25-26 April 2020 | Mumbai
Venue: Nehru Centre, Worli
TRACK – 1 | Time: 9:30 am – 6:30 pm
25-26 April 2020 | Mumbai
Venue: Nehru Centre, Worli
TRACK – 2 | Time: 10:00 am – 7:00 pm
Gann Analyst & Market Technician
Founder-ProRSI, MFTA, CMT, CFTe, MSTA
Market Technician and Founder - My Trading School
Technical & Derivative Analyst
Founder - Wave Analytics
Currency CPE Trainer - NISM
Founder - Arque tech
Co-Founder & Quant Head - Samssara
Founder - Wright Research
Shivram K R
Co-Founder & CEO - Curl Analytics
Managing Director - BP Wealth
CEO - Symphony Fintech
CMT and Algo Trader
Founder - Quantgym Solutions
India Strategist : Algo Trading - Curl Analytics
Co-Founder & CEO - FYERS
Founder - Inuvest Technologies
MD & CEO - NeuralTechSoft
(Country Manager - Transaction Network Services Inc.)
Gurmeet Singh Chawla
Director - Mastertrust
Traders Conference Sessions
Speaker: Praveen Pathiyil
- The uniqueness of HeikinAshi Chart.
- Power of a real market (sound filter) among the whole market (noise).
- The secret method HADC exposed
- Case study on Nifty.
- Practical Approach to the secretive method in modern day era.
Speaker: Bharat JhunJhunwala
- What is more important Money, Method or Mindset?
- When to think about trading fulltime?
- Understanding Overbought & Oversold markets.
- Trading Volatility Breakouts Intraday.
- Catching early trend reversals using ADX.
- Using Technical Analysis for Long Term Investing.
Speaker: Nitin Murarka
- Nifty and Bank Nifty – Weekly Option & Intraday.
- Stocks Options Strategy.
- Trading in Stocks before Results.
- Short Term Delivery Trading/ Delivery Data
- Which Stocks to avoid for buying.
- Expiry Day Data Reading and Trading.
- Simple and profitable Options Strategies.
Speaker: Narendra Prajapati
- Why Forex Trading ?
- Basics of Currency Market.
- Inter-relationships of various Asset Class & Multi-dimensional Positional Play.
- Trading Ideas – Future & Options.
Speaker: Kunal Bothra
- Discussion on The most Obvious (but most ignored) mistakes committed by traders.
- Apply basic principles of Discipline in the system.
- The ways to overcome it.
- One Premium Market Strategy – Rules with few Examples
Speaker: Jyoti Budhia
- Understanding Open Interest and Movement of Price.
- Use of Jodi Bhav of Options to find Trade on Monthly basis.
- Using Candle Stick to Understand the Trend of Open Interest.
- Important Days in a week to Trade Index (with 1 year Case Study).
Speaker: Piyush Chaudhry
While markets move leaps and bounds in Trends, markets remain in a range almost 2/3 of the time.
- How to identify range markets ?
- What kind of setups there are.
- Planning Entries
- Determination of Exit Targets.
Algo Conference Sessions
Speaker: Hrishav Sanghvi
Crude Oil Scalping strategy – Impact of poor execution and slippage.
Algo Risk management.
Popular Algo platforms in India.
Beginner and Institutional Architectures.
How to setup an Algo desk?
Predatory Bidding strategies.
Speaker: Manish Jalan
- Most algorithmic trading strategies uses various combinations of technical studies and other factors to develop strategies in short, medium to long term horizon.
- Various live practical examples from the market and how it effect the overall profitability of the strategy will also be discussed.
- Audience will be able to relate their day to day trading with key statistics parameters and comprehend the do’s and dont’s of algorithmic trading.
- Presentation will also cover statistics in Options Market where price series have non-linear behaviour due to Options greeks involved.
- Importance of statistics like standard deviations, correlations, mean and sharpe ratios which playsvital role in making a strategy long term profitable will be discussed.
- Large drawdowns and big flattish periods in algorithms can be avoided by using various mix of technicals with statistical factors.
- Alpha is often generated in Algorithmic trading when a mix of various statistics are applied both at the strategy level and portfolio level analytics.
- A technical algorithms can be made massively profitable if statistics is added to it in a systematic way.
- There are hidden statistics which if not taken into consideration cannot make an algorithm profitable.
Speaker: Sonam Srivastava
- Tactical Asset Allocation is an investment style where allocation to various asset classes is actively balanced based on market regimes.
- The aim of the strategy is to to maximize portfolio returns while keeping market risk to a minimum, as compared to a benchmark index.
- The market regimes to be used are modeled using macroeconomic variables and short term technical signals. In a trending market regime risky assets like equities get higher allocation while in a risky market bonds and gold get higher allocation.
- A tactical asset allocation strategy also tries to maximize the returns within the equity allocation choosing the best stock mix using equity market factors and modelling their behavior in various regimes.
Panelists: Praveen Gupta, Yuvraj Ashok Thakker, Tejas Khoday and Vagaram Chowdhary
Speaker: Vishal Mehta
- Why Intraday Trading Strategy.
- Advantages & Disadvantages of Automated Trading systems.
- How to decide when to stop trading a strategy.
- Risk Management of Trading Strategies.
- How to decide on Stop Loss and Target.
- Building strategy Rules.
- How to develop ideas about Trading Strategies.
Speaker: Subhadip Nandy
- How to take a common trend following concept and give it a quant spin.
- Removing the subjectivity associated with trend analysis.
- Using data and statistics to make an indicator which is quant based.
- Can be used as a trend filter for any existing system.
Speakers: Shivaram K R and Kusal Kansara
- How data is generated in huge quantities, mainly alternate data.
- Types of data and what kind of information can be found.
- The insights are stored in the data and have to be extracted.
- AI based models to create indicators.
- How to effectively do backtest to prevent overfitting.
- How to use ML on financial time series.
Speaker: Mahendra Mehta
- What is adaptive learning?
- Advantages for adaptive learning.
- How AI is deployed in adaptive learning.
- Examples from the Indian Market.
- Summary results.