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2answers
94 views

Extracting Signal from Noisy Data

Consider a scenario in which Y_t represents the % change in price and we want to use X_t to predict Y_t. We assume that X_t is information we get before Y_t is revealed. Suppose that in reality Y_t ...
4
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2answers
114 views

Is there a relation between these two forecasting/estimation approaches?

When learning econometrics I have usually seen stuff from the following perspective: Assume $Y_t = f(X_t) + e_t$, where f is some function of $X_t$ (typically linear). For example, assume $Y_t = X_t ...
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1answer
25 views

Diebold-Mariano test

I am trying to use the Diebold-Mariano test but it doesnt work for some reason. Here is my code: dm.test(maegarch14,maeegarch14,h=126) where ...
0
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1answer
42 views

Constant decreasing volatility, GARCH forecasting

I am trying to forecast the volatility using GARCH modelling in R. I fit an ARMA(1,1)-GARCH(1,1) model, but my sigma predictions are constantly decreasing. Anybody know why? ...
0
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1answer
54 views

Forecasting using GARCH in R

I am using the predict and ugarchforecast functions in R. When I fit my models and try to forecast, I get either only increasing or decreasing values for sigma, does anyone know why? Thank you ...
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0answers
74 views

GARCH modelling and forecasting

I have a few questions regarding GARCH modelling and forecasting and it would be great if someone could help me. I am modelling the log return of oil spot prices using various GARCH models: GARCH, ...
4
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1answer
214 views

Moving window forecasting in Python

I am looking to create some code that will out-of-sample forecast the HAR-RV model. The model itself is formulated as the following, and the betas are estimated through HAC-OLS or Newey-West. ...
1
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1answer
152 views

Machine learning to build top 3 price scenarios over n days

I have a time series of closing prices for a given stock. I would like to formulate possible future scenarios for the price. My intention is not to use these "likely" scenarios to take any position. ...
0
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1answer
89 views

How to forecast bond price with time series

I have the goal of being able to develop a model that can forecast the future prices of european government bond (or other private bonds), particularly from the historical prices and returns of the ...
0
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1answer
110 views

How to fit a SARIMA + GARCH in R?

I'd like to fit a non stationary time series using a SARIMA + GARCH model. I have not found any package that allow me to fit this model. I'm using rugarch: model=ugarchspec( variance.model = ...
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2answers
138 views

How to write a home task report which is part of the interview process for a quant position in a trading firm

I recently appeared in an interview for a quant research post in a trading company. As part of the interview, I was given a home-task to solve in a week. The inerviewer gave me a dataset consisting of ...
0
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1answer
58 views

How can I forecast future correlation?

There are some standard models for forecasting volatility (e.g., GARCH) and for forecasting returns (e.g., factor models). What kind of standard models exist for forecasting future correlation between ...
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0answers
16 views

Non-overlapping ranges of HCNN' observables and of state transition function

In the artcicle Forecasting and Trading the High-Low Range of Stocks and ETFs with Neural Networks HCNN is used for forecasting of nine time-series, namely: returns of the lows returns of the highs ...
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0answers
27 views

Forecasting bond yields

Do you know any models which can be used for prediction of corporate bonds yields (or goverment bonds yields) when we know forecasts of macroeconomic fundamentals (gdp, fed funds rate, interbank rate, ...
1
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2answers
263 views

Using Technical Indicators for forecasting Financial time series using Machine learning models

Hi I am trying to use financial technical Indicators for forecasting, using machine learning models. The usual approach in time series cross validation is to use a moving window or growing window. ...
2
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5answers
462 views

Is there any way to easily estimate and forecast seasonal ARIMA-GARCH model in any software?

I use R to estimate a seasonal ARIMA(8,0,0)(5,0,1)[7] model for the seasonal differences of logs of daily electricity prices: ...
2
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1answer
138 views

ARIMA model, cannot get rid of low order ACF spike

I've gone through all the steps to fit a good ARIMA model - I plotted the data, I looked at the ADF tests, I looked at the ACF plot with no AR and MA terms just a constants. I came up with an ...
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0answers
107 views

Stationarity tests in the frequency domain for regression

Strict stationarity is the strongest form of stationarity. It means that the joint statistical distribution of any collection of the time series variates never depends on time. So, the mean, variance ...
1
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1answer
143 views

Normalization of Market Data in Time Series Correlation

Suppose we have 2 time series of market data, one for each security and we want to correlate between these 2 securities. My question is How do we handle gaps of missing data in the time series? ...
1
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1answer
255 views

HAR-RV, realized GARCH and HEAVY model for realized volatility

I don't have much experience with volatility modeling using intraday data but I'm in the process of collecting 5mins data. Currently I have ~6 months of data. Is it enough to use these models with ...
6
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1answer
399 views

Estimate rolling stochastic volatility forecast using stochvol in R

I want to use the R package stochvol to fit a SV model to a DAX training set and use the output to estimate a rolling one-step-ahead forecast: ...
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2answers
86 views

How To Account For Inflation Over Historical Data

I believe inflation is greatly affecting my sample data, even when using percent-changes for movements. I have read this post, which recommends the formula ((Current-Base Year CPI) * Price) / ...
2
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4answers
353 views

Implementing A 50/50 Prediction Model Strategy

Reworded the question for clarity (see edits for original post): How can one knowingly foresee where a 50/50 prediction model will be profitable? For previous posts: I understand that if I have a ...
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3answers
429 views

What Is A Good Success Rate Using Machine Learning For A Beginner?

I know this question will be quickly destroyed and my account summarily banned, but I just have to ask: For a trader using machine-learning algorithms (SVMs, ANNs, GAs, Decision Trees) for ...
2
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1answer
245 views

Why are multiple custom curves (swap) built for one desk?

Currently in a journey of learning and getting my hands a bit dirty with Interest Rate Swaps. Why there are multiple customized curves built by many even within one desk? For e.g. Short Rates desk ...
1
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1answer
183 views

How would you correct a GARCH model to deal with non mean reverting volatility?

I am currently attempting to model and forecast volatility of bitcoin but have not been able to find a GARCH model that fits the data appropriately. I've used tick data sampled at 1 hour intervals ...
2
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1answer
92 views

To understand FOMC events and its impact on the market

Last month when FOMC meeting decision went out that fed would start to exit QE3, immediately we saw a deleveraging effect: SPY went down, GLD went down, and LQD (bond) went down, but US dollars went ...
2
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1answer
391 views

Calculating the probability of a price change using an options pricing formula

I don't know if I'm doing this right and I'd greatly appreciate help. I'm trying to use an option pricing formula to backout the likelihood of the Euro dropping below $1.27, even for a minute, at any ...
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2answers
342 views

What stock market indicators to model based on twitter feed? [closed]

We are developing an algorithm that models twitter users and groups of words that may indicate real world events. One application is modelling elections, i.e which party is likely going to win. ...
2
votes
1answer
192 views

How to calculate two-time scale variance?

I am having trouble understanding how to calculate two-time scale variance as I do not have a strong mathematical background. Suppose I want to calculate the TSRV at 5 min intervals. Do I calculate ...
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3answers
602 views

The Basis of Using Technical Indicators as Inputs

In the process of my research I very often come across academic papers regarding modelling and trading strategies that in one way or another incorporate some technical indicators. For example in some ...
0
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1answer
504 views

Selecting timeframe for time series analysis

In technical analysis, we may use confluence of direction for 3 timeframes to roughly gauge bias of market now. Similarly, if we use time series forecasting methods to predict(say daily data-whether ...
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2answers
755 views

How do you synthesize a probability density function (pdf) from equally weighted price data?

What I'm working with: I have a collection of prices that has very few to no repeating values (depending on the look back period) ie each price value is unique, some prices are clustered and some can ...
4
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1answer
513 views

Coin Toss System

Coin Toss Runs Calculator The expected number of runs for two consecutive heads or tails is 3. Is there an edge if we place a progressive constant size bet(limited to 3 times)for consecutive ...
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0answers
465 views

Oscillatory time-series forecasting

I was wondering if this mean(160)-reverting/oscillatory time series "SUM" can be considered chaotic & forecastable to some extend short-term? ...
4
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0answers
153 views

Rolling window Kendall's tau against APARCH(1,1) correlation

Assume you want to forecast the correlation matrix of a stocks' basket (say 15 ~ 20 stocks from different sectors); assume you need to forecast at $T$ days because you will use the forecast ouput with ...
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0answers
206 views

Modeling asset performance to Bitcoin revenue

I'm attempting to model asset performance to Bitcoin revenue, which is a driving force in the Bitcoin community. Question Is there any model, or research being done that tracks "hashes per second" ...
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2answers
564 views

Evaluating forecasting algorithm

I am trying to evaluate a forecasting algorithm for stock price prediction. However, the performance of the algorithm may be very much tied to the trading strategy. Is there a systematic way for ...
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4answers
480 views

Position management in presence of continuous forecast

Let's say we have an equity liquidity-providing model that was fitted on 1 minute bar periods. The model forecasts the 1-min next period return given the activity of the previous bars. Now, when we ...
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2answers
191 views

Is there an optimal covariance one would want forecasts to have?

Often in a quant process, one will generate a time series of return forecasts and use them in some sort of optimization to generate a portfolio. Generally, there will be a covariance matrix of market ...
6
votes
1answer
1k views

What is the best way to forecast prepayment rate in an emerging market mortgage loan portfolio?

I constructed a model to forecast the prepayment rates for a mortgage loan portfolio (of mortgages in an emerging market) using probit regression on factors such as loan-to-value, PTI, time from ...
2
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1answer
358 views

Econometric vs ANN models for forecast?

I hope this is an appropriate question for this forum... for me it is an obvious query since it intrigues me for a long time. Ok, assume there are 2 distinct classes of models: econometric (AR, MA, ...
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2answers
872 views

How to forecast expected volatility from high-frequency equity panel data?

I'm wading through the vast sea of literature on realized volatility estimation and expected volatility forecasting (see, e.g. Realized Volatility by Andersen and Benzoni, which cites 120 other ...
6
votes
4answers
236 views

What is a sound way to project Company X's earnings over the next Y years?

I need to estimate cumulative earnings over the next Y years and I'd like to find a solution that is theoretically sound and relatively simple. Can anyone recommend an approach? Given: I have 30 ...
9
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1answer
886 views

What is the Sugihara Trading System?

I recently heard the term Sugihara Trading System. I guess it might be some trading strategy or a special model to predict trends in market data, but I couldn't find out anything about it. Does anyone ...
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2answers
579 views

Is there any research on applying state-space or dynamic linear models to forecasting equity risk premia?

Is there any research on applying state-space or dynamic linear models to forecasting equity risk premia on a security-by-security basis with a medium term horizon (say 3 month to 12 months horizon)? ...
2
votes
1answer
382 views

Techniques for forecasting short-frame data?

I'm having a problem in which a time series of 24 data points is given to forecast the next 12 data points. This 24 data points might be sparse (many are missing). Do you have any suggestion on what ...
7
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2answers
397 views

The T+H Problem in Factor model forecasts

Suppose we train on M individuals consisting of T observations (i.e. TxM design matrix). The dependent variable is one-year return for each security (H = horizon of one year). In a factor model ...
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1answer
561 views

Rolling GARCH and higher moments

I m recently doing my dissertation and faced with problem in estimation basic rolling GARCh (1,1) process. I have 2500 observation and need to forecast 1 day ahead volatility in rolling form. I will ...
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2answers
869 views

How do I replicate John Hussman's recession forecasting methodology?

John Hussman has a recession forecasting methodology he often posts about on his blog, and I am trying to replicate it using publicly available data. I would like to assess his accuracy in predicting ...