Mr. Krishna Rawal is a senior trader with over 20 years of experience across various instruments – Stocks, Futures, Commodities and Currencies.
He is a professional algo trader and helped brokers and traders in designing their algo trading strategies and system for futures and hedging. He is a multiple time winner of trading challenges and has trained 100s of professional traders.
Currently, he plays multiple roles in trading-related institutions as Managing Partner at Commodities Trade Services and as CEO at STAT Institute – an institute that conducts advance courses in AI ML and Algo Trading.
Disclaimer: The User/ Licensee agrees and declares that the training that may be received by the User/ Licensee is not intended to provide, and should not be considered to be any investment advice from the Licensor and/ or the said trainer. No decisions should be taken by the User/ Licensee on the basis of any such training. It is agreed that the training that may be provided is only for the purpose of educating the User/ Licensee as to how the Software may be used.
Scenario analysis is the process of gauging the expected value of a security or portfolio over a specific period, with variations in key factors that may affect the price of the security.
For instance, in trading, scenario analysis could mean evaluating the impact of changing market conditions on your open positions. These scenarios could be a downward or upward trending market or even extremes like a complete market crash.
How does scenario-based approach to trading help?
Algorithmic trading allows scenario analysis using mathematical models. These assessments are helpful in understanding the risk level within a security with respect to various events that could range from least probable to highly probable.
Based on the results of the analysis, a trader can decide whether the risk levels lie within his/her comfort zone and whether the trading strategy will benefit them.
Basic and worst-case scenarios to account forwhen trading
When trading, you would obviously want to take into consideration various market scenarios like volatility, choppy trading, bullish trend, bearish trend, and so on. You may also want to have conditions like a complete market crash as a least probable scenario, but one that cannot be ignored.
Further, there are many possibilities such as power failures, hardware failures, Internet connection issues, broker downtime, and overnight positions that could go wrong, and huge opening gaps, which could wreak havoc in your trades.
To be fair, anything could happen. But, the question is how do we avoid this from affecting our trades?
This is where scenario grading comes in.
How scenario grading helps
Scenario grading scores your trading strategy in various market conditions. Essentially, your strategy receives a grade based on how it will perform in specific market scenarios such as a market crash, sideways.
The entire process involves grading any set of mechanical trading rules in a variety of market conditions.
This can help you fine-tune your strategy before you trade in the live market and avert huge losses. It also helps limit biased trading performance, as you may realize that your trading strategy works only in certain market conditions. It can also be handy to decide when to use a particular strategy.
PHI 1 offers scenario grading, unique only to the all-in-one platform
PHI 1’s scenario grading feature is a unique mechanism that measures the performance of any arbitrary trading strategy for multiple market scenarios.
Currently, the strategy grader checks for 7 different market scenarios – Uptrend High Volatility (Bull Market), Uptrend Low Volatility (Bull Market), Downtrend High Volatility (Bear Market), Downtrend Low Volatility (Bear Market), Sideways High Volatility, Sideways Low Volatility, and even Market Crash.
Before you put your trading strategy to work, it is essential to test it. The fundamental ways to evaluate your trading strategies include backtesting and forward testing.
Backtesting refers to testing your strategy using historical data sets. Forward testing, on the other hand, refers to evaluating your trading strategy using simulated environments.
As a trader, testing your trading strategy is of utmost importance, as it will not only help you avoid huge losses but also help you trade stress-free.
Here are some trading platforms you can use for trading strategy evaluation:
1. PHI 1:
As an all-in-one algorithmic trading platform, PHI 1 allows multiple testing strategies like bulk backtesting and forward testing (simulations), which you can achieve with the click of a few buttons, on a single dashboard.
All you need to do is select your parameters such as capital, slippage costs, and the risk controls you want to use for the tests.
PHI 1 also offers a unique feature called scenario grading. This is a disruptive offering that scores your strategy for various market scenarios such as volatile, sideways, and crash.
Comes with a form-based strategy creator so you don’t need coding knowledge to get started
It runs on cloud; no download or installation is required.
Allows backtesting to show results for metrics like maximum gain, maximum loss, average gain, average loss, etc. with a look-back period of up to five years.
You can run backtests using various parameters and also adjust for brokerage costs and other charges.
Streak does not offer simulations and scenario grading.
It runs on cloud; no download or installation required
AmiBroker allows you to backtest your trade set-up for multiple stocks as well as at the portfolio level, uses some pre-defined values like portfolio size, periodicity (daily/weekly/monthly), commission charges, interest rate, maximum loss and profit target stops, type of trades, price fields which can be changed.
However, you need to type in a strategy formula that contains at least buy and sell trading rules.
Amibroker also allows access to Monte Carlo simulation to check for worst-case market scenarios.You can also test the robustness of your trading strategy by evaluating its out-of-sample performance to avoid over-fitting after in-sample optimization.
Amibroker can be a pricey alternative for Indian traders and requires coding knowledge to use the platform.
NinjaTrader’s Strategy Analyzer tests automated strategies via backtesting and optimization.
It is designed for use of strategies built using NinjaScript, NinjaTrader’s modern C# based trading framework
You can select the Strategy Analyzer parameters like strategy, instrument, interval type and value and time frame.
The results display all performance statistics and metrics, data for various time periods for analysis, and charts.
However, NinjaTrader is available only on Windows.
MetaTrader 5’s Strategy Tester allows back testing, forward testing, and optimizations.
The Strategy Tester offers various testing modes, e.g., its Random Delay mode simulates network delays during the processing of trades
You can use custom settings during strategy testing like trading limits, margin settings, and commissions.
You can view results in graphical view and also perform visual testing
MetaTrader 5 is primarily used by Forex traders. Besides this, the programming language and advanced features might be difficult for beginners.
If you’re willing to try a one-stop trading platform with screening, charting, easy strategy creation, backtesting, forward testing and scenario grading, and deployment, PHI 1 can be a cost-effective option for you.
PHI 1 uses large sets of data to help you bulk backtest your strategy, offers a simulated environment for forward testing, and also ranks your strategies in multiple market scenarios.
Want a first-hand experience of how PHI 1 can elevate your trading?
Evaluating your trading strategy using backtesting and forward testing can help you double check your trade set-up. But what if you had one more tool at your disposal to triple check your strategy?
Well, there is! PHI 1’s unique – Strategy Grading.
First, what does strategy grading even mean…? Let us explain.
Strategy grading refers to the automatic scenario-based scoring of your trading strategies. In simple terms, it refers to scoring your algorithmic trading strategy for various market scenarios such as downtrend, uptrend, crash, and so on. The process involves grading any set of mechanical trading rules in a variety of market conditions.
Different market conditions are pre-defined in your algo trading system and when you enter your trading set-up or rules, the system generates a score or grade that shows how your strategy will perform in each market condition in the system.
Why should you grade your trading strategy?
Scoring your algorithmic trading strategy has obvious benefits. It can help you understand how your strategy will perform in various market conditions, including market extremes. This can enable you to refine your strategy before you trade and avert huge losses.
It also helps eliminate biased performance, when your trading strategy works only in certain market conditions or at least helps you decide when to use a particular strategy.
How does PHI 1’s strategy grading feature work?
The strategy grading mechanism measures the performance of any arbitrary trading strategy for various market scenarios. It can grade strategy for 7 different market scenarios currently:
1. Uptrend High Volatility (Bull Market)
2. Uptrend Low Volatility (Bull Market)
3. Downtrend High Volatility (Bear Market)
4. Downtrend Low Volatility (Bear Market)
5. Sideways High Volatility
6. Sideways Low Volatility
7. Market Crash
How to grade your trading strategy on PHI 1 in 6 simple steps
Step 1: First, you would need to create a strategy in the Code Mode or Form Mode (if you prefer not to code).
Step 2: Name the strategy and select Run and Save.
Caption: In this case, we have created the Trix Momentum strategy. The init code calculates the required indicator by providing the name and parameters of the built-in momentum indicator, and the step code takes entry and exit positions based on its values
The displayed summary results and individual trades can be assessed, and the strategy can be modified based on the analysis.
The Strategy Return Chart displays the equity return and drawdown for the strategy.
Step 3: You can now test the performance of your trading strategy over a wide range of market conditions. Simple select Strategy to list all your saved strategies.
Step 4: Select Grading corresponding to the strategy that you would like PHI 1 to score or grade.
This starts all relevant backtests that your strategy should be assessed on to know its suitability for a wide range of market scenarios.
Step 5: Once the process is complete, you can view and analyze the results. This will help you further fine tune your strategy or use it only in specific market environments.
Step 6: Well, this requires you to try it out! Are you still waiting? Well, you don’t have to, because PHI 1 offers a free trial for 14 days. Post the trial, you can choose a plan that suits you best.
Isn’t strategy grading a game changer in making trades more decisive?
Not just this, PHI 1 also offers screening, bulk backtesting, simulation, and deployment, all in one unified trading platform.
Experience the power of automation in trading. Go full throttle with PHI 1.
Here’s a surprise for you – Code for the above mentioned Trix Momentum Strategy. Try it now!
self.trix = Trix(self.data,period=20)
self.signal = EMA(self.trix, period=12)
if (self.trix > self.signal) and (self.trix[-1] < self.signal[-1]) and (self.position.size==0):
if (self.trix < self.signal) and (self.trix[-1] > self.signal[-1]) and (self.position.size > 0):
if (self.trix < self.signal) and (self.trix[-1] > self.signal[-1]) and (self.position.size==0):
if (self.trix > self.signal) and (self.trix[-1] < self.signal[-1]) and (self.position.size < 0):
What is the one thing you should avoid when your money is at stake? Being reckless! At least, that should be the case while you are trading, especially when you have the means to evaluate your trading strategy. Your two best friends, in trading, are backtesting and forward testing
What is Backtesting?
Backtesting is testing your trade set-up or trading strategy using historical data to assess its performance over a specific period. Backtesting trading strategies is simple using trading systems.
With backtesting, you can learn more about how viable your trading strategy is without the need to risk your money.
You can test both – simple and complex trading strategies requiring multiple parameters and inputs with backtesting. The analysis that you get from backtesting can optimize your trading strategy.
Here are some pros and cons of backtesting:
First, the pros:
1. Backtesting helps develop confidence in your trading strategy.
2. You can make necessary improvements to your trading strategy.
3. You can test your strategy for specific periods and parameters.
1. Past data does not guarantee future performance.
2. Historical data include limited market conditions and do not account for unplanned events.
3. There may be a chance of over-fitting strategy parameters. You may end up over-optimizing the strategy to a point where it perfectly fits historical data, but fails in most other scenarios.
Backtesting trading strategies does not tell you how your strategy will perform in forecasted or live trading conditions.
This is because live charts and backtesting charts may vary a lot, and your trading behavior may also be different when you put in actual money. Further, there are always unplanned events impacting markets.
Of course, backtesting helps optimize your trading strategies, but you need to take your strategy to the next level with forward testing.
What is Forward testing?
Forward testing, which is also known as paper trading, refers to testing your trading strategy in a live environment. However, as the name suggests, paper trading is done only on paper, with no actual money.
Here are some pros of forward testing:
1. You can validate the model’s ability to make profits in real trading.
2. You can assess how your trading strategy will be impacted by trends, volatility, and liquidity conditions.
3. It helps gain more confidence if done after backtesting
A disadvantage of forward testing is that because it is on paper, no actual money is involved, and since you’re aware of that, your trading psychology or behaviour may be biased.
How to perform backtesting and forward testing using PHI 1?
You are aware by now that backtesting assesses your trading strategy for historical data, while forward testing further adds a layer of safety by testing in a simulated market environment.
Hence, a combination of both is key to developing confidence in your trade set-up.
Here’s how you can perform these tests with ease on PHI 1:
You can screen the security you want to trade with, and use our charting tool (forever free!) to ideate your strategy.
It is that simple! Besides this, PHI 1 also offers scenario grading. This is a disruptive, “patent pending” feature that grades your strategy for various market scenarios such as volatile, sideways, crash,.
Also, you get to access all these features on a single dashboard for free during the 14-day trial period and can choose from a wide range of subscription plans anytime.
Don’t trade without double-checking your trading strategy! Test and test again for a better trading experience!
“Losses are necessary, as long as they are associated with a technique to help you learn from them” – David Sikhosana
By this, David Sikhosana perhaps meant that there is no way we can completely avoid failure while trading. However, if we do not identify the reasons for failures and learn from them, it is a huge problem.
The crux of the matter is to figure out what went wrong with your trading strategy and why it failed.
Here are some reasons why your trading strategy may fail you repeatedly:
1. Having a poor risk/reward ratio
Many traders focus on multiple metrics in their trading strategy, but do not account for a good risk/reward ratio. The ratio suggests how much risk you’re willing to take to earn a unit of profit.
A lot of times, traders end up using strategies that involve taking a tremendous risk for miniscule profit. Risk/Reward ratios should approximately be 1:3, but this should be in tandem with other measures like win rate and should not be considered in isolation.
2. Ignoring the key aspect of drawdown
One of the biggest factors that affects trading success is the lack of knowledge about using drawdown. Understandably, one’s trading strategy aims to achieve greater returns at the lowest potential risk.
However, while trying to avoid drawdowns, one may end up with a curve fitted or over-fitted system (where your strategy is not fit for changing market behaviour).
You cannot completely avoid drawdowns, but you can definitely factor in parameters such as the time to recover from a drawdown for better trading performance.
Time to recover from a drawdown helps you understand how prolonged a drawdown can be, whether it is temporary or permanent.
3. Using too many indicators
Having too many indicators at once in your trading strategies, whether they are intraday trading strategies or option trading strategies, can lead to failure. Having an excessive number of indicators leads to over-analysing and decision paralysis.
Remember, more tools do not mean better trading. In fact, it is quite the opposite. Keep your trading system simple and stick to a few indicators you are comfortable with, to form an optimal strategy, not the perfect one!
4. Not accounting for slippages and transaction costs
Transaction costs like broker fees, exchanges fees, taxes, etc. involved in trading are usually excluded from a trading plan while estimating profitability. However, these costs can be substantial.
It is also important to consider the effect of slippages, like the bid-ask spread when orders get filled. It helps to forecast these slippages as a percentage of the price of the security.
5. Over-fitting/ Using unreliable data while testing your trading strategy
Over-fitting in the trading context refers to adjusting your strategy too closely to a limited set of data. Over-fitting makes the strategy align so closely with the historical data that it ends up failing in other market conditions.
This is because past data does not perfectly determine future market behaviour. Over-fitting can give you false confidence while trading with your strategy. Instead, using extensive sets of reliable data and bulk backtesting can help you test your strategy for robustness.
6. Trying to use your trading strategy universally
Do you have a trading strategy that has worked for you in one particular scenario in different markets or in different scenarios in the same market?
Well, don’t make the mistake of using it universally across markets, securities, and scenarios. No one strategy can win in all situations and markets.
Instead, consider scenario grading and backtesting for different markets to fine-tune your trading strategy each time you use it.
Many a time, you may not be able to ensure that all the above points are taken care of, simply because you do not have the tools and resources for the same.
Further, PHI 1 offers backtesting using reliable sets of data, so you can evaluate your trading strategy in a jiffy! Not just that, you can also grade your strategy in multiple market scenarios like crash, volatile, choppy, etc. so you are more confident of trading in live markets.
From screening to deployment, PHI 1 is a unified algo trading platform that allows you to focus on the real deal, saving time and money spent on using multiple tools. Further, you do not need to install or download anything. You can access it directly through your browser.
Try our all-in-one algo trading platform for free and browse through our multiple plans for more features!
When the author of Market Wizards, Jack Schwager, said, “The hard work in trading comes in the preparation. The actual process of trading, however, should be effortless,” he implied one should focus on how ready one is for the live market.
And by being ready, the most important thing, perhaps, is to have a trading strategy that can withstand the vagaries of the ever-changing markets.
In this context, it is important to quantitatively assess your trading strategy to ensure that it helps you achieve your goal, eliminate emotional biases, and objectively analyze your strategy.
There are multiple metrics traders use to evaluate their trading performance. Most of these parameters are not used in isolation, but in combination.
With little ado, let us look at the 8 key metrics you can use for trading strategy evaluation:
A) P/L Metrics
These metrics focus on the return on your trading capital achieved using your strategy.
1. Wins vs. Losses
The win/loss ratio refers to the ratio of the total number of winning trades to the number of losing trades. This ratio does not factor in the size of the win or loss.
Win/Loss Ratio = Number of Wins/Number of losses
Besides this ratio, it is important to also look at the size of win/ loss and assess the ratio in various market conditions to avoid biases during bull/bear markets.
It also makes sense to look at this ratio with the win-rate, which is the number of profitable trades out of the total number of trades.
A win/loss ratio above 1.0 or a win-rate above 50% is typically preferred.
2. Profit Factor
Profit factor (PF) is the ratio of gross profit to gross loss (inclusive of commissions) for a trading period. This parameter shows the amount of profit per unit of risk.
Typically, a PF of more than 1 is preferred.
PF = Gross Profit/Gross Loss
3. Percentage Profitability
This metric denotes the probability of winning and is essentially the percentage of total trades that turned out to be profitable.
This parameter is calculated by dividing the number of profitable trades by the total number of trades for a specified period.
While looking at returns is important, it is essential to consider risk in your trading performance analysis, i.e. understand the probability of your strategy losing money. Here are some metrics that can help you gauge risk.
4. Maximum Drawdown
Maximum drawdown represents the largest fall in the security price from the peak to a trough over a period. It shows the largest downside risk level or the worst-case scenario of your trading strategy.
Maximum Drawdown = (Trough value – Peak value) / Peak value
Usually, a low maximum drawdown is preferred; however, it must be noted that this metric only measures the size of the largest fall and not the frequency or period for which the strategy underperformed.
5. Annualized Volatility
Annualized Volatility refers to the standard deviation of the daily returns of your trading strategy in a year. Since volatility denotes risk levels, the higher the annualized volatility, the riskier the strategy.
C) Risk/ Reward Metrics
Given that both reward and risk are important elements to examine trading strategy performance, risk/reward ratios can help measure the potential profit of a trade relative to the risk taken. Some important ones are mentioned below:
6. Sharpe Ratio
This ratio measures the average of excess returns to standard deviation. Excess returns refer to your trade’s return minus the risk-free return.
The higher the Sharpe ratio, the better.
Sharpe Ratio = (Portfolio Return – Risk-free Return)/ Standard Deviation
7. Sortino Ratio
The Sharpe ratio penalizes a trader even with upward volatility or upside risk. The Sortino ratio measures returns adjusted for downside risk only.
Sortino Ratio = (Portfolio Return – Risk-free Return) / Annualized Volatility of Negative Returns.
8. Calmar Ratio
Calmar ratio measures the ability of your trading strategy to bounce back from extreme lows. Since it considers maximum drawdown, which denotes the worst-case scenario, Calmar ratio can be a stringent measure of trading performance.
Calmar Ratio = Average (Portfolio Return – Risk-free Return) / Maximum Drawdown
Besides using these metrics for trading performance analysis, it would also be wise to consider factors such as the total costs of trading inclusive of broking charges and taxes, the average holding period which denotes how long your trades last, exposure of your capital to a single trade, and also the number of trades per year, which evaluates the frequency of trading.
Trading performance analysis should also involve using all these metrics in various market scenarios such as trending, volatile, sideways; so you know that your trading strategy works in multiple situations and not just in select or historical scenarios.
PHI 1 offers the bulk backtesting feature to assess your trading strategy with respect to multiple metrics such as ROI and Sharpe Ratio on really large sets of data in a snap.
Also, our grading process grades the risk/return metrics of your strategies in varied market scenarios. Our aim is to ensure that market scenarios should not decide how good your strategy is.
That said, would we ask you to use multiple tools for trading performance analysis? Hell, no!
The importance of strategy evaluation cannot be stressed enough in the trading context. Trading strategy evaluation has obvious benefits such as better risk management, refining your strategy, placing live trades more confidently, and avoiding huge losses.
Given the plethora of advantages and easy-to-use tools at your disposal, it makes little sense not to test your strategy prior to actual trading.
Let us look at some methods you can use to evaluate your trading strategy.
1. Choose a benchmark to assess the relative performance of your strategy
After you have devised your trading strategy, you need a benchmark to compare the relative performance of your strategy. Choose a benchmark that applies to the sector or market you are trading in. For example, if you are trading a stock like Infosys, having the Nifty IT index as a benchmark would be a wise choice.
Comparing your trading strategy’s performance vs. that of a benchmark can help you understand relative performance and develop confidence in your trades.
For example, let’s say your benchmark has returned a negative 2% annualized performance and your strategy has delivered a +1% annualized return. This tells you that your strategy has outperformed the benchmark.
2. Consider risk-adjusted returns
So, you have two strategies X and Y which may have given you the same returns over a specific period. However, strategy Y may deliver the returns with much more volatility/risk vs. strategy X. This implies that X delivers better risk-adjusted returns than strategy Y. Why would you take more risk to get the same return? Clearly, X is better.
To measure risk or volatility, you can use the standard deviation of returns.
Using a measure such as Sharpe Ratio can help you assess your strategy with respect to risk-adjusted returns.
Sharpe Ratio = (Return – Risk-free Rate)/ Standard Deviation of Returns
Remember, the higher the Sharpe ratio, the better.
However, Sharpe ratio can mislead as it does not consider the direction of volatility (upward volatility may not always be unfavorable). This is because more risky strategies will always rank lower with this ratio.
An alternative ratio in this case can be the Sortino ratio, as it only considers standard deviation of downside returns. Thus, it does not penalize upward volatility as in the Sharpe ratio.
3. Check Profit/ Loss performance alongside ratios
It is not always a great idea to use ratios in isolation. It always pays to use charts such as P/L in various market scenarios to assess your trading strategy.
Check how the strategy will perform or has performed not just during bull phases but also during bear markets and market crashes.
4. Use Maximum Drawdown
Maximum Drawdown is the distance between the largest peak to the lowest valley of your P/L. Maximum drawdown measures the biggest movement from a high point to a low point prior to a new peak.
Thus, it essentially measures the size of the largest loss, an indicator of downside. It focuses on capital preservation and should be as low as possible. Maximum drawdown can measure risk-adjusted returns using the Calmar Ratio.
However, it must be noted that it does not denote the frequency of loss or size of gains.
Calmar Ratio = Average Return/Max Drawdown
5. Assess metrics such as Win Rate, Average Size, and Average Profit/Loss – all together
Estimating other measures such as win rate, number of wins and losses, and average profit and loss over a specified period, when taken together, can reasonably show how your strategy has worked.
6. Backtest and forward-test using extensive sets of data and multiple scenarios
Finally, when you use backtesting to examine your strategy, the results depend on how reliable your data and model are. Most times, over-fitting (which refers to designing a trading system to adapt too closely to historical data) can give you false confidence that your trading strategy is robust.
Therefore, it is important to test your strategy in a wide range of market scenarios such as crash, choppy, sideways,. and to use extensive sets of data and instruments. Consider forward-testing your strategy in different simulated environments as well.
To evaluate your trading strategy well, you need backtesting and forward-testing capabilities that allow you to test with reliable and large sets of data in all market conditions.
Now, if you’re wondering where to get such strategy evaluation tools, you’re already there! PHI 1 allows bulk-back testing on vast sets of data in a matter of minutes and in different market scenarios like trending, choppy, sideways, crash.
In fact, we have a unique scenario grading process (patent pending) that assesses your strategy in multiple market scenarios – all this on one platform!
If you want to try out these features, simply visit app.phi.io and enjoy our free 14-day trial.
You can also avail a quick demo. And once you’re convinced (which we have no doubt about), check out our reasonably priced plans here.
American billionaire hedge fund manager, John Paulson, once said, “No one strategy is correct all the time.”
This quote should force us to dig deeper into our trading strategies and understand that even though we think our trading strategy has worked for us in the past, you would still need to plan for every trade you place.
What does planning in trading exactly involve, anyway?
Planning a trade involves deciding the time you want to commit to trading, your trading goals, deciding how much capital you want to allocate, risk levels, and your entry & exit points.
Then, you would need to focus on technical parameters such as research on securities, markets, trading opportunities, setting risk controls, creating a strategy and evaluating the strategy.
In this article, we focus on strategy evaluation, as it is one of the most important steps in risk management that many skip prior to placing orders.
Trading Strategy evaluation is assessing if the strategy you have chalked out would really work for you in different scenarios.
Often, you may be convinced that a strategy will work for you, and turns out it was a loss-making one.
Strategy evaluation can help you decide if your trading strategy is good enough and whether you should actually go ahead with your trade.
Why you must evaluate your trading strategy
1. Helps avoid the same mistakes:
You may have placed multiple trades earlier, and things just aren’t working out for you. What do you do? Use the same strategy thinking it will work this time? Stop! Go back and check your strategy.
Are there minor things you missed out on earlier? If yes, reusing the same strategy will do no good another time.
Evaluating your trading strategy will help you find these flaws and correct your strategy so it works in your favour the next time.
2. Allows assessment of strategy robustness in various scenarios:
Okay, maybe some of your trading strategies have worked for you so far. But will your strategy work if a crash like the one that happened at the start of the lockdown in 2020 strikes one more time?
Will your strategy work in case there is a black swan event? The bottom-line is even if your strategy has worked for you in the past, there are scenarios that may make your strategy useless.
Evaluating the robustness of your strategy in various scenarios can help you understand if it will serve you in extreme situations.
3. Helps develop confidence prior to deployment:
Before you deploy your strategy, you can use back-testing to examine how your strategy works on historical data using back-testing.
Further, you can also forward-test your strategy via simulation, which allows you to trade in a virtual environment without using actual money.
Back-testing and simulation can enhance your confidence of trading in the live market.
There are also features like bulk back-testing that some platforms like PHI 1 offer – this allows you to auto-analyze your strategy’s performance.
Your trading strategies are scored in various market scenarios such as volatility, market crash, and trending automatically.
4. Trading with less stress = less emotional interference:
Once you have evaluated your trading strategy, you would use a tested approach to trading after considering multiple possibilities.
This means trading with less stress and emotional impulses. If you are a trader, you know how good trading feels without the emotional bias.
PHI 1 with its bulk back-testing, scenario grading, advanced risk controls, and simulation features ensures that your trading strategy is strong enough for the live market.
Also, you don’t have to use different tools for screening, charts, strategy creation, and placing orders. You can do it all using PHI 1 alone – a single unified algo trading platform that automates your trades the way you want it to.
So you have devised a unique trading strategy for yourself and are excited to try it. However, you hold back for the fear of losing your money. Well, it’s only rational to think this way.
Before you actually go live with your trading strategy, it is important to test your strategy. One way to do so is in a virtual environment through a process known as “paper trading”.
Paper trading is essentially a practice of trading in a completely virtual or simulated environment.
The term “paper trading” came into being from the time when traders would mark their strategies on paper and compare it manually with the movement in stock prices to examine their robustness.
With paper trading, you do not need to actually invest your money as the entire trading environment is simulated.
So, anything that happens within paper trading will not affect your trading account or the stock market. Paper trading simulates real-time values of the markets and allows you to test your trading strategies and test them.
Paper trading is a must, especially if you are a beginner considering that it is your hard earned money that you deploy in the markets. In fact, it is advised not just for new traders but also for experienced traders to test novel strategies and ideas.
Here’s why you must paper-test your strategy before deployment
1. No risk involved
When you paper-test your strategy, it essentially costs you nothing. So, if you make a terrible trade, you cannot lose money. You can use the trade to identify flaws in your strategy and ensure that you do not repeat them during live trading, which further reduces your risk.
This can help you gain valuable initial experience as a beginner, and your hard-earned money stays with you while you practice your strategies.
2. No stress or emotions involved
Emotions are a large part of trading, especially for beginners. A lot of times, it is your impulses that cause a poor trade and not your strategy. Paper-testing your strategy does not allow your emotions like greed, fear, and panic take over. This allows you to stick to your strategy.
With enough paper trading, you may in fact gain control over your emotions and be able to keep them in check during actual trading. Thus, paper trading serves like mind training!
3. Gives you adequate practice and confidence before deployment
Paper trading gives you the much-needed experience you need before you actually start trading with your hard-earned money.
This prepares you thoroughly before you deploy your strategies. It also gives you enough room to make mistakes and helps develop confidence to trade in the live markets.
4. Boosts creativity to try out new strategies
You may have come up with an experimental strategy that may be hard to implement considering that you have never tried it before.
However, with paper trading, you can literally simulate any strategy under your belt. This particularly helps when you do not have any statistics on the strategy’s performance.
Paper trading is not just for beginners but also for experienced traders who have lost touch with the market. Every trader goes through periods of losses, which can affect their confidence. Paper-testing can be a lot of help with regaining your control on emotions and your confidence before you dive back into action.
While earlier, traders would test strategies on an actual paper, today, a lot of platforms offer simulated trading. PHI 1 offers a superior simulation experience that can help you paper-test your strategies before you get into the real deal.
All you need to do is create and save your strategy on PHI 1, enter the strategy you want to use for paper trading, choose an instrument, set testing parameters and amount, and add risk controls. You’re all set to drive a trading simulation using PHI 1.
Also, PHI 1 enables limitless creation of strategies with its form-based and multi-symbol strategy creator, and standard as well as calendar risk controls, taking your algo trading to the next level.
PHI 1 aims to set the trader free from the daily mundane tasks by automating them, so traders can focus on exploring opportunities in the stock market.
Whether you’re a beginner or experienced trader, paper-testing refines your trading game. With PHI1, you can paper-test your strategies with ease.