Questions tagged [simulations]
The simulations tag has no usage guidance.
256
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VEC model on log prices, for random simulation?
In the context of pair trading, I’m trying to regress a VEC model on cointegrated pairs (and also a GARCH model on the residual of that VEC model).I would like to generate random réalisations of each ...
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Does Backtrader and QuantConnect collect any data?
Building an API that integrates with backtrader and QuantConnect to run some backtests. I'm passing in machine generated data and I just want to make sure I'm not sending them too much stuff.
so what ...
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1
answer
89
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Fatigue with Historic Backtesting - Alternatives?
It seems to me like historic backtesting is the best of bad options out there for me to test my systematic strategies - even ones that are more macro-level trend spotting. I can't test enough ...
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Pathwise sensitivities of American options - Derivative of the American payoff function
How can I compute the derivative of the payoff function for an American put option?
In the paper "Smoking adjoints: fast Monte Carlo Greeks" by Giles and Glasserman (2006) they compare two ...
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113
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Continuation value in Longstaff-Schwartz: Why the expected value?
In the paper by Longstaff and Schwartz on American option pricing, the continuation value at time $t_k$ is given by:
\begin{align}
F(\omega;t_k) = \mathbb{E}_Q\Big[\sum_{j=k+1}^Kexp\Big(-\int_{t_k}^{...
- 521
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Estimating Returns with the Non-Central t-distribution
The Boost C++ Libraries provide a set of statistical distributions in their Math Toolkit library. The best candidate I can find among those available that will capture skew and kurtosis typically ...
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58
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Longstaff-Schwarz LS Monte Carlo - which approach is correct? [closed]
I'm trying to understand Least-Square Monte Carlo approach for pricing american options. I'm familiar with Tsitsiklis and van Roy (2001) approach where we are going backwards with:
$V_T = h(S_T)$, ...
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1
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119
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GARCH process simulation in R
I'm trying to learn how to simulate the GARCH(1,1) for option pricing using Monte Carlo. I need to learn how to code the equations for the stock log returns and the variance process. I'm trying to ...
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64
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Heston Process: Accept-Reject Sampling to Alleviate the Problem of Negative Variances
I've read even in recent papers, and on page 21 of the book "The Volatility Surface" by Jim Gatheral (2006), all the debate over whether to reflect or truncate negative variances whilst ...
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44
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Simple Monte Carlo Interest Rate Simulation Problem
I'm projecting interest rates using a log normal monte carlo simulation (lognormal.inv(rand(),mean ,std. dev.). I have provided an example below of a monthly and yearly simulation.
My first question ...
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110
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Choosing a time step in Monte Carlo simulation of forward rates in LIBOR Market Model
Lets talk about the Monte Carlo simulation of forward rates in Euler discretization scheme under the $T_N$-forward measure, a so called terminal measure. Suppose that we have a number of time steps ...
- 647
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35
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Inflation in wealth forecast [closed]
I am building a model to simulate people's wealth in the next years.
Say Mr X has a portfolio with an expected return of 3% (annual). From this I can simulate the return of his portfolio in the next ...
- 11
2
votes
1
answer
188
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Optimize interest rate swap calculations in Monte Carlo Simulation
I’m running a simulation in which I want to calculate the NPV of 100 swaps over 1000 (or even much more) different interest rate curves.
It looks like Quantlib is not really fast in performing these ...
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184
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CEV model effective simulation
I want to simulate the following CEV process : $$ dM_t = \sigma_t M_t^{\eta} dW_t $$
Using Euler discretization to $M_t$, if at a given time $t$, $M_t$ takes a negative value then $M_{t+1} = M_t + \...
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84
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Simulating the same stock price with different methods/distributions
I would like to ask if we could simulate stock price paths with different methods/techniques.
What I mean is : say we have a specific stock price hence we can extract historical mean and standard ...
- 129
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76
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Milstein Discretization of Heston Model
Given the following representation of the Heston Model:
$$d\left(\begin{array}{l}S_{t} \\ V_{t}\end{array}\right)=\left(\begin{array}{c}\mu S_{t} \\ \nu-\varrho V_{t}\end{array}\right) d t+\left(\...
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27
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Stress scenarios for Down In Put (DIP)
I am preparing stress scenarios for long Down In Puts (e.g -10%,-15% drop in underlying equity price). I assume that the maximum delta hedge is 300% for DIPs with barrier levels within 0%-5% ...
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1
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260
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Simulating Iterated Brownian Motions
I was going through an interesting article (https://arxiv.org/pdf/1112.3776.pdf) while I was trying to read about subordinated processes. I wanted to simulate subordinated processes (in R or python) ...
2
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1
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255
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Cholesky decomposition reduces volatility of simulated Wiener Process / Brownian Motions
I am trying to simulate $n$ correlated geometric brownian motions (GBM) given a specified correlation matrix $\Sigma$ by following this procedure which uses Cholesky decomposition.
However, when I ...
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397
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Euler Discretization python code
Write the Euler discretization of the 1-dimensional stochastic equation
$dXt = b (t, X_t) \space dt + \sigma (t, X_t) \space dW_t$
For this part I would say all right because it is a purely ...
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89
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Inconsistency between simulation and the probability of a "stock" hitting take profit before stop loss
Let's assume a stock at time $t$ is worth $X(t)$. If the returns of $X(t)$ are i.i.d. and normally distributed,the probability of $X(t)$ hitting a value $H>X(t)$ before $L<X(t)$ is $\frac{H-X(t)}...
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206
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What are common ways to realistically simulate the stock market using historical market data?
I am currently using the FinRL library to try to automate Trading using Reinforcement Learning. However, I wanted to understand how FinRL simulates the stock market using historical data. I read here ...
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1
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Simulating Correlation (but sample correlation is always too low)
I am trying to simulate correlation in order to price a correlation swap (via Monte-Carlo). For simplicity, let's assume we have 2 assets, and everything is correlated with $\rho$, and there is no ...
- 1,192
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115
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Why we introduce correlations between Wiener processes? [closed]
Wiener processes are used to model various assets, and I wonder why we are introducing correlations between the Wiener processes and what is the interpretation? Because when the correlations between ...
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1
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264
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Simulating the Value-at-Risk with $t$ distributed returns
I want to understand how the value at risk and the simulating the VaR with simple Monte Carlo method. But I want just a confirmation and are welcome any comments, since I don't have the full picture ...
user57440
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156
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Simulating sum of squared brownian motions process
I'm trying to simulate the following stochastic process:
\begin{equation}
R_t = \sum_{i=1}^nB_{i,t}^2
\end{equation}
which has the following dynamics:
\begin{equation}
\begin{aligned}
dR_t = \sum_{...
0
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2
answers
104
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seek clarification about PFE
I'm a software developer want to know a little about quant basics. My undserstanding of PFE is that a PFE of a trade at a future time point is commonly defined by taking the average of the highest (or ...
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Backtesting - treatment of holidays for global (i.e. multi-market) portfolios
Assume a daily trading strategy where each day we rebalance our portfolio weights:
Situation A: all constituents of our portfolio are from the same market (e.g. a portfolio of S&P 500 stocks)
...
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154
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Interpolation of $\mu(t,X(t))dt+\sigma(t,X(t))dW(t)$
Let's assume that we have SDE
$$dX(t)=\mu(t,X(t))dt+\sigma(t,X(t))dW(t)$$
and we simulate it on a time grid which contains points $t_k$ and $t_{k+1}$. How can we then calculate value of $X$ at time $...
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1
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Simulating Correlated Stock Returns in Python (SciPy)
I'm looking to generate stock returns with inter-stock correlation in Python. However, the output is not behaving properly and may have accidental temporal correlation causing issues.
This code is ...
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287
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Why can’t delta’s be used to price double no touch options?
Here is the link to a MATLAB one touch option pricing calculator I used:OT
I tried several inputs and I noticed that the one touch option price is approximately twice the delta of an equivalent ...
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1
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Efficient method for expanding 1 sim routine to the number of simulations? Brownian Bridge used with multiple underlying assets in a MC simulation,
I believe this is a (fairly) simple question for those familiar with quantitative finance and MC/QMC methods of pricing complex options. Or potentially its just a simple Python loop vectorization ...
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162
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How can I simulate the barrier option call model in Python?
We have a barrier call option of European type with strike price $K>0$ and a barrier value
$0 < b< S_0$,
where $S_0$ is the starting price.According to the contract, the times $0<t_1<....
user57440
2
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1
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330
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backtesting guide for research
I am a master student in finance and I am working on my portfolio management thesis. Within my thesis I will have to backtest a portfolio strategy for a balanced portfolio.
I am looking for a guide/ ...
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2
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Validation of XVA models
Hey what is the validation of XVA models (CVA, FVA etc)? As we know XVA calculation is rather complex problem (simulation, Valuation, aggregation) so what steps should be taken to check if the model ...
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1
answer
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How to simulate correlated stock prices (not returns)
Suppose we have two stocks following GBMs. Drift and volatility are calculated based on historical data. Furthermore the stocks are assumed to be correlated (i.e. they move together, if stock 1 goes ...
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Filtered Historical Simulation VaR for swaps
I am trying to understand how to calculate FHS VaR for a portofolio of vanilla swaps. I think I understand the main ideas behind FHS VaR and how to implement it for other assets such as equities. I ...
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147
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GBM drift when simulating correlation betwenn GBM with Cholesky Decomposition
I am currently trying to simulate correlated GBM paths and I found the Cholesky Composition for it. From my understanding, the Cholesky Decomposition can be used to create correlated random variables ...
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How to get Risk-Neutral Drift for Trading Volume from Time Series
I am trying to price an option with Monte-Carlo simulation, where the payoff depends on some constants and a time-series (trading volume) which I model to follow a GBM. Now if I understood it ...
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Distribution of Geometric Brownian Motion drawdowns from realizations of multivariate Normal and Laplace distributions
I am trying to simulate the distribution of Geometric Brownian Motion drawdowns from samples of multivariate Normal and Laplace distributions under the same covariance structure. Drawdowns are defined ...
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Testing severity of VaR by changing portfolio component weights
Let's assume that I have a portfolio with two components:$$\omega_i = 0.3$$ $$\omega_j = 0.7$$
I also have two P&L vectors, $v_i$ and $v_j$ each containing 1000 P&Ls. I would like to play ...
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804
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How to simulate Levy processes
Hey how to simulate Levy processes? I have no problem with Wiener process and compound Poisson process, I also know how to simulate Variance Gamma process but I have no idea how to simulate for ...
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How to test the difference between samples of sharpe ratios
I am testing the performance difference between 2 portfolio strategies. I use Monte Carlo simulation in R to generate $N$ simulations of portfolio returns for each strategy. I then compute the Sharpe ...
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1
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143
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VAR of Long & Short European Call Options
I have over 1000 simulated stock prices for an option that is expiring in 3 months. I have calculated the EU call option payoff of 1000 simulated prices and now I have 1000 simulated payoffs of call. ...
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1
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R - Plotting a 3-dimensional sample path in yuima?
Apologies if this is not the appropriate place to post this - this my very first contribution to Quantitative Finance Stack Exchange. I was hoping someone could help me with the following issue. I am ...
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3
answers
474
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EPE for interest rate swap
Hey how to calculate Expected positive exposure in the case of interest rate swap? Assume that I simulate $M$ interest rate paths for time grid $0=t_0\le t_1 \le ... \le t_N = T.$ What is the ...
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Creating a set of histories that satisfies certain statistics
I'm looking at a download of BlackRock's capital market assumptions, which gives a bunch of statistics, such as expected and quartiles for asset classes' returns for different timeframes, volatilities ...
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Valuing American Options using Tilley algorithm
Hey I want to implement Tilley's algorithm (Valuing American Options in a Path Simulation Model by JA Tilley, 1993) to price american options. Where can I find implementation of this method in any ...
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571
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Probability Distribution at each Simulation Period using Geometric Brownian Motion
I am using the equation $S_t = S_0e^{(\mu-\frac{\sigma^2}{2})t+\sigma\epsilon\sqrt{t}} $ to simulate a financial metric at each $t$, where $t=1$ and $T=5$. Stated in plain English, I am trying to ...
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Estimating VaR of bond due to changes in the US yield curve
I am attempting estimate the 99% 10-day VaR of an investment grade bond due to changes in the US yield curve. The data provided is the daily prices of the bond over time. In addition I have the Daily ...
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