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2
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2answers
180 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 =...
2
votes
1answer
184 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 ...
2
votes
1answer
474 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 ...
2
votes
0answers
62 views

Risk neutral probability and forecasting

When our goal is pricing of derivative products we, due to no arbitrage conditions, have to use the risk neutral probability. In other side if we have risk management purpose we have to use the “...
2
votes
1answer
89 views

Starting values for constrOptim() in R

I want to perform a constraint optimization for Maximum Likelihood Estimation in R to forecast volatility of returns. The probleme is that my initial values aren't in the permitted region. Is there ...
2
votes
1answer
49 views

List of Economic Data for Index Forecast

What econometric symbol list (or tickers) could be used to forecast return of global stock market indexes (S&P500, TSX, CAC40, ...) and their subsectors? I'm aware of the answer to question: ...
2
votes
0answers
202 views

Forecast of ARMA-GARCH model in R

I managed to forecast a GARCH model yesterday and run a Monte Carlo simulation on R. Nevertheless, I can't do the same with an ARMA-GARCH. I tested 4 different method but without achieving an ARMA-...
2
votes
0answers
290 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, ...
2
votes
0answers
24 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 ...
2
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0answers
201 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 ...
2
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4answers
455 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 50/...
1
vote
2answers
133 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) / (...
1
vote
2answers
114 views

Modelling and forecasting mixed frequency financial data

I was wondering if someone could provide some guidance to me. I would like to Combine various financial data of mixed frequencies (some daily, weekly, some quarterly) to a composite index. I have ...
1
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2answers
34 views

How do companies forecast revenue and earning estimates for a quarter or year in advance?

I'm sure there are models and they have low and high estimates. But how to do they decide on the percentage growth? A bit of art + science?
1
vote
1answer
374 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 = list(...
1
vote
1answer
76 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 ...
1
vote
3answers
698 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 ...
1
vote
1answer
89 views

how to calculate RMSE, MAE, given ugarchforecast results?

Given S&P500 returns for the past 20 years I fitted an ARMA(1,1)-GARCH(1,1) model using the rugarch package, so using ugarchspec() and the ugarchfit(), with different innovations distributions, i....
1
vote
1answer
138 views

One-step ahead forecast of a AR(1) process (GARCH context)

I am using a Matlab toolbox for obtaining one-step ahead forecasts of the conditional mean from the ARMA(1,0)-GARCH(1,1) process and I have encountered a piece of code that contains, in my opinion, a ...
1
vote
1answer
47 views

ARIMA Forecasting always converges?

I read an article about arima forecasting and i said that before we forecast arima model, its stationarity has to be checked. If the model is stationary, it is clear that forecasting converges to ...
1
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1answer
32 views

Aggregating growth rates

I'm working on a simple forecast model that uses Cumulative Annual Growth Rate (CAGR) to project future growth, and I've run into an apparent paradox. The model includes multiple lines of business ...
1
vote
1answer
210 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. ...
1
vote
2answers
160 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 ...
1
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2answers
485 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. ...
1
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2answers
582 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 ...
1
vote
1answer
23 views

Data of Credit Migration Matrices

Please advise that how to get the data of credit migration matrices There is a paper of credit migration matrices, I would import the data to Matlab or R for credit analysis. https://www....
1
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0answers
18 views

Relationship between in-sample and out-sample periods length

I have two general questions regarding "in-sample fitting vs. out-of-sample backtesting" kind of analyses. Is there any relationship between the length of the data collected for in-sample fitting ($a$)...
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0answers
27 views

Forecasting conditional returns in DCC-GARCH-copula approach in R

anyone who could help me interpreting and modifying this code? I have a dataset and want to reserve the last 100 returns for out-of-sample analysis. After specifying and fitting the garch-spd-copula, ...
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0answers
6 views

What are appropriate algorithms for forecasting contract schedules to maximize profit?

Imagine a situation where a business negotiates contracts for the maintenance of widgets it sells. Situation Customer buys 20 widgets. Customer negotiates contract for widgets to be serviced/...
1
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0answers
17 views

Relative merits of Adjusted versus Closing prices for market predictions

Basic question I am familiar with the data returned from Yahoo. For indices and the like (e.g. ETFs) there are seven columns of data: Date, Open, High, Low, Close, Volume, Adjusted. We only need ...
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0answers
56 views

How do I use common forecasting models to forecast FUTURE values? [closed]

I would like to forecast likely future demand based on historical demand. The problem is: I have no mathematical background and in relevant tutorials and even in literature formulas are used, that ...
1
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0answers
19 views

Reconciling forecasted growth of components and sum

I'm working with a very basic basic forecast model using Compound Annual Growth Rate and I need to reconcile the forecasts at different levels of detail. Suppose I have two business lines with ...
1
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0answers
57 views

Cross-sectional moments

I got a seminar topic named Forecasting risk from cross sectional moments? Could at least someone tell me what should I write about and if there is any paper that I could read. Thank you very much in ...
1
vote
0answers
475 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? http://sg.myfreepost.com/sgTOTO_analysispower.php?...
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0answers
218 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" (...
0
votes
2answers
398 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. ...
0
votes
1answer
213 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
votes
1answer
659 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 S&...
0
votes
1answer
121 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
votes
0answers
14 views

Is my demand prediction too low?

Hi i have a problem right now at work. For certian business segments,some sales target are establish each year. This targets are establish based on the managers feelings. Its like this: Manager: "so ...
0
votes
0answers
29 views

Approximating the conditional expectation in simulations

I am simulating stock returns, which are governed by the following equations $r_t = \mu + \delta r_{t-1} + \sigma_t z_t$ $\sigma^2_t = \omega + \alpha \varepsilon_{t-1}^2 + \beta \sigma^2_{t-1}$ $\...
0
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0answers
45 views

Macroeconomic forecasting

During the last year I was working on developing several forecasting models which I was checking mainly in energy markets. They are based on regression, autocorrelation and also machine learning ...
0
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0answers
70 views

Asset allocation and GARCH models

I am trying to solve an asset allocation problem and I am having some troubles grasping the concept. I am working with excess returns on 4 stock indices and I am obtaining the excess returns forecasts ...
0
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0answers
29 views

Are low oil prices and low shipping costs really a leading indicator for a shrinking economy

Recent article in Bloomberg saying that lowered shipping costs n the form of the Baltic Dry Index and lowered oil prices are in someway a concern for a growing global economy: http://www....
0
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0answers
50 views

Estimate volatility in forecast

I have a model with a rolling forecast. In each time step $t$, I predict the price for the next periods, e.g. $\hat{p}(t, t+1)$ and $\hat{p}(t, t+2)$. If I start in $t=0$ and arrive at $t=2$, I ...
-1
votes
1answer
46 views

Determining confidence level of directional signals

With regards to technical analysis, are there ways of determining the confidence level of a directional signal? Taking a relative strength index (RSI) as an example, can the extent to which an asset ...
-4
votes
0answers
49 views

How to simulate lognormal returns with Monte-Carlo?

I'm trying to forecast the price of silver over a 5 year period. I pulled silver price data going back to 1970, and then computed returns based on a 5-year lag. My problem is that these returns are ...