Algorithmic Trading


Rs 60,000
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Important information

Typology Course
Level Advanced
Methodology Online
Class hours 100 hours of study
Duration 6 Months
  • Course
  • Advanced
  • Online
  • 100 hours of study
  • Duration:
    6 Months

Important information

Where and when

Starts Location


Frequent Asked Questions

· What are the objectives of this course?

The objective of this program is to introduce the candidate with comprehensive aspect of algorithmic trading and execution. It is design for both buying and selling industry.

· Who is it intended for?

No prior experience required. Candidates who wants to start their career in financial market can join this course. The trader can join program to upgrade their skill.

· What marks this course apart?

Modrika provide best course content with experienced faculty. The course focus of the use of application to develop algorithmic trading strategy development.

· What happens after requesting information?

To enroll in this program interested candidate need to fill application provided by Modrika. Payment can done online and other payment option also available.

What you'll learn on the course

Algorithmic Trading
Electronic Trading
Advance Trading

Teachers and trainers (1)

Advance Algorithmic Trainer Modrika
Advance Algorithmic Trainer Modrika

Course programme

Module A: R software based back testing and Visual basic applications based trading (this module would be covered throughout the course)
R software based back testing Visual basic applications based coding and tradingProbability and statistics using R. regressions and model fitting.Time series analysis using R: Spectral analysis, ARIMA, moving averages and differencing models. Forecasting from model fitting and residual diagnostics.Pairs trading using R. Downloading S&P500 historical data, making pairs and simulating pairs trading.Options, futures and derivatives pricing using R. Portfolio optimization and performing finance managerial tasks using R.Backtesting trading strategies using systematic investor toolbox in R. Strategies based on:Probabilistic momentum, seven twelve portfolio strategies, volatility regimen based trading etc.One month reversal, seasonality, calendar strategies, based on dates on expiration of options etc.Visual basic applications based coding and tradingIntroduction to coding in VBAReal time trading simulation and implementation of technical analysis indicators using VBA Module B: Random number theory, and stock data analysis.
Trading Participants in TradingStocks, Options, Bonds, Mutual Funds, ETFs and Forex TradingCurrent Scenario of Trading & Future ProspectiveIntroduction to Algorithmic and High Frequency TradingStatistics and random number theoryProbability and StatisticsCombinatorial Analysis, Conditional Probability and Generating Functions.Sampling Distributions, Law of Large Numbers and Central Limit Theorem.Likelihood Functions, Estimation, Confidence Intervals, Hypothesis Testing.Regression and Analysis of Variance.Basics of CalculusCompounding and Interest CalculationTime series analysisTime Series Analysis: Autocorrelation, White noise, Stationarity, Autoregressive models. ARIMA models. Spectral Analysis, Fourier TransformationAnalysis of time series stock dataEstimation of volatility using various modelsPairs Trading: Correlation, Distance, Co integration Module C: Finance, economics, options and futures
Basics of FinanceFinancial PlanningVarious Types of Costs & Risks, Overview of TaxationFinancial Institutions & MarketsTopic 4: Capital Markets & Commodity Markets Operations Options and futureOptions TheoryOptions terminology, Options Payoffs, Options payoff profile and strategies.European and American Options. Asian options, greeksPricing of Options. Binomial tree models, black scholes equations, monte carlo random walks models for options pricing.Futures and Forwards MarketsSwap Contracts & Swap Markets Module D: Technical analysis; Indicators and candlestick patterns; Real trading
Technical AnalysisTradestation I: Getting started with Tradestation. Beginner level coding. Trend Analysis, Oscillators, Moving Averages, momentum indicators Technical Theory & Technical Analysis Indicators Inter market Technical AnalysisTradestation II: Medium level coding and sound knowledge of Technical Analysis (some of the practicals are listed below)Money management: stop loss, percent trailing loss, profit target etc.Implement a function that invests at Kelly’s fraction.Code for a Indicator based on maximas and minimasCode for various patterns candlestick patterns.Bearish engullfing, shooting star, Hanging man, piercing pattern,Doji star, etcImplement a strategy based on candlestick patterns and stochastic crossovers.Implement filters, such as a) stochastic, b) CCI, c) Trends or d) Day of week at which trading has to happen.Tradestation III: Higher level coding and sound knowledge of trading. (some of the practicals are listed below)Breakout strategy. I.e., how to capitalize on the rally up of the stocksWrite the code to pause for certain number of days if consecutive loose trades happen.Trading based on FibonacciTrading based on bar patternTrading based on Bollinger bands and keltner bandsMeander indicator and meander strategy (its a scalping stratgey)Intraday strategy: Bar Reversal Long/Short Entry Strategy. Stochastic trap: To get the optimum buy and sell

Achievements for this centre

Additional information

Algorithmic trading program focuse on algorithmic trading stratrgy development, coding and backtesting.

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