Algorithmic Trading – An Innovative Way for Stay at Home Mums to Earn Income

Algorithmic Trading – An Innovative Way for Stay at Home Mums to Earn Income

As a stay at home mum with limited time available between parenting commitments, discovering online income streams that fit around home-schooling the children presents a perpetual dilemma. Algorithmic trading proffers an intriguing solution – systematically earning money from financial markets via automated computer programmes coded with your trading strategies.

Read on as we thoroughly explore what algorithmic trading entails, which types of algorithms theoretically offer promise, pragmatic realities for adoption viability, and key sequential steps to code your own income producing auto-trading systems as a mum.

Introduction to Algorithmic Trading Concepts

Algorithmic trading refers to buying and selling monetary assets automatically based on a predefined coded strategy that continuously monitors market data for profitable signals. Consider the benefits:

• Hands-free – Once live, the algorithm independently trades 24/7 without manual oversight needed.
• Emotion-less – Coded logic determines actions solely on quantified data signals, removing behavioural bias threats.
• Flexible – Strategies perpetually earn around the clock while you handle other priorities

With exponential technology gains lowering skill barriers, algorithmic systems now prominently augment discretionary approaches – facilitating systematic profits for analytical parents willing to upskill where needed.

Types of Promising Trading Algorithms

Highlighting two foundational algorithm categories that balance profit potential and oversight needs proves instructive:

Trend Following Systems

• Conceptually basic algorithms requiring little human interference
• Code to trade favourably along momentum by identifying durable uptrends
• Compounding modest reliable gains cumulatively over months and years

Mean Reversion Strategies

• Statistical models identify pricing levels that are mathematically overextended
• Signal counter momentum trades targeting reversion to quantitatively average levels
• Precise quantitative rules limit emotional interference and overtrading

Algorithms structurally aligned to trade with prevailing momentum require the least active monitoring while steadily compounding gains long term – an ideal set up for busy parents.

Practical Realities to Consider

Some inherent challenges that influence likely automated trading success probabilities:

• Learning to Code – Getting started necessitates picking up languages like Python. But many free interactive online resources now exist lowering knowledge barriers.
• Risk Parameters – All algorithms face losses. But coding prudent stop loss limits and maximum size constraints lets profits reliably accumulate over months. Discipline rules.

If willing to upskill aspects and automate robust risk controls, coding algorithms tailored to your risk preferences and availability opens a promising opportunity. Support services also empower viability…

Algorithmic Trading Support Infrastructure

Relationships with brokerages, software tools and educational communities heavily sway adoption ease and sustained progress. For instance, remote prop firms like the Funded Trading Plus website provide fully funded accounts once traders pass risk-constrained evaluations – alleviating self-funding capital burdens.

Such supportive components enhance focus directly on crafting strategies, streamlining research, executing improvements and driving system output. Removing roadblocks through access to leverage, coaching and technology ultimately amplifies capacity for dedicated parents through structured frameworks.

Key Benefits Beyond Profit Potential

For intellectually curious and analytically oriented parents, algorithmic trading offers multifaceted cerebral stimulation through diverse challenges:

• Applying coding, data science, statistics, machine learning and finance principles simultaneously keeps abilities sharp.
• Creativity formulating new strategy hypotheses and rigorously evaluating performance characteristics exercises inventor spirit.
• Methodically optimising algorithms targeting incremental performance gains channels engineering inclinations.

The cross-disciplinary problem solving spanning leading edge technology, mathematics and model design provides a rich arena to exercise various aptitudes. Keeping engagement high!

Phased Pathway Towards Hands-Free Algo Trading

Transitioning from purely discretionary trading completely to fully independent algorithmic systems commonly involves gradual “hybrid” stepping stone phases at first rather than abrupt extremes.

Initially, manual traders may use automation for specific modular tasks like identifying setups or administering protective stop orders while still manually entering and exiting primary trades based on human judgements. This stage focuses automation power on the more mundane components while still overseeing and evaluating overall benefits.

As competency and trust in the automated logic expands thanks to demonstrated performance tracking, traders gradually assign greater end-to-end autonomy to their algorithms – allowing the systems to handle an expanding array of responsibilities independently without micromanagement. Eventually culminating the algorithm managing the full trade lifecycle decision chain – achieving true “set and forget” automation!

This stepped approach enables rapidly accelerating returns at milestone stages as refined algorithms relentlessly apply profitable strategies far faster and rationally than any lone human alone. Ultimately freeing up precious time while capitalising on machine strengths around the clock.

Exploring Algorithmic Trading As a Beginner

The methodical pathway towards ultimately implementing fully autonomous custom coded algo trading systems can be reasonably distilled into a few key sequential stages even for newcomers:

• Learn a Programming Language

Python remains a predominant choice for writing code that analyses financial data streams and executes trading strategies. Many free interactive online learning platforms like CodeAcademy offer introductory Python programming courses focused on language fundamentals and real world applications that can establish baseline coding competencies within weeks.

• Study Successful Strategies

Before attempting to formulate original profit-seeking algorithms, thoroughly understand time-tested trading strategy formulations like trend following, mean reversion, momentum etc that are grounded in robust behavioural finance and empirical evidence accumulated over decades. Replicate before trying to innovate as a beginner building competency and trust.

• Link Brokerage and Software Tools

Seamless access to streaming market data feeds, cloud computing power, backtesting capabilities, and ultimately connectivity to trade execution infrastructure carries tremendous weight. Advanced brokerages like Interactive Brokers cater access via Flex Web API configurations while platforms like QuantConnect share community code and historical data resources. Choose partners strategically.

Concluding Thoughts on Algorithmic Trading Systems

Implementing profitable financial trading strategies by codifying models and assumptions into meticulously designed and risk-managed algorithms offers busy stay at home parents an auspicious avenue to systematically generate passive income around dynamic family schedules and demands through automation. Although certainly still necessitating dedicating energy upfront to carefully construct, test and refine automated logic before trusting capital allocation.

Fortunately, structured online education now exists guiding even non-programmers to pick up foundational competencies like Python coding rapidly. And market-tested support frameworks like a funded trading account provide leverage aligned to performance for traders seeking more account scale after verification.

If willing to upskill select knowledge gaps around technology or modern trading techniques, encoding financially-motivated algorithms awakens a level of 24/7 hands-free productivity otherwise challenging to physically achieve individually – all while gracefully balancing pre-existing family commitments.

Guest Article.