada rate cut later this year, and ...
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Continuous prediction vs Event-based predictions
When making a high-frequency or mid-frequency prediction on an assets return, what are the advantages and disadvantages of making a continuous prediction vs a prediction that only fires on a ...
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Constructing a mid using signals from another asset
When delta-neutral market making it is important to construct a mid price. Often the mid price of the asset you are trading is influenced by another (correlated) asset. What methodologies would you ...
- 103
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282
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combining forecasts at different time horizons
I define a prediction of return of an asset as the following: at time $t=0$, I use my data and output that I expect the asset to make the following returns (in expected value) in the next n intervals $...
- 121
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Averaging Results Across Regressions due to Periodicity/Overlaps
Given data that arrives at a daily frequency, I aggregated it to a weekly frequency, and estimated an OLS regression on it. Given that there are roughly 5 trading days per week, I can construct 5 ...
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